Enhancing the performance of the Digital Cherenkov Viewing Device

Transcription

1 Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1708 Enhancing the performance of the Digital Cherenkov Viewing Device Detecting partial defects in irradiated nuclear fuel assemblies using Cherenkov light ERIK BRANGER ACTA UNIVERSITATIS UPSALIENSIS UPPSALA 2018 ISSN ISBN urn:nbn:se:uu:diva

2 Dissertation presented at Uppsala University to be publicly examined in Room 2005, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, Friday, 12 October 2018 at 13:00 for the degree of Doctor of Philosophy. The examination will be conducted in English. Faculty examiner: Dr. Christopher Orton (Pacific Northwest National Laboratory, PNNL). Abstract Branger, E Enhancing the performance of the Digital Cherenkov Viewing Device. Detecting partial defects in irradiated nuclear fuel assemblies using Cherenkov light. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology pp. Uppsala: Acta Universitatis Upsaliensis. ISBN The Digital Cherenkov Viewing Device (DCVD) is an instrument used by authority safeguards inspectors to verify irradiated nuclear fuel assemblies in wet storage based on Cherenkov light emission. It is frequently used to verify that parts of an assembly have not been diverted, which is done by comparing the measured Cherenkov light intensity to a predicted one. This thesis presents work done to further enhance the verification capability of the DCVD, and has focused on developing a second-generation prediction model (2GM), used to predict the Cherenkov light intensity of an assembly. The 2GM was developed to take into account the irradiation history, assembly type and beta decays, while still being usable to an inspector infield. The 2GM also introduces a method to correct for the Cherenkov light intensity emanating from neighbouring assemblies. Additionally, a method to simulate DCVD images has been seamlessly incorporated into the 2GM. The capabilities of the 2GM has been demonstrated on experimental data. In one verification campaign on fuel assemblies with short cooling time, the first-generation model showed a Root Mean Square error of 15.2% when comparing predictions and measurements. This was reduced by the 2GM to 7.8% and 8.1%, for predictions with and without near-neighbour corrections. A simplified version of the 2GM for single assemblies will be included in the next version of the official DCVD software, which will be available to inspectors shortly. The inclusion of the 2GM allows the DCVD to be used to verify short-cooled assemblies and assemblies with unusual irradiation history, with increased accuracy. Experimental measurements show that there are situations when the intensity contribution due to neighbours is significant, and should be included in the intensity predictions. The image simulation method has been demonstrated to also allow the effect of structural differences in the assemblies to be considered in the predictions, allowing assemblies of different designs to be compared with enhanced accuracy. Keywords: DCVD, Nuclear safeguards, Cherenkov light, Nuclear fuel assembly, Partial defect verification Erik Branger, Department of Physics and Astronomy, Applied Nuclear Physics, Box 516, Uppsala University, SE Uppsala, Sweden. Erik Branger 2018 ISSN ISBN urn:nbn:se:uu:diva (

3 There can be no doubt that the usefulness of this radiation [Cherenkov light] will in the future be rapidly extended. -Pavel Cerenkov [1]

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5 List of papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I II III IV V E. Branger, S. Grape, S. Jacobsson Svärd, P. Jansson, E. Andersson Sundén, On Cherenkov light production by irradiated nuclear fuel rods. Journal of Instrumentation, June DOI: / /12/06/T06001 My contribution: I made the simulations and analysed the results. I am the main author of the paper. E. Branger, S. Grape, S. Jacobsson Svärd, P. Jansson, E. Andersson Sundén, Comparison of prediction models for Cherenkov light emissions from nuclear fuel assemblies. Journal of Instrumentation, June DOI: / /12/06/P06007 My contribution: I made the simulations and analysed the results. I am the main author of the paper. E. Branger, S. Grape, P. Jansson, S. Jacobsson Svärd, Improving the prediction model for Cherenkov light generation by irradiated nuclear fuel assemblies in wet storage for enhanced partial-defect verification capability. The ESARDA Bulletin issue no. 53, June My contribution: I made the simulations and proposed the prediction method. I am the main author of the paper. E. Branger, S. Grape, P. Jansson, E. Andersson Sundén, S. Jacobsson Svärd, Investigating the Cherenkov light production due to cross-talk in closely stored nuclear fuel assemblies in wet storage. Paper presented at the 39 th ESARDA Annual Meeting, May 2017, Düsseldorf, Germany. Accepted for publication in the ESARDA Bulletin. My contribution: I made the simulations and proposed the prediction method. I am the main author of the paper. E. Branger, S. Grape, P. Jansson, S. Jacobsson Svärd, Experimental evaluation of models for predicting Cherenkov light intensities from short-cooled nuclear fuel assemblies. Journal of Instrumentation, February DOI: / /13/02/P02022 My contribution: I made the analyses of the results and the simulations. I am the main author of the paper.

6 VI VII E. Branger, S. Grape, P. Jansson, S. Jacobsson Svärd, On the inclusion of light transport in prediction tools for Cherenkov light intensity assessment of irradiated nuclear fuel assemblies. Manuscript. My contribution: I made the simulations and the analyses. I am the main author of the paper. E. Branger, S. Grape, P. Jansson, S. Jacobsson Svärd, Experimental study of background subtraction in Digital Cherenkov Viewing Device measurements. Journal of Instrumentation, August DOI: / /13/08/T08008 My contribution: I did the measurements and the analyses. I am the main author of the paper. Reprints were made with permission from the publishers. Additional papers part of this work, but not included in the thesis: i E. Branger, E. L. G. Wernersson, S. Grape, S. Jacobsson Svärd, Image analysis as a tool for improved use of the Digital Cherenkov Viewing Device for inspection of irradiated PWR fuel assemblies. Report, June Available in DiVA: diva2:3a My contribution: I assisted in writing the report. ii E. Branger, S. Grape, S. Jacobsson Svärd, E. L. G. Wernersson, Improved DCVD assessments of irradiated nuclear fuel using image analysis techniques. Paper presented at the 55 th INMM Annual Meeting, Atlanta, USA, My contribution: I wrote and presented the paper. I am the main author of the paper. iii E. Branger, S. Grape, S. Jacobsson Svärd, E. L. G. Wernersson, Towards unattended partial-defect verification of irradiated nuclear fuel assemblies using the DCVD. Paper presented at the IAEA Symposium on International Safeguards, Vienna, Austria, My contribution: I wrote and presented the paper. I am the main author of the paper.

7 Contents 1 Introduction The need for nuclear safeguards Outline of the thesis Nuclear safeguards The legal framework for nuclear safeguards Material and facilities under safeguards Safeguards verification of nuclear material Nuclear fuel assemblies Physical design of nuclear fuel assemblies Fuel usage in a reactor Safeguards verification of irradiated nuclear fuel assemblies Cherenkov light The physics of Cherenkov light Cherenkov light from irradiated nuclear fuel assemblies The Digital Cherenkov Viewing Device, DCVD History Measuring fuel assemblies with a DCVD Detecting partial defects using a DCVD Partial defect intensity limits First-generation method (1GM) for predicting Cherenkov light intensities Limitations addressed developing the second-generation prediction method (2GM) Practical aspects Simulations Simulation tools used Simulating sources of ionizing radiation Simulating radiation transport and Cherenkov light production Simulating light transport to the DCVD and image creation Simulated light production by single fuel rods Contributions from different types of radiation... 49

8 6.2.2 Effect of source distribution in a rod Anisotropy of produced light Dependencies of light production on fuel rod dimensions Simulated light production in complete fuel assemblies Systematic differences between assemblies of different types Contribution from beta emitters Simulated light production in neighbouring assemblies Including light transport and image creation in simulations Speeding up the simulations Predicting Cherenkov light intensities Suggested second-generation prediction method (2GM) General methodology Single assembly predictions Neighbourhood predictions Predictions adjusted for top plate designs Experimental evaluations of the 2GM Performance of near-neighbour predictions Performance on short-cooled fuel assemblies Performance of predictions adjusted for top plate design Background in DCVD measurements Intensity components Background subtraction Currently used background subtraction Alternative dark-frame subtraction Experimental evaluations Background light sources Conclusions and discussion Results of simulation studies Development and evaluation of prediction tools Improving the background subtraction routines Implementation of new prediction tools in IAEA safeguards Outlook Modelling partial defects Analysing image properties Enhancing the quality of the measured data Combining data from different instruments Acknowledgements... 91

9 12 Sammanfattning på Svenska References... 94

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11 List of abbreviations 1GM 2GM AP BU BWR Clab CT DA DCVD IAEA ICVD IE NDA NN NNWS NPT NWS PWR ROI SQ First-generation prediction model Second-generation prediction model Additional Protocol Burnup Boiling Water Reactor Swedish Central Interim Storage Facility for Spent Nuclear Fuel Cooling time Destructive Assay Digital Cherenkov Viewing Device International Atomic Energy Agency Improved Cherenkov Viewing Device Initial enrichment Non-Destructive Assay Near-Neighbour Non Nuclear Weapons State Non-Proliferation Treaty Nuclear Weapons State Pressurized Water Reactor Region Of Interest Significant Quantity 11

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13 1. Introduction 1.1 The need for nuclear safeguards Shortly after the discovery of nuclear fission [2], i.e. the splitting of atomic nuclei, researchers realized that vast amounts of energy could be released by creating a fission chain reaction. This energy has found peaceful applications in terms of electricity production in nuclear power plants, but also destructive use in terms of nuclear weapons. Whether used peacefully or for military purposes, nuclear energy requires nuclear material, i.e. material that is fissile or can be converted to fissile material through nuclear reactions. A fissile material contains nuclei that can fission following the absorption of a neutron, while emitting one or several neutrons following the fission, thus allowing a chain reaction to take place. To promote peaceful use of nuclear energy and nuclear technology, and to inhibit its use for nuclear weapons or other military purposes, the International Atomic Energy Agency (IAEA) was founded in 1957 [3]. About a decade later, the work of the IAEA was significantly expanded when the Treaty on Non-Proliferation of Nuclear Weapons (NPT) opened up for signatures in To ensure that nuclear materials and technologies are used peacefully, the NPT signatory states are required to sign a nuclear safeguards agreement with the IAEA. The safeguards agreement give the IAEA the right to inspect and verify a state s nuclear facilities, and to verify a state s possession of nuclear material. The IAEA also verifies that no undeclared nuclear activities take place within the state. Through these inspections the IAEA can provide credible, independent confirmation that states are using their nuclear technologies and materials only for peaceful purposes, and that no nuclear material is diverted to any clandestine nuclear weapons program, or for any other non-peaceful purposes. The civilian nuclear fuel cycle contains vast amounts of nuclear material that is placed under safeguards. As of 2018, there are about 450 commercial electricity-producing nuclear reactors in operation worldwide, with another 60 under construction [4]. The nuclear material under safeguards is monitored and verified throughout the entire nuclear fuel cycle, i.e. from when it is mined, through its conversion to and usage as nuclear fuel, as well as though any reprocessing to make new fuel from used fuel, and until its disposal in a final repository. Verifying that all nuclear material is accounted for and only used peacefully in each step of the nuclear fuel cycle is a massive undertaking, and consequently the inspections executed by the IAEA need to be efficient, accurate and comprehensive. 13

