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Journal ArticleDOI

Parallelization Strategies for Computational Fluid Dynamics Software: State of the Art Review

01 Apr 2017-Archives of Computational Methods in Engineering (Springer Netherlands)-Vol. 24, Iss: 2, pp 337-363
TL;DR: This article provides a comprehensive state of the art review of important CFD areas and parallelization strategies for the related software and offers suggestions for future work in parallel computing of CFD software.
Abstract: Computational fluid dynamics (CFD) is one of the most emerging fields of fluid mechanics used to analyze fluid flow situation. This analysis is based on simulations carried out on computing machines. For complex configurations, the grid points are so large that the computational time required to obtain the results are very high. Parallel computing is adopted to reduce the computational time of CFD by utilizing the available resource of computing. Parallel computing tools like OpenMP, MPI, CUDA, combination of these and few others are used to achieve parallelization of CFD software. This article provides a comprehensive state of the art review of important CFD areas and parallelization strategies for the related software. Issues related to the computational time complexities and parallelization of CFD software are highlighted. Benefits and issues of using various parallel computing tools for parallelization of CFD software are briefed. Open areas of CFD where parallelization is not much attempted are identified and parallel computing tools which can be useful for parallelization of CFD software are spotlighted. Few suggestions for future work in parallel computing of CFD software are also provided.
Citations
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Journal ArticleDOI
TL;DR: In this article, the authors reviewed the state of the art work carried out in the field of turbomachinery using computational fluid dynamics (CFD) and highlighted the prevailing merits and demerits of CFD in turbomachines.
Abstract: Computational fluid dynamics (CFD) plays an essential role to analyze fluid flows and heat transfer situations by using numerical methods. Turbomachines involve internal and external fluid flow problems in compressors and turbines. CFD at present is one of the most important tools to design and analyze all types of turbomachinery. The main purpose of this paper is to review the state of the art work carried out in the field of turbomachinery using CFD. Literature review of research work pertaining to CFD analysis in turbines, compressors and centrifugal pumps are described. Various issues of CFD codes used in turbomachinery and its parallelization strategy adopted are highlighted. Furthermore, the prevailing merits and demerits of CFD in turbomachinery are provided. Open areas pertinent to CFD investigation in turbomachinery and CFD code parallelization are also described.

110 citations

Journal ArticleDOI
TL;DR: In this article, the authors performed an experimental analysis of base pressure in suddenly expanded compressible flow from nozzles at different Mach numbers and found that microjets are efficient when the flow is under the influence of a favorable pressure gradient.

66 citations

Journal ArticleDOI
TL;DR: In this article, single and multi-objective optimization of thermal management characteristics, namely maximum temperature (Tb, max), average Nusselt number (Nuavg), and coefficient of friction (Fcavg) using Cuckoo search (CS) and artificial bee colony (ABC) algorithm is attempted.

58 citations

Journal ArticleDOI
TL;DR: The fitness function obtained are closer and indicate safe temperature of battery with enhanced Nusselt number and minimum friction coefficient and the maximum multi-objective fitness obtained after normalization is 0.9.
Abstract: A novel technique for multi-objective optimization of thermal management in battery system using hybrid Genetic algorithm and Fuzzy logic is developed. Secondly, Particle Swarm Optimization algorithm combined with Fuzzy logic is also proposed for the same. The combined algorithms and fitness function for fitness evaluation is written in-house C code. For the thermal performance fitness evaluation, realistic conjugate heat transfer condition at the battery and coolant interface is adopted. The objective functions are average Nusselt number, friction coefficient, and maximum temperature. Maximizing one causes proportional increase in another, hence to achieve a moderate condition of better Nusselt number with low pumping power cost and temperature within allowable limits, these algorithms assist in optimization. Five different independent operating parameters are selected for the Multi-objective optimization and brief results are presented. The Fuzzy logic membership functions adopted can be easily modified/selected by the user to suite the battery thermal problem at hand and to assign weight to each fitness function. The fitness function obtained using the proposed multi-objective optimization technique are closer and indicate safe temperature of battery with enhanced Nusselt number and minimum friction coefficient. The maximum multi-objective fitness obtained after normalization is 0.9.

56 citations

Journal ArticleDOI
TL;DR: There is enough scope for extended research for realizing optimal design of disc brake system by truly emulating all the relevant practical situations, according to the present article.
Abstract: Disc brake system is one of the most critical components in a vehicle, which is always exposed to nonlinear transient thermoelastic conditions. Optimal design of a brake system to suit the heat transfer, weight and packing requirements is an ongoing challenge. Substantial researches have been carried out and are underway, in order to address the diverse issues related to thermal, mechanical and structural performances of automobile disc brakes. With the extensive application of numerical tools and techniques, the analyses involved became easier and effective. The present article provides an exhaustive review of the numerical and experimental studies reported so far, on the analysis and design of solid and ventilated disc brakes. The directions for future works are also described. The review reveals that, there is enough scope for extended research for realizing optimal design of disc brake system by truly emulating all the relevant practical situations.

