Study about the application of acoustic agglomeration of aerosols for source term mitigation in nuclear accidents

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PROCEEDINGS of the 22 nd International Congress on Acoustics Sonochemistry and Sonoprocessing: Paper ICA2016-59 Study about the application of acoustic agglomeration of aerosols for source term

1 PROCEEDINGS of the 22 nd International Congress on Acoustics Sonochemistry and Sonoprocessing: Paper ICA Study about the application of acoustic agglomeration of aerosols for source term mitigation in nuclear accidents Manuel Aleixandre (a), Enrique Riera (a), Rosario Delgado-Tardáguila (b), Luis E. Herranz (b), Juan A. Gallego-Juárez (a) (a) Departamento de Sensores y Tecnologías Ultrasónicas, ITEFI, CSIC, Spain, enrique.riera@csic.es (b) Unidad de Seguridad Nuclear, División de Fisión Nuclear, CIEMAT, Spain, luisen.herranz@ciemat.es Abstract During severe accidents of nuclear power plants radioactive material can be released from fuel and form aerosols that, even though highly unlikely, might reach the environment. There exist a number of systems to mitigate any potential emission from a nuclear power plant and, in particular, what is known as Filtered Containment Venting System (FCVS). After the Fukushima accident some investigations have been launched to boost the efficiency of those systems as much as possible under any foreseen conditions. This work deals with an experimental study about the potential application of a power ultrasonic system as an innovative approach to precondition the particle load reaching the first filtration stages of the FCVS. This study includes the design and acoustic characterization of an ultrasonic agglomeration chamber at 21 khz in which a high intensity standing wave field is established. This system has been tested with SiO 2 aerosols of diameters of 0.3 µm, 1 µm and 2.5 µm, and polydisperse TiO 2 aerosols. The agglomeration effects have been studied, and the results compared with the theoretical model predictions. Keywords: Power ultrasonics, aerosol, agglomeration, modeling

2 Study about the application of acoustic agglomeration of aerosols for source term mitigation in nuclear accidents 1 Introduction While the safety of nuclear power reactors is very high, events like the Fukushima accident pushes the expected safety standards even higher. In case of an unlikely accident the high temperatures reached during nuclear reactor degradation cause that most of the radionuclides leave the reactor core in form of vapours [1]. These vapours nucleate in their path to containment (last barrier between radioactivity and environment) and generate aerosols [2] that need to be cleaned [3]. There are a number of procedures already installed in nuclear power plants such as wet scrubbing systems, sand bed filters, etc., known by the generic name of Filtered Containment Venting Systems (FCVS). All these mitigation systems have been proven to be effective but in order to comply with that increased demand for safety the European Union funded a project (PASSAM Grant agreement No Euratom 7FP ) that studies existing filtration systems in order to improve them and also innovative methods that have so far not been applied in the nuclear field. This is the case of Aerosol Acoustic Agglomeration (AAA) [4]. In the AAA the aerosol particles experience movement caused by the acoustic field inducing collisions and agglomeration resulting in larger particles that are much easily removed by sedimentation or by the conventional filtration systems. Since the first experiences in the AAA [5] the technology has improved its efficiency and reliability [4]. For nuclear aerosol agglomeration the AAA offers several advantages. The physical mechanisms are fairly independent on the temperature, which can reach very high values in these events, and. They are favoured by the humidity, usually present in nuclear plant accidents. Also very high particle concentrations increase the AAA efficiency. Nuclear aerosols are difficult to reproduce in laboratory and reliable models of the effects must be used to assess the possibility of using AAA to effectively contribute to radioactive aerosol retention in case of an accident. This work is a first approach to this problem through an agglomeration model and its validation with several experiments. 2 Aerosol acoustic agglomeration theory The AAA is a process integrated by several mechanisms. The main mechanisms are the orthokinetic effect [6], the scattering [7], and the mutual radiation pressure [7]. All them are described and analysed with more detail below. Particles in a sonic field with different size have different entrainment and experience a relative movement that leads to collisions. The movement of a spherical particle in a monochromatic acoustic field can be calculated by Basset Boussinesq Oseen equation. From such equation the complex entrainment factor (H) can be obtained [8], equations (1) and (2): 2