14 To aid the authority inspectors in verifying nuclear material in its various forms, a multitude of instruments have been developed to independently verify, describe, quantify or characterize nuclear material [5]. This thesis covers developments of analysis tools related to one such instrument, the Digital Cherenkov Viewing Device (DCVD). The DCVD is used to measure the Cherenkov light produced by spent nuclear fuel assemblies in wet storage, i.e. stored in water pools. Based on the presence, characteristics and intensity of the Cherenkov light, the properties of the nuclear fuel assembly can be verified. Considering the vast amounts of nuclear material existing in the form of spent nuclear fuel assemblies in this type of storages worldwide, it is important that the verification tools are both accurate and time-efficient. Accordingly, attention is paid to both the practical aspects of the developed tools and to the accuracy and precision in comparison to the currently used tools. 1.2 Outline of the thesis This thesis is based on seven scientific papers, which can be found at the end of this thesis. The key findings of all the papers are presented in the comprehensive summary, of which you are now reading the first chapter. Chapter 2 presents the fundamentals of nuclear safeguards, in terms of history, aims, and techniques and methods used. It also presents which nuclear materials are under safeguards, how the materials are verified, and provides the context in which the work summarized in this thesis should be seen. Chapter 3 introduces nuclear fuel assemblies, their design, and safeguards aspects that should be considered when verifying spent nuclear fuel assemblies. Important parameters describing the assemblies are presented, and differences in physical design for assemblies of different reactor types are discussed. Chapter 4 presents Cherenkov light and the physics behind its occurrence, and discusses how the Cherenkov light can be used to verify nuclear fuel assemblies. Chapter 5 introduces the DCVD and the measurement methodology used, and details how the DCVD data is used to verify spent nuclear fuel assemblies in wet storage. The chapter also presents some earlier research that has been done on safeguards verification with the DCVD prior to this thesis, and presents how this work allows for the capabilities of the instrument and associated analyses to be extended. Chapter 6 summarizes the Monte-Carlo simulations that have been performed as part of this work. The code used for the simulations is presented, and its capabilities are shown. Simulation results are presented for nuclear fuel rods, assemblies, and assemblies stored close to other neighbouring assemblies in wet storage. These results are primarily based on papers I and II, but also includes papers IV and VI. 14

15 Chapter 7 presents the Cherenkov light prediction tools that have been developed in this work, and how these tools extend the capabilities of the DCVD verification methodology compared to the previously used one. The tools developed can be used to predict the Cherenkov light production in isolated assemblies, to predict the light contribution due to nearby neighbouring assemblies, and to predict the effect on the measured light intensity due to various structural components of the assemblies. The performance of the prediction tools have been evaluated based on experimental data. The results presented in this chapter are based on papers III, IV, V and VI. Chapter 8 presents work done on improving the background-subtraction method used in DCVD measurements. An improved method is proposed and evaluated using experimental data. This chapter is based on paper VII. Finally, chapter 9 provides some concluding remarks on what have been considered the most important outcomes of this work, and chapter 10 discusses possible future work that can be done to further improve the performance of the DCVD and its associated analysis, based on the key findings of this thesis. For formal reasons, it should be noted that parts of chapter 2 and 4 are based on the author s licentiate thesis [6]. The material has been adapted to better fit into this work, but some portions of the text and some figures may have remained identical to [6]. 15

16 2. Nuclear safeguards 2.1 The legal framework for nuclear safeguards The Nuclear Non-Proliferation Treaty (NPT) opened for signatures in 1968 and entered into force in To date, the treaty has 191 signatory states [7], making it one of the most adhered to arms limitation and disarmament treaties in history. Currently, only India, Israel, Pakistan and South Sudan have not signed the treaty, and North Korea signed the treaty in 1985 but withdrew in The NPT serves three main purposes: To prevent the proliferation of nuclear weapons. The NPT prohibits the five nuclear weapon states (NWS) recognized by the treaty (China, France, Russia, the United Kingdom and the United States) from transferring nuclear weapons to other states. The treaty also prohibits the NWS from transferring equipment that can be used to produce nuclear weapons, or to encourage other states to obtain nuclear weapons. The signatory non-nuclear weapons states (NNWS) are obliged to refrain from receiving assistance in or trying to develop nuclear weapons. To promote nuclear disarmament. The NPT states that the NWS shall pursue negotiations in good faith for nuclear disarmament, though the NPT does not impose any nuclear disarmament agreements itself, and it does not set any time limit on when the disarmament should be completed. To promote peaceful use of nuclear technology. The NPT acknowledges the right of all parties to the treaty to develop nuclear technology for peaceful purposes. The treaty also encourages international cooperation on nuclear development, provided that the states can demonstrate that their nuclear programs are not being used for the development or production of nuclear weapons. As part of the NPT, the signatory NNWS are required to sign a safeguards agreement with the International Atomic Energy Agency. Under this agreement, all nuclear material and nuclear activities shall have safeguards applied to them, to verify that no nuclear material is diverted for production of nuclear weapons, and that the nuclear facilities are used only for peaceful purposes. The objectives of nuclear safeguards is the timely detection of diversion of nuclear material for the manufacture of nuclear weapons, or for other unknown purposes, and the deterrence of diversion by the risk of early detection. 16

17 The safeguards agreement signed by the NNWS is called the Comprehensive Safeguards Agreement [8], and under this agreement the IAEA has the right and obligation to ensure that safeguards measures are applied to all nuclear material in the state, and to verify that no material diversion takes place. Consequently, the IAEA can and shall provide credible and independent assurances that states are honouring their obligations and do not pursue obtaining nuclear weapons. In addition to the comprehensive safeguards agreement, a total of 146 states have also signed the Additional Protocol (AP), further extending the rights of the IAEA to inspect facilities suspected of being used for nuclear activities. More information on the IAEA safeguards legal framework can be found in [9]. In addition to the IAEA, other organizations are also part of the international safeguards work. For example, Euratom is a European organization founded under the Euratom treaty, with the purpose of creating a specialist market for nuclear power in Europe, and developing nuclear energy in Europe. As part of their work, Euratom perform inspections at nuclear facilities, and the goals of the inspections includes verifying that no nuclear material has been diverted, and that no nuclear facility is used for other purposes than intended. Euratom frequently performs safeguards inspections together with the IAEA in the European States. There are also national organizations working with domestic safeguards; one example is the Swedish Radiation Safety Authority, or Strålsäkerhetsmyndigheten (SSM). SSM has a mandate to work proactively and preventively with nuclear safety, radiation protection and nuclear non-proliferation in Sweden [10]. Within nuclear non-proliferation the authority works with export control, safeguards as well as illicit trafficking of nuclear material. SSM has also been appointed the task by the Swedish parliament of providing the IAEA with a support program concerning safeguards, where research and training, specifically for spent nuclear fuel verification, plays a major role. Furthermore, SSM supports scientific research of value for the work of the authority, which provides a scientific foundation to its recommendations and regulations. 2.2 Material and facilities under safeguards The foundation for verifying that no diversion of nuclear material has occurred lies in material accountancy. Under a safeguards agreement, a State must establish a bookkeeping system containing all nuclear material present in the State, and any material entering or exiting the state. The IAEA performs inspections to verify that the bookkeeping is correct and complete, and that all material is accounted for, thus verifying that no material has been diverted. During 2016, the IAEA collected and evaluated over 1 million nuclear materials reports [11]. 17

18 A central concept in IAEA safeguards is the "Significant Quantity" (SQ), which is "the approximate amount of nuclear material for which the possibility of manufacturing a nuclear explosive device cannot be excluded" [12]. The concept of a SQ takes into account unavoidable losses in the conversion and manufacturing processes required to produce a nuclear weapon. A SQ should not be confused with the critical mass of a nuclear material, which is lower. Two elements of particular importance for nuclear safeguards are uranium and plutonium. For uranium, there is one naturally occurring fissile isotope, 235 U. This isotope can be used in nuclear weapons, but it must first be separated from the much more abundant isotope 238 U, since natural uranium contains about 99.3% 238 U and only 0.7% 235 U. The process of removing 238 Uto increase the fraction of 235 U is called enrichment, and for a nuclear weapon the uranium is typically enriched to more than about 90% 235 U. Plutonium, on the other hand, does not occur in nature, but can be produced in a nuclear reactor. If 238 U absorbs a neutron, it will turn into 239 U, which will beta decay twice, at a half-life of in the order of a few days, turning it into 239 Pu, i.e. uranium is transmuted to plutonium. Once plutonium has been produced in a reactor, it can be chemically separated from the fuel, which is less complicated than uranium enrichment. The mass of one SQ depends on the type of material, and the SQ values for 235 U and plutonium are given in table 2.1. Note that for plutonium, certain isotopes are undesirable in a nuclear weapon for practical reasons, but within the safeguards framework all Pu isotopes are conservatively considered equally useful for weapons manufacturing [13]. By the end of 2016, there were a total of SQs of nuclear material under IAEA safeguards [11]. Table 2.1. Significant quantities for fissile materials of relevance in the context of nuclear fuel [12]. Material Significant Quantity Pu 8kg High-enriched U ( 235 U 20%) 25 kg 235 U Low-enriched U ( 235 U < 20%) 75 kg 235 U The IAEA has also set up detection timeliness goals, to ensure that the diversion of any nuclear material can be detected before the diverter has had enough time to convert it to a nuclear weapon. Different materials have different timeliness goals, reflecting the estimated time required to convert the material to a weapons-useable form, and these timeliness goals determine the frequency of inspections for these materials. Nuclear materials that can be used in the manufacturing of nuclear weapons without further enrichment or transmutation are referred to as direct-use materials, and are associated with short timeliness goals and frequent inspections. Materials falling in this category are e.g. Pu in fresh nuclear fuel assemblies of mixed-oxide type (see section 3), or high-enriched uranium ( 235 U 20%). Materials requiring addi- 18

19 tional enrichment or transmutation before being usable in a nuclear weapon, such as low-enriched U ( 235 U < 20%), have longer timeliness goals. Irradiated nuclear material such as spent nuclear fuel is also associated with longer timeliness goals, due to the difficulty of handling the strongly radioactive fission products present, and the difficulty of separating the nuclear material from all other fission products. The timeliness goals specified by the IAEA are presented in table 2.2. Table 2.2. Timeliness goals defined by the IAEA for detecting diversion of one or more SQ of nuclear material [12]. Direct use material refers to material that can be used to manufacture a nuclear weapon without transmutation or further enrichment. Material Example of material Timeliness goal Unirradiated direct- MOX fuel 1 month use material High-enriched U ( 235 U 20%) Irradiated direct- Spent fuel 3 months use material Indirect- Low-enriched U ( 235 U < 20%) 12 months use material In addition to material accountancy, design schematics of all nuclear facilities must be provided to the IAEA by the signatory States, and the physical design of the facilities is verified through inspections. This allows the IAEA to verify that the facilities are being used as declared. The inspections are also aimed at verifying the absence of undeclared activities, and with the introduction of the AP, the IAEA has gained extended rights to inspect also undeclared facilities in a State, further strengthening this capacity. 2.3 Safeguards verification of nuclear material Several instruments have been developed to assess nuclear material, in order to allow inspectors to independently characterize and verify it. A comprehensive survey of the safeguards techniques and equipment used by the IAEA can be found in [5]. Two general types of methods are commonly used when verifying nuclear material, Destructive Assay (DA) and Non-Destructive Assay (NDA). DA measurements are typically performed on samples of nuclear materials, which are sent to laboratories for analysis. Parts of, or the full sample, is consumed in the analysis, since DA methods requires that the samples are altered chemically or physically. DA usually offers superior precision compared to NDA, being able to identify a material and its isotopic composition with a high level of detail. Some downsides are that DA can only be used when it is possible to extract samples for analysis, such as when the nuclear material is handled 19

20 in bulk, and that sending a sample to a laboratory and analysing it is timeconsuming and sometimes difficult. NDA measurements typically make use of the gamma or neutron radiation emissions from a nuclear material. This radiation carries information about the material, and since it can penetrate relatively thick layers of materials, such as some storage containers, the radiation can be detected from the outside of the container. Thus, NDA measurements can verify and characterize nuclear material without altering the material itself, and there is often no need to open up a container to verify its contents. NDA measurements are typically quick, and may give immediate information about the measurement results, but they are rarely as precise as DA measurements. Verification of nuclear material and its accountancy can be done at different levels of precision, depending on the inspection goals, the material properties and on which instruments are available to assess them. The three main levels of verification used by the IAEA are [12]: Gross defect verification, where the inspector verifies the presence or absence of nuclear material in an inspected item. This level of verification is often performed using NDA techniques, since low precision is required and fast measurements are preferred. Partial defect verification, where the inspector verifies that a fraction of the nuclear material has not been diverted from an inspected item. The current IAEA requirement on instruments used to perform this level of verification is that they must be able to reliably detect a 50% removal or substitution of nuclear material from the item. Bias defect verification, where the inspector verifies that small portions of the nuclear material has not been diverted from an inspected item. This requires instruments and measurements with a high degree of precision. Once the nuclear material has been successfully verified, the IAEA deploys containment and surveillance (C/S) techniques to verify that no material is diverted at a later stage. Commonly used C/S techniques involve seals used to verify that containers remain sealed, or video surveillance to monitor that no diversion activities occurs at a site. The seals and surveillance ensure that the authorities maintain Continuity of Knowledge (CoK), by knowing that the material has not been diverted or altered since the last inspection. By maintaining CoK, the absence of diversion can be verified by inspecting the applied C/S devices, without having to re-verify the nuclear material. However, should the CoK be lost, all material affected will need to be re-verified, to ensure that no material has been diverted during the time that the CoK was lost. 20

