GPU-accelerated adaptive particle splitting and merging in SPH

Graphical processing unit (GPU) implementation of adaptive particle splitting and merging (APS) in the framework of smoothed particle hydrodynamics (SPH) is presented. Particle splitting and merging process are carried out based on a prescribed criterion. Multiple time stepping technology is used to reduce computational cost further. Detailed implementations on both single- and multi-GPU are discussed. A benchmark test that is a flow past fixed periodic circles is simulated to investigate the accuracy and speed of the algorithm. Comparable precision with uniformly fine simulation is achieved by APS, whereas computational demand is reduced considerably. Satisfactory speedup and acceptable scalability are obtained, demonstrating that GPU-accelerated APS is a promising tool to speed up large-scale particle-based simulations. (C) 2013 Elsevier B.V. All rights reserved

Chem. Eng. Sci.

Due to significant multi-scale heterogeneity, understanding sub-grid structures is critical to effective continuum-based description of gassolid flow. However, it is challenging for both physical measurements and numerical simulations. In this article, with the macro-scale pseudo-particle method (MaPPM) implemented on a GPU-based HPC system, up to 30,000 fluidized solids are simulated using the NS equation directly. The destabilization of uniform suspensions and the formation of solids clusters are reproduced in two-dimensional suspensions. Distinct scale-dependence of the statistical properties in the systems at moderate solid/gas density ratio is observed. Obvious cluster formation and its effect on drag coefficient are shown in a system at high solid/gas density ratio. On the computational side, about 19 folds speedup is obtained on one GT200 GPU, as compared to a mainstream CPU core. The necessity for investigating even larger systems is prospected. (C) 2010 Elsevier Ltd. All rights reserved.Due to significant multi-scale heterogeneity, understanding sub-grid structures is critical to effective continuum-based description of gassolid flow. However, it is challenging for both physical measurements and numerical simulations. In this article, with the macro-scale pseudo-particle method (MaPPM) implemented on a GPU-based HPC system, up to 30,000 fluidized solids are simulated using the NS equation directly. The destabilization of uniform suspensions and the formation of solids clusters are reproduced in two-dimensional suspensions. Distinct scale-dependence of the statistical properties in the systems at moderate solid/gas density ratio is observed. Obvious cluster formation and its effect on drag coefficient are shown in a system at high solid/gas density ratio. On the computational side, about 19 folds speedup is obtained on one GT200 GPU, as compared to a mainstream CPU core. The necessity for investigating even larger systems is prospected. (C) 2010 Elsevier Ltd. All rights reserved

Editorial overview – process design and intensification of biomass pyrolysis and gasification reactors: Experimental and modeling studies

Biomass pyrolysis and gasification are two novel and popular approaches to convert low energy-density raw biomass into high energy-density bio-oil and gas for fuel and chemical engineering. They have been viewed as potential ways to complement traditional fossil fuels to increase energy security and reduce environmental pollution. various studies demonstrating the use of various methods, developments, and theories in the field of process engineering to facilitate biomass pyrolysis or gasification at reactor and process scales are discussed. Scientific investigations and industrial practices on process operation, design and intensification to substantially improve efficiency and performance, and reduce time and cost are highlighted.</p

Direct numerical simulation of particle clustering in gas-solid flow with a macro-scale particle method

Particle clustering has long been a focus in the study of gas-solid flow. Detailed flow field information below the particle scale is required to understand the mechanism of its formation and the statistical properties of its dynamic behavior, but is not easily obtained in both experiments and numerical simulations. In this article, a meshless method is used to reveal such details in the destabilizing of a suspension with hundreds of particles. During the process, doublets, quadruplet and larger clusters are seen to form and disintegrate dynamically, showing a tendency to minimize local voidages. At the same time, single vertical streams, pairs of parallel streams and many irregular streams appear and disappear between particle clusters alternatively, exhibiting a tendency to suffer lowest resistance. Globally, the spatio-temporal compromise between these two tendencies results in a configuration of large clusters separated by fast flow streams. In the Clustering process, the inter-phase slip velocity is seen to increase long after the forces on each phase have stabilized, suggesting that inter-phase friction is not a function of local voidage and Reynolds number only, as commonly considered. The article concludes with prospects on the sub-grid scale models for continuum description of gas-solid flow that can be established upon such simulation results. (c) 2008 Elsevier Ltd. All rights reserved

