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Wyszukujesz frazę "Ibrahim, M.M." wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Application of genetic algorithm for optimization the safety system of the nuclear reactor
Autorzy:
El-Sayed Wahed, M.
Ibrahim, W. Z.
Effat, A. M.
Powiązania:
https://bibliotekanauki.pl/articles/146492.pdf
Data publikacji:
2009
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
genetic algorithm
non-dominated sorting
chimney water injection system (CWIS)
Egypt nuclear
Opis:
The purpose of this paper is to present an approach to optimization in which every target is considered as a separate objective to be optimized. Multi-objective optimization is a powerful tool for resolving conflicting objectives in engineering design and numerous other fields. One approach to solve multi-objective optimization problems is the non-dominated sorting genetic algorithm (NSGA). Genetic algorithm (GA) was applied in regarding the choice of the time intervals for the periodic testing of the components of the chimney water injection system (CWIS) of the 22 MW open pool multipurpose reactor (MPR), ETRR-2, at the Egyptian Atomic Energy Authority, has been used as a case study.
Źródło:
Nukleonika; 2009, 54, 1; 51-56
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genetic algorithms and neural networks for solving water quality model of the Egyptian research reactor
Autorzy:
El-Sayed Wahed, M.
Ibrahim, W. Z.
Effat, A. M.
Powiązania:
https://bibliotekanauki.pl/articles/148150.pdf
Data publikacji:
2009
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
genetic algorithm
neural networks
model calibration
water distribution system
water quality model
Opis:
The second Egyptian research reactor ETRR-2 became critical on 27th November, 1997. The National Center of Nuclear Safety and Radiation Control (NCNSRC) has the responsibility for the evaluation and assessment of safety of this reactor. Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. The purpose of this paper is to present an approach which combines both macro and detailed models to optimize the water quality parameters. For an efficient search through the solution space, we use a multi-objective genetic algorithm which allows us to identify a set of Pareto optimal solutions providing the decision maker with a complete spectrum of optimal solutions with respect to the various targets. This new combinative algorithm uses the radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS.
Źródło:
Nukleonika; 2009, 54, 4; 239-245
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Finding optimal of the Egyptian second nuclear reactor core patterns using genetic algorithm
Autorzy:
El-Sayed Wahed, M.
Ibrahim, W. Z.
Powiązania:
https://bibliotekanauki.pl/articles/148570.pdf
Data publikacji:
2010
Wydawca:
Instytut Chemii i Techniki Jądrowej
Tematy:
reloading fuel management
nuclear reactor
genetic algorithm
Opis:
The second Egyptian research reactor ETRR-2 went critical on the 27th of November 1997. The National Center of Nuclear Safety and Radiation Control (NCNSRC) has the responsibility of the evaluation and the assessment of the safety of this reactor. Fuel management reloads for Egypt’s second research reactor have been carried out according to the fuel management scheme suggested by the reactor designer (INVAP). The start up core consists of three different fuel types, while the equilibrium core has only one fuel type called standard fuel. The fuel management scheme consists in considering the core as being partitioned into eight zones. Each zone will correspond to a chain of fuel movements. In each fuel cycle two of these chains will be involved, in which eight fuel elements will be moved, from them two spent fuel elements will be extracted and two fresh fuel elements will be inserted in the core. In this paper we solve a model as a one big nonlinear multi objective discrete optimization problem using genetic algorithm. Results are compared with INVAP values.
Źródło:
Nukleonika; 2010, 55, 3; 331-338
0029-5922
1508-5791
Pojawia się w:
Nukleonika
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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