The Experts below are selected from a list of 12054 Experts worldwide ranked by ideXlab platform

Zaki Suud - One of the best experts on this subject based on the ideXlab platform.

  • comparison of uranium plutonium nitride u pu n and thorium nitride th n fuel for 500 mwth gas cooled Fast Reactor gfr long life without refueling
    International Journal of Energy Research, 2018
    Co-Authors: Ratna Dewi Syarifah, Dwi Irwanto, Zaki Suud, Khairul Basar, Sandro Clief Pattipawaej, Muhammad Ilham
    Abstract:

    Summary Comparison of uranium plutonium nitride and thorium nitride fuel for 500 MWth Gas-Cooled Fast Reactor has been done. Gas-Cooled Fast Reactor is one type of generation IV Reactor that can be operated in high temperature. Due to the high temperature, it can be used in hydrogen production. In this study, we compare the neutronic analysis of two fuel types, ie, uranium nitride fuel (U,Pu)N and thorium nitride fuel (Th,U233)N. The neutronic calculation uses SRAC2006 code system, and the data libraries use JENDL4.0. First, the fuel pin calculation (PIJ calculation) has been done to take the macro data that are used in CITATION calculation. Both uranium and thorium fuel use heterogeneous configuration with 3 variation fuel in the core. F1 is located in the central core, F2 middle core, and F3 outer core. The variation of fuel fraction is 40% until 65%, cladding 10%, and coolant 25% until 40%. For (U,Pu)N fuel, the diameter of the active core is 220 cm, and the height of the active core is 110 cm. And for (Th,U233)N, the diameter of the active core is 250 cm and the height of the active core is 150 cm. The reflector radial-axial width is 50 cm. For uranium plutonium nitride fuel, the type of the fuel in one core is varied; ie, F1 is 8%, F2 is 10%, and F3 is 12%. For thorium nitride fuel, the type of the fuel in one core also varied; ie, F1 is 7.8%, F2 is 8%, and F3 is 8.8%. The optimum value of thorium nitride is when fuel fraction of region F1 = 60%, F2 = 57.5%, F3 = 60%, the burn up time up to 20 years without refueling, max k-eff value is 1.0109, and max excess reactivity value is 1.08%. Neutronic analysis shows that both uranium and thorium fuel have excess reactivity value less than 2% but thorium fuel has excess reactivity less than uranium nitride fuel. Uranium fuel has better breeding capability than thorium fuel. Therefore, it is better to use uranium fuel for Fast Reactor like GFR, which has high breeding capability.

  • design study of small modified candle based long life gas cooled Fast Reactors
    Energy Procedia, 2017
    Co-Authors: Zaki Suud, Hiroshi Sekimoto, Menik Ariani, Abdul Waris, Fitria Miftasani, A Sarah, P Sidik
    Abstract:

    Abstract Small size modified CANDLE burn-up based Long Life Gas Cooled Fast Reactors have been investigated. In this study gas cooled Fast Reactor system are combined with modified CANDLE burn-up scheme to create long life Fast Reactors with natural circulation as fuel cycle input. Such system can utilize natural uranium resources efficiently without the necessity of fuel enrichment plant or fuel reprocessing plant. The investigated power level is in the range of 200-400 MWt. For small Reactors, modified CANDLE burn-up design has difficulty in term of criticality aspect. Therefore some important steps are adopted to overcome this problem. First, combined axial-radial shuffling is adopted. Then, high fuel volume fraction of about 65% is adopted. The optimization processes is then conducted which includes adjustment of fuel region movement scheme, volume fraction adjustment, core dimension, etc. Due to the limitation of thermal hydraulic aspects, the maximum average power density of the proposed design is selected of about 75 W/cc. All proposed Reactor design are operated for 10 years without refueling or fuel shuffling with just need natural uranium as fuel cycle input in every beginning of 10 years of cycle. With such conditions small sized cores from 200MWt to 400 MWt were investigated and optimized. The average discharge burn-up is about 20% HM. As an example, the dimension of 200 MWt case is 90 cm in radius and 180 cm height for the active core part. The reflector is 70 cm with. The burn-up level is about 20% HM.

