Numerical simulations of hydrogen peroxide decomposition in a monolithic catalyst for rocket engines applications

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1 Numerical simulations of hydrogen peroxide decomposition in a monolithic catalyst for rocket engines applications Nadia Maricelti DIAS - Department of Aerospace Engineering, University Federico II, P.le Tecchio 80, Naples (Italy), nadia.maricelti@tin.it The present thesis work is developed within the GRASP (GReen Advanced Space Propulsion) project (EC 7th FP) that aims at providing the European-space industry with alternative propellants to replace the currently used highly toxic and carcinogenic propellants. These alternative, so-called green propellants, will reduce the potential harm to human operators and the environment and thereby significantly reduce the associated handling costs. The three major elements of GRASP are propellant development, catalyst development and propulsion system development and application. This thesis deals with the catalyst development, namely has the purpose to analyze the decomposition process of a specific propellant (hydrogen peroxide) as it flows through the catalytic reactor. The analysis is based on the utilization of a Computational Fluid Dynamics (CFD) code. The CFD predictions have been carried out for both a 2D and a 3D catalytic chamber model, that represent respectively a tubular monolithic bed and a honeycomb reactor. A parametric analysis has been run, to assess the impact on the catalyst efficiency, or equivalently on the temperature of the exhaust gases produced by the exothermic decomposition reaction: a higher temperature corresponds to a higher reaction efficiency and so to an enhanced utilization of the reaction products for propulsive scope. I. Introduction Hydrogen peroxide has been used in many applications for propulsion and power in the past 70 years. The characteristics that make hydrogen peroxide really interesting in the space propulsion are the high density, the non toxicity, the storability, it is non-reacting with atmosphere but above all it is extremely versatile. The essential operating scheme of a H 2 O 2 -based engine is illustrated in Figure 1, reporting the basic scheme applicable to both a monopropellant and a bi-propellant configuration. Monopropellant rockets utilize the energy released by the decomposition of the peroxide, promoted by a catalyst. Hydrogen peroxide is fed from a pressurized tank and flows to the catalyst, that in this case replaces the combustion chamber, where the chemical reaction can occur. Then the reaction products expand in a convergent-divergent nozzle generating the thrust. This rocket configuration is useful when low specific impulse and a relatively simple configuration are required. An example of application is satellites attitude control. In a bi-propellant rocket, the thrust is generated by an oxidizing and a reducing agent that are injected in a combustion chamber where a chemical reaction starts, generating high pressure and high temperature values. This engine needs an injection and a pump system that make its configuration much more complex than a monopropellant. But if high specific impulses are required, a bi-prop has to been chosen. The advantages related to the utilization of as propellant are not only for macro-scale systems but also for micro-thrusters: it has been shown that for space, air, ground and sea applications monopropellant hydrogen peroxide based propulsion in general terms provides the best overall solution.[2] 1 of 11

2 Figure 1: H 2 O 2 -based engine scheme For the above-mentioned applications, the design of a highly efficient catalyst is of paramount importance to ensure high propulsion efficiencies. For such reason, this work presents a tool able to predict the performances of the catalytic chamber, in order to support the development of H 2 O 2 -based engines and to reduce the trial-and-error experimental procedure upon which such development has widely relied till now. II. Catalytic beds The heterogeneous catalytic decomposition of hydrogen peroxide has been extensively analyzed in the past and several technological options have been proposed; the solution where peroxide is injected in a monolithic reactor, flowing through parallel channels, has been considered as workhorse by the author of this paper. The utilization of a monolithic catalyst significantly reduces the pressure loss across the catalyst bed, compared to pellets or gauze catalysts. The lower pressure drop results in a lower feeding pressure, allowing the use of a lighter tank and hence reducing the total structural weight. Two different catalyst geometries, shown in Figure 2, have been dealt with in this thesis work: a tubular catalyst (for preliminary assessment of catalyst behaviour) and a honeycomb catalyst (that is actually used in both the monopropellant and the hybrid test rigs currently under development at the DIAS Laboratory of Propulsion). Figure 2: Tubular (left) and honeycomb (right) monoliths III. CFD simulations The heterogeneous decomposition of hydrogen peroxide presents a plenty of physical/chemical processes which should be properly accounted for in modelling and simulation: bulk phase phenomena, as the diffusion of reagents/products to/from the catalytic surface, and wall processes, as adsorption, catalytic reaction and desorption. This complex environment is further complicated by the multiphase nature of the flow (the peroxide enters the reactor in liquid phase, the product of the decomposition reaction exit as gases) and by the coupling of heat and mass transfer. A full simulation of the real decomposition process should require very complex tools and a huge computational effort. To support the design of the reactor with sufficiently accurate predictions and within reasonable times, a CFD model has 2 of 11

