{"title":"刚性流体","authors":"Yu Wang, M. Olano","doi":"10.1145/2787626.2787654","DOIUrl":null,"url":null,"abstract":"We present a framework for modeling solid-fluid phase change. Our framework is physically-motivated, with geometric constraints applied to define rigid dynamics using shape matching. In each simulation step, particle positions are updated using an extended SPH solver where they are treated as fluid. Then a geometric constraint is computed based on current particle configuration, which consists of an optimal translation and an optimal rotation. Our approach differs from methods such as [Carlson et al. 2004] in that we solve rigid dynamics by using a stable geometric constraint [Müller et al. 2005] embedded in a fluid simulator.","PeriodicalId":269034,"journal":{"name":"ACM SIGGRAPH 2015 Posters","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Rigid fluid\",\"authors\":\"Yu Wang, M. Olano\",\"doi\":\"10.1145/2787626.2787654\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a framework for modeling solid-fluid phase change. Our framework is physically-motivated, with geometric constraints applied to define rigid dynamics using shape matching. In each simulation step, particle positions are updated using an extended SPH solver where they are treated as fluid. Then a geometric constraint is computed based on current particle configuration, which consists of an optimal translation and an optimal rotation. Our approach differs from methods such as [Carlson et al. 2004] in that we solve rigid dynamics by using a stable geometric constraint [Müller et al. 2005] embedded in a fluid simulator.\",\"PeriodicalId\":269034,\"journal\":{\"name\":\"ACM SIGGRAPH 2015 Posters\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SIGGRAPH 2015 Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2787626.2787654\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGGRAPH 2015 Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2787626.2787654","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
摘要
我们提出了一个模拟固-流相变的框架。我们的框架是物理驱动的,使用几何约束来定义使用形状匹配的刚性动力学。在每个模拟步骤中,使用扩展SPH求解器更新粒子位置,其中它们被视为流体。然后基于当前粒子的构型计算几何约束,该约束由最优平移和最优旋转组成。我们的方法与[Carlson et al. 2004]等方法不同,因为我们通过使用嵌入在流体模拟器中的稳定几何约束[m ller et al. 2005]来求解刚性动力学。
We present a framework for modeling solid-fluid phase change. Our framework is physically-motivated, with geometric constraints applied to define rigid dynamics using shape matching. In each simulation step, particle positions are updated using an extended SPH solver where they are treated as fluid. Then a geometric constraint is computed based on current particle configuration, which consists of an optimal translation and an optimal rotation. Our approach differs from methods such as [Carlson et al. 2004] in that we solve rigid dynamics by using a stable geometric constraint [Müller et al. 2005] embedded in a fluid simulator.