Efficient parallel implementation of the lattice Boltzmann method on large clusters of graphic processing units

Many-core processors, such as graphic processing units (GPUs), are promising platforms for intrinsic parallel algorithms such as the lattice Boltzmann method (LBM). Although tremendous speedup has been obtained on a single GPU compared with mainstream CPUs, the performance of the LBM for multiple GPUs has not been studied extensively and systematically. In this article, we carry out LBM simulation on a GPU cluster with many nodes, each having multiple Fermi GPUs. Asynchronous execution with CUDA stream functions, OpenMP and non-blocking MPI communication are incorporated to improve efficiency. The algorithm is tested for two-dimensional Couette flow and the results are in good agreement with the analytical solution. For both the oneand two-dimensional decomposition of space, the algorithm performs well as most of the communication time is hidden. Direct numerical simulation of a two-dimensional gas-solid suspension containing more than one million solid particles and one billion gas lattice cells demonstrates the potential of this algorithm in large-scale engineering applications. The algorithm can be directly extended to the three-dimensional decomposition of space and other modeling methods including explicit grid-based methods

concurrently delivering and retrieving multicast data in parallel channels for mobile users

Wuhan University, China; Dalian University of Technology, China; IEEE Antennas and Propagation Society; Scientific Research Publishing, USA; IEEE Communications SocietyNowadays, the backbone network is capable of delivering countless information at extremely high performance and high throughput. However, the abundant information in the backbone may not be retrieved by the mobile users fingertips. This paper developed t

A comprehensive review on the application of hybrid nanofluids in solar energy collectors

Over the years, nanofluids have proved to be beneficial in various heat transfer applications, particularly in solar energy collectors. Hybrid nanofluids have also shown promise in such applications due to their enhanced thermal conductivity relative to mono-nanofluids and to pure fluids. The aim of this review paper is to scrutinize recent research in this topic in order to identify the key advantages and disadvantages of hybrid nanofluids as heat transfer agents in solar energy collectors. First, the various types of non-concentrating and concentrating solar collectors are described. Then, recent research on hybrid nanofluids is summarized and discussed. Most studies have reported significant enhancements in the thermal and optical performance of solar thermal energy devices operating on hybrid nanofluids. The thermal efficiency was found to be proportionally dependent on the nanoparticles' fraction in regular fluids with reasonable values. Finally, the limitations of the presented studies, relating to considerations such as stability and pumping power requirements, as well as recommendations for future investigation are addressed

Dataset for Fracture and Impact Toughness of High-Entropy Alloys

Measurement(s) Fracture Toughness; Impact Toughness; Impact Energy Technology Type(s) Mechanical Testing Syste

Efficient 3D DNS of gas-solid flows on Fermi GPGPU

Three-dimensional (3D) gas-solid Direct Numerical Simulation (DNS) requires huge computational resources which imposes a great challenge to both current hardware and software conditions. In this article, an efficient implementation of 3D gas-solid DNS with Lattice Boltzmann Method and Discrete Element Method is developed on a Fermi GPGPU. An Immersed Moving Boundary approach is utilized to impose the no-slip condition at particle-fluid interfaces. Optimization strategies such as changing the sequence of collision and propagation in grid evolution and making multiple kernel executing concurrently are discussed in detail. This algorithm is demonstrated to be competitive both in terms of accuracy and performance. Approximately 131 Millions of Lattices Update Per Second have been achieved, indicating that this GPGPU implementation is very suitable for 3D gas-solid DNS. (C) 2012 Elsevier Ltd. All rights reserved