Microscopic in-situ displacement/strain fields measurements with Digital Image Correlation

在高科技行业，如航空航天和电力行业，高效的设计工具与材料性能本身对于触发创新同样重要。这些行业的周期是这样的，新的设计在生产之前只能测试有限的次数。因此，工程师依靠过于保守的安全系数来确保他们的设计在第一次尝试时就符合认证要求。这些安全或无知的因素被用来弥补目前使用的预测模型中知识和准确性的缺乏。这种缺乏性能的原因是，大多数预测模型依赖于宏观变量，如应力和应变，而故障是一个多尺度过程，起源于纳米尺度，并通过尺度的层次结构传播到失败。我们认为，与其通过简单的模型来回避它，不如通过在每一个相关的长度尺度上理解、量化、预测和联系材料失效的各种机制来拥抱材料失效的全部复杂性。这是由该应用程序支持的非常雄心勃勃的研究计划。

In high technology industries, like aerospace and power industries, efficient designs tools are as important as the materials performance themselves for triggering innovations. These industries cycles are such that new designs can only be tested a limited number of times before being produced. Therefore, engineers rely on over-conservative safety factors to ensure that their designs meet the certification requirements in the first attempt. These safety, or ignorance, factors are used to compensate the lack of knowledge and accuracy in the predictive models currently used. This lack of performance results from the fact that most predictive models rely on macroscopic quantities, like stresses and strains, whereas failure is a multiscale process that originates at the nanoscopic scale and propagates through the hierarchy of scales up to failure. We believe that rather than eluding it through simple models, we must embrace the full complexity of materials failure by understanding, quantifying, predicting and linking its various mechanisms, at every relevant length scale. This is the very ambitious research program to be supported by this application.