  • power flattening on modified candle small long life gas cooled Fast Reactor
    4TH INTERNATIONAL CONFERENCE ON ADVANCES IN NUCLEAR SCIENCE AND ENGINEERING (ICANSE 2013), 2014
    Co-Authors: Fiber Monado, Zaki Suud, Menik Ariani, Abdul Waris, Khairul Basar, Hiroshi Sekimoto
    Abstract:

    Gas-Cooled Fast Reactor (GFR) is one of the candidates of next generation Nuclear Power Plants (NPPs) that expected to be operated commercially after 2030. In this research conceptual design study of long life 350 MWt GFR with natural uranium metallic fuel as fuel cycle input has been performed. Modified CANDLE burn-up strategy with first and second regions located near the last region (type B) has been applied. This Reactor can be operated for 10 years without refuelling and fuel shuffling. Power peaking reduction is conducted by arranging the core radial direction into three regions with respectively uses fuel volume fraction 62.5%, 64% and 67.5%. The average power density in the modified core is about 82 Watt/cc and the power peaking factor decreased from 4.03 to 3.43.

  • application of modified candle burnup to very small long life gas cooled Fast Reactor
    Advanced Materials Research, 2013
    Co-Authors: Fiber Monado, Zaki Suud, Menik Ariani, Abdul Waris, Khairul Basar, Hiroshi Sekimoto
    Abstract:

    Gas-Cooled Fast Reactor is a good candidate for fourth generation nuclear power plant that projected to be used started in 2030. In this study, modified CANDLE burn-up strategy is adopted to create 300 MWt long life Gas-Cooled Fast Reactor with metallic fuel U-10wt%Zr without enrichment. This design demonstrated excellent performance with the average discharge burn-up is about 25.9% HM.

  • conceptual design study of small long life gas cooled Fast Reactor with modified candle burn up scheme
    THE 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN NUCLEAR SCIENCE AND ENGINEERING 2009‐ICANSE 2009, 2010
    Co-Authors: Nur A Asiah, Zaki Suud, A Ferhat, Hiroshi Sekimoto
    Abstract:

    In this paper, conceptual design study of Small Long‐life Gas Cooled Fast Reactors with Natural Uranium as Fuel Cycle Input has been performed. In this study Gas Cooled Fast Reactor is slightly modified by employing modified CANDLE burn‐up scheme so that it can use Natural Uranium as fuel cycle input. Due to their hard spectrum, GCFR in this study showed very good performance in converting U‐238 to plutonium in order to maintain the operation condition requirement of long‐life Reactors. Due to the limitation of thermal hydraulic aspects, the average power density of the proposed design is selected about 70 W/cc. With such condition we got an optimal design of 325 MWt Reactors which can be operated 10 years without refueling and fuel shuffling and just need natural uranium as fuel cycle input. The average discharge burn‐up is about 290 GWd/ton HM.

Hiroshi Sekimoto - One of the best experts on this subject based on the ideXlab platform.

  • design study of small modified candle based long life gas cooled Fast Reactors
    Energy Procedia, 2017
    Co-Authors: Zaki Suud, Hiroshi Sekimoto, Menik Ariani, Abdul Waris, Fitria Miftasani, A Sarah, P Sidik
    Abstract:

    Abstract Small size modified CANDLE burn-up based Long Life Gas Cooled Fast Reactors have been investigated. In this study gas cooled Fast Reactor system are combined with modified CANDLE burn-up scheme to create long life Fast Reactors with natural circulation as fuel cycle input. Such system can utilize natural uranium resources efficiently without the necessity of fuel enrichment plant or fuel reprocessing plant. The investigated power level is in the range of 200-400 MWt. For small Reactors, modified CANDLE burn-up design has difficulty in term of criticality aspect. Therefore some important steps are adopted to overcome this problem. First, combined axial-radial shuffling is adopted. Then, high fuel volume fraction of about 65% is adopted. The optimization processes is then conducted which includes adjustment of fuel region movement scheme, volume fraction adjustment, core dimension, etc. Due to the limitation of thermal hydraulic aspects, the maximum average power density of the proposed design is selected of about 75 W/cc. All proposed Reactor design are operated for 10 years without refueling or fuel shuffling with just need natural uranium as fuel cycle input in every beginning of 10 years of cycle. With such conditions small sized cores from 200MWt to 400 MWt were investigated and optimized. The average discharge burn-up is about 20% HM. As an example, the dimension of 200 MWt case is 90 cm in radius and 180 cm height for the active core part. The reflector is 70 cm with. The burn-up level is about 20% HM.

  • power flattening on modified candle small long life gas cooled Fast Reactor
    4TH INTERNATIONAL CONFERENCE ON ADVANCES IN NUCLEAR SCIENCE AND ENGINEERING (ICANSE 2013), 2014
    Co-Authors: Fiber Monado, Zaki Suud, Menik Ariani, Abdul Waris, Khairul Basar, Hiroshi Sekimoto
    Abstract:

    Gas-Cooled Fast Reactor (GFR) is one of the candidates of next generation Nuclear Power Plants (NPPs) that expected to be operated commercially after 2030. In this research conceptual design study of long life 350 MWt GFR with natural uranium metallic fuel as fuel cycle input has been performed. Modified CANDLE burn-up strategy with first and second regions located near the last region (type B) has been applied. This Reactor can be operated for 10 years without refuelling and fuel shuffling. Power peaking reduction is conducted by arranging the core radial direction into three regions with respectively uses fuel volume fraction 62.5%, 64% and 67.5%. The average power density in the modified core is about 82 Watt/cc and the power peaking factor decreased from 4.03 to 3.43.

  • Conceptual design study on very small long-life gas cooled Fast Reactor using metallic natural Uranium-Zr as fuel cycle input
    2014
    Co-Authors: Fiber Monado, Menik Ariani, Zaki Su’ud, Abdul Waris, Ferhat Aziz, Khairul Basar, Sidik Permana, Hiroshi Sekimoto
    Abstract:

    A conceptual design study of very small 350 MWth Gas-Cooled Fast Reactors with Helium coolant has been performed. In this study Modified CANDLE burn-up scheme was implemented to create small and long life Fast Reactors with natural Uranium as fuel cycle input. Such system can utilize natural Uranium resources efficiently without the necessity of enrichment plant or reprocessing plant. The core with metallic fuel based was subdivided into 10 regions with the same volume. The fresh Natural Uranium is initially put in region-1, after one cycle of 10 years of burn-up it is shifted to region-2 and the each region-1 is filled by fresh Natural Uranium fuel. This concept is basically applied to all axial regions. The Reactor discharge burn-up is 31.8% HM. From the neutronic point of view, this design is in compliance with good performance.

  • application of modified candle burnup to very small long life gas cooled Fast Reactor
    Advanced Materials Research, 2013
    Co-Authors: Fiber Monado, Zaki Suud, Menik Ariani, Abdul Waris, Khairul Basar, Hiroshi Sekimoto
    Abstract:

    Gas-Cooled Fast Reactor is a good candidate for fourth generation nuclear power plant that projected to be used started in 2030. In this study, modified CANDLE burn-up strategy is adopted to create 300 MWt long life Gas-Cooled Fast Reactor with metallic fuel U-10wt%Zr without enrichment. This design demonstrated excellent performance with the average discharge burn-up is about 25.9% HM.

