BERRU Predictive Modeling

The first-ever book on the experimental calibration of best estimate numerical simulation models Demonstrates the model's implementation using various examples, e.g. from chemistry, geophysics, space and aeronautics, or nuclear science Shares the objective of predictive modeling, which is to extract best estimate values for model parameters and predicted results, together with best estimate uncertainties for these parameters and results

Autorentext
Dan Gabriel Cacuci received his Master of Science, Master and Doctor of Philosophy degrees in applied physics and nuclear engineering from Columbia University in New York City. His scientific expertise encompasses the following areas: predictive best-estimate analysis of large-scale physical and engineering systems, large-scale scientific computations, and nuclear engineering (reactor multi-physics, dynamics, and safety). He currently holds the South Carolina SmartState Endowed Chair and Directorship of the Center of Economic Excellence in Nuclear Science and Energy at the University of South Carolina in Columbia, USA. Professor Cacuci's career spans extensive work both in academia and at large-scale multidisciplinary research centers. His teaching and research experience as a full professor at leading academic institutions includes appointments at the University of Tennessee, University of California at Santa Barbara, University of Illinois at Urbana-Champaign, University of Virginia, University of Michigan, University of California at Berkeley, Royal Institute of Technology Stockholm (Sweden), the National Institute for Nuclear Sciences and Technologies (France), and the University of Karlsruhe and Karlsruhe Institute of Technology (Germany). Professor Cacuci's research and management experience at leading national research centers includes serving as Senior Section Head at Oak Ridge National Laboratory, Institute Director at the Nuclear Research Center Karlsruhe (Germany), and Scientific Director of the Nuclear Energy Directorate, Commissariat a l'Energie Atomique (CEA, France). Since 1984, Prof. Cacuci has been the Editor of Nuclear Science and Engineering, The Research Journal of the American Nuclear Society (ANS). He is a member of the European Academy of Arts and Sciences (2004), Honorary Member of the Romanian Academy (1994), an ANS Fellow (1986), and has received many prestigious awards, including four titles of Doctor Honoris Causa, the E. O. Lawrence Award and Gold Medal (US DOE, 1998), the Arthur Holly Compton Award (ANS 2011), the Eugene P. Wigner Reactor Physics Award (ANS, 2003), the Glenn Seaborg Medal (ANS, 2002), and the Alexander von Humboldt Prize for Senior Scholars (Germany, 1990). Professor Cacuci has served on numerous international committees, including as the founding coordinator of the EURATOM-Integrated Project NURESIM (European Platform for Nuclear Reactor Simulation, 20042008), and founding coordinator (20042007) of the Coordinated Action to establish a Sustainable Nuclear Fission Technology Platform in Europe. He has made over 600 presentations worldwide, authored 4 books, 250 articles, and has edited the comprehensive Handbook of Nuclear Engineering (5 volumes, 3580 pages, Springer, 2010).

Inhalt
Basics of predictive best-estimate model calibration.- Predictive best-estimate model-validation, model-calibration and model-verification concerning open and chaotic systems.- Differences to traditional statostic evaluation methods.- Examples.