21 3. Nuclear fuel assemblies The nuclear material used in a civilian power-producing reactor is in the form of Nuclear Fuel Assemblies. The design of these assemblies ensures that a controlled fission chain reaction can take place, and that the heat produced in the fuel material can be transported away, to be used to produce electricity. The design also ensures that radioactive fission products produced by fission events stay inside the assembly, and that no radioactive isotopes leak out into the reactor. A nuclear fuel assembly is normally the smallest unit of nuclear material handled at a reactor site, and is often referred to as an item in a safeguards inspection (see section 2.3). The two most common types of commercial reactors in the world are Boiling Water Reactor (BWR) and Pressurized Water Reactor (PWR). In a BWR, the energy released by the nuclear chain reaction produces steam directly inside the reactor vessel, which is led to a turbine where the steam is used to produce electricity. In a PWR, the high pressure in the reactor vessel keeps the water from boiling. Instead, the hot water is led to a steam generator, where it produces steam in a secondary loop. Due to the different modes of operation of these facilities, BWR and PWR nuclear fuel assemblies have noticeably different designs. Still, many of their properties are similar, and safeguards verification procedures do not differ significantly between fuel assembly types. 3.1 Physical design of nuclear fuel assemblies Most of the commercial nuclear reactors in the world use uranium dioxide (UO 2 ) as fuel, enriched to about 4-5% of 235 U, in order to increase the fissile content. A few reactors use a mixture of UO 2 and plutonium dioxide (PuO 2 ), which is referred to as Mixed-Oxide Fuel (MOX). In MOX fuel, 239 Pu is generally the dominant fissile isotope. To manufacture a nuclear fuel assembly, the fuel material is first turned into cylindrical pellets, with a height and diameter of typically about 1 cm. UO 2 and MOX are ceramic materials, which can withstand high temperatures without melting, and which can trap fission products inside the fuel material to ensure that they do not leak out. Next, several hundred pellets are stacked inside a metal tube, forming a fuel rod or pin, which is typically around 4 m in length. The tube, or cladding, is generally made of zircaloy, a metal alloy consisting primarily of zirconium, with a thickness of about 1 mm. Since 21

22 zirconium has a small neutron capture cross-section, few neutrons are lost by being absorbed by the zirconium, which is beneficial for sustaining the fission chain reaction. The fuel rods are assembled into a fuel assembly, with a BWR assembly typically containing rods and a PWR assembly typically containing rods. The fuel rods are held in position by spacers, which are manufactured from zircaloy or stainless steel (typically Inconel steel), and by steel top and bottom plates. At the top plate there is also a lifting handle, used when moving the assembly. In total, the length of an assembly is on the order of 4 m, and the width is around cm. As a gross means to control the neutron flux in the reactor, a BWR uses control rods (sometimes called control blades for a BWR), containing a neutron absorbing material, which can be inserted or removed from the reactor core during operation. The main use of the control rods are for stopping and starting the reactor. The control rods are inserted in between the assemblies, consequently the outer dimensions of all BWR assemblies in one reactor core must be similar to provide space for the control rods. However, the configuration of fuel rods inside the assembly can be chosen more freely. Thus, BWR assemblies of noticeably different designs can be present in the same reactor, and the number of fuel rods and their dimension may vary from assembly to assembly. In addition to the fuel rods, which are typically arranged in a square lattice in the assembly, there may also be water channels present to provide a higher flow of water in desired parts of the assembly. Some rod positions may contain part-length rods, to ensure that there is more space between the fuel rods at the top of the assembly as water turns into steam, which requires more space. BWR assemblies also feature a fuel channel, i.e. the entire assembly is placed inside a zircaloy containment box, to ensure that water does not escape the assembly when boiling occurs. In total, a fresh BWR assembly typically contains kg of UO 2 or MOX. A PWR also uses control rods, but these are inserted into the assemblies rather than in between them. As for the BWR, their main use is for starting and stopping the reactor. Since the control rods are inserted into the assemblies, the PWR assemblies feature guide tubes into which the control rods are inserted. For all assemblies accepting the same control rod type, the guide tubes must be placed in the same position, and because of optimizations, the fuel rod placement and dimensions will vary little for these assemblies. However, there are still some variations. One notable difference in the context of this work is that the top plate designs may vary noticeably, which affect the transport of Cherenkov light (see section 7.2.3). PWR assemblies also tend to be bigger than BWR ones, as illustrated in figure 3.1, and they typically contain around kg of UO 2 or MOX. 22

23 Figure 3.1. Left: Example of the fuel rod placement in a PWR 17x17 assembly Right: Example of the fuel rod placement in a BWR 8x8 assembly. The Cherenkov light production in these two assembly types have been studied in chapter 6. The BWR assembly has one rod position functioning as a water channel, and is enclosed by a fuel channel, illustrated schematically in the figure. The PWR assembly features a central instrumentation tube, and 24 control rod guide tubes. The BWR assembly is 13.6 cm wide, and the PWR assembly is 21.4 cm wide. The assembly height is around 4m. 3.2 Fuel usage in a reactor Nuclear power plants typically operate in cycles, with a long period of running the reactor, and a short period of downtime for replacing spent fuel assemblies and performing maintenance work. For Swedish reactors, the running time is typically about 11 months, with one month of downtime. The downtime is generally scheduled in the summer when the Swedish electricity consumption is lower. For countries with less pronounced seasonal electricity usage differences, longer cycles are often used, and 18 or even 24 months are common. Significantly longer running times are however not possible in most commercial reactors, since the reactor core cannot be loaded with too much fissile material, and the fuel must be replaced once it is used up. As the fuel material undergoes fission in the reactor, fission products are created, which build up as the fuel is irradiated. Many of the fission products are radioactive, and will decay until they have turned into stable isotopes. Several fission products are relatively long-lived, and consequently the fuel assemblies will emit radiation also after being discharged from the reactor. The activity is high enough that a noticeable amount of decay heat is produced. To shield the environment from the radiation, and to cool the residual heat, the assemblies are often stored in water. For this reason, reactors generally have a storage pool next to the reactor to store recently discharged assemblies. A civilian nuclear reactor, such as the ones in Sweden, will typically replace 20-25% of its fuel assembly inventory each year, corresponding to assemblies, or significant quantities of Pu. These assemblies are stored at the reactor for one to two years, after which their radioactivity has decayed 23

24 to a level low enough that they can be moved to the central Swedish interim storage for spent nuclear fuel, Clab. Worldwide, dry storages are also common, where the spent fuel assemblies are put in massive canisters to shield the surrounding environment from the radiation. Other than undergoing nuclear fission, the elements in the nuclear fuel may instead absorb neutrons, and turn into heavier isotopes. Thus, plutonium is produced, as described in section 2.2, as well as even heavier isotopes. These heavy metals are radioactive, and some have very long half-lives resulting in a need for long-term storage of the used fuel material. When a UO 2 fuel assembly is discharged, it contains about 1% 235 U, 1% Pu, 3-4% fission products, and the rest is 238 U, with some trace amounts of elements heavier than plutonium present. Two parameters used to describe a spent nuclear fuel assembly are its burnup (BU) and cooling time (CT). The BU is a measure of the amount of energy that has been released from the fuel material through fission, and it is given in units of MWd/kgU (Mega-Watt days per kilogram of uranium) or GWd/tU (Giga-Watt days per ton of uranium). Typical BU values of discharged commercial nuclear fuel assemblies are in the order of MWd/kgU, or equivalently around 1 million kwh per kg uranium. CT is the time since the assembly was discharged from the reactor. High BU results in a large production of radioactive isotopes in the fuel, while long CT implies that a relatively larger fraction of the activity has decayed away. Once a fuel assembly has been discharged from a reactor following its final cycle, it is often referred to as either a spent or a used fuel assembly. In this work, assemblies are generally referred to as irradiated, since assemblies that will be further irradiated in the reactor are also of interest. Since the nuclear power plants optimize the use of the nuclear fuel, most assemblies are used in a similar way. Depending on the reactor type, the fuel assemblies are used for 3-6 years, until they have reached their design BU, after which they are discharged. Occasionally, assemblies will be used in a different way from this standard usage. As an example, a fuel assembly may require reparation after suffering damage, which will result in it spending one or a few cycles outside the reactor, before being used again. Furthermore, some assemblies from the first core loading of a reactor may need to be replaced more quickly, resulting in a low burnup at discharge. 3.3 Safeguards verification of irradiated nuclear fuel assemblies Depending on the design of a nuclear fuel assembly, one or a few irradiated assemblies will contain one SQ of nuclear material. Accordingly, an important task carried out by safeguards inspectors is verifying that no nuclear material is diverted from the irradiated fuel assemblies. Of particular importance 24

25 is plutonium, since it is abundant in spent fuel, and can relatively easily be chemically separated from the other elements in the fuel assembly. Verifying the nuclear material in an irradiated fuel assembly is a challenging task, since the material is not accessible, preventing DA techniques from being used, and since the intense gamma and neutron radiation emitted by the fission products and minor actinides present interferes with direct NDA measurements of the fissile material. For this reason, safeguards verification of irradiated nuclear fuel assemblies often aim at verifying the BU and CT of the assemblies. This is often done by measuring the radiation emitted by the fission products, to verify that the abundance of fission products is consistent with irradiated nuclear fuel. While such indirect measurements do not assess the quantity of nuclear material, which is what is of interest to safeguards, the measurements can indicate that the nuclear fuel assembly has been used as declared, and that it has not been tampered with. The measurements can thus give an indication that no diversion has taken place, even if the nuclear material is not measured. An additional complication is that the intense radiation emitted by the assembly necessitates that it is stored in strong radiation shielding, which may make it difficult to place a detector close to the assembly. In the case of assemblies in wet storage, the measuring equipment may have to be submerged in the water to get close to the assembly, which presents additional technical challenges. As mentioned in section 2.3, different diversion scenarios are considered, requiring different instruments and measurement methodologies to detect diversion in irradiated nuclear fuel assemblies: For gross defects, diverting one or a few irradiated assemblies is sufficient to divert one SQ of Pu. To detect this type of diversion, the entire inventory needs to be verified to find if any assemblies are missing or replaced with non-radioactive substitutes. Consequently, the measurements must be fast to be able to cover a large assembly inventory, but they do not need to be very precise, since they only have to determine if an item under study is radioactive or not. Out of the safeguards instruments used by the IAEA to verify irradiated fuel assemblies [5], a majority are used for gross defect verification. For partial defects on the 50% level, diverting fuel rods from about 4-10 irradiated assemblies is sufficient to divert one SQ of Pu. This is still relatively few assemblies, and to ensure that these assemblies are covered in a verification campaign, a large part of the fuel assembly inventory needs to be measured. Thus, detecting this type of diversion calls for a fast measurement technique, which must also be sensitive enough to detect if 50% or more of the fuel rods have been removed or replaced with non-radioactive ones. The DCVD is suited for this scenario, since measurements are fast and since it can be used for partial defect verification [14], as further detailed in chapter 5. Other than the DCVD, the 25