3 been created to predict the behaviour for both 2D and 3D catalytic chamber. The use of such tool is necessary to evaluate the catalyst s performances, to simulate the ageing or sintering but also to analyze and predict some phenomena that could reduce the efficiency like the flooding or channelling. IV. Tubular catalyst: 2D flow simulations As a first step, 2D simulations have been run. The input data utilized for 2D predictions are reported in Table 1. The model has been created defining the geometry and fluid-dynamics proprieties. Geometric Parameters Geometry axial symmetric Channel side length (or diameter) 6 mm Channel length 60 mm Chemical Parameters Mass Flow rate kg/s Operating pressure 1 bar Inlet Temperature 413 K H 2 O 2 inlet mass fraction H 2 O inlet mass fraction Kinetic Parameters Pre exponential factor 1.1e+08 s -1 Activation energy Table 1: 2D input data - baseline case [3] 5.02e+07 J/kgmol Figure 3 shows the grid geometry, the boundary conditions and a number of radial sections that have been created for post-processing. A pressure-based solver with a coupled algorithm has been adopted and the equation energy has been activated. Turbulence has been modelled according to the realizable formulation. The reaction that has been considered on the wall is: The mass transfer is described according to a multi-component diffusion model. No heat transfer to/from the environment is allowed (adiabatic wall). Figure 3: 2D Grid geometry 3 of 11

4 To allow a proper setup of the CFD work environment, in terms of accuracy and reduction of computational costs, a grid analysis has been carried out to assess the impact of the computational meshes and numerical schemes on the CFD predictions. The following simulations have been run: 1) Grid Analysis a) Impact of the number of nodes along the catalyst axis: i) 20x400 nodes ii) 20x800 nodes b) Impact of the number of nodes along the catalyst radius: i) 20x400 nodes ii) 40x400 nodes 2) Impact of the numerical scheme: a) First order scheme b) Second order scheme From the grid analysis, an influence of the discretization along the axis on the ignition point has been highlighted (the ignition point is defined as the point where the wall temperature exhibits a very strong increase): the ignition point moves forward as the number of nodes along the axial coordinate increases, or equivalently as the cell size along the axis decreases (see Figure 4). Figure 4: Wall temperature - influence of the discretization along the axial coordinate (on the right zoom on the ignition point) About the discretization along the radius, Figure 5 shows an impact on the outlet temperature value. Figure 5: Wall temperature - influence of the discretization along the radial coordinate (on the right zoom on the ignition point) 4 of 11

5 At the exit of the monolithic catalyst, the temperature with a 40x400 mesh is greater of 48K than the temperature of a 20x400 mesh; there is also a shift of the ignition point. Additional simulations have been run to assess any difference between a 40x400 and a 40x800 mesh: comparing the results (Figure 6), the temperature profiles are almost identical. Figure 6: Wall Temperature - impact of additional mesh refinement along the axis (on the right zoom on the ignition point) According to these results, a 40x400 grid has been chosen. Moreover, in the policy statement of the Journal of Fluids Engineering on the Control of Numerical Accuracy [4] is specified that solutions over a range of significantly different grid resolutions should be presented, to demonstrate grid-independent or grid-convergent results. This criterion specifically addresses the use of improved grid resolution and may also be used to prove solution accuracy. The impact of the numerical scheme has been also investigated: fixed the number of cells, an increase in the accuracy of the scheme (from the first to the second order) has been evaluated (Figure 7). The high order discretization produces a shift of the ignition point towards the reactor outlet. This effect is similar to the one corresponding to an increase in the number of cells along the axial coordinate. Also the outflow temperature is increased by approximately 30K. Furthermore, it is interesting to note that in the policy statement of the Journal of Fluids Engineering, a paper will only be considered if the discretization scheme is at least second-order accurate in space (Freitas, 1993). For these reasons, the second order upwind scheme has been adopted. Figure 7: Wall temperature - influence of the numerical scheme Having defined the most appropriate CFD work environment, let focus now on the catalytic decomposition of hydrogen peroxide. Figure 8 reports the contours of hydrogen peroxide mole fraction and temperature and described how the 5 of 11

6 catalyst work: the peroxide enters the monolithic bed and reacts with the wall, decomposing and increasing the gas temperature. Figure 8: Tubular catalyst - contours of hydrogen peroxide mole fraction (left) and temperature (right) Figures 9, 10 and 11 report respectively the mean gas temperature, the catalyst (i.e. wall) temperature and the pressure drop. Figure 9: Tubular catalyst - Mean gas temperature Figure 10: Tubular catalyst: wall temperature Figure 11: Tubular catalyst - pressure drop 6 of 11

