• Presents a rigorous yet accessible treatment of the ASAP and FSAP methods of sensitivity analysis , including discussion of their relative advantages and disadvantages
• Includes three introductory chapters that review the relevant mathematical concepts of matrix and operator theory, probability and statistics, and the theory and practice of measurements and errors
• Explores local sensitivity and uncertainty analysis for both linear and nonlinear systems
• Describes a computational algorithm for global sensitivity analysis and illustrates its use with an application to the dynamic behavior of a boiling water nuclear reactorAbout the Author: Dan Gabriel Cacuci is Ordinarius Chair Professor and Director of the Institute for Nuclear Technology and Reactor Safety, University of Karlsruhe; Director of the Institute for Reactor Safety at the Research Center Karlsruhe, Germany; Adjunct Professor, Department of Nuclear Engineering, University of California, Berkeley, USA; and the Editor of Nuclear Science and Engineering, the Research Journal of the American Nuclear Society.

As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable investigative scientific tools. Most of the techniques used for these analyses are well documented. However, a particularly useful method based on adjoint operators and applicable to a much wider variety of problems than methods traditionally used in control theory has lacked a full, systematic treatment.

Sensitivity and Uncertainty Analysis. Volume I: Theory, fills that gap, focusing on the mathematical underpinnings of the Forward Sensitivity Analysis Procedure (FSAP), the Adjoint Sensitivity Analysis Procedure (ASAP), and the use of deterministically obtained sensitivities for uncertainty analysis. After a review of the requisite background material, the author explores the concepts of local sensitivity analysis for both linear and nonlinear systems. This leads to the presentation of a global sensitivity analysis procedure for determining all of the system's critical points, and then analyzing these points locally by the ASAP. Along the way, the book presents several significant paradigms that illustrate the unique advantages of using the ASAP for large-scale systems characterized by many variables and parameters.

The treatment is rigorous but accessible and includes a discussion of the relative advantages and disadvantages of the ASAP and FSAP methods. The broad applicability of ASAP and FSAP make them valuable additions to your analytical toolbox and make this book a welcome complement to the available literature.