26 FORK detector is occasionally used for partial defect verification at this level [15]. For bias defects, diverting single rods from irradiated assemblies is required to divert one SQ of Pu. This is a substantial number of assemblies, and thus a sampling of a relatively small fraction of the assembly inventory is sufficient to detect with high probability if this type of diversion has occurred. Consequently, measurement techniques for detecting this type of diversions can be more time-consuming, but they have to be highly precise to detect a single removed or substituted rod in an assembly. At present, gamma tomography is the only method approved by the IAEA to perform this type of verification [16]. One may also identify diversion scenarios with defect levels in between the three presented levels. This opens up for additional considerations with respect to time consumption and precision of the techniques used. In this context, one may note that enhancing the precision of the DCVD assessments would open up for additional segments of the defect levels to be covered, which is one motivation for the work of this thesis. 26

27 4. Cherenkov light 4.1 The physics of Cherenkov light In 1934 the Soviet scientist Pavel Cerenkov observed that when water was subjected to ionizing radiation, it emitted blue light. While initially thought to be caused by fluorescence, through careful observation he concluded that this light was produced by other means, and between 1934 and 1937 he published his investigations. In 1937 Ilya Frank and Igor Tamm provided a theoretical explanation of this light [17], explaining the mechanism behind its production and characterizing its properties. For this discovery and explanation, the three were awarded the Nobel Prize in physics in 1958 [18]. Cherenkov light is produced when a charged particle moves faster than the speed of light in a medium. While nothing can move faster than the speed of light in vacuum (c), the effective speed of light in a medium is lower. For a medium with refractive index n it is v l = c/n, and for example in water v l 0.75c for visible light. Thus, any charged particle with velocity v p in the range 0.75c < v p < c will radiate visible Cherenkov light in water. For an electron, this corresponds to a threshold kinetic energy of about 250 kev. When a charged particle propagates in a dielectric medium, it will disrupt the local electromagnetic field, polarizing the medium. If the particle moves slowly, this disruption will elastically relax back to an equilibrium state, and no photons are radiated. However, if the particle is moving faster than the speed of light in the medium, a disturbance is left in the wake of the particle, which will emit its energy in the form of a coherent shockwave, i.e. Cherenkov light is emitted. A common analogy to this phenomenon is the sonic boom of a supersonic aircraft. When a charged particle emits Cherenkov light, the radiated photons form an angle θ to the particle propagation direction. For a particle with velocity β = v p /c travelling in a medium with refractive index n, this angle will follow the relation given by equation 4.1, as illustrated in figure 4.1. cosθ = 1 (4.1) βn The spectral characteristic of the Cherenkov light is given by the Frank- Tamm formula [17], presented in equation 4.2 [19]. This equation gives the number of Cherenkov photons N emitted in a wavelength range dλ, for a charged particle with electric charge z traversing a distance dx in the medium. In equation 4.2, α is the so-called fine-structure constant (which is approximately 1/137). Equation 4.2 is valid as long as the expression in parenthesis is 27

28 v l t = c n t θ v p t = β c t Figure 4.1. Cherenkov light is produced at an angle θ to the charged particle propagation direction, determined by equation 4.1. Consequently, the produced Cherenkov light forms a cone. The length of the sides of the triangles are marked in the figure as a function of the particle and light velocity. Note that the refractive index n of a medium typically depends on photon wavelength, and as a result the angle θ is wavelength-specific. larger than zero, which corresponds to particles moving fast enough to radiate Cherenkov light, i.e. v p v l. d 2 ( ) N dxdλ = 2παz2 1 λ 2 1 β 2 n 2 (4.2) (λ) Equation 4.2 also show that the spectral intensity is proportional to 1/λ 2. As a result, the number of radiated photons of a short wavelength (such as blue) is higher than that of longer wavelengths (such as red). Consequently, Cherenkov light appears blue to the naked eye, although the Cherenkov light intensity can be even higher at shorter wavelengths, such as ultraviolet (UV). For Cherenkov light in water, one should note that at wavelengths shorter than UV, water is no longer transparent, and radiated Cherenkov photons of such wavelengths are immediately absorbed. No matter the medium, Cherenkov light cannot be produced with energy above roughly that of x-rays. 4.2 Cherenkov light from irradiated nuclear fuel assemblies As mentioned in chapter 3, irradiated nuclear fuel assemblies are often stored in water, both for radiation protection and for decay heat removal. The intense radiation emitted by these assemblies cause high-energy electrons to be 28

29 Relative Cherenkov intensity [arb. unit] Cherenkov spectrum (linear scale) Attenuation (log scale) Wavelength [nm] Attenuation coefficient [cm 1 ] Figure 4.2. The green line show the attenuation coefficient of water for soft-uv and visible light (on the log scale on the right axis) based on data from [20] and [21]. The blue line show the Cherenkov light spectrum measurable by the safeguards instrument considered in this work (on the left axis). The spectrum was calculated using equation 4.2 including the refractive index of water, and assuming a 480 kev electron, corresponding to the maximum energy of an electron after Compton-scattering of a 662 kev 137 Cs gamma. It was also assumed that the light must traverse 10 m of water, which attenuates the light, corresponding to the depth at which irradiated fuel assemblies are typically stored. released in the water surrounding the fuel assembly. These electrons will in turn radiate Cherenkov light as they propagate through the water. Thus, the presence of Cherenkov light surrounding an item indicates that the item is radioactive, and the quantity of the Cherenkov light depend on the quantity and energy of the radiation emitted by the item. Several safeguards instruments have been developed to measure the Cherenkov light emitted by a nuclear fuel assembly assembly, to verify that it is a strongly radioactive item and to quantify the Cherenkov light emitted. One such instrument, the DCVD, which is the subject of this thesis, is further described in chapter 5. As shown in figure 4.2, the Cherenkov light intensity peaks in the soft-uv range in water. For this reason, the safeguards instrument considered in this work was designed to be sensitive to the UV-light component of the Cherenkov light, where the intensity is the highest. By using a UV filter, visible light components are also excluded from the measurements, making them less sensitive to background light such as facility lighting. In irradiated nuclear fuel, several sources of ionizing radiation are present that cause Cherenkov light to be produced. One significant source of radiation is electrons produced in beta decays. These electrons frequently have more than 250 kev of kinetic energy [22], allowing them to produce Cherenkov light in water. However, electrons are effectively stopped in materials as they 29

30 continuously lose energy when interacting with electrons in the material. Electron ranges tend to be on the order of 1 mm per MeV in dense material, and on the order of 2 mm per MeV in low-density materials [23]. Since the cladding thickness is on the order of 1 mm and typically beta energies are lower than 1 MeV, electrons produced in the fuel material through beta decays may be expected to contribute negligibly to the Cherenkov light intensity in the water surrounding the fuel assembly. However, such contributions to the Cherenkov light production may still require attention. Another major source of ionizing radiation is gamma rays, which are frequently emitted in radioactive decays. Since gamma rays are high-energy photons, they carry no charge and do not directly emit Cherenkov light, but they can interact with matter, causing secondary high-energy electrons to be released. The gamma rays can also penetrate the fuel material and cladding relatively easily, hence they can interact in the water. The interactions of relevance to this work, i.e. those that can produce electrons with a kinetic energy above the 250 kev threshold for Cherenkov light production in water, are [23]: Photoelectric absorption. An atom absorbs the gamma-ray photon, and as a result it ejects one of its electrons. Any energy carried by the initial photon above the binding energy of the ejected electron becomes kinetic energy. Since electrons are relatively loosely bound in light materials such as oxygen and hydrogen, a gamma ray with only slightly more energy than the threshold energy can cause production of Cherenkov light. Compton Scattering. The gamma ray scatters on an electron, transferring parts of its energy to the electron. A gamma ray must have above roughly 420 kev of kinetic energy for a Compton-scattered electron to be able to recieve kinetic energy above the threshold for Cherenkov light production. Note that the cross section for scattering (as given by the Klein-Nishina formula [19]) gives at hand that the most likely scattering modes change the gamma-ray direction little, and consequently transfer very little energy to the electron. Instead the lower-probability, highangle scattering is what can produce electrons of sufficient energy to radiate Cherenkov light. Pair production. If a gamma ray has energy above twice the rest mass of an electron (i.e. above 1.02 MeV) it can be converted into an electronpositron pair, and any excess energy is converted into kinetic energy of the newly produced particles. A gamma ray with energy above roughly 1.5 MeV can then create an electron-positron pair having sufficient kinetic energy that they can radiate Cherenkov light in water. The positron will also annihilate on an electron in the material after it has lost most of its kinetic energy, which produces two 511 kev annihilation photons that may in turn result in the production of additional Cherenkov light. 30

31 Figure 4.3. A schematic of the dominant path of Cherenkov light production caused by gamma decays in nuclear fuel assembly. (1) A gamma ray is emitted following a radioactive decay. (2) The gamma ray Compton-scatters on an electron in the water, transferring its energy to the electron. (3) The electron radiates Cherenkov light. It has been shown in paper I that Compton scattering is the dominant type of interaction in water, when considering the radiation emitted by the fuel material with sufficient energy to produce Cherenkov light in water. This procedure is illustrated in figure 4.3. In the fuel material, photoelectric absorption will dominate up to about 800 kev, which is low enough that the photoelectron is not expected to escape the fuel rod with sufficient energy to produce Cherenkov light in the water. At energies above 800 kev, Compton scattering becomes dominant, and such high-energy electrons could potentially escape the fuel with more than 250 kev of kinetic energy. Pair production is not expected to contribute significantly to the interactions for the gamma-ray energies encountered in decays of fission product isotopes. Heavier isotopes present in the fuel material may spontaneously fission, and will emit neutrons while doing so. These neutrons cannot directly produce Cherenkov light due to their lack of charge, but they can cause other nuclear reactions to occur. The most likely neutron interaction of relevance to Cherenkov light production is absorption in a nuclei in the fuel material, which may produce new nuclei that decay with beta and/or gamma emissions. However, the intensity of neutron emission is expected to be much lower compared to beta and gamma emissions, and consequently the neutrons are not expected to contribute significantly to the Cherenkov light production. Heavier isotopes can also alpha decay, but due to the low intensity and since the alpha particles are easily stopped, they are not expected to contribute significantly to Cherenkov light production. For the produced Cherenkov light to be detected, it must escape the fuel assembly and reach the detector. However, due to oxidation in the harsh reactor environment, and due to material depositions (CRUD), the surfaces of any fuel rods or other structural components are typically dark, and thus the surfaces absorb any incoming visible or UV light to a large extent. Since Cherenkov light measurements are done from above the assembly, only the 31

32 vertical Cherenkov light can escape the assembly and be detected, as more horizontally directed light is likely to encounter a fuel assembly surface and be absorbed. As an additional consequence, the Cherenkov light that can be detected will be highly collimated along the direction of the fuel rods, and the intensity that can be measured depends strongly upon how the instrument is aligned above the assembly. Thus, when investigating the Cherenkov light produced in an assembly and its propagation to a detector, the vertical light component is of primary interest. 32

33 5. The Digital Cherenkov Viewing Device, DCVD 5.1 History Several instruments have been developed to assess irradiated nuclear fuel in wet storage based on the Cherenkov light produced, and the two instruments currently in use by the IAEA are the Improved Cherenkov Viewing Device (ICVD) and the Digital Cherenkov Viewing Device (DCVD). The ICVD is an analogue instrument, which converts UV light to visible light, allowing an inspector to visually inspect the Cherenkov light emitted by an assembly. The ICVD does not allow for storage of images for further processing or documentation. Furthermore, due to the modest efficiency of the light conversion, the ICVD is not sensitive enough to allow an inspector to verify assemblies with weak Cherenkov light emission, such as assemblies with long CT and low BU. The ICVD currently used (as of 2018) by the inspectors is the Mark IV CVD, which has been in use for close to thirty years [24]. The DCVD was originally developed to enable verification also of lowintensity assemblies using Cherenkov light. The initial target was the ability to reliably verify assemblies with a cooling time of 40 years and a burnup of 10 MWd/kgU, corresponding to low-bu assemblies from the first core loading of a reactor. In field tests, the initial DCVD prototype could not only measure the Cherenkov light from such assemblies, but it was also able to measure the light from assemblies with cooling times of 30 years and a burnup of only 1.1 MWd/kgU [25]. It was later realized that the DCVD could not only be used to qualitatively provide an image of the Cherenkov light emitted by an assembly, but it could also be used for quantitative measurements of the emitted Cherenkov light intensity. The recorded intensity is used to detect partial defects in an assembly, based on the change in Cherenkov light intensity caused by removing radioactive rods from an assembly. The DCVD is most frequently used for partial defect verification, as the ICVD is easier to use for gross defect verification. 5.2 Measuring fuel assemblies with a DCVD During a measurement with the DCVD, the instrument is normally mounted onto the railing of a fuel handling machine, as shown in figure 5.1. The DCVD is looking down into the fuel assembly storage pool, where the assemblies are 33

