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• Benchmark libraries are vital for validation of nuclear simulation tools. • Temperature-dependent reactor critical experiments developed as benchmarks. • Sensitivity analysis reveals reactivity most sensitive to fuel parameters. • Sample calculations demonstrate fitness of dataset for use as a benchmark. • Sensitivity of nuclear data assessed with different data evaluation libraries. Development of benchmark libraries based on accurate experimental measurements is crucial for validation of computational toolkits in nuclear reactor design and analysis. A benchmark library is developed based on the low-power isothermal critical experiments conducted at the Walthousen Reactor Critical Facility ranging in temperatures between 16 and 46 Celsius. Sensitivity analysis was performed to evaluate uncertainties in reactivity and its temperature coefficient due to core geometry, material composition, and temperature based on the temperature-dependent experimental data. A comprehensive sensitivity study of the effect of nuclear data on criticality was also performed. The total combined uncertainty in criticality of the benchmark model due to geometry and material parameters is determined to be 144 pcm. Prediction of criticality from sample calculations lies within the benchmark model combined uncertainty from measurements, demonstrating the acceptance of these datasets for use as a benchmark for validation of simulation toolkits and evaluation of nuclear data libraries. [ABSTRACT FROM AUTHOR]

Coupled reactors and the coupling features of large or heterogeneous core reactors can be investigated with the Avery’s theory; however, the complex geometries that are often encountered in association with coupled reactors, require a detailed geometry description that can be easily provided by modern Monte Carlo (MC) codes. The results presented in this paper show that the MC code SERPENT has been successfully modified in order to compute the needed quantities like coupling coefficients. Moreover, the capability for calculating sensitivities to the quantities of interest for coupling reactors has been developed and implemented in SERPENT. [ABSTRACT FROM AUTHOR]

In a previous paper, a method was investigated to calculate sensitivity coefficients in coupled Boltzmann/Bateman problem for nuclear data (ND) uncertainties propagation on the reactivity. Different methodologies were discussed and applied on an actual example of multigroup cross section uncertainty problem for a 2D Material Testing Reactor (MTR) benchmark. It was shown that differences between methods arose from correlations between input parameters, as far as the method enables to take them into account. Those methods, unlike Monte Carlo (MC) sampling for uncertainty propagation and quantification (UQ), allow obtaining sensitivity coefficients, as well as correlations values between nuclear data, during the depletion calculation for the parameters of interest. This work is here extended to local parameters such as power factors and isotopic concentrations. It also includes fission yield (FY) uncertainty propagation, on both reactivity and power factors. Furthermore, it introduces a new methodology enabling to decorrelate direct and transmutation terms for local quantities: a Monte-Carlo method using built samples from a multidimensional Gaussian law is used to extend the previous studies, and propagate fission yield uncertainties from the CEA’s COMAC covariance file. It is shown that, for power factors, the most impacting ND are the scattering reactions, principally coming from 27 Al and (bounded hydrogen in) H 2 O. The overall effect is a reduction of the propagated uncertainties throughout the cycle thanks to negatively correlated terms. For fission yield (FY), the results show that neither reactivity nor local power factors are strongly affected by uncertainties. However, they have a non-negligible impact on some isotopic concentrations, and can lead to biases on some burnup indicators. [ABSTRACT FROM AUTHOR]

Capabilities for nuclear data sensitivity and uncertainty analysis have been recently implemented in numerous continuous-energy Monte Carlo codes, including the Reactor Monte Carlo (RMC) code. Previous work developed the capability for RMC of computing sensitivity coefficients of the effective multiplication factor and related uncertainties, due to nuclear data. In this work, such capability was extended to generalized responses in the form of ratios of linear response functions of the forward flux based on the collision history-based approach as implemented in SERPENT2. The superhistory algorithm was also adopted in RMC to reduce memory consumption for generalized sensitivity calculations. These new capabilities of RMC were verified by comparing results of TSUNAMI-1D in SCALE6.1 code package, and SERPENT2 through Jezebel, Flattop and the UAM TMI PWR pin cell benchmark problems. [ABSTRACT FROM AUTHOR]

A new functionality of fuel depletion sensitivity calculations is developed as one module in a deterministic reactor physics code system CBZ. This is based on the generalized perturbation theory for fuel depletion problems. The theory for fuel depletion problems with a multi-layer depletion step division scheme is described in detail. Numerical techniques employed in actual implementation are also provided. Verification calculations are carried out for a 3 × 3 multi-cell problem consisting of two different types of fuel pins. It is shown that the sensitivities of nuclide number densities after fuel depletion with respect to the nuclear data calculated by the new module agree well with reference sensitivities calculated by direct numerical differentiation. To demonstrate the usefulness of the new module, fuel depletion sensitivities in different multi-cell arrangements are compared and non-negligible differences are observed. Nuclear data-induced uncertainties of nuclide number densities obtained with the calculated sensitivities are also compared. [ABSTRACT FROM AUTHOR]

JRC participated in the OECD/NEA FASTRUN benchmark reviewing fast-running software tools to model fission product releases during accidents at nuclear power plants. The main goal of fast-running software tools is to foresee the accident progression, so that mitigating actions can be taken and the population can be adequately protected. Within the FASTRUN, JRC used the MAAP 4.0.8 code and developed a methodology to obtain the source term (as activity released per radioisotope) of PWR and BWR station black-out accident scenarios. The modifications made in the MAAP models were limited to a minimum number of important parameters. This aims at reproducing a crisis situation with a limited time to adapt a generic input deck. This paper presents further studies, where JRC analysed the FASTRUN BWR scenario using MAAP 5.0.2 that has the capability of calculating doses. A sensitivity study was performed with the MAAP 5.0.2 DOSE package deactivated, using the same methodology as in the case of MAAP 4.0.8 for source term calculation. The results were close to the reference LTSBO SOARCA case, independently of the methodology used. One of the benefits of using the MAAP code is the short runtime of the simulations. [ABSTRACT FROM AUTHOR]

Forward quantification of simulation (code) response uncertainties requires knowledge of physical model parameter uncertainties. Nuclear thermal-hydraulics codes, such as RELAP5 and TRACE, do not provide any information on uncertainties of physical model parameters. A framework is developed to quantify uncertainties of physical model parameters using Maximum Likelihood Estimation (MLE), Bayesian Maximum A Priori (MAP), and Markov Chain Monte Carlo (MCMC) algorithms. The objective of the present work is to perform the sensitivity analysis of the physical model parameters in code TRACE and calculate their uncertainties using MLE, MAP, and MCMC algorithms. The OECD/NEA BWR Full-size fine-mesh Bundle Test (BFBT) data is used to quantify uncertainty of selected physical models of TRACE code. The BFBT is based on a multi-rod assembly with measured data available for single or two-phase pressure drop, axial and radial void fraction distributions, and critical power for a wide range of system conditions. In this work, the steady-state cross-sectional averaged void fraction distribution is used as the input data for inverse uncertainty quantification (IUQ) algorithms, and the selected physical model’s probability distribution function (PDF) is the desired output quantity. [ABSTRACT FROM AUTHOR]