3 H = δf 3 2 i(δf+ δf) δf i[(1+δ 2 )F+3 2 δf] (1) where δ = ρ 0, F = ωτ ρ p, τ p = ρ pd 2 p 18 μ (2) Where H is the complex entrainment of the particle, is the acoustic angular frequency, p is the relaxation time of the particle, d is the particle diameter, p is the particle density, 0 is the gas density, µ is the gas dynamic viscosity and i is the complex number. The relative motion between the particle and the gas is given by equation (3) and (4). u p = ηu 0 cos(wt kx φ) (3) H = ηe iφ (4) Where t is the time, u(t) is the particle velocity, and U 0 the incident acoustic velocity. This entrainment is different for particles with different diameter and/or density. Therefore the particles of a polydisperse aerosol will have different entrainment with the sound field. Such relative movements will generate particle collisions that produce agglomeration. When a pair of particles is close, their scattering waves interact. Such mutual scattering has the effect of redirecting the particles and changes the amplitude of their periodic relative movement. To calculate the ultrasonic field with the scattered waves we simply add the original wave with the scattered ones of each particle ignoring the higher order scattered waves. Song [7] modified the entrainment factor with the scattering effect as in equation (5) were G 12 is the new scattering function. η 12 = (H 1 H 2 ) + G 12 (5) The scattered wave cancels if the particles have the same size and density. When the particles are not the same size or density the scattering wave have the effect of deflecting the collision trajectories decreasing the possibility of two particles to agglomerate [9]. The scattering acoustic field is not uniform between two nearby particles. This asymmetry generates because of the Bernoulli s hydrodynamic law a force between the particles. This interaction is described by equations (8) and (9) where θ is the angle between the particles and g 21 is the hydrodynamic function [9] that depends on 1-H 1 and 1-H 2. As a result the radiation pressure force is not zero when the particles have the same size, this is very important when considering particle size distributions very narrow. Also when H is low the effect is higher, it means that high frequencies and larger particles improve the effect. u 21 = ρ 0U π 2 μ d 1 2 d 2 2 (d 1 +d 2 ) 3 (1 3 cos2 θ)g 21 (6) g 21 = f(1 H 1, 1 H 2 ) (7) 3

4 It is to be noted that the hydrodynamic effect is smaller than the orthokinetic one, however it increases faster with the sound pressure level, and consequently it is important with high sound pressure levels. 3 Model of aerosol acoustic agglomeration The model used has several assumptions: The particles are spherical and remain spherical for all the processes. The particles are binned by size and in each size bin the particles are assumed to have the same size, the agglomerates don t break up, and the particles are homogenously distributed in the agglomeration chamber. The Smoluchowski equation (8) gives the change of particles produced in the agglomeration in each instant of time for the particles of a size. dn k = 1 β m dt 2 i+j=k i,jn i n j n k β i,k n i i=1 (8) Where: n is the particle concentration in each size bin; i, j, and k are the indexes that indicate the size bin of the particles, and β is the agglomeration kernel. The first term on the right hand represents the particle gain in size bin k by the agglomeration of smaller ones, size i and j. The second term refers to the particles of that size k that agglomerate with others. For each agglomeration mechanism mentioned before a different kernel must be calculated. Once the kernels are determined, the dynamic of AAA can be simulated through equation (10). The simulation is programmed in Matlab. According to Mednikov [10] is possible to define an agglomeration volume for orthokinetic collisions as a as a cylinder whose length is the relative particle displacement and the crosssection is the area of the cross-section of the larger particle and smaller particle. The kernel, equation (9) is then calculated from volume and is illustrated in figure 1. β(i, j) = 1 2 (d i + d j ) 2 U 0 η ij (9) Where d i and d j are the particles diameters, U 0 is the incident vibrational velocity of the fluid and η ij is the relative entrainment factor of particles i and j. The scattering effect just modifies the ij by equation (5) in the agglomeration kernel of equation (8). The overall effect of this modification is to decrease the kernel value and is illustrated in figure 2. The mutual radiation pressure kernel is calculated from equation (6) and gives the equation (10). The image of this kernel is illustrated in figure 3. The figure 4 shows the kernel when all effect are taken into account. β(i, j) = 3ρ ou πμ d i 2 dj 2 (d i +d j ) g 21 (10) 4

Figure 1: Orthokinetic Kernel Figure 2: Orthokinetic with scattering Figure 3: Mutual Radiation Pressure Kernel Figure 4: All Kernels added 4 Experimental results 4.