54 citations

References
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Book
01 Jan 1996
TL;DR: This text develops and applies the techniques used to solve problems in fluid mechanics on computers and describes in detail those most often used in practice, including advanced techniques in computational fluid dynamics.
Abstract: Preface. Basic Concepts of Fluid Flow.- Introduction to Numerical Methods.- Finite Difference Methods.- Finite Volume Methods.- Solution of Linear Equation Systems.- Methods for Unsteady Problems.- Solution of the Navier-Stokes Equations.- Complex Geometries.- Turbulent Flows.- Compressible Flow.- Efficiency and Accuracy Improvement. Special Topics.- Appendeces.

7,066 citations

18 Dec 2006
TL;DR: The parallel landscape is frame with seven questions, and the following are recommended to explore the design space rapidly: • The overarching goal should be to make it easy to write programs that execute efficiently on highly parallel computing systems • The target should be 1000s of cores per chip, as these chips are built from processing elements that are the most efficient in MIPS (Million Instructions per Second) per watt, MIPS per area of silicon, and MIPS each development dollar.
Abstract: Author(s): Asanovic, K; Bodik, R; Catanzaro, B; Gebis, J; Husbands, P; Keutzer, K; Patterson, D; Plishker, W; Shalf, J; Williams, SW | Abstract: The recent switch to parallel microprocessors is a milestone in the history of computing. Industry has laid out a roadmap for multicore designs that preserves the programming paradigm of the past via binary compatibility and cache coherence. Conventional wisdom is now to double the number of cores on a chip with each silicon generation. A multidisciplinary group of Berkeley researchers met nearly two years to discuss this change. Our view is that this evolutionary approach to parallel hardware and software may work from 2 or 8 processor systems, but is likely to face diminishing returns as 16 and 32 processor systems are realized, just as returns fell with greater instruction-level parallelism. We believe that much can be learned by examining the success of parallelism at the extremes of the computing spectrum, namely embedded computing and high performance computing. This led us to frame the parallel landscape with seven questions, and to recommend the following: • The overarching goal should be to make it easy to write programs that execute efficiently on highly parallel computing systems • The target should be 1000s of cores per chip, as these chips are built from processing elements that are the most efficient in MIPS (Million Instructions per Second) per watt, MIPS per area of silicon, and MIPS per development dollar. • Instead of traditional benchmarks, use 13 “Dwarfs” to design and evaluate parallel programming models and architectures. (A dwarf is an algorithmic method that captures a pattern of computation and communication.) • “Autotuners” should play a larger role than conventional compilers in translating parallel programs. • To maximize programmer productivity, future programming models must be more human-centric than the conventional focus on hardware or applications. • To be successful, programming models should be independent of the number of processors. • To maximize application efficiency, programming models should support a wide range of data types and successful models of parallelism: task-level parallelism, word-level parallelism, and bit-level parallelism. 1 The Landscape of Parallel Computing Research: A View From Berkeley • Architects should not include features that significantly affect performance or energy if programmers cannot accurately measure their impact via performance counters and energy counters. • Traditional operating systems will be deconstructed and operating system functionality will be orchestrated using libraries and virtual machines. • To explore the design space rapidly, use system emulators based on Field Programmable Gate Arrays (FPGAs) that are highly scalable and low cost. Since real world applications are naturally parallel and hardware is naturally parallel, what we need is a programming model, system software, and a supporting architecture that are naturally parallel. Researchers have the rare opportunity to re-invent these cornerstones of computing, provided they simplify the efficient programming of highly parallel systems.

2,262 citations

Proceedings ArticleDOI
06 Nov 2004
TL;DR: A parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and the dispersion of airborne contaminants in the Times Square area of New York City are simulated.
Abstract: Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (GPUs), we propose to use a cluster of GPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.

485 citations

Journal ArticleDOI
TL;DR: Computational fluid dynamics (cfd) is a simulation tool which uses powerful computer and applied mathematics to model fluid flow situations for the prediction of heat, mass and momentum transfer and optimal design in industrial processes as mentioned in this paper.

315 citations

Journal ArticleDOI
01 Jan 2016-Heart
TL;DR: The adoption of CFD modelling signals a new era in cardiovascular medicine and a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.
Abstract: This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.

296 citations