Modelling of multi-phase flows using machine learning models for real-fluid thermodynamic closure of low-carbon fuels and viscoelastic heat-transfer enhancement fluids
Date: 2025/12/03 – 2025/12/03
Academic Seminar: Modelling of multi-phase flows using machine learning models for real-fluid thermodynamic closure of low-carbon fuels and viscoelastic heat-transfer enhancement fluids
Speaker: Professor Manolis Gavaises, City University London, UK.
Time: 10:00 – 11:00, December 3, 2025 (Beijing Time)
Location: Room 454, Long Bin Building, SJTU Global College
Abstract
Fuels in hard-to-abate transport sectors—such as maritime shipping, aviation and heavy-duty—are transitioning from conventional fossil fuels to low-carbon alternatives, including ammonia, hydrogen, biofuels, e-methanol and LNG. Increasingly, these fuels are being deployed in dual-fuel and flexible-fuel engine architectures, while maintaining reliability, improving combustion efficiency, and reducing lifecycle emissions. In parallel, the role of thermal management fluids is expanding across electrified propulsion and energy systems. Specialised heat-transfer and dielectric fluids are used for automotive battery thermal control, electric motor cooling, and the management of power electronics. These technologies further extend to other sectors, including efficient liquid-based cooling solutions for high-density electronics, data centres, aerospace avionics, and even naval embedded computing.
Modelling of such systems often requires accurate description of the physical and rheological properties of the involved fluids, over a wide range of pressure and temperature conditions and their composition. Appropriate thermodynamic closure involving accurate equations-of-state and constitutive equations in case of non-Newtonian formulations are required. Crucially, modern data-driven formulations combining high-fidelity CFD with machine-learning-based surrogate modelling and large-scale experimental datasets—enable improved prediction of multiphase flow behaviour. The presentation provides examples of relevant computational models, applied to the simulation of high-pressure fuel injectors and sprays where cavitation or flash boiling is realised, as well as heat transfer enhancement fluids. These hybrid modelling frameworks reduce computational cost while increasing accuracy, allowing rapid evaluation of design variations and operational conditions.
Biography
Prof. Gavaises obtained his PhD from Imperial College London in 1997, receiving the Richard Way Memorial Prize for the most outstanding doctoral thesis on internal combustion engines in the UK. His academic career began at City University London in 2001, with early research on electrification and NZE technologies supported by Toyota Motor Europe. He was appointed to the Delphi Technologies (UK) Research Chair in 2009 and holds honorary professorships at Sorbonne University and the University of Magdeburg, while also served as a visiting professor at EPFL (Switzerland) and the Von Karman Institute for Fluid Dynamics (Belgium). His research focuses on developing CFD tools for various multiphase flows, contributing to the design and commercialization by industry leaders of durable high pressure fuel injectors, novel additised fluids with tailored thermal and rheological properties and electrification technologies where multiphase flows play a key role.