Ultrascalable Modelling of Advanced Materials with Complex Architectures

发电和运输系统的技术进步目前受到材料的限制。理想的材料无法用于这些新型设计所需的日益极端的环境（高温、高热通量、压力、辐射损伤、疲劳等）。目前对这些问题提出的许多解决方案都是复合材料。然而，在这方面，将具有不同组成材料性质的两个或多个物理上不同的相结合形成单一材料充满了制造和建模困难，基于组成材料的性质和微观结构形态可靠地预测复合材料的体积性质是相当感兴趣的，因为这显然能够使新材料设计具有特定的要求（例如韧性、刚度）。再加上快速成型和对复合材料制造过程的更大控制，这可能会带来新一代的高性能材料。高分辨率三维成像，如X射线显微断层扫描（XMT），材料科学相当于医学CAT扫描，现在可以在亚微米尺度上进行探测，并与数值求解器相结合，原则上可以为物理过程建模提供交钥匙解决方案。然而，采用基于图像的分析存在两个主要的技术障碍：（1）稳健且准确地将3D数据转换成适合于求解器的计算网格;以及（2）以合适的分辨率和尺寸研究域所需的计算问题的尺寸，以将微观长度尺度与宏观长度尺度桥接，使得建模的体积代表材料的大部分。这两个问题都将在项目中通过结合和进一步发展申请人开发的用于解决大规模问题的最新技术来解决（新的迭代求解器）和用于从3-D图像网格化。为了为待开发和实施的求解技术提供确证，将考虑两个问题：陶瓷基质复合材料和开孔泡沫，其中一些申请人具有这两个问题的经验，并且这两个问题代表了非常广泛的工业和生物学上重要的结构。将探讨结构和热性能。这些材料是范例，因为它们代表了计算方法的两个不同挑战：复合材料具有多相复杂结构;泡沫经历非常大的应变变形，然后是元件接触和应变局部化。这个雄心勃勃的项目解决了三个密切相关的问题，这些问题需要团队内部的技能相结合，其解决方案将在计算和材料工程中产生深远的应用，即：预测具有复杂结构的材料的行为;大应变和接触问题的并行模拟;以及可变形介质重新网格化的有效算法。

Technological advances in power generation and transport systems are currently materials limited. Ideal materials are not available for use in the increasingly extreme environments (high temperatures, high thermal fluxes, pressures, irradiation damage, fatigue etc) these novel designs require. Many of the current suggested solutions to these problems are composites. However, the combination of two or more physically distinct phases with different constituent material properties to form a single material is fraught with fabrication and modelling difficulties.There is considerable interest in the reliable prediction of the bulk properties of composite materials based on the properties of the constituent materials and the microstructural morphology as this clearly enables novel materials to be designed with specified requirements (e.g. toughness, stiffness). Coupled with rapid prototyping and greater control of composite fabrication processes, this could deliver a new generation of high performance materials. High resolution imaging in 3-D such as x-ray microtomography (XMT), the materials science equivalent of medical CAT scans, can now probe at the sub-micron scale and coupled with numerical solvers could in principle provide turnkey solutions for modelling physical processes. However there are two main technical hurdles to the adoption of image based analysis: (1) robustly and accurately converting the 3-D data into computational meshes suitable for solvers; and (2) the size of computational problem required to study domains at suitable resolutions and size to bridge the micro to macro length scales such that the volumes modelled are representative of the bulk of the material. Both of these problems will be addressed within the project by combining and further developing state of the art techniques developed by the applicants for solving large scale problems (novel iterative solvers) and for meshing from 3-D images.In order to provide corroboration for the solution techniques to be developed and implemented, two problems with which some of the applicants have experience and which typify a very broad range of industrially and biologically important structures will be considered: ceramic matrix composites and open-celled foams. Both structural and thermal properties will be explored. These materials are exemplars as they represent two different challenges to the computational approach: the composite has a multiphase complex architecture; the foam undergoes very large strain deformation followed by element contact and strain localisation. These challenges are common to a wide range of materials.This ambitious project addresses three intimately linked problems that require the combination of skills contained within the team whose solutions will have far reaching application in computing, and materials engineering, namely: predicting behaviour of materials with complex architectures; parallel simulation of problems with large strains and contacts; and efficient algorithms for remeshing deformable media.