Predicting scatter in the ductile to brittle transitional fracture in steels

理解导致韧脆性转变的几个相互竞争的温度依赖物理过程的复杂相互作用，以及实验数据中固有的、温度依赖的不确定性，是本提案的主要动力和主要新颖之处。将这种复杂的相互作用纳入一个快速灵活的工程裂缝预测模型是另一个新颖之处。申请人提出了一种从微观结构和流动应力预测裂缝的多尺度模型，即不依赖于实验裂缝数据。除了预测完整的转变曲线外，该模型还可以预测温度相关的散射、断裂扩展路径、裂纹止裂和断口。用该模型预测的散射水平与热控轧制（TMCR）钢的有限Charpy实验数据在定性上一致。这是通过考虑晶粒尺寸分布和引入温度相关的晶粒取向偏差阈值来实现的。与许多复杂的微观结构变形模型（如晶体塑性有限元模型（CPFEM））相比，原型多尺度断裂模型给出了与工业直接相关的预测。该方法比目前基于神经网络或模糊逻辑的分散预测模型先进得多，因此完全脱离了裂缝物理。很少有模型预测过渡数据的不确定性。然而，尽管取得了相当大的成功，但原型模型尚不适合定量预测裂缝。目前模型中的裂纹扩展速度固定为每增加一个CA单元。这种限制导致裂缝扩展缓慢，最终导致下大陆架的总能量高得不切实际。然而，主要的障碍仍然是缺乏对过渡区主要微观力学参数的温度和应变速率敏感性的了解。这一建议将推动工程科学的发展，因为只有理解和模拟不同温度和应变速率下几个相互作用的断裂过程的所有复杂性，才能正确预测散射。对于高过渡散射的物理解释仍然不够充分，这意味着我们对断裂的基本物理认识还存在空白。该项目将在开发散点预测模型的过程中填补这些空白。

Understanding the complex interaction of several competing temperature dependent physical processes resulting in the ductile to brittle transition, and of the inherent, temperature-dependent uncertainty in experimental data, is the major drive, and the major novelty, of this proposal. Inclusion of this complex interaction into a single fast and flexible engineering fracture prediction model is another novelty.The applicant has proposed a multi-scale model predicting fracture from microstructure and flow stress, i.e. not relying on experimental fracture data. In addition to predicting the full transition curve, the model was shown to predict temperature dependent scatter, fracture propagation path, crack arrest and fracture surface. The levels of scatter predicted with the model showed qualitative agreement with limited experimental Charpy data for a thermomechanically controlled rolled (TMCR) steel. This was achieved by taking the grain size distribution into account, and by introducing a temperature dependent grain mis-orientation threshold.In contrast to many complex microstructure deformation models, like e.g. crystal plasticity finite element model (CPFEM) the prototype multi-scale fracture model gives predictions of immediate relevance to industry. The proposed approach is a much more advanced that the current scatter predicting models, which are typically based on neural network or fuzzy logic, and therefore are completely divorced from the physics of fracture. Very few models predict the uncertainty of the transitional data.Despite considerable success, however, the prototype model is not yet suitable for quantitative fracture prediction. At present the crack propagation speed in the model is fixed to one CA cell per time increment. This restriction leads to slower fracture propagation, and ultimately to unrealistically high total energies at the lower shelf. However, the major obstacle remains lack of understanding of the temperature and strain rate sensitivity of the major micro-mechanical parameters in the transition area.This proposal would advance the engineering science because correct prediction of scatter is possible only if all the complexity of several interacting fracture processes at various temperatures and strain rates is understood and modelled. The fact that there is still no adequate physical explanation of high transitional scatter means that there are gaps in our understanding of fundamental physics of fracture. This project would fill these gaps on the way to developing a scatter prediction model.