Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Simulation and optimization of gamma-ray linear attenuation coefficients of barite concrete shields
Highlights BBD-based DoE was implemented to the design of barite concrete shields. Regression learning method was used to develop a mathematical model for PSO. W/c ratio, barite and cement contents were optimized for superior shielding capability. A good agreement was found between XCOM and predicted values. PSO allowed to the best concrete shield design in terms of mixing parameters.
Abstract The remarkable increment in radioactivity risks of today’s industrial world is required to the efficient design of shielding structures. In the present study, the optimal design parameters of barite concrete shields for providing the highest gamma radiation shielding capability were researched by using a hybrid technique of the Box-Behnken Design based response surface method and Particle Swarm Optimization. Barite aggregate fraction, water-to-cement ratio and cement content of the shields were limited as 0:100 (by weight), 0.30:0.70 (by weight) and 200:600 (kg/m3) in the optimization problem, respectively. The regression equation derived from the regression learning process presented an excellent correlation to define the XCOM linear attenuation coefficients. A nonlinear response surface fitted to the regression equation was used as the validation of the PSO results obtained from MATLAB. The results of this study have shown that the proposed method provides satisfactory predictions for the barite concrete radiation-shielding capability depending on the design parameters. In addition, it was found that the linear attenuation coefficient could be increased by 102% by the design of the best shield according to the poorest mixture.
Simulation and optimization of gamma-ray linear attenuation coefficients of barite concrete shields
Highlights BBD-based DoE was implemented to the design of barite concrete shields. Regression learning method was used to develop a mathematical model for PSO. W/c ratio, barite and cement contents were optimized for superior shielding capability. A good agreement was found between XCOM and predicted values. PSO allowed to the best concrete shield design in terms of mixing parameters.
Abstract The remarkable increment in radioactivity risks of today’s industrial world is required to the efficient design of shielding structures. In the present study, the optimal design parameters of barite concrete shields for providing the highest gamma radiation shielding capability were researched by using a hybrid technique of the Box-Behnken Design based response surface method and Particle Swarm Optimization. Barite aggregate fraction, water-to-cement ratio and cement content of the shields were limited as 0:100 (by weight), 0.30:0.70 (by weight) and 200:600 (kg/m3) in the optimization problem, respectively. The regression equation derived from the regression learning process presented an excellent correlation to define the XCOM linear attenuation coefficients. A nonlinear response surface fitted to the regression equation was used as the validation of the PSO results obtained from MATLAB. The results of this study have shown that the proposed method provides satisfactory predictions for the barite concrete radiation-shielding capability depending on the design parameters. In addition, it was found that the linear attenuation coefficient could be increased by 102% by the design of the best shield according to the poorest mixture.
Simulation and optimization of gamma-ray linear attenuation coefficients of barite concrete shields
Şensoy, A.T. (Autor:in) / Gökçe, H.S. (Autor:in)
14.04.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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