The Doppler reactivity worth of various types of nuclear fuels is evaluated using verified modeling of thermal agitation in epithermal range in order to investigate the effect of thermal agitation on the Doppler reactivity worth of practical nuclear fuels including thorium-based fuel. The Doppler reactivity worth of UO 2 fuel, MOX fuel and thorium-based fuel is evaluated using sensitivity coefficient so as to reveal the breakdown of the impact. The result shows that the thermal agitation effect on the Doppler reactivity worth is mainly observed in the energy range from 10 eV to around 100 eV because of following two facts. One is that the probability of the scattering reaction becomes small at lower energy range and second is that the impact of thermal agitation on the scattering kernel becomes small at higher energy range. Regarding MOX fuel, it is found that thermal agitation effect on the Doppler reactivity worth is smaller than UO 2 fuel since the amount of Pu-240 is smaller than that of U-238 and Pu-239 has larger absorption from 10 eV to around 100 eV compared to U-238. As for thorium-based fuel, thermal agitation effect on the Doppler reactivity worth is smaller than that of UO 2 fuel since Th-232 has small number of resonances with large ratio σ s / σ t from 10 eV to around 100 eV. [ABSTRACT FROM AUTHOR]

In this work we performed a detailed analysis on the calculation of 43 critical experiments from 6 experimental series all describing plutonium nitrate in aqueous solution contained in metal spheres. The underlying experimental data is taken from the handbook of the International Criticality Safety Benchmark Evaluation Project (ICSBEP) working group. We present our modeling assumptions which were derived from the interpretation of the experimental data and discuss the resulting uncertainty and correlation analysis. Although the experiments share some components, the derived correlation coefficients are for many cases statistically not significant. Comparing our findings for the correlation coefficients with available data from the DICE Database we find an agreement for the correlation coefficients due to nuclear data. We also compare our results for the correlation coefficients due to experimental uncertainty. Our findings indicate that for the reliable determination of correlation coefficients a detailed study of the underlying experimental data, the modeling approach and assumptions, and the resulting sensitivity analysis seems to be inevitable. [ABSTRACT FROM AUTHOR]

The XGPT method extends the Generalized Perturbation Theory capabilities of Monte Carlo codes to continuous-energy sensitivity functions. In this work, this method is proposed as a new approach to nuclear data uncertainty propagation. XGPT overcomes some of the limitations of legacy perturbation-based approaches. In particular, it allows the nuclear data uncertainty propagation to be performed adopting continuous energy covariance matrices, instead of discretized (multi-group) data. The XGPT capabilities are demonstrated in three simple fast criticality benchmarks for 239 Pu and 208 Pb cross section uncertainties. The new method is also applied in selected cases to estimate higher moments of the k eff distribution, starting from TENDL random evaluations. The XGPT estimates, when compared against reference Total Monte Carlo (TMC) results, show a good agreement and a significant reduction in computational requirements with respect to the TMC approach. Finally, the capabilities for uncertainty propagation involving adjoint-weighted response functions are demonstrated. [ABSTRACT FROM AUTHOR]

This work uses the 2-D C5G7 benchmark to verify the accuracy and efficiency of the MOCUM code, a parallel neutronics program based on the method of characteristics (MOC) for arbitrary core geometries. Compared to references, MOCUM k eff , assembly and pin power maximum percentage errors are 0.02%, −0.06%, and 0.64%, respectively. The parallel algorithm achieves speed-ups of more than 17 times, compared to the calculation speed using one thread. The sensitivity study of various MOC parameters reveals that the C5G7 benchmark problem requires 48 or more azimuthal angles. The strong flux gradient and the heterogeneous effects demand fine unstructured meshes to yield accurate flux solution. The simulation uses 258 million zones with an average mesh size of 0.016 cm 2 . The investigation of the polar angle quadrature indicates that Leonard polar angle performs slightly better and more than three polar angles are not necessary. In addition, parameter sensitivity study shows that coarse parameters are prone to introduce error to the neutron flux but not k eff . [ABSTRACT FROM AUTHOR]

The current Monte Carlo (MC) adjoint-weighted tally techniques based on the iterated fission probability (IFP) concept require a memory amount which is proportional to the numbers of the adjoint-weighted tallies and histories per cycle to store history-wise tally estimates during the convergence of the adjoint flux. Especially the conventional MC adjoint-weighted perturbation (AWP) calculations for the nuclear data sensitivity and uncertainty (S/U) analysis suffer from the huge memory consumption to realize the IFP concept. In order to reduce the memory requirement drastically, we present a new adjoint estimation method in which the memory usage is irrelevant to the numbers of histories per cycle by applying the IFP concept for the MC Wielandt calculations. The new algorithms for the adjoint-weighted kinetics parameter estimation and the AWP calculations in the MC Wielandt method are implemented in a Seoul National University MC code, McCARD and its validity is demonstrated in critical facility problems. From the comparison of the nuclear data S/U analyses, it is demonstrated that the memory amounts to store the sensitivity estimates in the proposed method become negligibly small. [ABSTRACT FROM AUTHOR]

Control rod drop is the key part of ensuring the safety of nuclear reactor shutdown. Aiming at the control rod drop problem, we established a physical model of the control rod drive line. The proposed model considers the influence of the absorbing rod's position and hence evaluates the resultant force accurately on the control rod during the whole dropping process. Based on the physical model, a unified coupling state equation on the control rod drop and fluid flow is developed by integrating the motion variables of the control rod and the fluid into a state vector. A time step adaptive symplectic (TSAS) algorithm is proposed to solve the proposed state equation. The TSAS algorithm efficiently and stably predicts the motion states of the control rod and the fluid synchronously and accurately captures the sudden change of flow state. Numerical examples confirm the correctness of the proposed model and the TSAS algorithm. Sensitivity analysis is also conducted to discuss the effects of different parameters on the control rod drop, which provides reference and help for the design and manufacturing of the control rod drive line. [ABSTRACT FROM AUTHOR]

