权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Dislocation patterns beyond optimality

超出最优的位错模式

基本信息

批准号：
EP/N035631/1
负责人：
Lucia Scardia
金额：
$ 12.19万
依托单位：
University of Bath
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FN035631%2F1
关键词：
Dislocation patterns beyond optimality

项目摘要

Metals, and steel in particular, play a fundamental role in our everyday life and are used in countless applications, from the construction industry to transport, energy, packaging, and house appliances. Different applications, however, require different material properties of the metals, which need to be designed to meet the requirements. Materials design in its turn requires a deep understanding of the dependence of the mechanical behaviour of the metal on its chemical composition and microstructure. This is not possible without a good understanding of dislocations.Dislocations are defects in the atomic structure of metals which collectively, at the macroscopic scale, determine how metals deform. For this reason, any macroscopic model that aims for a predictive power has to take into account the presence of these defects. However, since the typical number of dislocations in even a small sample of metal is very high, formulating a model that keeps track of every single dislocation is unfeasible except for very small-scale problems. Although good models for dislocations are available at the level of the atomic lattice, it is not yet well-understood how to incorporate the effect of their presence and motion in a model at the macroscopic, engineering scale. This challenge has become the focus of intensive research in the last decade - in the engineering community because of the need of good macroscopic models for the development of new metals and alloys, and in the mathematical community for the central role it plays in understanding complex multiscale systems. Over the years, and in different communities, this challenge has been approached in several ways. The great advantage of a rigorous approach is that it is exact; the price to pay, however, is a strong limitation on the configurations that can be analysed. In the majority of the mathematical literature, dislocations are modelled as straight and parallel lines, while they are in fact three-dimensional curves. This assumption reduces the complexity of the theory enormously, although the mathematical challenges in this idealised setting are still countless. A special configuration that has received great attention in recent years is that of vertically periodic dislocation walls, similar to low-angle grain boundaries. One of the reasons why they are so popular is the general belief that they represent minimum energy arrangements for dislocations. The proposed research poses a more fundamental question: what are the energetically favourable configurations of dislocations? And, also, how do low-energy dislocation structures vary when a small but non-zero temperature is introduced in the model?Low-energy dislocation structures (LEDS) like walls, clusters and cells are one of the main features of the microstructure in metals. These high-density configurations increase the resistance of the material against plastic slip, thus leading to a stronger material. Characterising and hence exploiting and optimising LEDS is a key step in materials design: it would allow designers to construct lightweight structures which nevertheless have a high resistance to deformation, resulting, e.g., in safer and more fuel-efficient cars. Therefore, every advance in our research is relevant to mechanical engineering and industry.The research in this project however goes beyond the specific example of defects in metals. Dislocations are a paradigmatic example of a complex particle system and the analysis developed here would be applicable to a variety of problems dealing with the derivation of the collective behaviour of a large number of individual agents, e.g., crowd and traffic dynamics, swarming, networks.

金属，特别是钢铁，在我们的日常生活中发挥着重要作用，并在无数的应用中使用，从建筑业到运输，能源，包装和家用电器。然而，不同的应用需要不同的金属材料特性，需要设计以满足要求。材料设计反过来又需要深入了解金属的机械行为对其化学成分和微观结构的依赖性。如果不对位错有很好的理解，这是不可能的。位错是金属原子结构中的缺陷，在宏观尺度上，它们共同决定了金属如何变形。因此，任何旨在预测能力的宏观模型都必须考虑这些缺陷的存在。然而，由于即使是很小的金属样品中位错的典型数量也非常高，因此除了非常小的问题之外，制定跟踪每个单个位错的模型是不可行的。虽然位错的良好模型在原子晶格的水平上是可用的，但如何在宏观的工程尺度上将它们的存在和运动的影响纳入模型中还没有很好的理解。在过去的十年里，这一挑战已经成为深入研究的焦点-在工程界，因为需要良好的宏观模型来开发新的金属和合金，在数学界，它在理解复杂的多尺度系统中发挥着核心作用。多年来，在不同的社区，人们以多种方式应对这一挑战。严格方法的最大优点是它是精确的;然而，付出的代价是对可以分析的构型的强烈限制。在大多数数学文献中，位错被建模为直线和平行线，而实际上它们是三维曲线。这个假设极大地降低了理论的复杂性，尽管在这个理想化的环境中数学上的挑战仍然是无数的。近年来受到极大关注的一种特殊构型是垂直周期性位错壁，类似于小角度晶界。它们如此受欢迎的原因之一是人们普遍认为它们代表了位错的最小能量排列。拟议中的研究提出了一个更基本的问题：位错的能量有利的配置是什么？此外，当模型中引入一个小的但非零的温度时，低能位错结构是如何变化的？低能位错结构（LEDS）是金属微观结构的主要特征之一。这些高密度配置增加了材料对塑性滑动的抵抗力，从而导致更坚固的材料。表征并因此开发和优化LED是材料设计中的关键步骤：它将允许设计师构建轻质结构，但具有高抗变形性，从而产生例如，更安全更省油的汽车。因此，我们研究的每一项进展都与机械工程和工业有关。然而，本项目的研究超出了金属缺陷的具体例子。位错是复杂粒子系统的一个典型例子，这里开发的分析将适用于处理大量个体代理的集体行为的衍生的各种问题，例如，人群和交通动态，群集，网络。