近日，德国达姆施塔特工业大学Christoph Graf团队研究了基于GPU加速的化学循环气化CFD-DEM模拟放大。这一研究成果发表在2026年3月12日出版的《颗粒学报》杂志上。

化学链气化技术是一种用于化学回收和生物能源的高效工艺。虽然该工艺已在实验室和中试规模进行测试，但尚未尝试将其放大至示范或工业规模。辅助放大的潜在工具是计算流体动力学与离散元方法耦合模拟。然而，采用传统模拟技术所需的计算时间过长而不可行。

研究组通过采用图形处理器与中央处理器混合加速方法，实现了80倍的加速效果。通过对模拟时间主要影响因素进行分析，进一步提高了模拟效率。基于这些成果，研究组成功完成了200兆瓦工厂的放大模拟，并在合理时间内获得了可信结果。因此，该研究为流化床气化工艺的工业规模CFD-DEM模拟提供了概念验证。

附：英文原文

Title: Scale-up of CFD-DEM simulation of chemical looping gasification by GPU acceleration

Author: Christoph Graf

Issue&Volume: 2026/03/12

Abstract: The chemical looping gasification process is an efficient technology for chemical recycling and bioenergy. While the process has been tested in lab and pilot scale, a scale-up to demonstration or industrial scale has not yet been attempted. A potential tool to assist the scale-up is coupled computational fluid dynamics (CFD) and discrete element method (DEM) simulation. However, with conventional simulation techniques the required simulation time is unfeasibly long. In this work the simulation was accelerated by a hybrid approach using both, graphics processing unit (GPU) and central processing unit (CPU) achieving a speed-up of 80 times. An analysis of the main influences on the simulation time was conducted to improve the simulation efficiency. With these results an upscaled simulation of a 200MW plant was performed achieving plausible results in a reasonable time. Thus, this work provides a proof of concept for CFD-DEM simulation of fluidized bed gasification at industrial scale.

DOI: 10.1016/j.partic.2026.02.020

Source: https://www.sciencedirect.com/science/article/pii/S1674200126000854