High Fidelity Computational Nuclear Engineering

该项目将侧重于结合计算多学科方法，以获得一系列通用核系统的解决方案，如燃料流体流后处理，混合沉降器和液-液萃取塔，这些系统在工业中遇到退役和废物管理问题。鉴于这种数值解的基本性质，还将分析从中获得的信息，以提供对一系列实际相关系统的更好理解，在设计改进的治疗方法时具有价值。主要目的是扩展基于多学科模拟的预测模型，以包括优化方法，如实验设计和替代建模技术，该项目的成果将是一系列替代模型，这些模型有助于提供对此类系统的基本理解，并可用于验证工业中使用的预测方法。特别是后者，为那些使用简化预测技术的人提供了加强质量保证和技术卓越证书的机会，因为他们参与了一项计划，消除了由于建模中应用的必要近似而导致的错误。

The project will focus on combining computational multi-disciplinary approaches to obtain solutions to a range of generic nuclear systems such as fuel fluid flow reprocessing, mixer settler and liquid-liquid extraction columns encountered in the industry for decommissioning and waste management. Given the fundamental nature of such numerical solutions, the information derived from them will also be analysed to provide improved understanding of a range of practically relevant systems, of value in the design of improved treatment methods.The key aim is to extend a predictive model, based on multi-disciplinary simulations, to include optimisation approaches such design of experiment and surrogate modelling techniques, capable of predicting the types of thermal fluid flow systems encountered in nuclear.The outcomes of the project will be a series of surrogate models which are useful in providing fundamental understanding of such systems, as well as being available for use in the validation of the predictive approaches used within the industry. The latter, in particular, gives those using simplified predictive techniques the opportunity to reinforce their quality assurance and technical excellence credentials by getting involved in an initiative that removes the potential for error due to the necessary approximations applied in modelling.