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Author: Chunyu Liu
Publisher: Springer Spektrum
ISBN: 9783658434212
Category : Science
Languages : en
Pages : 0
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Book Description
In this book, the author provides a deep study into multiscale and multiphysics modeling of nuclear facilities, underscoring the critical role of uncertainty quantification and sensitivity analysis to ensure the confidence in the numerical results and to identify the system characteristics. Through an in-depth study of the liquid metal cooling system from the TALL-3D loop to the SMDFR core, the research highlights the natural circulation instability, strong coupling effects, perturbation tolerance, and system stability. The culmination of the research is the formulation of an optimized uncertainty-based control scheme, demonstrating its versatility beyond the nuclear domain to other energy sectors. This groundbreaking work not only advances the comprehension and utilization of coupling schemes and uncertainty methodologies in nuclear system modeling but also adeptly bridges the theoretical constructs with tangible application, positioning itself as an indispensable resource for design, safety analysis, and advanced numerical modeling in the broader energy sector.
Author: Chunyu Liu
Publisher: Springer Spektrum
ISBN: 9783658434212
Category : Science
Languages : en
Pages : 0
Get Book Here
Book Description
In this book, the author provides a deep study into multiscale and multiphysics modeling of nuclear facilities, underscoring the critical role of uncertainty quantification and sensitivity analysis to ensure the confidence in the numerical results and to identify the system characteristics. Through an in-depth study of the liquid metal cooling system from the TALL-3D loop to the SMDFR core, the research highlights the natural circulation instability, strong coupling effects, perturbation tolerance, and system stability. The culmination of the research is the formulation of an optimized uncertainty-based control scheme, demonstrating its versatility beyond the nuclear domain to other energy sectors. This groundbreaking work not only advances the comprehension and utilization of coupling schemes and uncertainty methodologies in nuclear system modeling but also adeptly bridges the theoretical constructs with tangible application, positioning itself as an indispensable resource for design, safety analysis, and advanced numerical modeling in the broader energy sector.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 9
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Book Description
In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis for computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.
Author: Maria Avramova
Publisher: Woodhead Publishing Series in
ISBN: 9780128149546
Category : Technology & Engineering
Languages : en
Pages : 300
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Book Description
Verification, Validation and Uncertainty Quantification in Multi-Physics Modeling of Nuclear Reactors is a key reference for those tasked with ensuring the credibility and reliability of engineering models and simulations for the nuclear industry and nuclear energy research. Sections discuss simulation challenges and revise key definitions, concepts and terminology. Chapters cover solution verification, the frontier discipline of multi-physics coupling verification, model validation and its applications to single and multi-scale models, and uncertainty quantification. This essential guide will greatly assist engineers, scientists, regulators and students in applying rigorous verification, validation and uncertainty quantification methodologies to the M&S tools used in the industry. The book contains a strong focus on the verification and validation procedures required for the emerging multi-physics M&S tools that have great potential for use in the licensing of new reactors, as well as for power uprating and life extensions of operating reactors. Uniquely--and crucially for nuclear engineers--demonstrates the application of verification, validation and uncertainty methodologies to the modeling and simulation (M&S) of nuclear reactors Equips the reader to develop a rigorously defensible validation process irrespective of the particular M&S tool used Brings the audience up-to-speed on validation methods for traditional M&S tools Extends the discussion to the emerging area of validation of multi-physics and multi-scale nuclear reactor simulations
Author: Jun Wang
Publisher: Woodhead Publishing
ISBN: 0128181915
Category : Technology & Engineering
Languages : en
Pages : 612
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Book Description
Nuclear Power Plant Design and Analysis Codes: Development, Validation, and Application presents the latest research on the most widely used nuclear codes and the wealth of successful accomplishments which have been achieved over the past decades by experts in the field. Editors Wang, Li,Allison, and Hohorst and their team of authors provide readers with a comprehensive understanding of nuclear code development and how to apply it to their work and research to make their energy production more flexible, economical, reliable and safe.Written in an accessible and practical way, each chapter considers strengths and limitations, data availability needs, verification and validation methodologies and quality assurance guidelines to develop thorough and robust models and simulation tools both inside and outside a nuclear setting. This book benefits those working in nuclear reactor physics and thermal-hydraulics, as well as those involved in nuclear reactor licensing. It also provides early career researchers with a solid understanding of fundamental knowledge of mainstream nuclear modelling codes, as well as the more experienced engineers seeking advanced information on the best solutions to suit their needs. Captures important research conducted over last few decades by experts and allows new researchers and professionals to learn from the work of their predecessors Presents the most recent updates and developments, including the capabilities, limitations, and future development needs of all codes Incudes applications for each code to ensure readers have complete knowledge to apply to their own setting
Author: Yan Wang
Publisher: Woodhead Publishing Limited
ISBN: 0081029411
Category : Materials science
Languages : en
Pages : 604
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Book Description
Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales.
