{"title":"Gaussian process emulation of particle method for estimating free-surface heights","authors":"Yoshiki Mizuno, S. Koshizuka","doi":"10.1299/jfst.2020jfst0021","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":44704,"journal":{"name":"Journal of Fluid Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Fluid Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1299/jfst.2020jfst0021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MECHANICS","Score":null,"Total":0}
引用次数: 2
Abstract
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.
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.