GREENCDT Robust Validation Methods for Computational Fluid Dynamics Models of Waste Flows

Establishing credibility in engineering simulations through a process of model validation is an essential part of any engineering analysis. It is well-established that validation of computational models should include a comparison of predictions from the simulation with measurements from a physical experiment or prototype that closely resembles the conditions in service, i.e. real-world, everyday circumstances. Advances in digital sensor technology allow information-rich data fields to be acquire in real-time leading to large quantities of measured data, sometimes referred to as ‘big data’, which presents challenges in making quantitative and meaningful comparisons with predictions from simulations. In solid mechanics, Patterson and his coworkers have used orthogonal decomposition to reduce the dimensionality of both measured and predicted data to feature vectors that can readily be compared. This process is becoming routine for two-dimensional fields of data and is being developed for volumes of data. In both cases, feature vectors representing measurements and predictions can be compared to establish the probability that they belong to the same population. In this project these techniques will be extended to fluid dynamics in collaboration with

Professor Rob Poole. It is expected that the outcome will be a significant advance in the rigour with which simulations based on computational fluid dynamics models can be validated through detailed comparison to measurements and that this will enable updating of simulations to increase their fidelity. Work will be carried out in collaboration with Dr. Helen Steele at Sellafield (Industrial Supervisor) and Dr. Theirry Wiss at the Institute of Transuranic (ITU) in Germany.

Applications should include a cover letter including the applicant motivation in this PhD studentship, a full CV, and the contact details of two academic referees and should be sent by email to Dr. Maulik Patel ([Email Address Removed]) indicating “PhD studentship – GREEN CDT” in the subject line.