7 After the assessment on the baseline case, a parametric analysis has been run: in Table 2, input data are presented. Test case Mass flow rate, g/s Operating pressure, bar Kinetic parameters, heterogeneous reaction Kinetic parameters, homogeneous reaction Nr. 1 Baseline case 5 1 baseline case (nominal A/Ea) not active Nr increase A, keep nominal Ea value not active Nr decrease A, keep nominal Ea value not active Nr increase/decrease Ea, keep nominal A value not active Nr baseline case active Nr. 6 LSL 1 baseline case not active Nr. 7 USL 1 baseline case not active Table 2: Parametric analysis - input data [3] Test cases nr. 2 to nr. 4 are run varying the pre-exponential factor and the activation energy in the Arrhenius equation. Test case nr. 5 is run to evaluate a possible impact of the homogenous decomposition of peroxide, but comparing the temperature profile with the one corresponding to the baseline case, no differences can be noted. Such result confirms the necessity of a catalyst to promote hydrogen peroxide decomposition. Test cases nr. 6 and 7 are run to assess the impact of the catalyst bed loading (CBL). The CBL is given by, i.e. is the mass flow rate per unit surface. For traditional catalysts this parameter varies from about 60kg/(m 2 s) (corresponding to the Lower Specification Limit, or LSL) to about 235kg/(m 2 s) (corresponding to the Upper Specification Limit, or USL. The results of the parametric analysis on kinetic parameters are summarized in Figure 12. Figure 12: Tubular catalyst - Influence of pre-exponential factor on the mean gas temperature (left); influence of the activation energy on the wall temperature (right) Different values of the pre-exponential factor may be representative of a reduction in the active phase content, due for example to catalyst ageing: within the range reported in Figure 12 (four-fold variation) no significant differences can be noted. The activation energy should be strongly increased, with respect to the value commonly reported in literature for the decomposition of hydrogen peroxide promoted by a manganese-based catalyst (about 50000J/mol, as reported in Table 1) to point out the effect of this parameter. A significantly different activation energy may be representative of a different active phase (for example platinum), hence the above analysis may support the conclusion that, within a certain range of operating conditions, the selection of the active phase may play a key role in catalyst performances. Turning now to the impact of the catalyst bed loading, Figure 13 demonstrates that increasing the mass flux that enters the catalyst, the temperature decreases. 7 of 11

8 Figure 13: Tubular catalyst - Influence of CBL V. Honeycomb catalyst: 3D flow simulations Having completed the assessment on the tubular catalyst, 3D simulations, representative of the decomposition process in a honeycomb reactor, have been run. This geometry has been chosen because the available interface area between the propellant and the catalyst (where the decomposition reaction occurs) is bigger than in a tubular catalyst (having fixed the transversal area and length), so a greater quantity can be decomposed. The overall mass flow rate is supposed to be injected uniformly across the monolith: according to this assumption, only the flow in a single honeycomb channel is modelled; the performance of the whole honeycomb is then supposed to be the sum of the performance of each individual channel or, equivalently, that the decomposition process occurs identically in every channel. Such hypothesis leads of course to a simplification of the real process, mainly due to the following reasons: a) a homogeneous distribution of the peroxide over the honeycomb cross section can be theoretically achieved, using a properly designed injection plate (having a one-to-one correspondence between the injection holes and the honeycomb channels), but variability in the flow rate injected in each channel should be actually expected, as a result of a number of factors, the most important being the hole-to-hole geometrical variability, as well as additional effects related to channelling and clogging; b) coupling between channels: namely, in the present work no heat transfer from/to the environment is modelled (an adiabatic boundary condition is assigned on the catalyst wall, as presented above); the thermal interaction occurring in a real honeycomb may affect its performance and lead to variations with respect to the values predicted assuming a simple scale up of the behaviour of a single channel supposed to operate adiabatically. A summary of the input data and operating conditions used in the 3D simulations is reported in Table 3. Test case nr. 8 Test case nr. 9 Test case nr. 10 Geometric Parameters Channel side length 1.1 mm 1.1 mm 1.1 mm Channel length 60 mm 60 mm 60 mm Chemical Parameters Mass flow rate for a single channel 0,075 g/s 0,075 g/s 0,075 g/s CBL Operating pressure 10 bar 10 bar 15 bar System configuration Monopropellant Monopropellant Hybrid Table 3: 3D flow simulations - input data 8 of 11

9 The other parameters not specified in Table 3 are equal to the baseline case. In Figure 14 the 3D channel honeycomb section has been shown. Figure 14: 3D channel honeycomb section Operating conditions representative of both a monopropellant and a hybrid configurations functioning have been simulated: the results are summarized in Figures 15 to 17. Figure 15: Monopropellant configuration hydrogen peroxide mole fraction (left) and temperature (right) contours Figure 16: Hybrid configuration hydrogen peroxide mole fraction (left) and temperature (right) contours 9 of 11

