Modern metals processing: transfer of knowledge and core skills to new and emerging technologies

金属制造业的创造力和创新对于保持英国金属行业的竞争力至关重要。这既适用于当前的生产方法，如轧制，锻造等，也适用于新兴的颠覆性技术，如成形金属沉积。在过去的十年中，IMMPETUS（谢菲尔德大学微观结构和机械工艺工程研究所）已经开发出其独特的系统驱动方法，用于最新金属工艺路线的工艺和性能优化，并在国内/国际舞台上取得了重大成功。预测微观结构和性能的理想方法是使用由明确定义的物理方程驱动的多尺度建模。然而，即使在这个过程已经建立并被认为是很好理解的地方，现实情况是，在这种多尺度模型中存在不可避免的不确定性，因此大多数模型都不是真正基于物理的。相反，它们依赖于允许模型拟合数据的经验参数。此外，在过程不成熟的情况下，就像我们打算调查的项目一样，在实验完全建立机制之前，无法准确描述基本物理学，这可能会被证明是耗时的。为了涵盖基于物理的模型不能充分和完全描述的棘手因素，并快速跟踪新兴的非传统金属制造技术的发展，我们使用混合模型，将离散数据与基于知识和基于物理的模型合并（融合），以考虑材料加工路线中的不确定性。这是一种强大的方法，即使在数据稀疏、知识不精确但更新频繁的情况下，也能准确、透明地预测过程行为。所有的建模都是通过使用一系列令人印象深刻但又吝啬的实验技术来获得信息和验证的。我们认为，现在正是将这种战略应用于新的令人兴奋的技术的时候，因为这些技术的研究不可避免地具有高风险、高冒险性和高影响力。具体来说，我们打算建立一种新的方法来建模的摩擦搅拌和线性摩擦焊接的钢和钛合金使用我们独特的任意应变路径和热机械压缩机和访问完全仪表化的摩擦焊接机的组合。此外，我们还将利用我们的技术进行创新金属加工，直接使用最先进的设备，例如成形金属沉积。贯穿所有这些过程的是，最终的微观结构是通过在动态条件下的转变形成的，其中存在陡峭的热梯度、有意/无意的应力和塑性应变速率，对于这些，当前的相变模型不能充分预测微观结构。对于所有这些领域，留住在跨学科综合研究方面有良好记录的高技能人员至关重要。

Creativity and innovation in metal manufacturing is crucial for maintaining a competitive UK based metals industry. This applies to both current production methodologies such as rolling, forging etc and emerging disruptive technologies such as shaped metal deposition. Over the last ten years IMMPETUS (Institute for Microstructural and Mechanical Process Engineering: The University of Sheffield) has developed its unique systems driven approach for process and property optimisation for the latest metals process routes with significant success on the national/international stages. The ideal for predicting microstructure and properties is to use multi-scale modelling driven by well defined physically based equations. However, even where the process is well established and thought to be well understood, the reality is that there are inevitable uncertainties within such multi-scale models, and consequently most are not truly physically-based. Rather they rely on empirical parameters that allow the models to fit the data. Moreover, where the process is immature, as is the case with the projects we intend to investigate, the basic physics cannot be described accurately until the mechanisms are fully established experimentally, which can prove time-consuming. In order to cover the intractable factors not adequately and entirely described by physically based models, and to fast track the development of emerging non-traditional metal manufacturing technologies, we use hybrid models that merge (fuse) discrete data with knowledge-based and physically-based models to account for the uncertainties in the material processing route. This is a powerful approach for accurate and transparent process behaviour prediction even when data is sparse, knowledge is imprecise, but updated more often than not. All the modelling is informed and verified through the use of an impressive but parsimonious array of experimental techniques. We believe it is timely to apply such a strategy to new exciting technologies where the research is inevitably high risk, high adventure and certainly high impact. Specifically, we intend establish a novel approach to the modelling of friction stir and linear friction welding of steels and titanium alloys using a combination of our unique arbitrary strain path and thermomechanical compression machines and access to fully instrumented friction welding machines. In addition, we will bring our skills to bear on innovative metals processing with direct access to state-of-the-art equipment for e.g. shaped metal deposition. Pervasive to all of these processes is that the final microstructure is formed through transformation under dynamic conditions, with the presence of steep thermal gradients, intentional/unintentional stresses and plastic strain rates for which the current phase transformation models do not adequately predict microstructure. For all these areas, it is essential to retain highly skilled staff who have a proven track record in interdisciplinary integrated research.