Semi-analytical source (SAS) method for 3-D transient heat conduction problems with moving heat source of arbitrary shape
Semi-analytical source (SAS) method for 3-D transient heat conduction problems with moving heat source of arbitrary shape
复制标题
用于任意形状移动热源的 3-D 瞬态热传导问题的半解析源 (SAS) 方法
DOI：
10.1016/j.ijheatmasstransfer.2020.120692
复制
发表时间：
2021
影响因子：
5.2
通讯作者：
K. Cole
中科院分区：
文献类型：
--
作者：
B. Çetin;Yiğit F. Kuşcu;B. Çetin;Ö. Tümüklü;K. Cole
本文采用作者最近提出的半解析源方法，对具有移动热源的三维全瞬态热传导问题进行了求解。该方法对具有分段恒定热源的扩散问题使用精确的格林函数，这意味着热源项被定义为在每个时间间隔和每个空间间隔中分段恒定贡献的叠加。这种方法可以模拟任何随时间变化的加热空间分布。此外，该方法不限于热源的直线运动，并且可以包括内部加热以及表面加热。该方法的一个重要方面是，只需要在热源路径和感兴趣的观测位置上进行空间离散化，因此不需要像全数值方法那样对整个域进行离散化。为了验证半解析源方法，搭建了实验装置，并用光纤激光器进行了实验，得到了满意的结果。用高斯热源进行了几个实例研究。半解析源方法特别适合于并行计算。为了探索这方面，使用消息传递接口（MPI）和Stampede2上多达800个处理器的域分解来探索该方法的并行化。并行计算结果表明，半解析方法非常适合于并行计算。对于强扩展，该方法显示出理想的线性扩展，随着处理器数量的增加和适当的负载平衡。弱尺度表明，由于该方法在时间上的卷积特性，并行化性能随着时域的增加呈指数级增长。
In this study, the semi-analytical source method, which has recently developed by the authors, is implemented for a 3-D fully-transient heat conduction problem with a moving heat source. The method utilizes the exact Green’s function for a diffusion problem with a piecewise constant heat source meaning that the heat source term is defined as the superposition of piece-wise constant contributions in each time interval and in each spatial interval. This approach allows the modeling of any arbitrary spatial distribution of heating with time varying power. Moreover, the method is not limited to straight-line motion of the heat source, and can include internal heating as well as surface heating. One important aspect of the method is that spatial discretization is required only on the path of the heating source and at the observation locations of interest, consequently the discretization of the entire domain is not required as in the case of fully-numerical methods. To verify the semi-analytical source method, an experimental setup was constructed and experiments were conducted with a fiber laser, and satisfactory agreement is achieved. Several case studies are also demonstrated with a Gaussian heat source. The semi-analytical source method is particularly well-suited for parallel computing. To explore this aspect, the parallelization of the method is explored using the Message Passing Interface (MPI) and domain decomposition with up to 800 processors on Stampede2. The parallelization results reveal that semi-analytical method is very suitable for parallel computation. For a strong scaling, the method shows an ideal linear scaling with increasing number of processors with a proper load balance. The weak scaling reveals that the parallelization performance exponentially increases with the increasing time domain due to convolution nature of the method in time.