The ultrasound was generated within a Mitigative System Acoustic Agglomerator (MSAA) designed by the CSIC.

The details of the system are described elsewere [14]. The experimental conditions are briefly described the following point. 4.

5 Figure 1: Orthokinetic Kernel Figure 2: Orthokinetic with scattering Figure 3: Mutual Radiation Pressure Kernel Figure 4: All Kernels added 4 Experimental results 4.1 Experimental setup The experiments were carried out in the Experimental Plant for Aerosol Generation and Characterization (PECA) in the CIEMAT, Spain. The ultrasound was generated within a Mitigative System Acoustic Agglomerator (MSAA) designed by the CSIC. The l aerosol characteristics were adapted to those of the expected aerosols in the nuclear event as much as allowed by the generation system [11] [12] [13]. The details of the system are described elsewere [14]. The experimental conditions are briefly described the following point. 4.2 Experimental conditions The MSAA generated a 21 khz standing wave field inside the chamber with an average sound pressure level of 155 db. The ultrasonic generators were of the kind of airborne power steppedplate transducers with electronic resonance control [15]. The gas flow that carried the aerosol trough the acoustic chamber was air with a flow between 12.5 kg/h and 200 kg/h. The aerosols were constituted of particles of 0.3 µm diameter SiO 2, 1 µm diameter SiO 2, 2.5 µm diameter SiO 2, and polydisperse TiO 2 particles. Ten experiments were carried out with the features summarized in Table 1. The procedure followed in the experiments can be divided into several steps. First there was a stabilization step in which the aerosol generation was monitored at the inlet by an electric- 5

6 collector system (ELPI device) [16]. After reaching stabilization the second step consisted in the measurement of the aerosol particles at the outlet of the MSAA by means of an Aerodynamic Particle Sizer (APS) [17].Such measurements were carried out with and without ultrasounds. Each experiment was repeated once. The details of the experimental procedure are explained in more detail below ad in [14]. Name Flow (kg/h) Table 1: Experimental variables of the experimental matrix Residence time (s) Input Total Mass Concentration (mg/m 3 ) Mass proportion of SiO μm (%) Mass proportion of SiO 2 1 μm (%) Mass proportion of SiO μm (%) Mass proportion of TiO 2 (%) AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA Experimental measurements Membrane filters The measurements of the aerosol mass concentration at the inlet of the MSAA where carried out with membrane filters in all tests. The membrane filters were weighted before and after the measurement and the flow rate passing through the filters was measured with a flowmeter. With these two variables the mass concentration of the aerosol was calculated Electric collector system (ELPI) The ELPI is a system with an uncertainty around 130 particles per cm 3 [18] and a uncertainty in the size around a 5% [18]. It was placed at the inlet took the input aerosol data during all the testing time making measurements each second. The particle concentration and its distribution characteristics were mostly steady during the tests; however there were some small instabilities APS system At the outlet of the MSAA the Aerodynamic Particle Sizer (APS) measured the particle size distributions in the range 0.5 to 20 μm in intervals of dlogdp of 0.03 every second. The typical uncertainty of the number distribution of a single channel of the APS is 18% [17] and the aerodynamic diameter uncertainty ranges between 18% and 20% [17]. In our measurements the relative standard deviation of particle number concentration for each experimental phase ranged from 2% to 34% with an average of 10% and the relative standard deviation of the ACMD ranged from 0% to 25% with a mean of 3%. 6

As an example of the ultrasound effect, the figure 5 shows the APS measurements of one experiment (AAA9) in which the ultrasound field was switched on and off.