Author: Vijay Subramaniam Mahadevan
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The modeling of nuclear reactors involves the solution of a multi-physics problem with widely varying time and length scales. This translates mathematically to solving a system of coupled, non-linear, and stiff partial differential equations (PDEs). Multi-physics applications possess the added complexity that most of the solution fields participate in various physics components, potentially yielding spatial and/or temporal coupling errors. This dissertation deals with the verification aspects associated with such a multi-physics code, i.e., the substantiation that the mathematical description of the multi-physics equations are solved correctly (both in time and space). Conventional paradigms used in reactor analysis problems employed to couple various physics components are often non-iterative and can be inconsistent in their treatment of the non-linear terms. This leads to the usage of smaller time steps to maintain stability and accuracy requirements, thereby increasing the overall computational time for simulation. The inconsistencies of these weakly coupled solution methods can be overcome using tighter coupling strategies and yield a better approximation to the coupled non-linear operator, by resolving the dominant spatial and temporal scales involved in the multi-physics simulation. A multi-physics framework, KARMA (K(c)ode for Analysis of Reactor and other Multi-physics Applications), is presented. KARMA uses tight coupling strategies for various physical models based on a Matrix-free Nonlinear-Krylov (MFNK) framework in order to attain high-order spatio-temporal accuracy for all solution fields in amenable wall clock times, for various test problems. The framework also utilizes traditional loosely coupled methods as lower-order solvers, which serve as efficient preconditioners for the tightly coupled solution. Since the software platform employs both lower and higher-order coupling strategies, it can easily be used to test and evaluate different coupling strategies and numerical methods and to compare their efficiency for problems of interest. Multi-physics code verification efforts pertaining to reactor applications are described and associated numerical results obtained using the developed multi-physics framework are provided. The versatility of numerical methods used here for coupled problems and feasibility of general non-linear solvers with appropriate physics-based preconditioners in the KARMA framework offer significantly efficient techniques to solve multi-physics problems in reactor analysis.
Author: Emmanuel Boafo
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
There is an increasing interest in computational reactor safety analysis to systematically replace the conservative calculations by best estimate calculations augmented by quantitative uncertainty analysis methods. This has been necessitated by recent regulatory requirements that have permitted the use of such methods in reactor safety analysis. Stochastic uncertainty quantification methods have shown great promise, as they are better suited to capture the complexities in real engineering problems. This study proposes a framework for performing uncertainty quantification based on the stochastic approach, which can be applied to enhance safety analysis. Additionally, risk level has increased with the degradation of Nuclear Power Plant (NPP) equipment and instrumentation. In order to achieve NPP safety, it is important to continuously evaluate risk for all potential hazards and fault propagation scenarios and map protection layers to fault / failure / hazard propagation scenarios to be able to evaluate and verify safety level during NPP operation. In this study, the Fault Semantic Network (FSN) methodology is proposed. This involved the development of static and dynamic fault semantic network (FSN) to model possible fault propagation scenarios and the interrelationships among associated process variables. The proposed method was demonstrated by its application to two selected case studies. The use of FSN is essential for fault detection, understanding fault propagation scenarios and to aid in the prevention of catastrophic events. Two transient scenarios were simulated with a best estimate thermal hydraulic code, CATHENA. Stochastic uncertainty quantification and sensitivity analyses were performed using the OPENCOSSAN software which is based on the Monte Carlo method. The effect of uncertainty in input parameters were investigated by analyzing the probability distribution of output parameters. The first four moments (mean, variance, skewness and kurtosis) of the output parameters were computed and analyzed. The uncertainty in output pressure was 0.61% and 0.57% was found for the mass flow rate in the Edward's blowdown transient. An uncertainty of 0.087% was obtained for output pressure and 0.048% for fuel pin temperature in the RD-14 test case. These results are expected to be useful for providing insight into safety margins related to safety analysis and verification.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