34 typically covered by around 10 meters of water, as schematically shown to the left in figure 5.2. The result of a measurement is an image of the Cherenkov light emitted by an assembly, an example of which is shown to the right in figure 5.2. The digital image obtained from the measurement can then be analysed, as further detailed in section 5.3. When qualitatively measuring the Cherenkov light emission from an assembly, using either an ICVD or a DCVD, the instrument is positioned above and then moved across an assembly, to confirm the presence of Cherenkov light, and to verify that the light is collimated, as discussed in section 4.2. The presence and characteristics of the Cherenkov light then confirms whether or not the item under study is an irradiated nuclear fuel assembly, as opposed to a non-radioactive item. When quantitatively measuring an assembly with the DCVD, the inspector will first align the DCVD above the centre of the assembly, along the direction of the fuel rods (which is close the vertical direction, but the assemblies may be slightly tilted). Next, the inspector manually selects a Region Of Interest (ROI) in the image, containing the fuel assembly and excluding its surroundings. After that, the measurements are performed, including typically three to five measurements per assembly. For each measurement, a backgroundsubtraction is performed, aimed at removing an electronics-induced offset in the pixel values (further described in section 8). The pixel values inside the ROI are then summed to provide a total emitted intensity value of the assembly. The reported assembly intensity value is the average of the three to five measurements. The reason for performing multiple measurements of each assembly is to reduce the effect of noise and changing conditions over time, such as the effect of ripples on the water surface that can slightly distort an image. Note that the pixel values are expected to be proportional to the measured light intensity (further discussed in section 8), but no calibration is done to convert the pixel values to a photon flux. The DCVD detector consists of a Charged-Coupled Device (CCD) chip sensitive to UV-light. The DCVD optics consists primarily of a motorized zoom lens, which allows different zoom levels to be set, and for the focus to be adjusted to ensure that the top of the fuel assembly is in focus. The optics also contains a UV-filter for selecting relevant wavelengths, ensuring that visible light will not be detected. The detector setup can be extended or tilted, to allow the detector to be positioned vertically above a fuel assembly. The DCVD can be powered either by two hot-swappable batteries, or by a power cable if a wall-socket is available. The DCVD contains an on-board computer, which handles the data output from the detector. The user interacts with the DCVD software through a touchsensitive LCD screen. Customised software performs image processing and calculates the total Cherenkov light intensity based on the recorded images provided by the detector. The software also keeps track of which measurement 34

35 Figure 5.1. Top: A DCVD instrument. To the right is the CCD detector and optics, mounted on a yoke that can be extended and tilted. The computer and electronics are housed inside the casing, and the batteries are seen to the left. On top is an LCD screen providing the user interface. Bottom: A DCVD in use. Images courtesy of Dennis Parcey and Channel Systems Inc. 35

36 Figure 5.2. Left: A schematic illustration of the measurement situation when using the DCVD. Note that the assemblies are typically around 4 m in length, and covered by about 10 m of water. Right: An example of an image obtained from a measurement of a PWR fuel assembly with the DCVD. The bright, circular regions are the guide tubes of the PWR assembly, the smaller bright spots are the regions in between fuel rods. corresponds to which assembly, if the user provides information about the assemblies verified in a measurement campaign. The DCVD has several advantages and disadvantages compared to other safeguards instruments, which are considered when selecting an instrument for a verification campaign. Advantages include: Non-intrusiveness: The fuel assemblies are measured where they are stored, and there is no need to move the assemblies to a dedicated measurement station. There is neither any need to insert the device or any associated equipment into the water to get close to an assembly, which reduces the risk of contamination. Speed: Since there is no need for moving any assemblies, measurements are quick, typically requiring approximately seconds for one assembly, depending on the assembly intensity and storage conditions. This speed makes it feasible to verify a large assembly inventory using the DCVD. The DCVD also has some limitations, which must be considered when verifying a fuel assembly inventory: Limited information: The currently used methodology analyses the total Cherenkov light intensity, which depends on the intensity of the ionizing radiation emitted by the assembly. It does not provide any information about the source of the radiation, such as the presence or abundance of fission product isotopes, nor of the fissile contents of the assembly. 36

37 Limited sensitivity: In order to detect a partial defect, sufficiently many rods must have been diverted to affect the total Cherenkov light intensity of an assembly noticeably. Furthermore, some rods may be hidden under the top plate or lifting handle and contribute little to the measured Cherenkov light intensity, making the diversion of such rods difficult to detect using Cherenkov light. As a consequence of these characteristics, the DCVD is well suited for detecting partial defects (as described in section 3.3) in scenarios where a large fraction of the fuel rods in an assembly have been removed or replaced with non-radioactive ones. Previous work has shown that the DCVD is sensitive enough to detect diversions on the order of % removed or substituted rods [14]. Furthermore, the measurements are fast enough that the DCVD can be used to verify a large assembly inventory, to find the relatively few assemblies where such diversion may have taken place. 5.3 Detecting partial defects using a DCVD There are two methods in use to detect partial defects with the DCVD. The first method uses image analysis to identify removed rods, which is based on the identification of bright regions in the images which should be dark due to the expected presence of a fuel rod in that position. This method can thus detect removed rods in visible positions, and it is frequently used for BWR fuel assemblies since individual rods are often visible in BWR assembly designs. An example of an intact BWR assembly and one with two removed rods is shown in figure 5.3. Figure 5.3. Left: A DCVD measurement of a complete BWR assembly. Right: A BWR assembly with two removed rods. Images courtesy of Dennis Parcey and Channel Systems Inc. 37

38 The second method, which is the focus of this thesis, is based on quantitatively measuring the total Cherenkov light intensity from an assembly, and comparing it to a predicted intensity, which is calculated based on the declared assembly information [26]. This method is capable of detecting diversion scenarios where fuel rods have been substituted with non-radioactive replacements. Previously performed simulations [14] have shown that a 50% substitution of irradiated fuel rods with non-radioactive steel rods will decrease the Cherenkov light intensity by at least 30%. Thus, if a measured intensity is 30% or more below the predicted intensity, the fuel is flagged by the DCVD software as an outlier requiring additional investigation, as illustrated in figure 5.4. Key to this procedure is a prediction method with high accuracy, and improving the prediction model is a major part of this work. Furthermore, the predictions must be quickly executed on modest hardware, to allow for in-field use by an inspector. Measured intenisty [arb. unit] Predicted intenisty [arb. unit] Figure 5.4. Example of the analysis performed as part of quantitative Cherenkov light verification. Once the measurements and predictions are available, a least-square fit is performed to find the multiplier that relates the two. The solid line indicates the expected agreement between predictions and measurement, after adjustment with the multiplier. The dashed lines indicate a ±30% deviation. The data point marked with a red circle has a measured intensity more than 30% below expected, and is flagged as an outlier requiring further investigation. An inspector in the field performs quantitative intensity verification according to the following steps: 1. The inspector obtains information about the fuel assemblies present at the facility, including parameters such as assembly type, BU, and CT. These parameters are used to predict the Cherenkov light intensity of the assembly, as further detailed in section 5.4. Based on the declara- 38

39 tions, the assemblies will be grouped according to their type, or physical design. 2. The inspector measures the Cherenkov light emissions from the assemblies in the inventory. If there are not too many assemblies, all of them can be measured; otherwise the inspector will make a random sampling of the assemblies present. 3. For each group of assemblies, a least-square fit is made to find the multiplier relating the predictions to the measurements, corresponding to an assembly-type specific calibration factor. After adjusting the predictions with this multiplier, the measured intensities are compared to the predictions, and any assembly with an intensity deviating more than 30% from expected is flagged as an outlier requiring further investigation. Due to the least-square fitting, the predicted intensity of an assembly need only to correspond to the relative intensity of the assembly, as compared to all other assemblies in the group. While it is in principle possible to predict the absolute intensity, such predictions must take into account the assembly design, the storage conditions, the water quality and the instrument response, information that is not always available with sufficient detail to be included in a prediction. However, in a verification campaign using the same instrument on fuel assemblies of the same type, all stored under the same conditions, these parameters will affect all measurements equally, and thus the relative intensity of the assemblies can be used instead of the absolute intensity. As a consequence of this procedure, analyses can only be made for a certain fuel assembly type if a sufficiently large number of assemblies are available for the calibration and comparison to be relevant Partial defect intensity limits The currently used partial defect intensity limits are based on the work of [14], which showed that a 50% substitution of radioactive fuel rods with nonradioactive steel substitute rods will lower the Cherenkov light intensity of the assembly by at least 30%. These results are based on simulations of different substitution scenarios in a BWR 8x8 and a PWR 17x17 assembly, and the 30% limit comes from the diversion cases most difficult to detect using Cherenkov light. Note that currently, fuel assemblies are tested against a global 30% limit, although there are diversion scenarios on the level of 50% that are expected to lower the Cherenkov light intensity by more than 30%. Simulations of assemblies with partial defects require that DCVD images are simulated, and these simulations are performed in three steps [27]: 1) Simulating the gamma emission spectra of an assembly with a typical BU and CT 2) Simulating the gamma transport and Cherenkov light production in an assembly geometry, and 3) Simulating the propagation of the Cherenkov light 39

40 in an assembly geometry, and its detection in a camera model. Simulations of assemblies with partial defects are necessary, since very few documented assemblies are subject to a significant removal or replacement of rods. Thus, simulations of DCVD measurements are required to assess the performance of the instrument to detect partial defects in assemblies, and the three-step methodology of [27] is capable of simulating DCVD images for assemblies with partial defects. 5.4 First-generation method (1GM) for predicting Cherenkov light intensities The method that has been used previously by the IAEA for predicting the total Cherenkov light intensity from a fuel assembly is based on [28], and will be referred to as the first-generation method (1GM) in this work. This method takes into account the BU and CT of the assembly, which are the two dominant parameters describing the intensity of the Cherenkov light. Furthermore, these parameters are fundamental enough that an inspector should be able to obtain them for any assembly. The predictions rely on pre-calculated Cherenkov light intensities for BWR assemblies of varying BU and CT, which were used to obtain intensity curves relating the BU and CT to the Cherenkov light intensity, as shown in figure 5.5. To obtain a prediction, the operator-declared BU and CT of the assembly under study are used to interpolate the Cherenkov light intensity from the curves in figure 5.5. In later unpublished work, the curves in figure 5.5 were extended to consider longer cooling times, and lower burnups than the ones considered in [28]. To calculate the Cherenkov light intensity curves in figure 5.5, the following simulation procedure was used: 1. The abundance of gamma- and beta-emitting isotopes were calculated using the nuclear fuel depletion code ORIGEN [29], for BWR assemblies with various BU and CT. The six most abundant isotopes were considered, namely 106 Ru, 134 Cs, 137 Cs, 144 Ce, 154 Eu and 90 Sr. The first five of these isotopes undergo gamma decay, and 90 Sr and its daughter 90 Y undergo beta decay. All of these isotopes, or their short lived daughters, decay with energy high enough that Cherenkov light can be produced. A standard irradiation history was assumed when calculating the fission product inventory, which matches the typical irradiation experienced by a fuel assembly in a commercial reactor, with a 12-month cycle The calculated gamma spectrum was used as a source in a Monte-Carlo radiation transport code, simulating the radiation and its interactions in a BWR 8x8 assembly. The simulations included the interactions of the

