The talks are on:
Erica Quadarella
Ph.D. Student, supervised by Prof. Hong Im
Abstract: Formulation of a turbulence-chemistry interaction
model comprehensive of detailed chemistry description represents a
long-standing problem. A generalized Partially-Stirred Reactor (PaSR) model is
presented in this work based on the inclusion of multiple chemical times. PaSR
model divides the computational domain into reactive and non-reactive parts.
The factor defining this partition is expressed as a function of the system
characteristic chemical and mixing times. However, the estimation of these
factors, particularly the chemical one, is often oversimplified. The approach
proposed in this study seeks to include in the PaSR model the whole set of
chemical times involved in the reactive system. Besides, the concept of fine
structures, first introduced in the EDC and often adopted also in the PaSR
model to characterize the evolution of chemistry in the reactive part of the
fluid, is here abandoned in favour of direct manipulation of species production
rates. The mean source term is formulated according to the new generalized
model through a modal decomposition of the Jacobian matrix. The method is
validated a priori with DNS data of a syngas non-premixed jet flame, whose
filtered data represent the validation benchmark.
Bio: Erica is a PhD candidate in mechanical engineering under the supervision of Prof. Hong Im. She obtained her Bachelor’s at Sapienza University of Rome in 2015 and her Master’s at Politecnico of Milan in 2017, both in chemical engineering. She is currently working on soot prediction in turbulent systems and on a generalized partially stirred reactor model for turbulent combustion closure.
Juan Restrepo Cano
Ph.D. Student, supervised by Prof. Hong Im
Abstract: Multiphase flows involving complex phase change processes, as well as complex attraction-repulsion and cohesion-adhesion forces, exhibit a large spectrum of physical scales ranging from micro to macroscales, and modeling of the important physical phenomena, such as fuel cells, microfluidic reactors, novel condensation systems, novel anti-icing and self-cleaning technologies, and cryogenic carbon capture, using the continuum computational fluid dynamics (CFD) is limited. An alternative mesoscopic and kinetic-based simulation approach, the lattice Boltzmann method (LBM), bridges the micro- and macro-scales, is well suited for complex multi-physics and geometries, and is highly parallelizable, offering advantages in both simulation fidelity and computational efficiency. For these problems, it has been demonstrated that LBM can be one order of magnitude faster than conventional CFD methods.
Bio: Juan Restrepo is a Ph.D. student under the supervision of Prof. Hong Im. He obtained his M.Sc. degree in chemical engineering here at KAUST in 2019. During his M.Sc., Juan studied the puffing and micro-explosion events occurring during the droplet evaporation and pyrolysis of complex fuels and proposed a statistical approach to quantify and classify such break-up events. Currently, he is implementing a multiscale lattice-Boltzmann (LB) model for studying multiphase flows with complex vapor-liquid-solid interactions.