BERRU Predictive Modeling

BERRU Predictive Modeling PDF Author: Dan Gabriel Cacuci
Publisher: Springer
ISBN: 366258395X
Category : Technology & Engineering
Languages : en
Pages : 463

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Book Description
This book addresses the experimental calibration of best-estimate numerical simulation models. The results of measurements and computations are never exact. Therefore, knowing only the nominal values of experimentally measured or computed quantities is insufficient for applications, particularly since the respective experimental and computed nominal values seldom coincide. In the author’s view, the objective of predictive modeling is to extract “best estimate” values for model parameters and predicted results, together with “best estimate” uncertainties for these parameters and results. To achieve this goal, predictive modeling combines imprecisely known experimental and computational data, which calls for reasoning on the basis of incomplete, error-rich, and occasionally discrepant information. The customary methods used for data assimilation combine experimental and computational information by minimizing an a priori, user-chosen, “cost functional” (usually a quadratic functional that represents the weighted errors between measured and computed responses). In contrast to these user-influenced methods, the BERRU (Best Estimate Results with Reduced Uncertainties) Predictive Modeling methodology developed by the author relies on the thermodynamics-based maximum entropy principle to eliminate the need for relying on minimizing user-chosen functionals, thus generalizing the “data adjustment” and/or the “4D-VAR” data assimilation procedures used in the geophysical sciences. The BERRU predictive modeling methodology also provides a “model validation metric” which quantifies the consistency (agreement/disagreement) between measurements and computations. This “model validation metric” (or “consistency indicator”) is constructed from parameter covariance matrices, response covariance matrices (measured and computed), and response sensitivities to model parameters. Traditional methods for computing response sensitivities are hampered by the “curse of dimensionality,” which makes them impractical for applications to large-scale systems that involve many imprecisely known parameters. Reducing the computational effort required for precisely calculating the response sensitivities is paramount, and the comprehensive adjoint sensitivity analysis methodology developed by the author shows great promise in this regard, as shown in this book. After discarding inconsistent data (if any) using the consistency indicator, the BERRU predictive modeling methodology provides best-estimate values for predicted parameters and responses along with best-estimate reduced uncertainties (i.e., smaller predicted standard deviations) for the predicted quantities. Applying the BERRU methodology yields optimal, experimentally validated, “best estimate” predictive modeling tools for designing new technologies and facilities, while also improving on existing ones.

Theory, Application, and Implementation of Monte Carlo Method in Science and Technology

Theory, Application, and Implementation of Monte Carlo Method in Science and Technology PDF Author: Pooneh Saidi Bidokhti
Publisher: BoD – Books on Demand
ISBN: 1789855454
Category : Computers
Languages : en
Pages : 189

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Book Description
The Monte Carlo method is a numerical technique to model the probability of all possible outcomes in a process that cannot easily be predicted due to the interference of random variables. It is a technique used to understand the impact of risk, uncertainty, and ambiguity in forecasting models. However, this technique is complicated by the amount of computer time required to achieve sufficient precision in the simulations and evaluate their accuracy. This book discusses the general principles of the Monte Carlo method with an emphasis on techniques to decrease simulation time and increase accuracy.

Radiation serving society

Radiation serving society PDF Author: American Nuclear Society. Radiation Protection and Shielding Division. Biennial Topical Meeting
Publisher:
ISBN: 9780894486678
Category : Nuclear engineering
Languages : en
Pages :

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Book Description


Theory, Application, and Implementation of Monte Carlo Method in Science and Technology

Theory, Application, and Implementation of Monte Carlo Method in Science and Technology PDF Author:
Publisher:
ISBN: 9781789855463
Category :
Languages : en
Pages :

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Book Description


New Nuclear Data

New Nuclear Data PDF Author:
Publisher:
ISBN:
Category : Nuclear physics
Languages : en
Pages : 172

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Book Description


Launch-vehicle Dynamics

Launch-vehicle Dynamics PDF Author: Harry L. Runyan
Publisher:
ISBN:
Category : Launch vehicles (Astronautics)
Languages : en
Pages : 22

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Book Description


Diseases of the Pancreas

Diseases of the Pancreas PDF Author: Hans Günther Beger
Publisher: Springer Science & Business Media
ISBN: 354028656X
Category : Medical
Languages : en
Pages : 921

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Book Description
This book is based on the latest comprehensive data about molecular mechanism of acute pancreatitis, chronic pancreatitis and pancreatic cancer. The diagnostic techniques including histology, radiology, sonography etc. are based on the sensitivity and specificity of the respective methods. Special focus is given to the indication and contraindication to surgical techniques. The book contains specific treatment modality and results for the first time after long-term outcome evaluation. There is detailed description of diagnosis and treatment, and the book is abundantly illustrated with approximately 300 color illustrations.

Fusion Reactor Physics

Fusion Reactor Physics PDF Author: Terry Kammash
Publisher: Ann Arbor Science Publishers
ISBN:
Category : Science
Languages : en
Pages : 518

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Book Description


Fusion Neutronics

Fusion Neutronics PDF Author: Yican Wu
Publisher: Springer
ISBN: 981105469X
Category : Science
Languages : en
Pages : 402

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Book Description
This book provides a systematic and comprehensive introduction to fusion neutronics, covering all key topics from the fundamental theories and methodologies, as well as a wide range of fusion system designs and experiments. It is the first-ever book focusing on the subject of fusion neutronics research. Compared with other nuclear devices such as fission reactors and accelerators, fusion systems are normally characterized by their complex geometry and nuclear physics, which entail new challenges for neutronics such as complicated modeling, deep penetration, low simulation efficiency, multi-physics coupling, etc. The book focuses on the neutronic characteristics of fusion systems and introduces a series of theories and methodologies that were developed to address the challenges of fusion neutronics. Further, it introduces readers to the unique principles and procedures of neutronics design, experimental methodologies and methodologies for fusion systems. The book not only highlights the latest advances and trends in the field, but also draws on the experiences and skills collected in the author’s more than 40 years of research. To make it more accessible and enhance its practical value, various representative examples are included to illustrate the application and efficiency of the methods, designs and experimental techniques discussed.

The Second-Order Adjoint Sensitivity Analysis Methodology

The Second-Order Adjoint Sensitivity Analysis Methodology PDF Author: Dan Gabriel Cacuci
Publisher: CRC Press
ISBN: 1351646583
Category : Mathematics
Languages : en
Pages : 432

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Book Description
The Second-Order Adjoint Sensitivity Analysis Methodology generalizes the First-Order Theory presented in the author’s previous books published by CRC Press. This breakthrough has many applications in sensitivity and uncertainty analysis, optimization, data assimilation, model calibration, and reducing uncertainties in model predictions. The book has many illustrative examples that will help readers understand the complexity of the subject and will enable them to apply this methodology to problems in their own fields. Highlights: • Covers a wide range of needs, from graduate students to advanced researchers • Provides a text positioned to be the primary reference for high-order sensitivity and uncertainty analysis • Applies to all fields involving numerical modeling, optimization, quantification of sensitivities in direct and inverse problems in the presence of uncertainties. About the Author: Dan Gabriel Cacuci is a South Carolina SmartState Endowed Chair Professor and the Director of the Center for Nuclear Science and Energy, Department of Mechanical Engineering at the University of South Carolina. He has a Ph.D. in Applied Physics, Mechanical and Nuclear Engineering from Columbia University. He is also the recipient of many awards including four honorary doctorates, the Ernest Orlando Lawrence Memorial award from the U.S. Dept. of Energy and the Arthur Holly Compton, Eugene P. Wigner and the Glenn Seaborg Awards from the American Nuclear Society.