| کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن | 
|---|---|---|---|---|
| 6744735 | 1429331 | 2017 | 6 صفحه PDF | دانلود رایگان | 
عنوان انگلیسی مقاله ISI
												Advanced geometry navigation methods without cavity representation for fusion reactors
												
											ترجمه فارسی عنوان
													روش های ناوبری پیشرفته هندسی بدون نمایش حفره برای راکتورهای همجوشی 
													
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																																												کلمات کلیدی
												
											موضوعات مرتبط
												
													مهندسی و علوم پایه
													مهندسی انرژی
													مهندسی انرژی و فناوری های برق
												
											چکیده انگلیسی
												Particle transport simulations of models comprising large numbers of complex and irregular geometrical shapes is a great challenge in neutronics design and analysis of fusion reactors. All the space in the particle transport universe should be described including cavity in MCNP which is the most common deployed tool in fusion reactors. The quality of the cavity directly affects the calculation accuracy and efficiency. In view of the difficulty in describing the cavity and the instability of calculation efficiency, a new geometry representation method without cavity description was formed in Super Monte Carlo Program for Nuclear and Radiation Simulation (SuperMC). Advanced geometry navigation was developed in SuperMC to get high performance for particle transport in fusion reactors. The ITER benchmark model, a validation model released by ITER International Organization, was used to verify the accuracy and efficiency of geometry representation and navigation methods in SuperMC. The results in SuperMC showed consistency with MCNP. Besides, the computation speed was 10% faster than MCNP, while it brought more convenience without cavity representation for fusion reactors.
											ناشر
												Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fusion Engineering and Design - Volume 122, November 2017, Pages 232-237
											Journal: Fusion Engineering and Design - Volume 122, November 2017, Pages 232-237
نویسندگان
												Bin Wu, Shengpeng Yu, Lijuan Hao, Jing Song, Longfeng Shen, Pengcheng Long, 
											