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Sökning: WFRF:(Koning Arjan J.)

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1.
  • Rochman, D., et al. (författare)
  • A Bayesian Monte Carlo method for fission yield covariance information
  • 2016
  • Ingår i: Annals of Nuclear Energy. - 0306-4549 .- 1873-2100. ; 95, s. 125-134
  • Tidskriftsartikel (refereegranskat)abstract
    • The present work proposes a Bayesian method to combine theoretical fission yields with a set of reference data. These two sources of information are merged using a Monte Carlo process, and leads to a so-called Bayesian Monte Carlo update. Examples are presented for the independent fission yields of four major actinides, using the GEF code as a source of theoretical calculations and an evaluated library of fission yields for the reference data. The impact of the updated fission yields and their covariances is shown for two distinct applications: a UO2 pincell with burn-up up to 40 GWD/tHM and decay heat calculations of a thermal neutron pulse on U-235 and Pu-239.
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2.
  • Rochman, D., et al. (författare)
  • A Statistical Analysis of Evaluated Neutron Resonances with TARES for JEFF-3.3, JENDL-4.0, ENDF/B-VIII.0 and TENDL-2019
  • 2020
  • Ingår i: Nuclear Data Sheets. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0090-3752 .- 1095-9904. ; 163, s. 163-190
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper, a statistical analysis of resonance evaluations from the most recent nuclear data libraries is performed with the code TARES. A description of the TARES framework is provided, but also for its use in the production of resonance parameters for the entire TENDL library. Various observables are calculated (e.g., thermal cross sections, capture integrals but also D-0 and other average resonance quantities) for different libraries and compared to experimental values when available. Finally, for isotopes with no or little information, details are provided for the production of statistical resonances, based on a variety of compound nucleus reaction models.
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3.
  • Rochman, Dimitri, et al. (författare)
  • The TENDL library : Hope, reality and future
  • 2017
  • Ingår i: Nd 2016 Bruges. - Les Ulis : EDP Sciences. - 9782759890200
  • Konferensbidrag (refereegranskat)abstract
    • The TALYS Evaluated Nuclear Data Library (TENDL) has now 8 releases since 2008. Considerable experience has been acquired for the production of such general-purpose nuclear data library based on the feedback from users, evaluators and processing experts. The backbone of this achievement is simple and robust: completeness, quality and reproducibility. If TENDL is extensively used in many fields of applications, it is necessary to understand its strong points and remaining weaknesses. Alternatively, the essential knowledge is not the TENDL library itself, but rather the necessary method and tools, making the library a side product and focusing the efforts on the evaluation knowledge. The future of such approach will be discussed with the hope of nearby greater success.
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4.
  • Alhassan, Erwin, et al. (författare)
  • Benchmark selection methodology for reactor calculations and nuclear data uncertainty reduction
  • 2015
  • Ingår i: Annals of Nuclear Energy. - 0306-4549 .- 1873-2100.
  • Tidskriftsartikel (refereegranskat)abstract
    • Criticality, reactor physics and shielding benchmarks are expected to play important roles in GEN-IV design, safety analysis and in the validation of analytical tools used to design these reactors. For existing reactor technology, benchmarks are used for validating computer codes and for testing nuclear data libraries. Given the large number of benchmarks available, selecting these benchmarks for specic applications can be rather tedious and difficult. Until recently, the selection process has been based usually on expert judgement which is dependent on the expertise and the experience of the user and there by introducing a user bias into the process. This approach is also not suitable for the Total Monte Carlo methodology which lays strong emphasis on automation, reproducibility and quality assurance. In this paper a method for selecting these benchmarks for reactor calculation and for nuclear data uncertainty reduction based on the Total Monte Carlo (TMC) method is presented. For reactor code validation purposes, similarities between a real reactor application and one or several benchmarks are quantied using a similarity index while the Pearson correlation coecient is used to select benchmarks for nuclear data uncertainty reduction. Also, a correlation based sensitivity method is used to identify the sensitivity of benchmarks to particular nuclear reactions. Based on the benchmark selection methodology, two approaches are presented for reducing nuclear data uncertainty using integral benchmark experiments as an additional constraint in the TMC method: a binary accept/reject and a method of assigning file weights using the likelihood function. Finally, the methods are applied to a full lead-cooled fast reactor core and a set of criticality benchmarks. Signicant reductions in Pu-239 and Pb-208 nuclear data uncertainties were obtained after implementing the two methods with some benchmarks.
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5.
  • Alhassan, E., et al. (författare)
  • In search of the best nuclear data file for proton induced reactions : Varying both models and their parameters
  • 2020
  • Ingår i: ND 2019. - : EDP Sciences. - 9782759891061
  • Konferensbidrag (refereegranskat)abstract
    • A lot of research work has been carried out in fine tuning model parameters to reproduce experimental data for neutron induced reactions. This however is not the case for proton induced reactions where large deviations still exist between model calculations and experiments for some cross sections. In this work, we present a method for searching both the model and model parameter space in order to identify the 'best' nuclear reaction models with their parameter sets that reproduces carefully selected experimental data. Three sets of experimental data from EXFOR are used in this work: (1) cross sections of the target nucleus (2) cross sections of the residual nuclei and (3) angular distributions. Selected models and their parameters were varied simultaneously to produce a large set of random nuclear data files. The goodness of fit between our adjustments and experimental data was achieved by computing a global reduced chi square which took into consideration the above listed experimental data. The method has been applied for the adjustment of proton induced reactions on Co-59 between 1 to 100 MeV. The adjusted files obtained are compared with available experimental data and evaluations from other nuclear data libraries.
