High Fidelity Numerical Simulation of Flow, Heat-Transfer and Combustion in Energy Related Fluid Mechanics
||High Fidelity Numerical Simulation of Flow, Heat-Transfer and Combustion in Energy Related Fluid Mechanics|
||SNIC Medium Storage|
||Christer Fureby <email@example.com>|
||2023-01-01 – 2024-01-01|
||20304 20306 20399|
This proposal concerns high performance computing of fluid mechanics and heat transfer related to energy conversion. This means addressing several fundamental modelling issues such as thermofluid flows, multi-phase flow, combustion, thermal radiation and fluid-structure interaction. One or more of these issues come into the energy conversion related applications addressed in this proposal: Heat exchangers, aero engines and wind turbines. Some issues are also important for other industrial sectors such as food industry. High fidelity fluid dynamics simulations require that turbulence is modelled and treated in a proper way, meaning that either large eddy simulation or direct numerical simulation would be required. In turn this means that proper resolution of the flow scales is of the essence, which lead to large computational meshes and long computational times. The data from these simulations are analysed by a variety of techniques ranging for more straight forward ones such as 1st and 2nd moment statistics in time to more complex and resource consuming such as POD and DMD. Many of these techniques require storage (at least temporary) of simulation data well resolved in both time and space. Adding further complexity to the simulations, e.g. chemical reactions or thermal radiation, further increases the storage needs. With new large projects starting during 2023, such as NEUMANN and MYTHOS, and other large projects coming out of the initial phase, e.g. CESTAP and HERMES, we foresee a substantial increase in the need for computational resources as well as accompanying storage especially within the areas of combustion of biofuels. Contributing to this is also the increase in group size with two PhD-students recruited during 2022 and further recruitments planned for 2023.