• Multiplication factors of LMFR experiments were calculated with MCNP using various ENDF/B and JEFF libraries. • Considerable discrepancies were observed between the results obtained with the different libraries. • Best agreement of the ENDF/B-VII.1 results with the experimental findings was obtained. • NDaST was used for identifying the most important cross sections responsible for the differences to ENDF/B-VII.1 results. The paper presents results for multiplication factors of reactor physics experiments with fast spectrum systems, representative of liquid metal fast reactors, documented in the IRPhEP Handbook. The calculations were performed with the Monte Carlo code MCNP 6.1, using continuous-energy data based on ENDF/B-VII.1, ENDF/B-VIII.0, JEFF-3.1.2, JEFF-3.2, and JEFF-3.3. Considerable discrepancies were observed between the results obtained with the different data libraries. In comparison with the benchmark values of the experiments, the ENDF/B-VII.1 results show the best agreement, while for the JEFF-3.3 results, the deviations are largest. In addition, the sensitivity tool NDaST, using linear perturbation theory, was applied to identify the most important microscopic cross sections responsible for the differences of the latest library revisions ENDF/B-VIII.0 and JEFF-3.3 as compared to ENDF/B-VII.1. For JEFF-3.3 vs ENDF/B-VII.1, where the deviations are overall largest, the main contributors are U-238n, γ and, for systems containing plutonium, Pu-239 fission and total neutron multiplicity. [ABSTRACT FROM AUTHOR]

• The direct transport code SHARK was verified with the plate-type JRR-3M macro benchmark with a series of cases from 2D lattice cases to 3D whole-core cases. • The detailed geometry modeling was conducted to show the high-fidelity calculation ability in SHARK. • Sensitivity analyses were applied in the plate-type calculation with the 2D/1D transport method. The amount azimuthal angles needs to be increased compared to the traditional pin-cell cases. The JRR-3M reactor is a water-cooled plate-type reactor for research. A macro benchmark based on the JRR-3M reactor is established with the Monte-Carlo code RMC and deterministic direct transport code SHARK with accurate and explicit geometry modeling. A series of cases from 2D lattice to 3D whole-core are adopted for the verification of SHARK. In the verification, sensitivity analyses are conducted with the 2D lattice case and applied in the 3D whole-core calculation. Numerical results indicate the good accuracy of SHARK for the plate-type JRR-3M macro benchmark. [ABSTRACT FROM AUTHOR]

• Development and verification of a NEM-M2B2 mathematical inhomogeneous-adjoint nodal diffusion solver. • Application of the Lagrangian multipliers method to derive the nodal mathematical inhomogeneous-adjoint. • Derived the local linear prediction formula, specific for the forward NEM-M2B2 model, and utilized it to study the repercussions of perturbations in the IAEA-3D benchmark on the Axial Offset (AO). • Verified the generalized adjoint code developed while showing detailed steps of how inhomogeneous adjoint codes can be verified. • Compared between the low-order inhomogeneous NEM-M0 adjoint and the developed higher order inhomogeneous NEM-M2B2 model for the AO as a RoI. • Introduced the Mantissa theory to explain the behavior of the linear adjoint models and prediction formulas. A higher-order nodal mathematical inhomogeneous adjoint model conjugate to the NEM-M2B2 nodal diffusion forward model is developed and introduced in this research. Verification of the developed model is presented through applications in perturbation analysis and the IAEA-3D benchmark including adjusted forms of it. This paper's objective is to explore ways of extending and optimizing a mathematical adjoint capability suitable for use in an industrial reactor code, such that it becomes not merely an approximate but rather the exact adjoint counterpart to the typically used higher-order nodal forward solvers used in mature industrial reactor codes. Specifically, it is investigated how to upgrade an already available lower-order nodal mathematical adjoint solver towards higher-order accuracy. An example of the latter is the lower-order nodal adjoint solver used in the ARTEMIS reactor code, in the technical context of stabilization and acceleration of embedded control rod search mechanisms. Though the latter adjoint solver proved suitable for the needed preconditioning purposes, while also enabling the benefit of computationally very lean adjoint iterations, several future developments could benefit from having a higher-order adjoint nodal solver available as well. By using a preconditioned form of the base NEM-M2B2 nodal diffusion forward model and by using variational analysis, we have obtained a higher-order nodal mathematical adjoint that can have a physical interpretation associated with it as a Lagrangian multiplier. The nodal mathematical adjoint is then developed for the Axial Offset (AO) as a Response of Interest (RoI) which leads to an inhomogeneous adjoint system of equations. A solution verification of the adjoint developed is done through analyzing the effects coming from perturbations in the absorption and the scattering cross-sections. The applications investigated include axially and radially traveling perturbations along the reactor's core. Several locations for the traveling perturbations are chosen to represent important locations in the core. Comparison between the low-order and the higher-order adjoint models is conducted. The forward model is set to the NEM-M2B2 nodal diffusion equation for both adjoints during the comparison. The higher-order adjoint model developed show consistent results in comparison to its lower-order sibling, suggesting the preference of using the developed higher-order model for adjoint computations. [ABSTRACT FROM AUTHOR]

• Sensitivity of the accident rate on the plant demand rate is relevant also. • The Generalized Perturbation Theory (GPT) is useful for sensitivity analysis. • We make a sensitivity analysis by GPT (accident rate) for an aging protective channel. • We compare the results with those of the direct method (varying demand rate). We present a sensitivity analysis of a protection system of a nuclear plant equipped with a single aging protection channel. This analysis is related to the plant accident rate and considers the variation of the plant demand rate. Traditionally, the calculation of the values for this analysis has a high computational cost when considering the wear-out period. To overcome this difficulty, we used the Generalized Perturbation Theory (GPT). We developed four case studies for a wide range of demand rates. Due to the use of a first-order GPT approach, the results agree with those of the direct method for the steady-state behavior of the accident rate but not for its transient behavior. Computer times were highly reduced by the application even of the first-order GPT approach to the problem. [ABSTRACT FROM AUTHOR]

VERA-CS (Virtual Environment for Reactor Applications, Core Simulator) is a coupled neutron transport and thermal-hydraulics code under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). An approach to uncertainty quantification and sensitivity analysis with VERA-CS was developed and a new toolkit was created to perform uncertainty quantification and sensitivity analysis. A 2 × 2 fuel assembly model was developed and simulated by VERA-CS, and uncertainty quantification and sensitivity analysis were performed with fourteen uncertain input parameters. The minimum departure from nucleate boiling ratio (MDNBR), maximum fuel center-line temperature, and maximum outer clad surface temperature were chosen as the selected figures of merit. Pearson, Spearman, and partial correlation coefficients were considered for all of the figures of merit in sensitivity analysis and coolant inlet temperature was consistently the most influential parameter. Parameters used as inputs to the critical heat flux calculation with the W-3 correlation were shown to be the most influential on the MDNBR, maximum fuel center-line temperature, and maximum outer clad surface temperature. [ABSTRACT FROM AUTHOR]

