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Quasi-linear computational cost adaptive solvers for three dimensional modeling of heating of a human head induced by cell phone

机译:用于手机引起的人头发热的三维建模的拟线性计算成本自适应求解器

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In this paper we propose a new algorithm for solving of challenging adaptive time-dependent problems with Crank-Nicolson kind of time integration in parallel. The new algorithm allows for parallel execution of computations from different time steps. Time steps are distributed between processors. The number of processors working over consecutive time steps increases with each iteration of the adaptive algorithm. The following time steps utilize the previous time steps's solutions with the same level of accuracy. Our new parallel algorithm is compared with other methods. First, we compare it with a traditional method which performs all the adaptive iterations in the first time step, next it restarts the adaptive iterations in the second time step, and continues, one time step after another. Second, we compare our algorithm with the one that performs all the adaptive iterations in the first time step, and then starts the following time steps with the optimal mesh obtained from the previous iteration. Finally, we compare our algorithm to the one that executes the projection-based interpolation of the material data in the first time step, then it solves the problem over the obtained mesh, and then starts the following time steps with the optimal mesh obtained from the previous iteration. All the mentioned algorithms are tested on the challenging computational problem, which is the solution of the Pennes equation over a human head. The heat source is obtained by approximation of the solution of the Maxwell equation computed over the model human head. From our numerical results it follows that 10 min (600s) of exposure to the cell phone radiation may cause up to 2 degrees C increase of the temperature of the brain in the range close to the cell phone. (C) 2015 Elsevier B.V. All rights reserved.
机译:在本文中,我们提出了一种新的算法,可以并行解决Crank-Nicolson类型的时间积分难题,解决具有挑战性的自适应时间相关问题。新算法允许并行执行来自不同时间步长的计算。时间步长在处理器之间分配。随着自适应算法的每次迭代,在连续时间步长上工作的处理器数量会增加。接下来的时间步以相同的精度使用先前时间步的解决方案。我们将新的并行算法与其他方法进行了比较。首先,我们将其与传统方法进行比较,该传统方法在第一时间步骤中执行所有自适应迭代,然后在第二时间步骤中重新启动自适应迭代,然后继续进行一个时间步长。其次,我们将我们的算法与在第一时间步执行所有自适应迭代的算法进行比较,然后以从前一次迭代获得的最佳网格开始接下来的时间步。最后,我们将我们的算法与在第一步中执行基于投影的材料数据插值的算法进行比较,然后对获得的网格进行求解,然后使用从网格中获得的最佳网格开始以下时间步先前的迭代。所有提到的算法都在具有挑战性的计算问题上进行了测试,这是Pennes方程在人头上的解决方案。通过在模型人的头部上计算出的麦克斯韦方程的解的近似值来获得热源。根据我们的数值结果,可以得出结论,在手机辐射下暴露10分钟(600 s)可能会在接近手机的范围内使大脑温度升高多达2摄氏度。 (C)2015 Elsevier B.V.保留所有权利。

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