Mehtap Günay

Bio: Mehtap Günay is an academic researcher from İnönü University. The author has contributed to research in topics: Hybrid reactor & Nuclear data. The author has an hindex of 9, co-authored 17 publications receiving 181 citations.

Three-Dimensional Neutronic Calculations for the Fusion Breeder APEX Reactor

Abstract: Three-dimensional analysis has been made using the MCNP Monte Carlo code and ENDF/B-VI nuclear data. The nuclear characteristics of a fusion-fission hybrid reactor such as tritium breeding ratio, energy multiplication factor, fissile fuel breeding, first wall radiation damage, and heat deposition have been investigated in a liquid first wall, blanket, and shield for the various mixture compositions of molten salt and heavy metals for blanket layer thicknesses of 20, 30, 40, and 50 cm. The neutron flux load at the first wall is assumed to be 10 MW/ m 2 . The flowing molten salt wall is composed of flibe (Li 2 BeF 4 ) as the main constituent with increased mole fractions of heavy metals, 2 to 10% ThF 4 and UF 4 . In terms of all parameters, the mixtures with UF 4 show better performance than the mixtures with ThF 4 . The atomic displacement and the helium, tritium production rates remain well below the presumable limits for all mixture compositions of molten salt and heavy metals and thicknesses of the blanket.

Artificial Intelligence Techniques for Rational Decision Making

Abstract: Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simons bounded rationality theory are flexible due to advanced signal processing techniques, Moores Law and artificial intelligence. Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making: Theory of the marginalization of irrelevant information Principal component analysis Independent component analysis Automatic relevance determination method In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence. Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.