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6.
  • Alhassan, Erwin, et al. (författare)
  • Iterative Bayesian Monte Carlo for nuclear data evaluation
  • 2022
  • Ingår i: NUCLEAR SCIENCE AND TECHNIQUES. - : Springer Nature. - 1001-8042 .- 2210-3147. ; 33:4
  • Tidskriftsartikel (refereegranskat)abstract
    • In this work, we explore the use of an iterative Bayesian Monte Carlo (iBMC) method for nuclear data evaluation within a TALYS Evaluated Nuclear Data Library (TENDL) framework. The goal is to probe the model and parameter space of the TALYS code system to find the optimal model and parameter sets that reproduces selected experimental data. The method involves the simultaneous variation of many nuclear reaction models as well as their parameters included in the TALYS code. The `best' model set with its parameter set was obtained by comparing model calculations with selected experimental data. Three experimental data types were used: (1) reaction cross sections, (2) residual production cross sections, and (3) the elastic angular distributions. To improve our fit to experimental data, we update our 'best' parameter set-the file that maximizes the likelihood function-in an iterative fashion. Convergence was determined by monitoring the evolution of the maximum likelihood estimate (MLE) values and was considered reached when the relative change in the MLE for the last two iterations was within 5%. Once the final 'best' file is identified, we infer parameter uncertainties and covariance information to this file by varying model parameters around this file. In this way, we ensured that the parameter distributions are centered on our evaluation. The proposed method was applied to the evaluation of p+ Co-59 between 1 and 100 MeV. Finally, the adjusted files were compared with experimental data from the EXFOR database as well as with evaluations from the TENDL-2019, JENDL/He-2007 and JENDL-4.0/HE nuclear data libraries.
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7.
  • Alhassan, Erwin, et al. (författare)
  • On the use of integral experiments for uncertainty reduction of reactor macroscopic parameters within the TMC methodology
  • 2016
  • Ingår i: Progress in nuclear energy (New series). - 0149-1970 .- 1878-4224. ; 88, s. 43-52
  • Tidskriftsartikel (refereegranskat)abstract
    • The current nuclear data uncertainties observed in reactor safety parameters for some nuclides call for safety concerns especially with respect to the design of GEN-IV reactors and must therefore be reduced significantly. In this work, uncertainty reduction using criticality benchmark experiments within the Total Monte Carlo methodology is presented. Random nuclear data libraries generated are processed and used to analyze a set of criticality benchmarks. Since the calculated results for each random nuclear data used are different, an algorithm was used to select (or assign weights to) the libraries which give a good description of experimental data for the analyses of the benchmarks. The selected or weighted libraries were then used to analyze the ELECTRA reactor. By using random nuclear data libraries constrained with only differential experimental data as our prior, the uncertainties observed were further reduced by constraining the files with integral experimental data to obtain a posteriori uncertainties on the k(eff). Two approaches are presented and compared: a binary accept/reject and a method of assigning file weights based on the likelihood function. Significant reductions in (PU)-P-239 and Pb-208 nuclear data uncertainties in the k(eff) were observed after implementing the two methods with some criticality benchmarks for the ELELIRA reactor. (C) 2015 Elsevier Ltd. All rights reserved.
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8.
