Digital twining for deformable objects – achieving real-time simulations

A step change in the simulation of the complex interactions between flexible objects and immersing fluid flows is required in the development of digital twin technologies, to enable real-time predictions by scientists and engineers for problems and applications ranging from virtual reality in the gaming and film industries, through to river adaptation and extreme weather flood mitigation.

This project is about being able to predict the interactions of complex, highly flexible, changing morphologies with fluid flow dynamics in real-time using mathematical models and numerical simulation. This is an exciting project, working at the interface between computing science and computational mechanics within NVIDIA’s Omniverse platform – the largest digital twin platform in the world.

The project will explore the development of rigorous and robust mathematical models that combine continuum mechanics with rapid particle-based algorithms to solve the resulting partial differential equations. Recognising that the target to deliver realistic simulations at real-time cannot be achieved by solving the physics-based mathematical models directly, we will use GPU and cloud-based parallel processing techniques within NVidia’s Omniverse simulation environment to create high-fidelity, highest speed, benchmark solutions. Physics-informed machine learning (PIML) will bridge the gap to real-time simulations, trained and validated using high-fidelity benchmark solutions.

This project will focus on the solid mechanics mathematical modelling and simulation component of the overall problem. You will need a strong background and interest in computational solid mechanics, either in continuum or discrete representations, combined with relevant computing science knowledge, e.g., Computer Graphics, and good programming skills (e.g., C++, Python with Pytorch/TensorFlow).

Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent.  We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.

Application enquires: 

Prof. Peter Gosling, p.d.gosling@ncl.ac.uk, https://www.ncl.ac.uk/engineering/staff/profile/petergosling.html