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

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

现代金属加工：将知识和核心技能转移到新兴技术

基本信息

批准号：
EP/E063497/1
负责人：
W Rainforth
金额：
$ 111.05万
依托单位：
University of Sheffield
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2007
资助国家：
英国
起止时间：
2007 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FE063497%2F1
关键词：
Modern metals processing transfer knowledge

项目摘要

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.

金属制造业的创造力和创新对于保持英国金属工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，如异形金属沉积。在过去的十年里，impetus（谢菲尔德大学微结构和机械过程工程研究所）开发了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，并在国家/国际舞台上取得了重大成功。预测微观结构和性质的理想方法是使用由定义良好的基于物理的方程驱动的多尺度建模。然而，即使这个过程已经很好地建立起来并被认为很好地理解，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，因此大多数模型并不是真正基于物理的。相反，他们依赖于经验参数，使模型能够拟合数据。此外，在过程不成熟的地方，就像我们打算调查的项目一样，在实验机制完全建立之前，基本物理不能准确描述，这可能证明是耗时的。为了涵盖物理模型不能充分和完全描述的棘手因素，并快速跟踪新兴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），以解释材料加工路线中的不确定性。这是准确和透明的过程行为预测的强大方法，即使在数据稀疏，知识不精确，但经常更新的情况下也是如此。所有的建模都是通过使用令人印象深刻但吝啬的实验技术来了解和验证的。我们认为，将这种策略应用于令人兴奋的新技术是及时的，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。具体来说，我们打算建立一种新的方法来模拟钢和钛合金的搅拌摩擦和线性摩擦焊接，使用我们独特的任意应变路径和热机械压缩机的组合，并获得完全仪器化的摩擦焊接机。此外，我们将把我们的技能，承担创新的金属加工，直接获得最先进的设备，如异形金属沉积。在所有这些过程中普遍存在的是，最终的微观组织是在动态条件下通过转变形成的，存在陡峭的热梯度，有意/无意的应力和塑性应变率，目前的相变模型不能充分预测微观组织。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。