  • Alhassan, Erwin, et al. (författare)
  • Reducing A Priori 239Pu Nuclear Data Uncertainty In The Keff Using A Set Of Criticality Benchmarks With Different Nuclear Data Libraries
  • 2015
  • Konferensbidrag (övrigt vetenskapligt)abstract
    • In the Total Monte Carlo (TMC) method [1] developed at the Nuclear Research and Consultancy Group for nuclear data uncertainty propagation, model calculations are compared with differential experimental data and a specific a priori uncertainty is assigned to each model parameter. By varying the model parameters all together within model parameter uncertainties, a full covariance matrix is obtained with its off diagonal elements if desired [1]. In this way, differential experimental data serve as a constraint for the model parameters used in the TALYS nuclear reactions code for the production of random nuclear data files. These files are processed into usable formats and used in transport codes for reactor calculations and for uncertainty propagation to reactor macroscopic parameters of interest. Even though differential experimental data together with their uncertainties are included (implicitly) in the production of these random nuclear data files in the TMC method, wide spreads in parameter distributions have been observed, leading to large uncertainties in reactor parameters for some nuclides for the European Lead cooled Training Reactor [2]. Due to safety concerns and the development of GEN-IV reactors with their challenging technological goals, the present uncertainties should be reduced significantly if the benefits from advances in modelling and simulations are to be utilized fully [3]. In Ref.[4], a binary accept/reject approach and a more rigorous method of assigning file weights based on the likelihood function were proposed and presented for reducing nuclear data uncertainties using a set of integral benchmarks obtained from the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP). These methods are depended on the reference nuclear data library used, the combined benchmark uncertainty and the relevance of each benchmark for reducing nuclear data uncertainties for a particular reactor system. Since each nuclear data library normally comes with its own nominal values and covariance matrices, reactor calculations and uncertainties computed with these libraries differ from library to library. In this work, we apply the binary accept/reject approach and the method of assigning file weights based on the likelihood function for reducing a priori 239Pu nuclear data uncertainties for the European Lead Cooled Training Reactor (ELECTRA) using a set of criticality benchmarks. Prior and posterior uncertainties computed for ELECTRA using ENDF/B-VII.1, JEFF-3.2 and JENDL-4.0 are compared after including experimental information from over 10 benchmarks.[1] A.J. Koning and D. Rochman, Modern Nuclear Data Evaluation with the TALYS Code System. Nuclear Data Sheets 113 (2012) 2841-2934. [2] E. Alhassan, H. Sjöstrand, P. Helgesson, A. J. Koning, M. Österlund, S. Pomp, D. Rochman, Uncertainty and correlation analysis of lead nuclear data on reactor parameters for the European Lead Cooled Training reactor (ELECTRA). Annals of Nuclear Energy 75 (2015) 26-37. [3] G. Palmiotti, M. Salvatores, G. Aliberti, H. Hiruta, R. McKnight, P. Oblozinsky, W. Yang, A global approach to the physics validation of simulation codes for future nuclear systems, Annals of Nuclear Energy 36 (3) (2009) 355-361. [4] E. Alhassan, H. Sjöstrand, J. Duan, P. Helgesson, S. Pomp, M. Österlund, D. Rochman, A.J. Koning, Selecting benchmarks for reactor calculations: In proc. PHYSOR 2014 - The Role of Reactor Physics toward a Sustainable Future, kyoto, Japan, Sep. 28 - 3 Oct. (2014).
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9.
  • Alhassan, Erwin, et al. (författare)
  • Selecting benchmarks for reactor calculations
  • 2014
  • Ingår i: PHYSOR 2014 - The Role of Reactor Physics toward a Sustainable Future.
  • Konferensbidrag (refereegranskat)abstract
    • Criticality, reactor physics, fusion and shielding benchmarks are expected to play important roles in GENIV design, safety analysis and in the validation of analytical tools used to design these reactors. For existing reactor technology, benchmarks are used to validate computer codes and test nuclear data libraries. However the selection of these benchmarks are usually done by visual inspection which is dependent on the expertise and the experience of the user and there by resulting in a user bias in the process. In this paper we present a method for the selection of these benchmarks for reactor applications based on Total Monte Carlo (TMC). Similarities betweenan application case and one or several benchmarks are quantified using the correlation coefficient. Based on the method, we also propose an approach for reducing nuclear data uncertainty using integral benchmark experiments as an additional constrain on nuclear reaction models: a binary accept/reject criterion. Finally, the method was applied to a full Lead Fast Reactor core and a set of criticality benchmarks.
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10.
  • Alhassan, Erwin, et al. (författare)
  • Selecting benchmarks for reactor simulations : an application to a Lead Fast Reactor
  • 2016
  • Ingår i: Annals of Nuclear Energy. - 0306-4549 .- 1873-2100. ; 96, s. 158-169
  • Tidskriftsartikel (refereegranskat)abstract
    • For several decades reactor design has been supported by computer codes for the investigation of reactor behavior under both steady state and transient conditions. The use of computer codes to simulate reactor behavior enables the investigation of various safety scenarios saving time and cost. There has been an increase in the development of in-house (local) codes by various research groups in recent times for preliminary design of specific or targeted nuclear reactor applications. These codes must be validated and calibrated against experimental benchmark data with their evolution and improvements. Given the large number of benchmarks available, selecting these benchmarks for reactor calculations and validation of simulation codes for specific or target applications can be rather tedious and difficult. In the past, the traditional approach based on expert judgement using information provided in various handbooks, has been used for the selection of these benchmarks. This approach has been criticized because it introduces a user bias into the selection process. This paper presents a method for selecting these benchmarks for reactor calculations for specific reactor applications based on the Total Monte Carlo (TMC) method. First, nuclear model parameters are randomly sampled within a given probability distribution and a large set of random nuclear data files are produced using the TALYS code system. These files are processed and used to analyze a target reactor system and a set of criticality benchmarks. Similarity between the target reactor system and one or several benchmarks is quantified using a similarity index. The method has been applied to the European Lead Cooled Reactor (ELECTRA) and a set of plutonium and lead sensitive criticality benchmarks using the effective multiplication factor (keffkeff). From the study, strong similarity were observed in the keffkeff between ELECTRA and some plutonium and lead sensitive criticality benchmarks. Also, for validation purposes, simulation results for a list of selected criticality benchmarks simulated with the MCNPX and SERPENT codes using different nuclear data libraries have been compared with experimentally measured benchmark keff values.
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  • Resultat 1-10 av 27
  • [1]23Nästa

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