Hierarchically refined and coarsened splines for moving interface problems, with particular application to phase-field models of prostate tumor growth

被引:40
|
作者
Lorenzo, G. [1 ]
Scott, M. A. [2 ]
Tew, K. [3 ]
Hughes, T. J. R. [4 ]
Gomez, H. [5 ]
机构
[1] Univ A Coruna, Dept Metodos Matemat & Representac, Campus Elvina S-N, La Coruna 15071, Spain
[2] Brigham Young Univ, Dept Civil & Environm Engn, Provo, UT 84602 USA
[3] Brigham Young Univ, Dept Informat Technol, Provo, UT 84602 USA
[4] Univ Texas Austin, Inst Computat Engn & Sci, 201 East 24th St,C0200, Austin, TX 78712 USA
[5] Purdue Univ, Sch Mech Engn, 585 Purdue Mall, W Lafayette, IN 47907 USA
基金
欧洲研究理事会;
关键词
Isogeometric analysis; Bezier projection; Local refinement and coarsening; Hierarchical spline spaces; Phase field; Tumor growth; FLUID-STRUCTURE INTERACTION; ADAPTIVE ISOGEOMETRIC ANALYSIS; SUITABLE T-SPLINES; MATHEMATICAL ONCOLOGY; LINEAR INDEPENDENCE; POLYNOMIAL SPLINES; LOCAL REFINEMENT; B-SPLINES; SIMULATION; DESIGN;
D O I
10.1016/j.cma.2017.03.009
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Moving interface problems are ubiquitous in science and engineering. To develop an accurate and efficient methodology for this class of problems, we present algorithms for local h-adaptivity of hierarchical B-splines to be utilized in isogeometric analysis. We extend Bezier projection, an efficient quadrature-free local projection technique, to the hierarchical setting. In this case, extraction operators may not be invertible. To address this issue we develop a multi-level reconstruction operator which maintains the locality properties of the projection. We also introduce a balance parameter to control the overlap of hierarchical functions leading to improved numerical conditioning. We apply our algorithms to the simulation of localized prostate cancer growth. We model this disease using the phase-field method and a set of diffusion reaction equations to account for the dynamics of nutrients and a key biomarker termed Prostate Specific Antigen. Our results include examples on simple 2D and 3D domains and a more compelling tissue-scale, patient-specific simulation, which is run over a prostate anatomy extracted from medical images. Our methods for local h-adaptivity efficiently capture the evolving interface between the tumor and the neighboring healthy tissue with remarkable accuracy in all cases. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:515 / 548
页数:34
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