  • conceptual design study of small long life gas cooled Fast Reactor with modified candle burn up scheme
    THE 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN NUCLEAR SCIENCE AND ENGINEERING 2009‐ICANSE 2009, 2010
    Co-Authors: Nur A Asiah, Zaki Suud, A Ferhat, Hiroshi Sekimoto
    Abstract:

    In this paper, conceptual design study of Small Long‐life Gas Cooled Fast Reactors with Natural Uranium as Fuel Cycle Input has been performed. In this study Gas Cooled Fast Reactor is slightly modified by employing modified CANDLE burn‐up scheme so that it can use Natural Uranium as fuel cycle input. Due to their hard spectrum, GCFR in this study showed very good performance in converting U‐238 to plutonium in order to maintain the operation condition requirement of long‐life Reactors. Due to the limitation of thermal hydraulic aspects, the average power density of the proposed design is selected about 70 W/cc. With such condition we got an optimal design of 325 MWt Reactors which can be operated 10 years without refueling and fuel shuffling and just need natural uranium as fuel cycle input. The average discharge burn‐up is about 290 GWd/ton HM.

Nicola Pedroni - One of the best experts on this subject based on the ideXlab platform.

  • Estimating the small failure probability of a nuclear passive safety system by means of an efficient Adaptive Metamodel-Based Subset Importance Sampling method
    2015
    Co-Authors: Nicola Pedroni, Enrico Zio
    Abstract:

    The assessment of the functional failure probability of a thermal-hydraulic (T-H) passive system can be done by Monte Carlo (MC) sampling of the uncertainties affecting the T-H system model and its parameters. The computational effort associated to this approach can be prohibitive because of the large number of lengthy T-H code simulations necessary for the accurate and precise quantification of the (typically small) failure probability. To overcome this issue, in the present paper we propose an Adaptive Metamodel-Based Subset Importance Sampling (AM-SIS) approach that originally and efficiently combines the powerful features of several advanced computational methods of literature: in particular, Subset Simulation (SS) and Fast-running Artificial Neural Network (ANN) metamodels are coupled within an adaptive MC-based Importance Sampling (IS) scheme. The objective is to construct a fully nonparametric estimator of the ideal, zero-variance Importance Sampling Density (ISD) and iteratively refine it, in such a way that: (i) the accuracy and precision of the corresponding failure probability estimates are improved and (ii) the number of burdensome T-H code runs is reduced, along with the associated computational cost. The method is demonstrated on a case study of an emergency passive decay heat removal system of a Gas-Cooled Fast Reactor (GFR). A thorough comparison is made with respect to several advanced MC methods of literature.

  • monte carlo simulation based sensitivity analysis of the model of a thermal hydraulic passive system
    Reliability Engineering & System Safety, 2012
    Co-Authors: Enrico Zio, Nicola Pedroni
    Abstract:

    Thermal-Hydraulic (T-H) passive safety systems are potentially more reliable than active systems, and for this reason are expected to improve the safety of nuclear power plants. However, uncertainties are present in the operation and modeling of a T-H passive system and the system may find itself unable to accomplish its function. For the analysis of the system functional failures, a mechanistic code is used and the probability of failure is estimated based on a Monte Carlo (MC) sample of code runs which propagate the uncertainties in the model and numerical values of its parameters/variables. Within this framework, sensitivity analysis aims at determining the contribution of the individual uncertain parameters (i.e., the inputs to the mechanistic code) to (i) the uncertainty in the outputs of the T-H model code and (ii) the probability of functional failure of the passive system. The analysis requires multiple (e.g., many hundreds or thousands) evaluations of the code for different combinations of system inputs: this makes the associated computational effort prohibitive in those practical cases in which the computer code requires several hours to run a single simulation. To tackle the computational issue, in this work the use of the Subset Simulation (SS) and Line Sampling (LS) methods is investigated. The methods are tested on two case studies: the first one is based on the well-known Ishigami function [1]; the second one involves the natural convection cooling in a Gas-Cooled Fast Reactor (GFR) after a Loss of Coolant Accident (LOCA) [2].

