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Towards Real-Time Magnetic Dosimetry Simulations for Inductive Charging Systems
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2020-10-24 , DOI: arxiv-2010.12879 Norman Haussmann, Martin Zang, Robin Mease, Markus Clemens, Benedikt Schmuelling and Matthias Bolten
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2020-10-24 , DOI: arxiv-2010.12879 Norman Haussmann, Martin Zang, Robin Mease, Markus Clemens, Benedikt Schmuelling and Matthias Bolten
The exposure of a human by magneto-quasistatic fields from wireless charging
systems is to be determined from magnetic field measurements in near real-time.
This requires a fast linear equations solver for the discrete Poisson system of
the Co-Simulation Scalar Potential Finite Difference (Co-Sim. SPFD) scheme.
Here, the use of the AmgX library on NVIDIA GPUs is presented for this task. It
enables solving the equation system resulting from an ICNIRP recommended human
voxel model resolution of 2 mm in less than 0.5 seconds on a single NVIDIA
Tesla V100 GPU.
中文翻译:
实现感应充电系统的实时磁剂量学仿真
来自无线充电系统的准静态磁场对人体的暴露将通过近乎实时的磁场测量来确定。这需要针对协同仿真标量势有限差分 (Co-Sim. SPFD) 方案的离散泊松系统的快速线性方程求解器。此处,展示了在 NVIDIA GPU 上使用 AmgX 库来完成此任务。它能够在不到 0.5 秒的时间内在单个 NVIDIA Tesla V100 GPU 上求解由 ICNIRP 推荐的 2 毫米人体素模型分辨率产生的方程系统。
更新日期:2020-10-27
中文翻译:
实现感应充电系统的实时磁剂量学仿真
来自无线充电系统的准静态磁场对人体的暴露将通过近乎实时的磁场测量来确定。这需要针对协同仿真标量势有限差分 (Co-Sim. SPFD) 方案的离散泊松系统的快速线性方程求解器。此处,展示了在 NVIDIA GPU 上使用 AmgX 库来完成此任务。它能够在不到 0.5 秒的时间内在单个 NVIDIA Tesla V100 GPU 上求解由 ICNIRP 推荐的 2 毫米人体素模型分辨率产生的方程系统。