期刊
ACM TRANSACTIONS ON GRAPHICS
卷 32, 期 4, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2461912.2462006
关键词
reduced models; fluid simulation; solid-fluid coupling; radiosity
资金
- NSF [IIS-0953985]
- NSF AIR Award [IIP 1127777, IIS-0964562]
- ONR [N00014-11-1-0295]
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [953985] Funding Source: National Science Foundation
This paper extends Galerkin projection to a large class of nonpolynomial functions typically encountered in graphics. We demonstrate the broad applicability of our approach by applying it to two strikingly different problems: fluid simulation and radiosity rendering, both using deforming meshes. Standard Galerkin projection cannot efficiently approximate these phenomena. Our approach, by contrast, enables the compact representation and approximation of these complex non-polynomial systems, including quotients and roots of polynomials. We rely on representing each function to be model-reduced as a composition of tensor products, matrix inversions, and matrix roots. Once a function has been represented in this form, it can be easily model-reduced, and its reduced form can be evaluated with time and memory costs dependent only on the dimension of the reduced space.
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