  • estimation of the failure probability of a thermal hydraulic passive system by means of artificial neural networks and quadratic response surfaces
    European Safety and RELiability (ESREL) 2010 Conference, 2010
    Co-Authors: Enrico Zio, George E Apostolakis, Nicola Pedroni
    Abstract:

    In this paper, Artificial Neural Network (ANN) and quadratic Response Surface (RS) empirical regression models are used as Fast-running surrogates of a thermal-hydraulic (T-H) system code to reduce the computational burden associated with the estimation of the functional failure probability of a T-H passive system. The ANN and quadratic RS models are constructed on a limited-size set of input/output data examples of the nonlinear relationships underlying the original T-H code; once built, these models are used for performing, in an acceptable computational time, the numerous system response calculations needed for an accurate uncertainty propagation and failure probability estimation. An application to the functional failure analysis of an emergency passive decay heat removal system in a simple steady-state model of a Gas-Cooled Fast Reactor (GFR) is presented.

  • comparison of bootstrapped artificial neural networks and quadratic response surfaces for the estimation of the functional failure probability of a thermal hydraulic passive system
    Reliability Engineering & System Safety, 2010
    Co-Authors: Nicola Pedroni, Enrico Zio, George E Apostolakis
    Abstract:

    In this work, bootstrapped artificial neural network (ANN) and quadratic response surface (RS) empirical regression models are used as Fast-running surrogates of a thermal-hydraulic (T-H) system code to reduce the computational burden associated with estimation of functional failure probability of a T-H passive system. The ANN and quadratic RS models are built on a few data representative of the input/output nonlinear relationships underlying the T-H code. Once built, these models are used for performing, in reasonable computational time, the numerous system response calculations required for failure probability estimation. A bootstrap of the regression models is implemented for quantifying, in terms of confidence intervals, the uncertainties associated with the estimates provided by ANNs and RSs. The alternative empirical models are compared on a case study of an emergency passive decay heat removal system of a Gas-Cooled Fast Reactor (GFR).

  • estimation of the functional failure probability of a thermal hydraulic passive system by subset simulation
    Nuclear Engineering and Design, 2009
    Co-Authors: Enrico Zio, Nicola Pedroni
    Abstract:

    Abstract In the light of epistemic uncertainties affecting the model of a thermal–hydraulic (T–H) passive system and the numerical values of its parameters, the system may find itself in working conditions which do not allow it to accomplish its function as required. The estimation of the probability of these functional failures can be done by Monte Carlo (MC) sampling of the uncertainties in the model followed by the computation of the system response by a mechanistic T–H code. The procedure requires considerable computational efforts for achieving accurate estimates. Efficient methods for sampling the uncertainties in the model are thus in order. In this paper, the recently developed Subset Simulation (SS) method is considered for improving the efficiency of the random sampling. The method, originally developed to solve structural reliability problems, is founded on the idea that a small failure probability can be expressed as a product of larger conditional probabilities of some intermediate events: with a proper choice of the conditional events, the conditional probabilities can be made sufficiently large to allow accurate estimation with a small number of samples. Markov Chain Monte Carlo (MCMC) simulation, based on the Metropolis algorithm, is used to efficiently generate the conditional samples, which is otherwise a non-trivial task. The method is here developed for efficiently estimating the probability of functional failure of an emergency passive decay heat removal system in a simple steady-state model of a Gas-Cooled Fast Reactor (GFR). The efficiency of the method is demonstrated by comparison to the commonly adopted standard Monte Carlo Simulation (MCS).

Enrico Zio - One of the best experts on this subject based on the ideXlab platform.

  • Estimating the small failure probability of a nuclear passive safety system by means of an efficient Adaptive Metamodel-Based Subset Importance Sampling method
    2015
    Co-Authors: Nicola Pedroni, Enrico Zio
    Abstract:

    The assessment of the functional failure probability of a thermal-hydraulic (T-H) passive system can be done by Monte Carlo (MC) sampling of the uncertainties affecting the T-H system model and its parameters. The computational effort associated to this approach can be prohibitive because of the large number of lengthy T-H code simulations necessary for the accurate and precise quantification of the (typically small) failure probability. To overcome this issue, in the present paper we propose an Adaptive Metamodel-Based Subset Importance Sampling (AM-SIS) approach that originally and efficiently combines the powerful features of several advanced computational methods of literature: in particular, Subset Simulation (SS) and Fast-running Artificial Neural Network (ANN) metamodels are coupled within an adaptive MC-based Importance Sampling (IS) scheme. The objective is to construct a fully nonparametric estimator of the ideal, zero-variance Importance Sampling Density (ISD) and iteratively refine it, in such a way that: (i) the accuracy and precision of the corresponding failure probability estimates are improved and (ii) the number of burdensome T-H code runs is reduced, along with the associated computational cost. The method is demonstrated on a case study of an emergency passive decay heat removal system of a Gas-Cooled Fast Reactor (GFR). A thorough comparison is made with respect to several advanced MC methods of literature.