Melt fragmentation, quenching and long term coolability in a deep pool of water under the reactor vessel are employed as a severe accident mitigation strategy in several designs of light water reactors. The success of such strategy is contingent upon the natural circulation effectiveness in removing the decay heat generated in the porous debris bed. The maximum height of the bed is one of the important factors which affect the debris coolability. The two-phase flow within the bed generates mechanical energy which can change the geometry of the debris bed by the “self-leveling” phenomenon. In this work we developed an approach to modeling of the self-leveling phenomenon. Sensitivity analysis was carried out to rank the importance of the model uncertainties and uncertain input parameters i.e. the conditions of the accident scenario and the debris bed properties. The results provided some useful insights for further improvement of the model and reduction of the output uncertainties through separate-effect experimental studies. Finally, we assessed the self-leveling effectiveness, quantified its uncertainties in prototypic severe accident conditions and demonstrated that the effect of self-leveling phenomenon is robust with respect to the considered input uncertainties. [ABSTRACT FROM AUTHOR]

The MARS-LMR code has been developed to analyze transients in a pool-type sodium-cooled fast reactor (SFR) which has been designed by the Korea Atomic Energy Research Institute (KAERI). Currently, KAERI has developed a prototype Gen-IV SFR (PGSFR) with metallic fuel. The MARS-LMR code is based on the MARS code, and supplements various liquid metal related features including sodium properties, sodium heat transfer and pressure drop models. In order to validate the newly developed MARS-LMR, KAERI has joined the International Atomic Energy Agency (IAEA) coordinated research project (CRP) on the “Benchmark Analysis of an EBR-II shutdown heat removal test” (Briggs et al., 2013, 2015). Argonne National Laboratory (ANL) has operated the EBR-II technically supported and is participating in this program (Sumner and Wei, 2012). In addition, various institutes and countries have joined the IAEA-CRP. The EBR-II SHRT-17 is a kind of loss of flow test, and thus sodium natural circulation is a major phenomenon. The benchmark analysis is conducted using MARS-LMR with the original input data provided by ANL. Qualitatively, MARS-LMR predicted well the natural circulation flow in the core. In addition, sensitivity tests were carried out for various influential parameters to get a better prediction. This study can give validation data for MARS-LMR and a better understanding of EBR-II SHRT-17. [ABSTRACT FROM AUTHOR]

In-vessel corium retention (IVR) through external reactor vessel cooling is adopted in China small modular reactor (SMR) ACP100 as an important severe accident strategy. In the present study, thermal load analyses and IVR margin evaluation for China SMR ACP100 are performed. The thermal load analyses for steady molten pool are carried out based on a two layer final bounding state (FIBS). For FIBS analysis, the maximum heat flux 0.36 MW/m 2 is obtained based on conservative input, which is remarkably lower than the SBLB pool boiling CHF. Sensitivity analyses indicate that the maximum heat flux could reach 0.58 MW/m 2 if an extreme decay heat is assumed. The FIBS studies show that enough thermal margins could be obtained for ACP100 IVR. Then, transient thermal load analyses are carried out based on the simplified SCDAP/RELAP5 system model and detailed COUPLE model. For transient analysis, the peak value of transient thermal load can be up to 0.37 MW/m 2 , which is also remarkably lower than the corresponding CHF. However, the maximum q/CHF ratio happens at the bottom of the vessel. The studies of transient thermal load based on SCDAP/RELAP5 also show that the transient heat transfer characteristics during molten pool formation could be divided into two different stages, namely the dramatic heat transfer stage at the beginning and the quasi steady state heat transfer after the crust formation. [ABSTRACT FROM AUTHOR]

In order to assess the nuclear data uncertainty propagation in the depletion calculation, a computational code named SUNDEW has been developed based on the home-developed lattice code NECP-CACTI. In the SUNDEW, Generalized Perturbation Theory (GPT) is applied to calculate sensitivity coefficients of response function with respect to the nuclear cross sections. Method of Characteristics (MOC) is employed to solve the transport equation, adjoint and generalized adjoint transport equations. Chebyshev Rational Approximation Method (CRAM) is implemented to solve the depletion equation and adjoint depletion equation. The sensitivity coefficients of K eff and nuclide density with respect to the nuclear cross sections are verified by comparing with the results of direct perturbation calculation. The uncertainties on K eff and the nuclide density at different depletions, which are induced by the nuclear cross sections uncertainties, are analyzed based on ENDF/B-VII.1 covariance data for LWR and fast reactor pin-cells. The numerical results show that there are significant differences between LWR and fast reactor pin-cells. The differences are mainly caused by the differences of the sensitivity coefficients between the LWR and fast reactor pin-cells. In addition, to identify the cross section improvement priority for nuclides, reactions and energy ranges, the dominant contributors to K eff and nuclide density uncertainties are analyzed at different depletions. [ABSTRACT FROM AUTHOR]

Environmental contamination subsequent to the atmospheric releases during the Fukushima accident resulted in high radioactive concentrations in feed and foodstuffs. Producing a realistic health risk assessment after severe nuclear accidents, and developing a sufficient understanding of environmental transfer and exposure processes, appears to be a research priority. Specifically, the characterization of uncertainties in the human ingestion pathway, as outlined by the radioecological community, is of great interest. The present work aims to (i) characterize spatial variability and parametric uncertainties raised by the processes involved in the transfer of radionuclides ( 134 Cs and 137 Cs) after atmospheric releases during the Fukushima accident into the terrestrial ecosystems, and (ii) study the impact of these variability and uncertainties on radioactive contamination of leafy vegetables. The implemented approach quantified uncertainties under a probabilistic modelling framework. This resulted in probability distributions derived mainly from Bayesian inference and by performing transfer calculations in the modelling platform SYMBIOSE. [ABSTRACT FROM AUTHOR]

