高斯过程仿真的粒子法估计自由表面高度

IF 0.7 Q4 MECHANICS
Yoshiki Mizuno, S. Koshizuka
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引用次数: 2

摘要

本文介绍了一种统计仿真器的开发,以比粒子法更少的计算时间来估计自由表面高度。粒子方法可以通过求解NavierStokes方程和连续性方程来模拟自由表面流动问题,但随着计算域中粒子数量的增加,它们需要更多的计算时间。因此,用粒子法对各种初始条件下的自由曲面问题进行统计分析是不实用的。统计仿真器可以用较少的计算时间来估计这些问题的预测值,从而代替了仿真方法。在这项研究中,我们应用高斯过程设计了一个显式移动粒子模拟(EMPS)方法的统计模拟器,并预测了溃坝问题中的自由面高度。一旦它是基于仅从溃坝问题的一次模拟运行中生成的数据集开发的,高斯过程模拟器就能够在其他溃坝问题中近似这些高度。通过测量决定系数、均方根误差和平均绝对误差,我们评估了在初始条件下水柱形状与原始形状不同的溃坝问题中模拟自由水面高度的准确性。我们在x方向上改变初始长度,在z方向上改变初始高度,在y方向上保持相同的初始宽度。结果表明,在计算速度和精度方面,特别是在不同初始条件下反复进行自由面流分析时,可以采用高斯过程仿真器代替EMPS仿真器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gaussian process emulation of particle method for estimating free-surface heights
This paper presents the development of a statistical emulator to estimate free-surface heights with less computational time than a particle method. Particle methods can simulate free-surface flow problems by solving NavierStokes and continuity equations, but they require more computational time as the number of particles becomes greater in computational domains. Accordingly, it is not pragmatic to conduct statistical analysis of free-surface problems with respect to a variety of initial conditions by particle methods. In the place of the simulation methods, statistical emulators can estimate predictive values in these problems with less computational time. In this study, we apply a Gaussian process for designing a statistical emulator of the Explicit Moving Particle Simulation (EMPS) method and predict free-surface heights in dam break problems. Once it is developed based on a dataset made from only one simulation run of a dam break problem, the Gaussian process emulator is able to approximate these heights in other dam break problems. By measuring the coefficient of determination, root mean squared error, and mean absolute error, we evaluate the accuracy of emulated free-surface heights in dam break problems where the shapes of water columns are distinct from the original shape at the initial condition. We alter the initial lengths in the x-direction and the initial heights in the z-direction remaining the same initial width in the y-direction. Consequently, in terms of the computational speed and the accuracy, it is demonstrated that we can adopt the Gaussian process emulator as a replacement of the EMPS simulator especially when free-surface flow analysis is repeatedly conducted with different initial conditions.
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来源期刊
CiteScore
1.00
自引率
12.50%
发文量
2
期刊介绍: Journal of Fluid Science and Technology (JFST) is an international journal published by the Fluids Engineering Division in the Japan Society of Mechanical Engineers (JSME). JSME had been publishing Bulletin of the JSME (1958-1986) and JSME International Journal (1987-2006) by the continuous volume numbers. Considering the recent circumstances of the academic journals in the field of mechanical engineering, JSME reorganized the journal editorial system. Namely, JSME discontinued former International Journals and projected new publications from the divisions belonging to JSME. The Fluids Engineering Division acted quickly among all divisions and launched the premiere issue of JFST in January 2006. JFST aims at contributing to the development of fluid engineering by publishing superior papers of the scientific and technological studies in this field. The editorial committee will make all efforts for promoting strictly fair and speedy review for submitted articles. All JFST papers will be available for free at the website of J-STAGE (http://www.i-product.biz/jsme/eng/), which is hosted by Japan Science and Technology Agency (JST). Thus papers can be accessed worldwide by lead scientists and engineers. In addition, authors can express their results variedly by high-quality color drawings and pictures. JFST invites the submission of original papers on wide variety of fields related to fluid mechanics and fluid engineering. The topics to be treated should be corresponding to the following keywords of the Fluids Engineering Division of the JSME. Basic keywords include: turbulent flow; multiphase flow; non-Newtonian fluids; functional fluids; quantum and molecular dynamics; wave; acoustics; vibration; free surface flows; cavitation; fluid machinery; computational fluid dynamics (CFD); experimental fluid dynamics (EFD); Bio-fluid.
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