10 Figure 17: Thermal efficiency - differences between monopropellant and hybrid configurations Note that the thermal efficiency reported in this paper has been calculated thanks to the equation. VI. Comparison with experimental data The Department of Aerospace Engineering is developing hydrogen peroxide based propulsive systems, in both mono-propellant and hybrid configurations, within the GRASP project. In the propulsion laboratory situated in the Italian Air-force Base of Grazzanise, a -fed monopropellant test rig has been realized and various typologies of catalysts have been tested in order to evaluate catalysts and thruster performances. Representative data acquired during these tests have been used as input data for additional CFD simulations, as reported in Table 4. Test conditions Experimental case nr. 1 Experimental case nr. 2 Nr of honeycomb 6 6 Nr of channels per honeycomb Mass flow rate total (g/s) 10,5 13,8 Mass flow rate single channel (g/s) 0,039 0,051 Operating Pressure (bar) 9 10 Measured temperature ( C) Table 4: Experimental data The honeycombs actually utilized in the laboratory are 30 mm long, while the computational domain extends up to 60 mm: for this reason, the numerical predictions corresponding to the section at 30mm should be used to perform a comparison with experimental data. Figure 18: Mean gas temperature - experimental case nr. 1 (left) and nr. 2 (right) On the left side of Figure 18 the temperature profile for the experimental case nr. 1 has been reported: considering the value corresponding to 30mm, the predicted temperature is lower than the measured value (by about 130 C). A higher discrepancy between CFD predictions and measurements arise for the experimental case nr. 2: the test has indeed 10 of 11

11 pointed out a significant decrease in temperature (from 610 C to 200 C), possibly as a consequence of the increased mass flow rate. According to CFD predictions (Figure 18, right side), the expected temperature decrease at x=30mm is instead limited to less than 30 C. There a number of factors that may explain this discrepancy: on the numerical side, the simplifying assumptions embedded in the CFD model; on the experimental side, the temperature measurement may not be representative of the average value within the chamber but may be related to local phenomena. VII. Conclusion and future works In this paper a CFD-based tool has been presented: the tool is able to describe the catalytic decomposition of hydrogen peroxide in a monolithic catalyst and can be used to support the design and the development of a H 2 O 2 -based rocket engine. Among the possible future works, a number of modifications in the model can be considered, for example removing the adiabatic boundary condition on the catalyst wall and extending the computational domain, to allow the simulation of the flow in multiple channels and investigate the effect of possible channel-to-channel interactions. [1] References [2] Wernimont E.J. General Kinetiks Inc. Monopropellant Hydrogen Peroxide Rocket Systems: Optimum for Small Scale, 42 nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit AIAA, 2006 [3] Scelzo F., Maiello D., Caratterizzazione di catalizzatori monolitici per H2O2 in sistemi propulsivi spaziali, Master of Science Thesis, Università di Napoli "Federico II", Naples 2010 [4] Freitas C.J., Editorial Policy Statement on the Control of Numerical Accuracy, ASME J. Fluids Eng., 115, 2, 339, 1993 [5] Russo Sorge A., Turco M., Pilone G., Bagnasco G., Decomposition of Hydrogen peroxide on MnO2/TiO2 Catalysts, Journal of Propulsion and Power, Vol.20, nr. 6, 2004 [6] Bonifacio S. Analysis and Design of a Multi-phase Catalytic Reactor for the Decomposition of Hydrogen Peroxide in Space Propulsive Systems Tesi di dottorato di ricerca in Ingegneria Aerospaziale, Navale e della Qualità XVIII Ciclo, Università Federico II, Napoli, A.A. 2005/2006 [7] Ventura M., Garboden G., Brief History of Hydrogen Peroxide Uses AIAA Conf, 1999 [8] Sutton, George P. History of Liquid Propellant Rocket Engines, 2006 Edition, American Institute of Aeronautics and Astronautics, Reston, Virginia [9] Kappenstein C., Catalysis for Propulsion GRASP progress meeting, Napoli, 2010 [10] Davis N.S., McCormick J.C., Design of Catalyst Packs for the Decomposition of Hydrogen Peroxide, American Rocket Society paper nr In Bollinger, L.E., et al (eds) "Progress in Astronautics and Rocketry," vol 2, "Liquid Rockets and Propellants," Academic Press, [11] Sutton K., Gnoffo P.A., Multi-component diffusion with application to computational aerothermodynamics, AIAA Paper [12] Cybulski A., Moulijn J.A., Stankiewicz A., Novel concepts in catalysis and chemical reactors: improving the efficiency for the future Wiley VCH of 11