In nuclear engineering, understanding the safety margins of the nuclear reactor via simulations is arguably of paramount importance in predicting and preventing nuclear accidents. It is therefore crucial to perform sensitivity analysis to understand how changes in the model inputs affect the outputs. Modern nuclear simulation tools rely on numerical representations of the sensitivity information -- inherently lacking in visual encodings -- offering limited effectiveness in communicating and exploring the generated data. In this paper, we design a framework for sensitivity analysis and visualization of multidimensional nuclear simulation data using partition-based, topology-inspired regression models and report on its efficacy. We rely on the established Morse-Smale regression technique, which allows us to partition the domain into monotonic regions where easily interpretable linear models can be used to assess the influence of inputs on the output variability. The underlying computation is augmented with an intuitive and interactive visual design to effectively communicate sensitivity information to the nuclear scientists. Our framework is being deployed into the multi-purpose probabilistic risk assessment and uncertainty quantification framework RAVEN (Reactor Analysis and Virtual Control Environment). We evaluate our framework using an simulation dataset studying nuclear fuel performance.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 52
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Book Description
Understanding and improving microstructural mechanical stability in metals and alloys is central to the development of high strength and high ductility materials for cladding and cores structures in advanced fast reactors. Design and enhancement of radiation-induced damage tolerant alloys are facilitated by better understanding the connection of various unit processes to collective responses in a multiscale model chain, including: dislocation nucleation, absorption and desorption at interfaces; vacancy production, radiation-induced segregation of Cr and Ni at defect clusters (point defect sinks) in BCC Fe-Cr ferritic/martensitic steels; investigation of interaction of interstitials and vacancies with impurities (V, Nb, Ta, Mo, W, Al, Si, P, S); time evolution of swelling (cluster growth) phenomena of irradiated materials; and energetics and kinetics of dislocation bypass of defects formed by interstitial clustering and formation of prismatic loops, informing statistical models of continuum character with regard to processes of dislocation glide, vacancy agglomeration and swelling, climb and cross slip.
Author:
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Category :
Languages : en
Pages :
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Book Description
Many evolving nuclear energy programs plan to use advanced predictive multi-scale multi-physics simulation and modeling capabilities to reduce cost and time from design through licensing. Historically, the role of experiments was primary tool for design and understanding of nuclear system behavior while modeling and simulation played the subordinate role of supporting experiments. In the new era of multi-scale multi-physics computational based technology development, the experiments will still be needed but they will be performed at different scales to calibrate and validate models leading predictive simulations. Cost saving goals of programs will require us to minimize the required number of validation experiments. Utilization of more multi-scale multi-physics models introduces complexities in the validation of predictive tools. Traditional methodologies will have to be modified to address these arising issues. This paper lays out the basic aspects of a methodology that can be potentially used to address these new challenges in design and licensing of evolving nuclear technology programs. The main components of the proposed methodology are verification, validation, calibration, and uncertainty quantification. An enhanced calibration concept is introduced and is accomplished through data assimilation. The goal is to enable best-estimate prediction of system behaviors in both normal and safety related environments. To achieve this goal requires the additional steps of estimating the domain of validation and quantification of uncertainties that allow for extension of results to areas of the validation domain that are not directly tested with experiments, which might include extension of the modeling and simulation (M & S) capabilities for application to full-scale systems. The new methodology suggests a formalism to quantify an adequate level of validation (predictive maturity) with respect to required selective data so that required testing can be minimized for cost saving purposes by showing further testing wold not enhance the quality of the validation of predictive tools. The proposed methodology is at a conceptual level. When matured and if considered favorably by the stakeholders, it could serve as a new framework for the next generation of the best estimate plus uncertainty licensing methodology that USNRC developed previously. In order to come to that level of maturity it is necessary to communicate the methodology to scientific, design and regulatory stakeholders for discussion and debates. This paper is the first step to establish this communication.