Kazuhiko Kakuda¹, Tsuyoki Nagashima¹, Yuki Hayashi¹, Shunsuke Obara¹, Jun Toyotani¹, Nobuya Katsurada², Shunji Higuchisup>2, Shohei Matsuda²

CMES-Computer Modeling in Engineering & Sciences, Vol.88, No.1, pp. 17-28, 2012, DOI:10.3970/cmes.2012.088.017

Abstract An acceleration of the particle-based incompressible fluid flow simulations on GPU using CUDA is presented. The particle method is based on the MPS (Moving Particle Semi-implicit) scheme using logarithmic-type weighting function to stabilize the spurious oscillatory solutions for the pressure fields which are governed by Poisson equation. The standard MPS scheme is widely utilized as a particle strategy for the free surface flow, the problem of moving boundary, multi-physics/multi-scale ones, and so forth. Numerical results demonstrate the workability and the validity of the present approach through dam-breaking flow problem. More >

Xinhua Liu^1,2, Yongzhi Liu¹, Hao Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.91, No.1, pp. 65-80, 2013, DOI:10.3970/cmes.2013.091.065

Abstract In order to study the rheological characteristics of magnetorheological fluids, a simulation approach through integration of Monte Carlo method and GPU accelerated technology was proposed and the three-dimensional micro-structure of magnetic particles in different strength magnetic fields were simulated. The Monte Carlo method to magnetic particles of magnetorheological fluids and its key steps such as particle modeling, magnetic energy equations calculating and system state updating were elaborated. Moreover, GPU accelerated technology was applied to the simulation of magnetorheological fluids to reduce computational time and a flowchart for the proposed approach was designed. Finally, a physics experiment was carried out and… More >

Lili He^1,2, Hongtao Bai^1,2, Dantong Ouyang^1,2, Changshuai Wang^1,2, Chong Wang^1,2,3, Yu Jiang^1,2,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 599-613, 2019, DOI:10.32604/cmc.2019.05928

Abstract Cloud-derived wind refers to the wind field data product reversely derived through satellite remote sensing cloud images. Satellite cloud-derived wind inversion has the characteristics of large scale, computationally intensive and long time. The most widely used cloud-derived serial--tracer cloud tracking method is the maximum cross-correlation coefficient (MCC) method. In order to overcome the efficiency bottleneck of the cloud-derived serial MCC algorithm, we proposed a parallel cloud-derived wind inversion algorithm based on GPU framework in this paper, according to the characteristics of independence between each wind vector calculation. In this algorithm, each iteration is considered as a thread of GPU cores,… More >