Towards predictive 4D computational models for the heart

迈向心脏的预测 4D 计算模型

• 批准号: DP220103160
• 负责人: Prof Santiago Badia
• 金额: $ 28.49万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-08-09 至 2025-08-08
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP220103160
• 关键词: Towards; predictive; 4D; computational; models

This project aims to develop novel high-performance numerical algorithms for multiscale and multiphysics PDEs with dynamic interfaces, the development and analysis of a novel PDE system modelling the electromechanics of heart and torso, and the combination of these numerical techniques and models to deliver predictive tools for patient-specific simulations of the cardiac function. It involves the design and mathematical analysis of space-time variational discretisations on embedded meshes, 4D computational geometry algorithms for numerical integration and multilevel solvers. By combining scientific computing and machine learning, one anticipated outcome of this research is a new generation of nonlinear PDE approximations and solvers.

该项目旨在为具有动态接口的多尺度和多物理场偏微分方程开发新型高性能数值算法，开发和分析模拟心脏和躯干机电的新型偏微分方程系统，并结合这些数值技术和模型，为患者特定的心脏功能模拟提供预测工具。它涉及嵌入式网格时空变分离散化的设计和数学分析、数值积分的 4D 计算几何算法和多级求解器。通过将科学计算和机器学习相结合，这项研究的预期成果之一是新一代非线性 PDE 近似和求解器。