The steam generator is a type of heat exchanger which produces steam to drive the turbine generator. For the APR-1400, Doosan Heavy Industries & Construction manufactures a vertical type of steam generator that has a horizontal tube sheet with a central support design, called a stay cylinder. In this design, the stay cylinder limits tube sheet deformation and effectively reduces thickness of tube sheet and increases structural integrity. A concentric hole in the stay cylinder facilitates welding to the primary head and to the tube sheet. In this study, the APR-1400 steam generator tube sheet thickness parameters were investigated within the constraint of maintaining the overall deformation of the tube sheet in comparison to the current design. A parametric evaluation to reduce the thickness of the steam generator tube sheet is performed by varying the inner diameter of the stay cylinder and the thickness of the tube sheet. The solutions are developed based on two-dimensional finite element analyses. The effect of a reduction of the tube sheet is beneficial in the manufacturing of steam generator by using less material and reducing manufacturing time and allowing easier assembly process of U-tube bundles to the tube sheet. [ABSTRACT FROM AUTHOR]

This research focuses on a sensitivity analysis of accumulators configuration in a Large Break Loss of Coolant Accident (LB-LOCA) in Bushehr Nuclear Power Plant (BNPP). In this way, primary and secondary side components are modeled using RELAP5/MOD3.3 code. Having modeled the BNPP in a steady state hot full power operation, the thermal hydraulic consequences of a LB-LOCA in the reactor inlet is considered and sensitivity analysis for four major different configurations of accumulators are studied in detail. It is shown that any arrangement of accumulators in the Reactor Pressure Chamber (RPC) or Reactor Collection Chambers (RCC) leads to variation of fuel and clad temperatures during the accident and it is important to study the worst condition. Meeting the needs of the safety criteria necessitates tracing of fuel and clad temperatures in short time following the accident in the worst case, emphasizing on the importance of this study. Performance of accumulators when connected to the RCC is also compared to the case of their connection to the RPC and it is shown that the former has a superior efficiency over the latter. Finally, it is proved that in all accumulator arrangements, fuel and clad temperatures do not cross the safety red line despite some variations in the core cooling process following the accident. [ABSTRACT FROM AUTHOR]

China Fast Reactor (CFR) with 600 MW electric power is under development in China. Lots of efforts are being made to its Research and Development (R&D). The CFR600 steam generator with straight tubes consists of the evaporator and the superheater. Phase change exists in the water/steam side and the thermal–hydraulic behavior is difficult to predict. It is challenging to design such a steam generator. Therefore, a suitable thermal–hydraulic code is necessary to assist its design and analysis. A steady-state thermal–hydraulic model is derived based on the mass, energy and momentum equations. The characteristic tube is divided into four regions: subcooled region, nucleate boiling region, film boiling region and superheated region. Equal node enthalpy increment in a region is applied to enhance the numerical accuracy. The model is verified with the design results of design code SG-33 and CEFR. It is proven that the code developed can be used to design and analyze the thermal–hydraulic behavior. Sensitivity analysis is performed to investigate the influence on the heat transfer from key parameters. A preliminary design of CFR600 steam generator is presented using the developed code and reasonable results are obtained. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to apply our improved method for calculating sensitivities and uncertainties of reactivity responses for UO 2 and MOX ( ThO 2 – UO 2 and PuO 2 – UO 2 ) fueled pressurized water reactor cells. The improved method has been used to calculate sensitivity coefficients relative to infinite dilution cross-sections with self-shielding effect taken into account. Two types of reactivities are considered: Doppler reactivity and coolant void reactivity. For each type of reactivity, the sensitivities are calculated for small and large changes of reactivity. The results have demonstrated that the sensitivities are dependent on the changes of reactivity, and the reactivity variation uncertainty is larger than the eigenvalue uncertainty. In addition, the uncertainty of coolant void reactivity is much greater than Doppler reactivity especially for large changes of reactivity because the contribution of U-238 inelastic scattering becomes large. The sensitivity coefficients and uncertainties of both reactivities were verified by comparing with SCALE code results using ENDF/B-VII library and good agreements have been found. [ABSTRACT FROM AUTHOR]

A novel method has been developed to calculate sensitivity coefficients in coupled Boltzmann/Bateman problem for nuclear data (ND) uncertainties propagation on the reactivity. Different uncertainty propagation methodologies, such as One-At-a-Time (OAT) and hybrid Monte-Carlo/deterministic methods have been tested and are discussed on an actual example of ND uncertainty problem on a Material Testing Reactor (MTR) benchmark. Those methods, unlike total Monte Carlo (MC) sampling for uncertainty propagation and quantification (UQ), allow obtaining sensitivity coefficients, as well as Bravais–Pearson correlations values between Boltzmann and Bateman, during the depletion calculation for global neutronics parameters such as the effective multiplication coefficient. The methodologies are compared to a pure MC sampling method, usually considered as the “reference” method. It is shown that methodologies can seriously underestimate propagated variances, when Bravais–Pearson correlations on ND are not taken into account in the UQ process. [ABSTRACT FROM AUTHOR]

Maintenance planning is a critical issue for all heavy industrial sectors such as aeronautics, automobile factories and power plants. The study herein is aimed towards improvement of safety systems reliability in a nuclear power plant. Optimization of maintenance and surveillance test activities is one of the best strategies to improve the reliability of the related safety systems in this kind of plants. Maintenance programs can be formulated in terms of a multi-objective optimization where unavailability, cost and Exposure Time (ET) act as decision criteria and surveillance tests, Allowed Outage Time (AOT) and Preventive Maintenance (PM) intervals act as decision variables. In this paper, Genetic Algorithm (GA) is used to find the best series of answers in the form of Pareto front curve. Sensitivity Index (SI) is applied as a decision making tool to extract the most optimized and promising solution. The unavailability, cost and ET functions, for the most optimal solutions, were reduced by 86%, 58% and 30%, respectively. [ABSTRACT FROM AUTHOR]

Generalised Polynomial Chaos (GPC) in conjunction with sparse grid stochastic collocation and High Dimensional Model Representation (HDMR) is used to perform uncertainty and global sensitivity analysis for the neutron chain survival and extinction probabilities, with and without an intrinsic random source. Starting with a lumped backward Master equation formulation, uncertainty is introduced by allowing the factorial moments of the fission multiplicity distribution, the neutron lifetime, and strength of the intrinsic source to be independent and uniformly distributed random variables. A multidimensional Legendre chaos representation of the random survival and extinction probabilities is used to achieve optimal numerical convergence in the stochastic dimension and the relative variance contributions from each random parameter are then quantified using High Dimensional Model Representation (HDMR). The underlying deterministic results of the model are found to closely match analytical benchmarks and, once uncertainty is introduced, the GPC results match both Monte Carlo simulations and analytical results for polynomial order greater than two. The GPC method is found to require significantly less computational time to achieve a given accuracy on the survival and extinction probabilities than the Monte Carlo method. It is found that, the probabilities are most sensitive to χ i for lower i and have a significant sensitivity to χ 2 in all cases. A chain’s survival probability is moderately sensitive to the neutron lifetime early in simulation. In the subcritical case this sensitivity increases as the simulation continues whilst it decreases in the supercritical case. The extinction probability is sensitive to the source strength. [ABSTRACT FROM AUTHOR]