41 Cherenkov light intensity [arb. unit] MWd/kgU 20 MWd/kgU 30 MWd/kgU 40 MWd/kgU 50 MWd/kgU Cooling time [years] Figure 5.5. Intensity of the Cherenkov light as a function of fuel assembly BU and CT, from [28]. Given the BU and CT of an assembly, the expected Cherenkov light intensity can be interpolated from these curves, forming the first-generation prediction model (1GM). gamma rays with the fuel and water, the production of Cherenkov light, and the transport of the Cherenkov light to a detector position. The result of the simulations was an estimate of the detectable Cherenkov light intensity for an assembly with the simulated BU and CT. This prediction method has proven itself to work well at long cooling times, when the most important gamma-emitting isotope is 137 Cs. This isotope builds up linearly with burnup, and it has a relatively long half-life. Consequently, knowing the BU and CT is sufficient for a good estimate of the abundance of 137 Cs, and thus of the Cherenkov light intensity at long CT. This prediction method does however include several simplifying assumptions, which limit the applicability of the method. The limitations are further discussed in the next section. 5.5 Limitations addressed developing the second-generation prediction method (2GM) While the DCVD has been used successfully for partial defect verification before this work, it is possible to improve the verification procedure and methodology further. Improvements are primarily aimed at developing and enhancing the procedure for predicting the expected Cherenkov light intensity of an assembly. The procedure described in section 5.4 has limitations, some due to the procedure itself, and some due to approximations and simplifications that were necessary at the time it was developed. The primary limitations that are 41

42 addressed in this work to develop the second-generation prediction method (2GM) are: The 1GM considers gamma emissions from the fuel material caused by a limited set of six fission product isotopes, which were found to cause a majority of the Cherenkov light after a few years of cooling. The accuracy of the predictions can be improved if all gamma-emitting isotopes are included, especially for short cooling times when additional shortlived isotopes are present. 42 The 1GM assumes that all beta-decay electrons are stopped in the fuel material, emitting bremsstrahlung as they are stopped. The simulations performed as part of this work, presented in chapter 6, however show that some beta electrons may escape the fuel rods and directly produce Cherenkov light in the surrounding water. Including this contribution can further improve the precision of the predictions. The 1GM assumes a standard irradiation history, matching the typical irradiation an assembly experiences in the reactor. However, for assemblies with a more irregular irradiation history, this assumption is no longer valid. The prediction model could thus be improved to include also the irradiation history. This is particularly important for assemblies with a short CT or an unusual irradiation history. The 1GM assumes that all assemblies behave as a BWR 8x8 assembly. Thus, any systematic effects caused by differences in physical assembly design is ignored. Consequently, the prediction model may be improved if also the assembly design is taken into account. Assemblies are often stored close together, and radiation from one assembly can enter a neighbour to create Cherenkov light there. This socalled near-neighbour effect is not included in the 1GM predictions, and limits the accuracy of the verification, in particular for situations where a low-intensity assembly is surrounded by high-intensity neighbours. This problem can be remedied by developing a near-neighbour intensity prediction model. The current analysis groups assemblies according to their type, to make comparisons of assemblies with similar physical design. Should a fuel inventory contain a single assembly of a certain type, there will be no other assemblies to group it with. To solve this problem, correction factors based on assembly design could be introduced, allowing assemblies of different designs to be compared. The 1GM simulations include light transport to a detector position, but no image creation calculations. Later image creation simulations used a different level of detail in the Monte-Carlo radiation transport step and

43 the optical photon propagation step, and required the use of licensed software for the optical photon step. The image creation simulations could be improved if these two steps were seamlessly integrated, and using one code rather than two simplifies the simulation workflow. To gain more knowledge regarding Cherenkov light and nuclear fuel assemblies, much of this work has focused on developing software to simulate the production of Cherenkov light in nuclear fuel assemblies (described in chapter 6), and its propagation to a detector position and subsequent image creation. In a second step, these simulations were used to develop the 2GM (described in chapter 7). The aim of the 2GM was to enable better accuracy in the predictions, which may enable a higher sensitivity of the instrument in detecting partial defects. A goal of developing the 2GM was also to extend the range of fuel assemblies that can be verified with the instrument, by overcoming limitations in the 1GM, making DCVD measurements viable in more situations. 5.6 Practical aspects While the aim of this project was to improve the partial defect detection capabilities of the DCVD, a number of limitations were identified with respect to possible improvements in hardware, software and inspection procedure: Several DCVD instruments are already in use, consequently improvements to the partial defect verification methodology should not require changes to the existing hardware, but should focus on software, and possibly on inspection procedures. Important advantages of DCVD measurements are that they are quick and non-intrusive. Any changes in inspection procedure should aim at preserving these advantages. The improvements should not significantly increase the amount of work that an inspector needs to carry out to prepare for an inspection, perform the inspection or analyse the results. An inspector has access to fundamental parameters of an assembly, but may not have access to a more detailed description of it. Any suggested improvements to the partial defect detection procedure must consider that only limited data of an assembly may be available. Consequently, the primary area where improvements could be made, while only making small changes to the inspection procedure, is in calculating the predicted Cherenkov light intensity of an assembly. Considering the above points, attention was paid to the time consumption when applying a new prediction model, both in terms of inspector intervention and in-field computational requirements. In addition, some initial work has been performed to 43

44 enhance the procedure used for data collection with the DCVD. In particular, the background subtraction method used was considered, which is further described in chapter 8. 44

45 6. Simulations Using Monte-Carlo radiation transport codes, it is possible to investigate and characterize the production of Cherenkov light in irradiated nuclear fuel assemblies, without the need for access to irradiated nuclear fuel assemblies or a DCVD instrument. The simulations allow for investigations of various fuel assembly designs, decay sources and radiation interactions, which may be difficult or impossible to study experimentally. Furthermore, nuclear power plants tend to irradiate groups of assemblies in a similar way to optimize the use of the nuclear fuel, and consequently certain combinations of burnups and cooling times may be rare. Simulations allow for investigations of also these rare cases, where experimental data is scarce. One of the main aims of the simulations performed in this work was to obtain information that a new prediction model could be based on. The developed prediction model is further discussed in chapter Simulation tools used The simulations performed in this work can be divided into three steps: 1. Simulating the source of ionizing radiation in an assembly. 2. Simulating the transport of ionizing radiation, interaction in the fuel material, cladding and water, and the production of Cherenkov light. 3. Simulating the transport of the Cherenkov light to a detector position, and creation of an image. Which steps are included in a simulation depends on what information is desired. Most of the simulations performed in this work were aimed at characterizing how Cherenkov light is produced in an assembly. For those simulations, mono-energetic sources of ionizing radiation of various energies were sufficient, and the light transport step was neglected; hence only the second step was included in those simulations. For simulations of the DCVD image of an assembly with chosen parameters, all three steps had to be performed Simulating sources of ionizing radiation As mentioned in section 4.2, the dominant interaction that results in the production of Cherenkov light is that a gamma ray Compton-scatters in the water, 45

46 producing a high-speed electron, which radiates Cherenkov light. Hence, for accurate simulations of the Cherenkov light production, the gamma emission spectrum of the assembly needs to be calculated. These calculations were performed using the fuel depletion code ORIGEN [29]. ORIGEN takes as input the parameters of an assembly, such as type and initial enrichment, and the irradiation history of the assembly, i.e. the power level experienced by the assembly in the reactor, the duration of irradiation, and the duration of any periods without irradiation. Based on this information, ORIGEN calculates the build-up of fission products in the fuel assembly during its use in a reactor. ORIGEN also calculates the gamma emission spectrum based on the isotopes present, and the calculated gamma spectrum includes contributions from X-rays, gamma-rays, bremsstrahlung, spontaneous fission gamma-rays and gamma rays accompanying (α, n) reactions. (n, γ) reactions are however not included in the calculated spectrum [30]. Also discussed in section 4.2 is that beta particles can directly produce Cherenkov light, if they can pass through the fuel and cladding with energy above the threshold for Cherenkov light production. The abundance of betadecaying isotopes can be obtained from the ORIGEN calculations, from which a beta-emission spectrum can be calculated. Accordingly, this source may also be included in the simulations. In the simulations performed here, spontaneous neutron emissions have been neglected when simulating the emission of radiation from the fuel, which is justified by the discussion in section 4.2. Gamma rays following (n,γ) reactions are also neglected. However, should the need to simulate the neutron emission arise, ORIGEN is capable of calculating the neutron emission spectrum of an assembly. Alpha particles have a very short range and will be stopped in the fuel material, and gamma rays produced following (α, n) reactions in the fuel material are already included in the ORIGEN-calculated gamma spectrum. While radiation originating from the fuel material is expected to be the dominant source of radiation, other sources may be present. One such source is caused by 59 Ni which may attach to the cladding, forming so-called CRUD deposits on the surface, which is transmuted to 60 Co. This isotope decays with a relatively high gamma-ray energy, and being emitted from the cladding, the radiation will easily reach the water. However, in previous studies this source has been found to contribute negligibly to the Cherenkov light production in comparison to the radiation emitted by the fuel material [27], and has consequently been neglected in this work. 46

47 6.1.2 Simulating radiation transport and Cherenkov light production The radiation transport simulations that were executed as part of this work used the established Monte-Carlo particle transport code Geant4 [31]. The Geant4-based simulation toolkit used in this work is based on a previously developed toolkit, which was developed for the same purpose [32]. Geant4 was originally chosen for its customisability and its focus on accurate physics modelling. Furthermore, at the time of the initial development of the simulation toolkit, Geant4 was the only major simulation code that allowed for simulations including Cherenkov light. The simulation toolkit has been continuously modified and extended during this work, to be able to simulate new assembly types, storage conditions and types of radiation of interest. The Geant4 simulations performed in this work have applied a standard physics list, containing the physics interactions that are included in the simulations. Initially the list QSGP_BERT_HP was used, but it was later replaced with the list QSGP_BERT_EMZ. For both these physics lists, optical photon physics (G4OpticalPhysics) was also added. Other Geant4 simulations have found that the treatment of multiple-scattering in the physics list QSGP_BERT_HP can potentially introduce a bias in the directionality of the produced Cherenkov light [33]. However, for the cases simulated here, no significant differences were found between the results of the simulations using the two physics lists, and for later works QSGP_BERT_EMZ was used since it incorporates a more detailed treatment of electron scattering at energies of relevance for the simulations performed here. The simulated geometries included uranium rods modelled as homogeneous cylinders and covered by a zircaloy cladding. For simplicity, the fuel material was modelled as UO 2, neglecting any other isotopes. However, even for assemblies with high burnup, about 95% of the mass in the fuel rod will still be UO 2, so the presence of fission products and heavier actinides does not strongly affect the attenuation of gamma and beta particles, justifying this assumption. Structural components such as water channels for BWR assemblies and guide tubes for PWR assemblies were also implemented. For simulations of full 3D geometries, the simulations included a simplified square spacer grid, and the replacement of the top of the uranium pellet stack with helium, corresponding to the gas plenum present in the uppermost parts of a fuel rod. A square storage rack holding the assembly has also been included in some simulations, to simulate an assembly and the storage geometry. All properties of any rods and structural components were specified through input files read by the simulation toolkit, making it easy to run simulations with various parameters. The initial particles simulated were either gamma rays or electrons, corresponding to gamma and beta decays. Some simulations used a a monoenergetic source for the initial particles, while others used a source spectrum 47

