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The Second-Order Adjoint Sensitivity Analysis Methodology

The Second-Order Adjoint Sensitivity Analysis Methodology

Autorzy
Wydawnictwo Productivity Press Inc
Data wydania 01/02/2018
Wydanie Pierwsze
Liczba stron 306
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla szkół wyższych i kształcenia podyplomowego
Język angielski
ISBN 9781498726481
Kategorie Teorie nieliniowe
496.00 PLN (z VAT)
$135.33 / €116.99 / £102.90 /
Produkt dostępny
Przesyłka w 14 dni
Ilość
Do schowka

Opis książki

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.

The Second-Order Adjoint Sensitivity Analysis Methodology

Spis treści

MOTIVATION FOR COMPUTING FIRST- AND SECOND-ORDER SENSITIVITIES OF SYSTEM RESPONSES TO THE SYSTEM'S PARAMETERS


The Fundamental Role of Response Sensitivities for Uncertainty Quantification


The Fundamental Role of Response Sensitivities for Predictive Modeling


Advantages and Disadvantages of Statistical and Deterministic Methods for Computing Response Sensitivities





ILLUSTRATIVE APPLICATION OF THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) TO A LINEAR EVOLUTION PROBLEM


Exact Computation of the 1st-Order Response Sensitivities


Exact Computation of the 2nd-Order Response Sensitivities


Computing the 2nd-Order Response Sensitivities Corresponding to the 1st-Order Sensitivities


Discussion of the Essential Features of the 2nd-ASAM


Illustrative Use of Response Sensitivities for Predictive Modeling





THE SECOND-ORDER ADJOINT SENSITIVITY ANALYSIS METHODOLOGY (2nd-ASAM) FOR LINEAR SYSTEMS


Mathematical Modeling of a General Linear System


The 1st-Level Adjoint Sensitivity System (1st-LASS) for Computing Exactly and Efficiently 1st-Order Sensitivities of Scalar-Valued Responses for Linear Systems


The 2nd-Level Adjoint Sensitivity System (2nd-LASS) for Computing Exactly and Efficiently 1st-Order Sensitivities of Scalar-Valued Responses for Linear Systems








APPLICATION OF THE 2nd-ASAM TO A LINEAR HEAT CONDUCTION AND CONVECTION BENCHMARK PROBLEM


Heat Transport Benchmark Problem: Mathematical Modeling


Computation of First-Order Sensitivities Using the 2nd-ASAM


Computation of first-order sensitivities of the heated rod temperature


Computation of first-order sensitivities of the coolant temperature


Verification of the "ANSYS/FLUENT Adjoint Solver"


Applying the 2nd-ASAM to Compute the Second-Order Sensitivities and Uncertainties for the Heat Transport Benchmark Problem











APPLICATION OF THE 2nd-ASAM TO A LINEAR PARTICLE DIFFUSION PROBLEM


Paradigm Diffusion Problem Description


Applying the 2nd-ASAM to Compute the First-Order Response Sensitivities to Model Parameters


Applying the 2nd-ASAM to Compute the Second-Order Response Sensitivities to Model Parameters


Role of Second-Order Response Sensitivities for Quantifying Non-Gaussian Features of the Response Uncertainty Distribution


Illustrative Application of First-Order Response Sensitivities for Predictive Modeling








APPLICATION OF THE 2nd-ASAM FOR COMPUTING SENSITIVITIES OF DETECTOR RESPONSES TO UNCOLLIDED RADIATION TRANSPORT


The Ray-Tracing Form of the Forward and Ad

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