Recently, there is a need to develop advanced methods of computing eigenvalue sensitivity coefficients to nuclear data in the continuous-energy Monte Carlo codes. One of these methods is the iterated fission probability (IFP) method, which is adopted by most of Monte Carlo codes of having the capabilities of computing sensitivity coefficients, including the Reactor Monte Carlo code RMC. Though it is accurate theoretically, the IFP method faces the challenge of huge memory consumption. Therefore, it may sometimes produce poor sensitivity coefficients since the number of particles in each active cycle is not sufficient enough due to the limitation of computer memory capacity. In this work, two algorithms of the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method, namely, the collision-event-based algorithm (C-CLUTCH) which is also implemented in SCALE and the fission-event-based algorithm (F-CLUTCH) which is put forward in this work, are investigated and implemented in RMC to reduce memory requirements for computing eigenvalue sensitivity coefficients. While the C-CLUTCH algorithm requires to store concerning reaction rates of every collision, the F-CLUTCH algorithm only stores concerning reaction rates of every fission point. In addition, the fission matrix method is put forward to generate the adjoint fission source distribution for the CLUTCH method to compute sensitivity coefficients. These newly proposed approaches implemented in RMC code are verified by a SF96 lattice model and the MIT BEAVRS benchmark problem. The numerical results indicate the accuracy of the F-CLUTCH algorithm is the same as the C-CLUTCH algorithm while the F-CLUTCH algorithm requires less memory and has higher computational efficiency. [ABSTRACT FROM AUTHOR]

In the previous work, the continuous-energy Reactor Monte Carlo code RMC has been developed with the capability of calculating eigenvalue sensitivity coefficients with regard to nuclear data based on the iterated fission probability (IFP) method. By applying the physical meaning of adjoint flux, the IFP method computes adjoint-weighted reaction rates directly in the forward transport calculations without any discretization in space, energy and angle. The IFP method is accurate theoretically, however, it may produce poor sensitivity coefficients in practice since its memory requirements are proportional to the number of particle histories in each Monte Carlo cycle and the huge memory requirement further restricts the number of particles due to the limitation of the computer memory capability. To overcome this drawback of the IFP method, the adjoint Wielandt method and the adjoint superhistory method are investigated. Both methods allow computing sensitivity coefficients within a single particle history and thus provide the possibility of reducing memory consumption. Furthermore, they preserve the merits of the IFP method such as no need for any discretization. The accuracy as well as the computational performance of the adjoint Wielandt method and the adjoint superhistory method are compared with the IFP method through several cases such as a multi-group infinite-medium problem, an assembly-level problem and a full-core PWR problem. [ABSTRACT FROM AUTHOR]

The uncertainties of multigroup cross sections notably impact eigenvalue of neutron-transport equation. We report on a total sensitivity analysis and total uncertainty analysis code named UNICORN that has been developed by applying the direct numerical perturbation method and statistical sampling method. In order to consider the contributions of various basic cross sections and the implicit effects which are indirect results of multigroup cross sections through resonance self-shielding calculation, an improved multigroup cross-section perturbation model is developed. The DRAGON 4.0 code, with application of WIMSD-4 format library, is used by UNICORN to carry out the resonance self-shielding and neutron-transport calculations. In addition, the bootstrap technique has been applied to the statistical sampling method in UNICORN to obtain much steadier and more reliable uncertainty results. The UNICORN code has been verified against TSUNAMI-1D by analyzing the case of TMI-1 pin-cell. The numerical results show that the total uncertainty of eigenvalue caused by cross sections can reach up to be about 0.72%. Therefore the contributions of the basic cross sections and their implicit effects are not negligible. [ABSTRACT FROM AUTHOR]

The paper presents a general strategy applicable for sensitivity analysis (SA), and uncertainity quantification analysis (UA) of parameters related to a nuclear reactor design. This work also validates the use of linear regression (LR) for predictive analysis in a nuclear reactor design. The analysis helps to determine the parameters on which a LR model can be fit for predictive analysis. For those parameters, a regression surface is created based on trial data and predictions are made using this surface. A general strategy of SA to determine and identify the influential parameters those affect the operation of the reactor is mentioned. Identification of design parameters and validation of linearity assumption for the application of LR of reactor design based on a set of tests is performed. The testing methods used to determine the behavior of the parameters can be used as a general strategy for UA, and SA of nuclear reactor models, and thermal hydraulics calculations. A design of a gas cooled fast breeder reactor (GCFBR), with thermal–hydraulics, and energy transfer has been used for the demonstration of this method. MCNP6 is used to simulate the GCFBR design, and perform the necessary criticality calculations. Java is used to build and run input samples, and to extract data from the output files of MCNP6, and R is used to perform regression analysis and other multivariate variance, and analysis of the collinearity of data. [ABSTRACT FROM AUTHOR]

In this work, the implementation of a collision history-based approach to sensitivity/perturbation calculations in the Monte Carlo code SERPENT is discussed. The proposed methods allow the calculation of the effects of nuclear data perturbation on several response functions: the effective multiplication factor, reaction rate ratios and bilinear ratios (e.g., effective kinetics parameters). SERPENT results are compared to ERANOS and TSUNAMI Generalized Perturbation Theory calculations for two fast metallic systems and for a PWR pin-cell benchmark. New methods for the calculation of sensitivities to angular scattering distributions are also presented, which adopts fully continuous (in energy and angle) Monte Carlo estimators. [ABSTRACT FROM AUTHOR]

In this paper, effect of the spallation target neutronic parameters such as beam profile, proton beam energy ( E p ), target thicknesses and for different materials in an Accelerator Driven Subcritical TRIGA reactor has been investigated. Monte Carlo code MCNPX has been used to calculate neutronic parameters such as: spallation neutron yield ( Y n / p ), neutron spectrum, angular distribution of the spallation neutrons coming out of the target and spallation neutron production spectra in the target region for two cases of uniform and parabolic beam spatial distributions. According to the results, the relative difference of spallation neutron yield increases by 3.45% using a parabolic spatial distribution instead of a uniform spatial distribution and also this parameter increases by 7.91% using a thick target instead of a thin target, respectively. Moreover, with increasing E p from 115 MeV up to 2 GeV, the relative difference of spallation neutron yield improves by 4813.58%. Additionally, in comparison to uniform spatial distribution of the proton beam, having parabolic spatial distribution has the advantage of more homogeneity in the spatial distribution of generated spallation neutrons as well as heat generation in the target. Also, Y n / p / E p parameter increases with target atomic number and proton beam energy. Therefore, our results are indicative of the fact that investigating sensitivity of the target spallation neutronic parameters is necessary in order to optimally design a cost-efficient Accelerator Driven Subcritical Reactors (ADSRs). [ABSTRACT FROM AUTHOR]

