3D打印医学植入物的微观几何形状和性能的博士预测

拉夫堡大学在研究强度（REF2014）方面是英格兰排名前十的大学，并且有资格提交给REF的拉夫堡学术人员中有66％的杰出工作被评为“世界领先”。 €™或“国际一流”，相比之下，全国平均水平为43％。<br>项目详细信息：用于骨折修复的尖端医疗植入物是由可生物降解的聚合物制成的，因为与永久性装置不同，它们可以在几个月内被人体完全吸收，并且治愈后无需进行手术移除。3D打印技术的未来发展将很快使这种植入物能够进行3D打印，以匹配各个患者的独特骨骼形状。<br>该项目将开发新的突破性工具，以预测3D微观尺度的几何
Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough's academic staff who were eligible to be submitted to the REF was judged as ‘world-leading' or ‘internationally excellent', compared to a national average figure of 43%. In choosing Loughborough for your research, you'll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career. Find out more. Motorcycles are involved in a disproportionately high number of deaths and serious injuries on the road: even though motorcycles drove only 0.9% of the distance covered by all vehicles on British roads in 2018, they accounted for 20% of deaths and 23% of serious injuries. Although modern cars are fitted with many advanced safety technologies such as anti-lock braking systems (ABS), electronic stability control (ESP), and autonomous emergency braking (AEB), the uptake of equivalent systems for motorcycles has been much slower. For example, ABS has been mandatory on all new cars since 2004, but on motorcycles only since 2016. This project aims to investigate the potential for active stabilisation and manoeuvre assistance to mitigate motorcycle accidents through actuation of the steering and/or brakes. This will require modelling of the vehicle dynamics and design of suitable control strategies, with the goal of demonstrating via simulation that crash avoidance or mitigation is feasible in common accident scenarios. Successful candidates should have an interest in vehicle dynamics and will have the opportunity to develop sought-after skills in modelling, control and state estimation.