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Boltzmann熵函数的LBM分解及其应用
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作者 许友生 《浙江师大学报(自然科学版)》 CAS 2001年第4期353-355,共3页
运用格子气Boltzmann方法 (LBM) ,将Boltzmann熵函数分解成与过程无关的温度熵和体积熵两类成分 ,并对其应用进行了举例 .
关键词 格子气Boltzmann方法 LBM 虚拟元格 分解 Boltzmann函数 热力学 温度 体积熵
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Optimization of volume to point conduction problem based on a novel thermal conductivity discretization algorithm
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作者 杜文静 王沛丽 +1 位作者 宋立鹏 程林 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第7期1161-1168,共8页
A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to ... A conduction heat transfer process is enhanced by filling prescribed quantity and optimized-shaped high thermal conductivity materials to the substrate. Numerical simulations and analyses are performed on a volume to point conduction problem based on the principle of minimum entropy generation. In the optimization, the arrangement of high thermal conductivity materials is variable, the quantity of high thermal-conductivity material is constrained, and the objective is to obtain the maximum heat conduction rate as the entropy is the minimum.A novel algorithm of thermal conductivity discretization is proposed based on large quantity of calculations.Compared with other algorithms in literature, the average temperature in the substrate by the new algorithm is lower, while the highest temperature in the substrate is in a reasonable range. Thus the new algorithm is feasible. The optimization of volume to point heat conduction is carried out in a rectangular model with radiation boundary condition and constant surface temperature boundary condition. The results demonstrate that the algorithm of thermal conductivity discretization is applicable for volume to point heat conduction problems. 展开更多
关键词 Volume to point conduction Principle of minimum entropy generation Algorithm of thermal conductivity discretization Optimization
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