A computer code, MUSAD was developed for the uncertainty and sensitivity analysis on the DeCART neutron transport calculations for a high temperature gas-cooled reactor. MUSAD is based on a deterministic method in which the sensitivity coefficients of the multiplication factor and the microscopic cross sections are derived using the generalized perturbation theory. Then, the uncertainties of the reactor physics responses are calculated by the product of the covariance matrix and the sensitivity coefficients. MUSAD has been verified against the uncertainty analyses on several benchmark problems including the GODIVA benchmark problem, the PMR-200 pin-cell, and the MHTGR-350 core benchmark problems. A good agreement in comparison with the reference codes, TSUNAMI and McCARD shows the applicability of MUSAD to the uncertainty and sensitivity analyses on the HTGR neutron transport calculations. [ABSTRACT FROM AUTHOR]

The complex and coupled behavior of the variables that affect the currently developing generation IV reactors and the increase of interest in Small Modular Reactors are major incentives to seek efficient design methods. Instead of the brute force design methodology, often applied to the analysis of nuclear reactors, other more economical and systematic methods should be applied. In a complex system with a high number of variables, it often is necessary to develop models to describe the behavior of each performance characteristic with respect to a set of variables and their interactions. If expensive experiments are needed to develop these models, the number of experiments should be minimized. This can be achieved by designing the experiments to be performed. Once the system’s models are developed, they can be used to decouple the variables’ effects on the performance characteristics and simplify the optimization process. In this article, three screening and sensitivity analysis methods are applied to decouple and understand the effects of fourteen variables on six performance characteristics of a Small Modular Reactor’s design, based on the Advanced Passive (AP-1000) reactor. The application of these methods facilitated the determination of the most important parameters of each performance characteristic, and resulted in several distinctive findings. These findings are applicable to any Light Water Small Modular Reactor that falls within the variables’ design domain. [ABSTRACT FROM AUTHOR]

Since some years, there is a worldwide trend to move towards “higher-fidelity” simulation techniques in reactor analysis. One of the main objectives of the research in this area is to enhance the prediction capability of the computations used for safety demonstration of the current LWR nuclear power plants through the dynamic 3D coupling of the codes simulating the different physics of the problem into a common multi-physics simulation scheme. In this context, the NURESAFE European project aims at delivering to the European stakeholders an advanced and reliable software capacity usable for safety analysis needs of present and future LWR reactors and developing a high level of expertise in Europe in the proper use of the most recent simulation tools including uncertainty assessment to quantify the margins toward feared phenomena occurring during an accident. This software capacity is based on the NURESIM European simulation platform created during FP6 NURESIM project which includes advanced core physics, two-phase thermal–hydraulics, fuel modeling and multi-scale and multi-physics features together with sensitivity and uncertainty tools. These physics are fully integrated into the platform in order to provide a standardized state-of-the-art code system to support safety analysis of current and evolving LWRs. [ABSTRACT FROM AUTHOR]

• Fast inversion of nuclear accident source term is achieved based on deep feedforward neural network. • The hyperparameters of deep feedforward neural network suitable for the inversion of single-point and stable-release source are determined. • Sensitivity analysis and uncertainty analysis improve the reliability of the inversion source term and reduce the risk of failure to emergency response. Source term estimation based on environmental monitoring data is a key method for obtaining source information, which is required by the emergency response system. This study investigates the applicability of deep feedforward neural network (DFNN) for source inversion. Twenty thousand sets of simulated data containing I-131 release rate, meteorological information, and simulated radioactive concentration are generated based on radionuclide atmospheric dispersion codes RADC. These are used to train and test a DFNN. The influence of key network hyperparameters is studied. The results show that the average prediction error of DFNN is 2.24%, and that over 80% of prediction errors are less than 2.0%. The Bayesian MCMC algorithm is used to analyze the prediction uncertainty of DFNN when there are uncertainties in the input parameters. The confidence interval and risk curve are likely to provide more reliable source-term information for nuclear accident emergency response and decision-making. [ABSTRACT FROM AUTHOR]

Fuel rod performance codes are used to predict the behavior of fuel rods in reactors. The uncertainty and sensitivity analysis are always needed when developing or using these codes. However, fuel rod codes typically have two characteristics that make relevant analysis challenging: First, there are many input parameters for which uncertainty needs to be considered. Second, the structure of the models is complex, non-linear and non-additive. To make the uncertainty and sensitivity analysis of a fuel rod code effectively and conveniently, an assistant toolkit, FUAS, has been developed recently by China Nuclear Power Technology Research Institute Co. Ltd. FUAS considers the fuel rod codes as black boxes and applies sampling-based approaches. Several statistical methods are available in this toolkit. A hypothetical steady-state scenario of the PWR fuel rod was simulated, and uncertainty and sensitivity analysis were performed with the sampling-based approach by coupling the fuel rod code and FUAS toolkit. [ABSTRACT FROM AUTHOR]

• A transient performance analysis code of high-temperature heat pipe with consideration of NCG effect is developed. • The heat transfer performance of a lithium heat pipe with NCG is simulated during startup from the frozen state. • Key parameters sensitivity analysis of the lithium heat pipe with NCG are carried out. The high-temperature lithium heat pipe utilized in the reactor will be irradiated by neutrons, causing non-condensable gas (NCG) to generate within and deteriorate thermal performance. This study develops a high-temperature heat pipe transient analysis code that takes into account the NCG effect. Heat pipe frozen start-up and key parameters sensitivity study are numerically evaluated. The NCG influence can be well described by the code. When compared to heat pipes without NCG, the start-up time of heat pipes with 25% NCG volume fraction increases by 54.2%. However, the existence of NCG can make the start-up process go more smoothly. The temperature drop in the NCG area changes from 40 K to 395 K as the NCG volume fraction increases from 5% to 25%. Increased input power can lower the volume fraction of NCG and hence diminish the negative thermal effects. This work provides foundation for transient analysis of high temperature heat pipe containing NCG. [ABSTRACT FROM AUTHOR]