7 As an example of the ultrasound effect, the figure 5 shows the APS measurements of one experiment (AAA9) in which the ultrasound field was switched on and off. During the time in which the ultrasound is switched off the particle number rise and when the ultrasound is switched on again the particles agglomerate and the peaks of the distribution drop. 4.4 Experimental results To compare the particle number at the inlet and the outlet the two different particle counters (APS and ELPI) were used only in the common size range. Figure 6 shows the output number of particles measured by the APS relative to the input number of particles measured by the ELPI in the particle diameter range between 0.52 µm and 9.8 µm without ultrasound (phases F1, F1 ) and with ultrasound (phases F2 and F2 ). The effect of the ultrasound on the particle number was quantified by using the equation (16) where the Np b is the relative particle number, during the phases with and without ultrasound and R C is the coefficient of number reduction. R C = 1 mean (Np b with US) mean (Np b without US ) 100% (16) Table 2 summarizes the results of all tests. The ultrasound effects reached values up to 91% for RC. The expected increase effect with decreased flow and increase effect with higher polydispersion are also shown. Figure 5: AAA9 APS measurement during the F2 phase Figure 6: Relative particle number vs time in test AAA3 in the range between 0.52 µm and 9.8 µm 7

8 5 Modeling results As mentioned before the ultrasonic field was modelled as a 21 khz standing wave with an average sound pressure level of 155 db. The gas was modelled as air at atmospheric pressure and room temperature. The input aerosol generation for the model was calculated from the membrane filter measurements and the composition of the aerosol used in the aerosol generator. The exposure times for the aerosols are taken from table 1. The results are summarized in table 2. Since the particle distribution of TiO 2 was not clearly known and the model is not prepared to work with particles with different densities, the experiment AAA10 was excluded from the simulations. The equation (17) was used to calculate the model number reduction. R C = 1 Np b before Np b after 100% (17) Figure 7: Model of the simulation of experiment AAA3 with Orthokinetic, Scattering and mutual radiation pressure kernels. 6 Conclusions As it is known, the ultrasound effect on aerosol agglomeration very much depends on particle concentration and size dispersion. The results obtained in this study confirm such previous knowledge: when the aerosol was polydisperse and the concentration reached the adequate level the agglomeration effect was clearly observed. The main effect of the agglomeration was an overall reduction of the particle number concentration up to 91%. This is an important result because of the difficulty to remove such tiny particles. The model is reliable because reproduces the results of the agglomeration experiments, showing that the orthokinetic effect with scattering combined with the radiation pressure effect include the most important agglomeration 8

9 mechanisms. The model underestimates the results when the concentrations of the aerosols are low and when the particles are big (AAA8). It is worth noticing also that while the model results seem very closely matched to the experimental ones there was a very strong mass reduction in the real experiments not predicted by the model. This mass reduction caused by the application of the ultrasounds could be due to an increasing mass deposition in the acoustic chamber or the tubes, particles trapped in the sound field or particles outside the limited size ranges of the APS. This indicates that the model overestimates the agglomeration. The temperature and humidity were kept at ambient conditions, however an additional increase of the humidity would increase the agglomeration effect as it is known [19]. In fact the combination of the ultrasonic agglomeration with spray techniques developed in other task of the PASSAM project would result in a common improvement of both processes. Table 2: Summary of the model results Modeling Results Experiment Name Aerosol Particle Mixture Flow Rate Experimental Results Orthokinetic (No Scattering) Orthokinetic (With Scattering) Orthokinetic (With Scattering) + Hydrodynamic Mean RC Mean RC Mean RC Mean RC [%-%-%] [kg/h] [%] [%] [%] [%] AAA AAA AAA AAA AAA AAA AAA AAA AAA Acknowledgments This work has been founded by the EU-PASSAM project (Grant agreement No Euratom 7FP). References [1] Y. Pontillon y G. Ducros, «Behaviour of fission products under severe PWR accident conditions: The VERCORS experimental programme Part 2: Release and transport of fission gases and volatile fission products», Nucl. Eng. Des., vol. 240, n. o 7, pp , jul [2] M. P. Kissane, «On the nature of aerosols produced during a severe accident of a water-cooled nuclear reactor», Nucl. Eng. Des., vol. 238, n. o 10, pp , oct