48 to set the energy of the initial particles. For simulations used to characterize the Cherenkov light production in an assembly, the initial radiation was situated at the vertical center of a rod, and the rods were long enough that no radiation could reach the top or bottom of the assembly. For full 3D simulations, a vertical source distribution was instead provided, corresponding to the vertical burnup profile of an assembly. The simulated source has generally been homogeneously distributed in the circular cross section of a fuel rod, but in some simulations, a source placed at a fixed distance from the rod center has been used. The simulation toolkit has built-in code used to collect statistics on the Cherenkov light produced, and on the interactions taking place. It allows produced Cherenkov photons to be saved to file for later analysis, and for followup simulations. Since the DCVD is normally placed vertically above the fuel assembly, the vertically directed Cherenkov light is the light component that can be measured, and the toolkit has been designed to gather statistics on this light component specifically. For most simulations, photons forming an angle less than 3 to the vertical direction has been considered representative of the measurable, vertically directed light. This selection is somewhat arbitrary, but was selected as a trade-off between authenticity (obtained using a small angle) and statistics in the Monte-Carlo simulations (obtained using a large angle), and to be able to compare the simulation results to earlier works such as [27] Simulating light transport to the DCVD and image creation While papers I - V studied the production of Cherenkov light, paper VI also considered the propagation and detection of the light, and the image creation in the detector. To simulate the image creation, a three-step procedure was applied, similarly to earlier simulations of DCVD images [27]. The method used in this work was aimed at streamlining the simulations compared to [27] by seamlessly using Geant4 for the simulations of both the radiation and Cherenkov light transport, and thus to allow for more time-efficient simulations of cases of interest, with greater control over any simplifications made. The first step is a source calculation step, which was performed identically as described above using ORIGEN. The next step is a Monte-Carlo simulation of radiation transport in the assembly geometry, identical to the simulations described above, but with several extensions. The vertical source profile of the assembly was included, and the simulations included the Cherenkov light propagation inside the assembly until the photon reaches the top of the assembly. Once a photon reached the top of the assembly, it was saved to be used in the final image creation step. For these simulations, all metal surfaces were modelled with a 10% diffuse 48

49 reflectivity, i.e. 10% of all incoming photons were reflected. Any photons not reflected were absorbed by the surfaces. In the final image creation step, the photons saved from the Monte-Carlo simulations were projected onto an imaging plane, using a pinhole camera model. The pinhole camera is a simplified model of the DCVD detector and its optics, which proved to be sufficient for the investigations performed here. The image creation step was quick, and allows for obtaining simulated images for various detector positions, without having to redo the computationally expensive Monte-Carlo step. Structural components at the top of the assembly were also added in the final step. This was done by applying a mask, representing where the Cherenkov light was blocked by the top plate and lifting handle, and where light could pass through to be detected. By applying masks rather than simulating the top plate and lifting handle, it is possible to simulate one assembly without any top structure, and then use the masks to study various different top structures, without having to redo the relatively expensive second step. This is further detailed in section Simulated light production by single fuel rods Contributions from different types of radiation Earlier work studying the Cherenkov light production in fuel assemblies, such as [28] and [34], have mainly considered gamma decays. It was assumed that all beta particles were stopped in the fuel material, and that the bremsstrahlung created in this interaction was taken into account by the gamma emission spectrum calculations of ORIGEN. To test the assumption that all beta electrons are stopped in the fuel material, simulations were run for one fuel rod in a large water volume, as presented in papers I and II. The Cherenkov light production was characterized as a function of the initial particle energy, for both gamma and beta decays. For the beta decays, only Cherenkov photons produced directly by the initial beta particle were investigated, since bremsstrahlung is already included as gamma emissions from the fuel material. The results are presented in figure 6.1. As noted in section 4.2, the threshold kinetic energy for an electron to radiate Cherenkov light in water is about 250 kev, and figure 6.1 shows that gamma rays with slightly higher energy can produce some Cherenkov light. In order for an electron in the water to obtain this energy from the photon, the photon must be absorbed through the photoelectric effect. Also noted in section 4.2 is that around 410 kev a Compton-scattered electron can obtain sufficient energy to radiate Cherenkov light. Accordingly, a bump can be seen in the gamma curve in figure 6.1 above this energy, when the number of Cherenkov photons increases significantly due to the higher probability of Compton-scattering compared to photoelectric absorption at these energies. 49

50 Cherenkov photons per initial particle Gamma Beta Initial particle energy [MeV] Figure 6.1. Intensity of the Cherenkov light produced due to gamma and beta emission from a fuel rod with 10 mm diameter pellets, and a 0.6 mm thick cladding. The source was homogeneously distributed in the pellet in both cases. For beta emission, bremsstrahlung was omitted since it can be treated as gamma emissions from the fuel material. At even higher energies, pair production may also contribute to creating highenergy electrons, positrons and subsequent annihilation gammas. However, the cross-section for this interaction is low at energies near the pair production threshold at MeV, and it will not start to dominate until at energies around 7 MeV in water [23]. For fission products with a long enough half-life to be of relevance to this work no such high-energy decays were abundant, making this contribution negligible. Figure 6.1 also show that beta electrons may exit a fuel rod and enter the water with sufficient energy to produce Cherenkov light. However, for this simulated rod with a cladding thickness of 0.6 mm, the beta electrons need more than 750 kev of kinetic energy to penetrate the fuel material and cladding, and still have at least 250 kev when they enter the water. Thus, only high-energy beta decays may directly produce Cherenkov light at a level comparable to gamma decays. One situation in which this may occur is for long-cooled assemblies (a few decades), where the most abundant source of gamma rays is 137 Cs, and the most abundant source of high-energy beta decays is 90 Sr and its daughter 90 Y. 90 Sr has an abundance in irradiated nuclear fuel material comparable to that of 137 Cs, and both isotopes have a similar half-life of about 30 years. Furthermore, 90 Y beta decays with an energy of up to 2.2 MeV [22], and as shown in figure 6.1, such a beta particle energy can produce Cherenkov light at a level comparable to a 662 kev 137 Cs decay. However, since the beta particles are emitted with energy following a continuous energy spectrum, few particles are emitted with energy close to the maximum energy. It was how- 50

51 ever concluded in paper I that there is reason to consider also beta decays when investigating the Cherenkov light production by nuclear fuel assemblies, in particular for long-cooled assemblies Effect of source distribution in a rod The Cherenkov light production is sensitive to the location of the fission products in the rod, since the dense fuel material will attenuate the radiation, as discussed in section 4.2. Figure 6.2 shows the produced vertically directed Cherenkov light intensity as a function of the radial source location in the rod, for decays of 137 Cs and 90 Y, as presented in paper I. Although a 662 kev gamma ray from 137 Cs has high enough energy to easily penetrate the fuel and cladding material, it can still be seen that a gamma decay originating at the center of the rod will to a larger extent be absorbed in the fuel material, and consequently produce less Cherenkov light as compared to a decay occurring near the pellet rim. Figure 6.2 also shows that 90 Y beta decays near the pellet rim may exit the fuel rod and contribute to the Cherenkov light production, while decays occurring closer to the fuel pellet center will not. Consequently, since only 90 Y beta decays on the rim will contribute to the Cherenkov light production, the total light production due to beta decays will strongly depend on the fuel rod dimensions, at least when considering a homogeneous source distribution in the rod. As seen in figure 6.2, this effect will also suppress the production of Cherenkov light by beta decays to a higher degree as compared to gamma decays. Taking the actual radial source distribution in the fuel pellet into account is challenging, since this distribution is rarely known. Irradiated nuclear fuel pellets tend to have a higher burnup on the rim, which consequently will contain a higher concentration of fission products. In addition, some elements such as Cs can migrate in the fuel pellet from a high-temperature region to a lower-temperature one [35]. Due to the difficulty of finding a "standard" source distribution, most simulations executed in this work assume a homogeneous distribution. However, if a "standard" radial distribution is assumed, or if there is a need to simulate some particular distribution, the simulation code is capable of including such a distribution Anisotropy of produced light Due to the attenuation of radiation in the dense fuel material, fuel rods do not emit gamma and beta radiation isotropically, and therefore the produced Cherenkov light will not be isotropic. Since measurements with the DCVD are done vertically above the fuel assembly (and since the assembly surfaces are oxidized and highly absorbing of light), only the vertical light component 51

52 Vertical Cherenkov photons per 137 Cs decay Vertical Cherenkov photons per 90 Y decay Cs Source distance from fuel pellet center [mm] 90 Y Source distance from fuel pellet center [mm] Figure 6.2. The average number of produced vertically directed Cherenkov photons for a 137 Cs decay (top) and an 90 Y beta decay (bottom) at various radial positions in a rod. The dashed lines indicate the average intensity per decay for a homogeneously distributed source. Note that an 90 Y decay on the pellet rim will produce a similar number of Cherenkov photons as a 137 Cs decay. 52

53 10 2 Relative Cherenkov light production MeV gamma 1.0 MeV gamma 2.0 MeV gamma 90 Y beta cos(φ) Figure 6.3. Directionality of the produced Cherenkov light for three gamma-ray energies and for 90 Y beta decays, for an isolated fuel rod in water. The angle φ is the angle between the Cherenkov photon and the vertical direction. An isotropic light distribution would be shown as a flat line in the graph. The intensities are scaled to the same total intensity. is measured, which may differ from the total light intensity. This effect was investigated in papers I and II. For a Compton-scattered electron, the events that produce the maximum amount of Cherenkov light have both the Compton-scattered electron and the Cherenkov light propagating in a similar direction to the initial gamma ray. Thus, a non-isotropic source of gamma radiation, such as a fuel rod, will result in a non-isotropic source of Cherenkov light. To investigate this anisotropy, simulations were run for an isolated rod in water, to characterize the anisotropy as a function of the energy of the initial decay particle. As can be seen in figure 6.3, the simulation results show that the directionality of the produced Cherenkov light depend on the gamma energy. For high-energy gamma rays, the Cherenkov light produced was found to be almost isotropic, but as the energy of the gamma ray decreases, the Cherenkov light became more and more horizontally directed. A similar effect could be seen for the simulated 90 Y beta-decay electrons, for which the full energy distribution was simulated. These electrons were strongly attenuated by the fuel material and cladding, and vertically directed electrons were to a larger extent stopped in the rod compared to horizontally directed ones, which suppressed the vertical Cherenkov light production. 53

54 6.2.4 Dependencies of light production on fuel rod dimensions The dimensions of the fuel pellets and the cladding thickness of a fuel rod differ between different types of fuel assemblies. In general, PWR assemblies tend to have a smaller diameter of the fuel rods and a thinner cladding compared to BWR assemblies. Furthermore, older assemblies tend to have both larger rods and thicker claddings compared to more modern designs. To investigate what effect the pellet diameter and cladding thickness have on the Cherenkov light production, simulations were executed for a single isolated rod in water, as presented in paper I. The results showed that for gamma decays, the cladding was thin enough for all studied designs to negligibly affected the results. This was expected, since a thin sheet of metal does not attenuate gamma rays significantly. The dimensions of the fuel pellet did however have a noticeable influence, since the gamma rays were more strongly attenuated in the dense fuel material. Comparing rods with dimensions typical of an older BWR and a PWR assembly, the thinner PWR rod produced on average 5-20% more Cherenkov light per gamma decay, and the extent depended on the energy of the initial gamma ray. These results show that one should expect systematic differences between assemblies of different designs. For beta emissions, the cladding was found to have a significant effect on the production of Cherenkov light, since such a thin metal sheet is sufficient for stopping electrons with energies less than 0.5 to 1 MeV. Thus, for beta decays there exists significant systematic differences between BWR and PWR assemblies, caused by differences in cladding thickness. Due to the short range of the beta electrons, only beta particles emitted near the pellet rim can pass through the cladding and enter the water with sufficient energy to produce Cherenkov light. As described in section 6.2.2, Cherenkov light production from beta decays is also affected by the pellet diameter, but this effect is primarily due to the relative size of the rim as compared to the total volume of a pellet in a fuel rod. 6.3 Simulated light production in complete fuel assemblies Systematic differences between assemblies of different types As noted in the preceding section, there are systematic differences in the Cherenkov light production by single rods caused by the differing physical dimensions. Consequently, the systematic differences should also extend to assemblies of different designs, since they have fuel rods with different dimensions as well as placements in the assembly. To further investigate the dependencies between fuel type and Cherenkov light production, simulations were 54