• Effect of thermo-physical properties of ATFs on the reactor safety has been studied in four basic transients. • Transients of the temperature increase and the depressurization should try to avoid. • Higher thermal diffusivity may cause undesirable effects in transient. Research on thermal hydraulics of accident tolerant fuels (ATFs) in transient is a complex issue. Based on a 5 × 5 fuel bundle model, four transients (power increase, flow reduction, depressurization and temperature increase) that are the basic elements of most of reactor accidents were used to comprehensively evaluate fuel behaviors and the safety of ATFs. A global sensitivity analysis indicates that fuel behaviors are the most sensitive to the temperature increase and the second to the depressurization, which should be avoided in practical. ATF pellets possessing higher thermal diffusivity were easier to cause a soaring cladding temperature in transient, thus leading to a higher peak cladding temperature (PCT), a lower minimal departure from nucleate boiling ratio (MDNBR) and a lower critical power. ATF claddings performed a better accident tolerance capacity in transient due to the lower thermal diffusivity, especially for the SiC cladding. [ABSTRACT FROM AUTHOR]

SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2. [ABSTRACT FROM AUTHOR]

In designing radioactive waste management and decommissioning facilities, understanding the physical mechanisms for burnup actinide composition is indispensable to satisfy requirements for its validity and reliability. Therefore, the uncertainty associated with physical quantities, such as nuclear data, needs to be quantitatively analyzed. The present paper illustrates an analysis methodology to investigate the physical mechanisms of burnup actinide composition with nuclear-data sensitivity based on the generalized depletion perturbation theory. The target in this paper is the MOX fuel of the light water reactor. We start with the discussion of the basic physical mechanisms for burnup actinide compositions using the reaction-rate flow chart on the burnup chain. After that, the physical mechanisms of the productions of Cm-244 and Pu-238 are analyzed in detail with burnup sensitivity calculation. Conclusively, we can identify the source of actinide productions and evaluate the indirect influence of the nuclear reactions if the physical mechanisms of burnup actinide composition are analyzed using the reaction-rate flow chart on the burnup chain and burnup sensitivity calculation. Finally, we demonstrate the usefulness of the burnup sensitivity coefficients in an application to determine the priority of accuracy improvement in nuclear data in combination with the covariance of the nuclear data. In addition, the target actinides and reactions are categorized into patterns according to a sensitivity trend. [ABSTRACT FROM AUTHOR]

The iterated fission probability (IFP) method has been demonstrated to be an accurate alternative for estimating the adjoint-weighted parameters in continuous-energy Monte Carlo forward calculations. However, the memory requirements of this method are huge especially when a large number of sensitivity coefficients are desired. Therefore, data decomposition techniques are proposed in this work. Two parallel strategies based on the neutron production rate (NPR) estimator and the fission neutron population (FNP) estimator for adjoint fluxes, as well as a more efficient algorithm which has multiple overlapping blocks (MOB) in a cycle, are investigated and implemented in the continuous-energy Reactor Monte Carlo code RMC for sensitivity analysis. Furthermore, a region-specific sensitivity analysis capability is developed in RMC. These new strategies, algorithms and capabilities are verified against analytic solutions of a multi-group infinite-medium problem and against results from other software packages including MCNP6, TSUANAMI-1D and multi-group TSUNAMI-3D. While the results generated by the NPR and FNP strategies agree within 0.1% of the analytic sensitivity coefficients, the MOB strategy surprisingly produces sensitivity coefficients exactly equal to the analytic ones. Meanwhile, the results generated by the three strategies in RMC are in agreement with those produced by other codes within a few percent. Moreover, the MOB strategy performs the most efficient sensitivity coefficient calculations (offering as much as an order of magnitude gain in FoMs over MCNP6), followed by the NPR and FNP strategies, and then MCNP6. The results also reveal that these three strategies employed by RMC maintain high parallel efficiency of approximately 96–98% within the observed 600 processors, and the memory requirements per processor decrease almost linearly as the number of processors increases from 120 to 600. To conclude, RMC is capable of performing sensitivity analysis with sufficient accuracy and high efficiency. [ABSTRACT FROM AUTHOR]

The HPCI is designed to inject into one of the two feedwater lines, which eventually results in the uneven distribution of core inlet temperature. This paper develops a methodology to determine the penalty of HPCI flow to cover the defect of RETRAN computer code in the volume-averaged parameter and satisfy the requirement for a conservative analysis. The detailed inlet temperature calculated by CFD supports the determination of ΔCPR by using RETRAN hot channel model for the selected 56 potential channels. The Spearman rank correlation coefficient method is adopted to evaluate the dependence of the ΔCPR on the characteristics in the channel. Finally, the inlet subcooling in the channel is found to be in a medium to strong dependence on CPR change. The sensitivity studies verify that 20% penalty kept in HPCI flow covers 95% subcooling in all channels and the calculated ΔCPR has a rank of 54 (from low to high), which can cover 96.4% of CPR change in the 56 potential channels. [ABSTRACT FROM AUTHOR]

SHARKX is a set of Perl-based tools built around the lattice code CASMO-5 which is used to perform sensitivity analysis and uncertainty quantification (UQ). SHARKX has been recently extended to perform UQ on pinpower and representativity analysis (RA). Its aim is to calculate uncertainties due to the nuclear data cross sections on the fission rate of selected pins and to provide a rigorous basis to assess the relevance of an experiment to a given application. The main objective of the work summarised in the present paper is to verify the proper implementation of the SHARKX UQ and RA methodologies. The verification is carried out by comparing the UQ and RA results of SHARKX to the ones of the TSUNAMI code, currently the reference in the field for this kind of calculations. The verification of the proper UQ and RA implementation in SHARKX is performed for a set of test cases relevant to the LWR-PROTEUS experimental campaign. Only nuclear data (cross sections) uncertainty is considered and propagated in the SHARKX and TSUNAMI codes. For various test problems, the comparison with TSUNAMI has shown that the new UQ and RA implementations in the SHARKX methodology are carried out successfully. However, it is found that discrepancies are introduced in sensitivity coefficient calculation of SHARKX by neglecting the perturbation of the resonance self-shielding treatment, the so called “implicit effect”. Such approximation can have significant impact on both UQ and RA especially for Gadolinium doped fuel. The effect of the input uncertainty in UQ and RA is also investigated by comparing the results obtained with the variance–covariance matrix (VCM) of ENDF/B-VII.1, JENDL4.0 and SCALE6. The choice of input VCM is the major source of result discrepancies for UQ on k inf and pinpower. However, for RA, it is found to be of the same order of magnitude than the method discrepancies, i.e. the differences between SHARKX and TSUNAMI coming from the “implicit effect”. [ABSTRACT FROM AUTHOR]