10 [3] H. J. Allelein, A. Auvinen, J. Ball, S. Güntay, L. E. Herranz, A. Hidaka, A. V. Jones, M. Kissane, D. Powers, y G. Weber, «State-of-the-Art Report on Nuclear Aerosols». Nuclear Energy Agency Committee On The Safety Of Nuclear Installations, 02-jul [4] E. Riera, I. González-Gomez, G. Rodríguez, y J. A. Gallego-Juárez, «34 - Ultrasonic agglomeration and preconditioning of aerosol particles for environmental and other applications», en Power Ultrasonics, Oxford: Woodhead Publishing, 2015, pp [5] H. S. Patterson y W. Cawood, «Phenomena in a Sounding Tube.», Nature, vol. 127, n. o 3209, pp , may [6] S. Temkin, Elements of Acoustics, Later Printing edition. New York: John Wiley & Sons Inc, [7] L. Song, G. H. Koopmann, y T. L. Hoffmann, «An Improved Theoretical Model of Acoustic Agglomeration», J. Vib. Acoust., vol. 116, n. o 2, pp , abr [8] S. Temkin, «Gasdynamic agglomeration of aerosols. I. Acoustic waves», Phys. Fluids 1994-Present, vol. 6, n. o 7, pp , jul [9] L. Song, «Modeling of Acoustic Agglomeration of Fine Aerosol Particles.», PhD Thesis, ene [10] E. P. Mednikov, Acoustic Coagulation and Precipitation of Aerosols. Boston, MA: Springer US, [11] N. Yamaguchi, M. Mitome, A.-H. Kotone, M. Asano, K. Adachi, y T. Kogure, «Internal structure of cesium-bearing radioactive microparticles released from Fukushima nuclear power plant», Sci. Rep., vol. 6, p , feb [12] H. Malá, P. Rulík, V. Bečková, J. Mihalík, y M. Slezáková, «Particle size distribution of radioactive aerosols after the Fukushima and the Chernobyl accidents», J. Environ. Radioact., vol. 126, pp , dic [13] E. I. Kauppinen, R. E. Hillamo, S. H. Aaltonen, y K. T. S. Sinkko, «Radioactivity size distributions of ambient aerosols in Helsinki, Finland, during May 1986 after Chernobyl accident: preliminary report», Environ. Sci. Technol., vol. 20, n. o 12, pp , dic [14] M. Aleixandre, E. Rierra, R. Delgado-Tardáguila, L. Herranz, V. Acosta, A. Pinto, I. Martínez, y J. A. Gallego-Juárez, «Characterization Of The Changes Of The Particle Size Distribution Of Different Aerosols During An Acoustic Agglomeration Process», en 42 o CONGRESO ESPAÑOL DE ACÚSTICA, Valencia, [15] J. A. Gallego-Juarez, G. Rodriguez-Corral, y L. Gaete-Garreton, «An ultrasonic transducer for high power applications in gases», Ultrasonics, vol. 16, n. o 6, pp , nov [16] A. Järvinen, M. Aitomaa, A. Rostedt, J. Keskinen, y J. Yli-Ojanperä, «Calibration of the new electrical low pressure impactor (ELPI+)», J. Aerosol Sci., vol. 69, pp , mar [17] G. Buonanno, M. Dell Isola, L. Stabile, y A. Viola, «Uncertainty Budget of the SMPS APS System in the Measurement of PM1, PM2.5, and PM10», Aerosol Sci. Technol., vol. 43, n. o 11, pp , oct [18] M. Marjamäki, J. Keskinen, D.-R. Chen, y D. Y. H. Pui, «PERFORMANCE EVALUATION OF THE ELECTRICAL LOW-PRESSURE IMPACTOR (ELPI)», J. Aerosol Sci., vol. 31, n. o 2, pp , feb [19] E. Riera-Franco de Sarabia, L. Elvira-Segura, I. González-Gómez, J. J. Rodrıǵuez-Maroto, R. Muñoz- Bueno, y J. L. Dorronsoro-Areal, «Investigation of the influence of humidity on the ultrasonic agglomeration of submicron particles in diesel exhausts», Ultrasonics, vol. 41, n. o 4, pp , jun

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