  • monte carlo simulation based sensitivity analysis of the model of a thermal hydraulic passive system
    Reliability Engineering & System Safety, 2012
    Co-Authors: Enrico Zio, Nicola Pedroni
    Abstract:

    Thermal-Hydraulic (T-H) passive safety systems are potentially more reliable than active systems, and for this reason are expected to improve the safety of nuclear power plants. However, uncertainties are present in the operation and modeling of a T-H passive system and the system may find itself unable to accomplish its function. For the analysis of the system functional failures, a mechanistic code is used and the probability of failure is estimated based on a Monte Carlo (MC) sample of code runs which propagate the uncertainties in the model and numerical values of its parameters/variables. Within this framework, sensitivity analysis aims at determining the contribution of the individual uncertain parameters (i.e., the inputs to the mechanistic code) to (i) the uncertainty in the outputs of the T-H model code and (ii) the probability of functional failure of the passive system. The analysis requires multiple (e.g., many hundreds or thousands) evaluations of the code for different combinations of system inputs: this makes the associated computational effort prohibitive in those practical cases in which the computer code requires several hours to run a single simulation. To tackle the computational issue, in this work the use of the Subset Simulation (SS) and Line Sampling (LS) methods is investigated. The methods are tested on two case studies: the first one is based on the well-known Ishigami function [1]; the second one involves the natural convection cooling in a Gas-Cooled Fast Reactor (GFR) after a Loss of Coolant Accident (LOCA) [2].

  • estimation of the failure probability of a thermal hydraulic passive system by means of artificial neural networks and quadratic response surfaces
    European Safety and RELiability (ESREL) 2010 Conference, 2010
    Co-Authors: Enrico Zio, George E Apostolakis, Nicola Pedroni
    Abstract:

    In this paper, Artificial Neural Network (ANN) and quadratic Response Surface (RS) empirical regression models are used as Fast-running surrogates of a thermal-hydraulic (T-H) system code to reduce the computational burden associated with the estimation of the functional failure probability of a T-H passive system. The ANN and quadratic RS models are constructed on a limited-size set of input/output data examples of the nonlinear relationships underlying the original T-H code; once built, these models are used for performing, in an acceptable computational time, the numerous system response calculations needed for an accurate uncertainty propagation and failure probability estimation. An application to the functional failure analysis of an emergency passive decay heat removal system in a simple steady-state model of a Gas-Cooled Fast Reactor (GFR) is presented.

  • comparison of bootstrapped artificial neural networks and quadratic response surfaces for the estimation of the functional failure probability of a thermal hydraulic passive system
    Reliability Engineering & System Safety, 2010
    Co-Authors: Nicola Pedroni, Enrico Zio, George E Apostolakis
    Abstract:

    In this work, bootstrapped artificial neural network (ANN) and quadratic response surface (RS) empirical regression models are used as Fast-running surrogates of a thermal-hydraulic (T-H) system code to reduce the computational burden associated with estimation of functional failure probability of a T-H passive system. The ANN and quadratic RS models are built on a few data representative of the input/output nonlinear relationships underlying the T-H code. Once built, these models are used for performing, in reasonable computational time, the numerous system response calculations required for failure probability estimation. A bootstrap of the regression models is implemented for quantifying, in terms of confidence intervals, the uncertainties associated with the estimates provided by ANNs and RSs. The alternative empirical models are compared on a case study of an emergency passive decay heat removal system of a Gas-Cooled Fast Reactor (GFR).