55 Cherenkov photons per gamma quantum BWR BWR PWR 1.45 PWR/BWR Initial gamma-ray energy [MeV] Cherenkov light ratio PWR/BWR Figure 6.4. Intensity of the produced Cherenkov light intensity in a BWR 8x8 and a PWR 17x17 assembly, as a function of gamma-ray energy, and the ratio of the simulated vertical Cherenkov light production for the two assembly types. executed for a complete BWR 8x8 assembly and a complete PWR 17x17 assembly, as presented in paper II, and the simulations investigated the Cherenkov light production as a function of gamma energy. The Cherenkov light production in each assembly and the ratio of the produced intensities as a function of gamma energy for the two studied assemblies are shown in figure 6.4. The results show that the PWR assembly will produce more Cherenkov light per gamma decay, due to the smaller rods, and since the PWR assembly contains a larger fraction of water as compared to the BWR assembly. It can also be seen that the PWR/BWR ratio of the Cherenkov light production is not constant as a function of gamma-ray energy. As a fuel assembly is kept in storage, short-lived isotopes decay and the gamma emission spectrum changes, typically towards lower-energy emissions at longer CT [36]. The non-constant ratio means that even when assuming the same initial fission product inventory in a BWR and a PWR assembly, the Cherenkov light intensity will change differently with time for different assembly types. Consequently, when making a prediction of the Cherenkov light intensity of an assembly, systematic errors may be introduced if the prediction is based on simulations of one assembly type, but the measured assembly is of a different type. Thus, it is expected that the accuracy of the predictions will improve if the prediction model take the physical characteristics of an assembly into account. 55

56 Table 6.1. Contribution of 90 Y beta decays to the total Cherenkov light intensity from a fuel assembly with a burnup of 40 MWd/kgU. The BWR fuel assembly was simulated with a cladding thickness of 0.91 mm as compared to 0.57 mm in the PWR case. % of Cherenkov light intensity due to 90 Y Cooling time 5 years 10 years 40 years BWR 8x8 0.33% 0.63% 1.0% PWR 17x17 2.2% 4.2% 6.7% Contribution from beta emitters As noted in the preceding sections, the contribution from 90 Y beta decays to the Cherenkov light production depends on a multitude of factors. As part of the simulation studies covered in paper II, the contribution from 90 Ytothe total Cherenkov light production was investigated as a function of CT, for a BWR and a PWR assembly. The results are shown in table 6.1, for assemblies with a simulated BU of 40 MWd/kgU and for three selected CTs. The results show that the relative contribution from 90 Y is noticeably larger for the PWR assembly, due to the thinner cladding. The proportion of light produced by 90 Y was found to increase with cooling time, since then most short-lived gammaemitting isotopes have decayed, and 137 Cs and 90 Y become more dominating. These results show that for assembly types with thin cladding, the contribution due to 90 Y is significant and it is recommended to include this contribution in predictions. For assemblies with thick claddings, the direct contributions by beta decays can be neglected with low loss of accuracy. 6.4 Simulated light production in neighbouring assemblies One of the main advantages of verifying assemblies in wet storage using Cherenkov light is that the assemblies can be verified where they are stored, and there is no need to move the assemblies to a dedicated measurement area, which is time-consuming. However, the assemblies are normally stored closely together, allowing radiation from one assembly to enter a neighbouring assembly and create Cherenkov light there, an effect that was investigated in paper IV. This is called the near-neighbour effect. Figure 6.5 shows an example of how BWR assemblies are stored at the Swedish central interim storage for spent nuclear fuel, Clab. In paper IV, simulations were performed to characterize the near-neighbour effect, and to identify parameters affecting its intensity. In the simulations, one assembly was active and emitting radiation, at the position called "Main" in figure 6.5. Note that due to the short range of beta electrons, only gamma rays will contribute to the near-neighbour effect. The radiation emitted by the main assembly resulted in Cherenkov light production in both the main assembly 56

57 N5 N4 N3 N4 N5 N4 N2 N1 N2 N4 N3 N1 Main N1 N3 N4 N2 N1 N2 N4 N5 N4 N3 N4 N5 Figure 6.5. Left: A DCVD image of 25 BWR assemblies stored at the Swedish central interim storage facility for spent nuclear fuel, Clab. Image courtesy of SKB, Dennis Parcey and Channel Systems Inc. Right: In the near-neighbour simulations, the central assembly in the position denoted "Main" emitted radiation, and the Cherenkov light production in the other positions were investigated. itself, as well as in the neighbouring assemblies. The neighbouring positions were named N1 to N5, as indicated by figure 6.5. Due to the symmetry of the problem, the near-neighbour intensity at a neighbouring position due to the radiation from the main assembly is the same as the intensity at the main position if instead the neighbour is active. Thus, by simulating how the main assembly affects all its neighbours, it is possible to assess how all neighbours contribute to the Cherenkov light intensity at the main assembly. Simulations were run for both BWR 8x8 and PWR 17x17 assemblies, and for two different storage configurations. One configuration was close-packed, with only a few millimetres of steel separating the assemblies, which is similar to the situation at Clab shown in figure 6.5. The second configuration had a water gap between the assemblies, which matches the storage conditions at the Swedish nuclear power plant Forsmark for the BWR assembly case. Simulations were also run where some of the assembly storage positions were empty, since not all assembly positions at a storage site are occupied. The results of the close-packed BWR simulations are presented in table 6.2 for two cooling times. A few conclusions can be drawn regarding the near-neighbour effect based on table 6.2: The intensity of the near-neighbour contribution changes with cooling time, since the gamma emission spectrum of an assembly changes with time. For the intensity contribution due to assemblies at the N2 and N3 positions, the presence or absence of an assembly at the N1 position will noticeably affect how much the radiation is attenuated. Consequently it 57

58 Table 6.2. Magnitude of the near-neighbour Cherenkov light contributions for a closepacked BWR assembly storage. The intensities are normalised so that the simulated intensity in the main assembly is 100%, with only the main assembly being active. Positions N2, N3, N4 and N5 were simulated both with all other neighbouring positions N1-N5 empty and with assemblies present. 1 year cooled 40 years cooled Main 100% 100% N ± 0.02% 1.86 ± 0.01% N2 with all neighbours 0.39 ± 0.01% 0.18 ± 0.01% N2 without any neighbours 0.89 ± 0.01% 0.49 ± 0.01% N3 with all neighbours 0.04 ± 0.01% 0.02 ± 0.01% N3 without any neighbours 0.50 ± 0.01% 0.29 ± 0.01% N4 with all neighbours ± 0.002% ± 0.001% N4 without any neighbours 0.25 ± 0.01% 0.14 ± 0.01% N5 with all neighbours ± 0.001% 0.00 ± 0.00% N5 without any neighbours 0.11 ± 0.01% 0.05 ± 0.01% is important to keep track of which positions are empty and which are occupied. For the N3, N4 and N5 positions, the contribution will only be relevant if all other nearby neighbouring positions are empty. For a situation with close-packed identical BWR assemblies, up to 14% of the measured Cherenkov light intensity originates from the neighbours of the measured assembly. For situations when measuring a low-intensity assembly surrounded by high-intensity neighbours, the near-neighbour effect may end up causing the majority of the measured Cherenkov light, and in such situations the near-neighbour effect needs to be predicted and compensated for to accurately verify the assembly. Based on the results of the simulations presented here and in paper IV, it was concluded that the near-neighbour intensity decreased with cooling time for both BWR and PWR assemblies, but at slightly different rates. Thus, there exist systematic differences between the two assembly designs. The nearneighbour intensity is also affected by the distance between assemblies and the amount of material in between them. Thus, when predicting the intensity contribution by near neighbours, the storage geometry must also be taken into account. 58

59 Figure 6.6. Left: An example DCVD measurement of a PWR 17x17 assembly. Center: The mask obtained by applying an intensity threshold to the left image. The edges of the assembly are covered by the lifting handle, and the central parts are partly covered by the top plate. Right: A photograph of the top structure of a PWR 17x17 assembly model, of the same design as the assembly in the left image. 6.5 Including light transport and image creation in simulations Papers I to V presented investigations of the production of Cherenkov light in a nuclear fuel assembly, and assumed that the detected intensity should be proportional to the produced one. Earlier simulations have shown that this is expected to be a valid assumption [37]. By extending the simulations to not only cover the production of Cherenkov light, but also its propagation and detection, the validity of this assumption could be investigated further. Using the three-step image creation procedure presented in section 6.1.3, a PWR 17x17 assembly was simulated for a set of selected BUs and CTs, and the intensities of the simulated images were compared to the simulated produced intensities. Ideally, to obtain the masks representing the fuel top plates, which are required to create the simulated images, a design drawing or high-resolution photo should be used. Since neither was available, the masks for the studied assembly types were instead extracted from measurements. For each assembly design encountered, one measurement was selected, and an intensity threshold was applied to separate the dark parts of the image (corresponding to regions covered by the top plate and lifting handle) from the bright parts (corresponding to open regions). The downside of using this type of threshold procedure was that smaller details regarding the top plate shape were lost, and only larger structures could be identified, due to the relatively poor resolution of the experimental DCVD images available. An example DCVD image of a PWR 17x17 assembly, and the corresponding mask obtained using the threshold procedure are shown in figure 6.6, together with a photograph of an assembly model of similar design. An example of a simulated image obtained with an applied mask is shown in figure 6.7, together with an experimentally measured image for compari- 59

60 son. The simulated image had a Gaussian blur applied to it, to simulate the blur in the experimental images introduced by e.g. turbulence in the water. Qualitatively, there is good agreement between the images, with e.g. similar gradients in the guide tubes and a good match of the overall light distribution. The only major difference is the hole at the center of the assembly, which appears larger in the simulated image. This is an effect of that the assembly images are slightly brighter in the center, and the threshold procedure will then make this hole larger than if the hole had been further away from the center. Quantitatively, there is also good agreement between the produced intensity and the intensity in the simulated images, as shown in figure 6.8. The produced Cherenkov light intensity in figure 6.8 has been multiplied by a factor to relate the produced and detected intensity, which was found through a least-square fit (this fitting is identical to the one done when relating predictions and measured data when verifying assemblies with the DCVD, as described in section 5.3). It was found that the simulated image intensities were within 0.5% of the produced intensities for the data sets in figure 6.8, and the difference changed little with CT. Consequently, the assumption that the detected intensity is proportional to the produced one appears valid. Accordingly, the time-consuming light transport and image creation step may be omitted when predicting the light intensity of an assembly. Furthermore, the good agreement between simulated production and simulated image intensity hold for the different masks studied (the set of assemblies is further detailed in section 7.2.3). Finally, the application of top plate masks also enables the comparison of produced Cherenkov light intensities from assemblies with slightly different designs, if the rod configurations are similar and design differences can be described by the top plate mask. The applicability of masks for analysing assemblies of different designs is further discussed in section Speeding up the simulations While papers IV and V have shown that the Geant4 simulations of the fuel assemblies and their neighbourhood provide accurate results, they are also time-consuming. This work has focused on a limited set of assembly types, making the time consumption acceptable, but if simulations are required for many more assembly types, the time consumption may be a limiting factor. To speed up the simulations, various simplifications can be considered, which will lower the time needed to complete the simulations but will also introduce systematic errors in the results. Five different simplifications have been analysed as part of papers II and VII, and are summarised in table 6.3. In table 6.3, the maximum error is the estimated maximum error that can be introduced in an intensity prediction, when comparing a prediction model with the simplification to a prediction model without the simplification. The maximum error would typically occur when verifying a fuel assembly inventory 60

61 Figure 6.7. Left: An example DCVD image of a PWR 17x17 assembly. Right: A simulated image of the same PWR 17x17 assembly design, obtained using the threestep simulation method described in section Predicted intensity [arb. unit] Production intensity (40 MWd/kgU) Image intensity (40 MWd/kgU) Production intensity (10 MWd/kgU) Image intensity (10 MWd/kgU) Cooling time [years] Figure 6.8. Comparison of the intensity of produced Cherenkov light in a simulation to the simulated image intensity for a PWR 17x17 assembly. The images were simulated for BUs of 10 and 40 MWd/kgU and CTs of 2, 10 and 40 years. The production-based predicted intensities were multiplied by a constant factor to relate it to the simulated image intensity predictions, as done when comparing predictions and measurements in a DCVD verification, as described in 5.3. The uncertainty in the intensities due to the Monte-Carlo nature of the simulations are below 0.4% for the simulated images and below 0.1% for the production-based simulated intensities. 61