  • estimation of the functional failure probability of a thermal hydraulic passive system by subset simulation
    Nuclear Engineering and Design, 2009
    Co-Authors: Enrico Zio, Nicola Pedroni
    Abstract:

    Abstract In the light of epistemic uncertainties affecting the model of a thermal–hydraulic (T–H) passive system and the numerical values of its parameters, the system may find itself in working conditions which do not allow it to accomplish its function as required. The estimation of the probability of these functional failures can be done by Monte Carlo (MC) sampling of the uncertainties in the model followed by the computation of the system response by a mechanistic T–H code. The procedure requires considerable computational efforts for achieving accurate estimates. Efficient methods for sampling the uncertainties in the model are thus in order. In this paper, the recently developed Subset Simulation (SS) method is considered for improving the efficiency of the random sampling. The method, originally developed to solve structural reliability problems, is founded on the idea that a small failure probability can be expressed as a product of larger conditional probabilities of some intermediate events: with a proper choice of the conditional events, the conditional probabilities can be made sufficiently large to allow accurate estimation with a small number of samples. Markov Chain Monte Carlo (MCMC) simulation, based on the Metropolis algorithm, is used to efficiently generate the conditional samples, which is otherwise a non-trivial task. The method is here developed for efficiently estimating the probability of functional failure of an emergency passive decay heat removal system in a simple steady-state model of a Gas-Cooled Fast Reactor (GFR). The efficiency of the method is demonstrated by comparison to the commonly adopted standard Monte Carlo Simulation (MCS).

Fabienne Audubert - One of the best experts on this subject based on the ideXlab platform.

  • chemical degradation of sic sic composite for the cladding of gas cooled Fast Reactor in case of severe accident scenarios
    Corrosion Science, 2012
    Co-Authors: Ludovic Charpentier, Marianne Balatpichelin, Eric Beche, K Dawi, Fabienne Audubert
    Abstract:

    Abstract High temperature oxidation was performed on structural materials made of fibres of SiC in a SiC matrix (SiC/SiC) + β-SiC coating, considered for the cladding of the Gas-Cooled Fast Reactor. Tests carried out in various atmospheres (helium, nitrogen, air) coupled to mass variation, SEM and XPS analysis enabled the study of resistance to chemical degradation of such composites from 1400 to 2300 K. Monolithic β-SiC was also studied for comparison. The degradation of the composite material was Faster than the monolithic one above 1970 K due to the damage of the β-SiC coating enabling the oxidizing species to penetrate inside the composite.

  • high temperature oxidation of sic under helium with low pressure oxygen part 1 sintered α sic
    Journal of The European Ceramic Society, 2010
    Co-Authors: Ludovic Charpentier, Marianne Balatpichelin, H Glenat, Eric Beche, E Laborde, Fabienne Audubert
    Abstract:

    Abstract In the frame of the Generation IV International Forum, Gas-Cooled Fast Reactor (GFR) is one system studied by CEA (France). Helium pressurized at 7 MPa is the coolant and the nominal temperature of use is about 1300 K. The cladding materials currently considered is a SiC/SiC composite with a β-SiC coating. In case of accident, Reactor temperatures can reach 1900–2300 K. A previous study was carried out to determine the physico-chemical behavior of another polytype, α-SiC, for comparison on the position of the active to passive transition and of the mass loss rates under active conditions to simulate a typical accident. Experimental oxidation tests at high temperature (1400–2300 K) on massive β-SiC samples processed by Chemical Vapor Deposition (CVD) coupled to mass variation, SEM, XPS, AFM and roughness analyses enabled to determine the transition between passive and active oxidation regimes, and to study the resistance to oxidation of such material in some conditions that might be encountered in case of accident (high temperature increase up to 2300 K). Finally, the experimental results have shown that the transition from passive to active regime occurs at higher temperature for β-SiC than for α-SiC and that the mass loss rate of β-SiC is lower than the one measured for α-SiC on the common temperature range investigated (up to 2100 K).