arXiv subjects

Qin Lou

Publications and source records attributed to Qin Lou.

4 recordsLinked to original sources

arXiv2024

Effects of heating strategies and ballistic transport on the transient thermal conduction in 3D FinFETs

Efficiently capturing the three-dimensional spatiotemporal distributions of temperature is of great significance for alleviating hotspot issues in 3D FinFETs. However, most previous thermal simulations mainly focused on the steady-state problem with continuous heating. Few studies are conducted for the transient thermal conduction in 3D FinFETs with non-continuous heating, which is actually closer to the reality. To investigate the effects of heating strategies on the transient micro/nano scale thermal conduction in 3D FinFETs, three heating strategies are considered, including `Continuous', `Intermittent' and `Alternating' heating. A comparison is made between the phonon BTE solutions and the data predicted by the macroscopic diffusion equation, where the effect of boundary scattering on phonon transport is added into the effective thermal conductivity. Numerical results show that it is not easy to accurately capture the heat conduction in 3D FinFETs by the macroscopic diffusion equation, especially near the hotspot areas where ballistic phonon transport dominates and the temperature diffusion is no longer valid. Different heating strategies have great influence on the peak temperature rise and transient thermal dissipation process. Compared to `Intermittent' or `Continuous' heating, the temperature variance of `Alternating' heating is smaller.

cond-mat.mes-hall↗

arXiv2024

Synthetic iterative scheme for thermal applications in hotspot systems with large temperature variance

A synthetic iterative scheme is developed for thermal applications in hotspot systems with large temperature variance. Different from previous work with linearized equilibrium state and small temperature difference assumption, the phonon equilibrium distribution shows a nonlinear relationship with temperature and mean free path changes with the spatial temperature when the temperature difference of system is large, so that the same phonon mode may suffer different transport processes in different geometric regions. In order to efficiently capture nonlinear and multiscale thermal behaviors, the Newton method is used and a macroscopic iteration is introduced for preprocessing based on the iterative solutions of the stationary phonon BTE. Macroscopic and mesoscopic physical evolution processes are connected by the heat flux, which is no longer calculated by classical Fourier's law but obtained by taking the moment of phonon distribution function. These two processes exchange information from different scales, such that the present scheme could efficiently deal with heat conduction problems from ballistic to diffusive regime. Numerical tests show that the present scheme could efficiently capture the multiscale heat conduction in hotspot systems with large temperature variances. In addition, a comparison is made between the solutions of the present scheme and effective Fourier's law by several heat dissipations problems under different sizes or selective phonon excitation. Numerical results show that compared to the classical Fourier's law, the results of the effective Fourier's law could be closer to the BTE solutions by adjusting effective coefficients. However, it is still difficult to capture some local nonlinear phenomena in complex geometries.

cond-mat.mes-hall↗

arXiv2022

Numerical study of three-dimensional single-mode Rayleigh-Taylor instability in turbulent mixing stage

Rayleigh-Taylor instability (RTI) as a multi-scale, strongly nonlinear physical phenomenon which plays an important role in the engineering applications and scientific research. In this paper, the mesoscopic lattice Boltzmann method is used to numerically study the late-time evolutional mechanism of three-dimensional (3D) single-mode RTI and the influences of extensive dimensionless Reynolds number and Atwood number on phase interfacial dynamics, spike and bubble growth are investigated in details. For a high Reynolds number, it is reported that the development of 3D single-mode RTI would undergo four different stages: linear growth stage, saturated velocity growth stage, reacceleration stage and turbulent mixing stage. A series of complex interfacial structures with large topological changes can be observed at the turbulent mixing stage, which always preserve the symmetries with respect to the middle axis at a low Atwood number, and the lines of symmetry within spike and bubble are broken as the Atwood number is increased. Five statistical methods for computing the spike and bubble growth rates are then analyzed to reveal the growth law of 3D single-mode RTI in turbulent mixing stage. It is found that the spike late-time growth rate shows an overall increase with the Atwood number, while the bubble growth rate seems to be independence of the Atwood number, approaching a constant of around 0.1. When the Reynolds number decreases, the later stages cannot be reached gradually and the evolution of phase interface presents a laminar flow state.

physics.flu-dyn↗

arXiv2020

Physics-informed neural networks for solving forward and inverse flow problems via the Boltzmann-BGK formulation

In this study, we employ physics-informed neural networks (PINNs) to solve forward and inverse problems via the Boltzmann-BGK formulation (PINN-BGK), enabling PINNs to model flows in both the continuum and rarefied regimes. In particular, the PINN-BGK is composed of three sub-networks, i.e., the first for approximating the equilibrium distribution function, the second for approximating the non-equilibrium distribution function, and the third one for encoding the Boltzmann-BGK equation as well as the corresponding boundary/initial conditions. By minimizing the residuals of the governing equations and the mismatch between the predicted and provided boundary/initial conditions, we can approximate the Boltzmann-BGK equation for both continuous and rarefied flows. For forward problems, the PINN-BGK is utilized to solve various benchmark flows given boundary/initial conditions, e.g., Kovasznay flow, Taylor-Green flow, cavity flow, and micro Couette flow for Knudsen number up to 5. For inverse problems, we focus on rarefied flows in which accurate boundary conditions are difficult to obtain. We employ the PINN-BGK to infer the flow field in the entire computational domain given a limited number of interior scattered measurements on the velocity with unknown boundary conditions. Results for the two-dimensional micro Couette and micro cavity flows with Knudsen numbers ranging from 0.1 to 10 indicate that the PINN-BGK can infer the velocity field in the entire domain with good accuracy. Finally, we also present some results on using transfer learning to accelerate the training process. Specifically, we can obtain a three-fold speedup compared to the standard training process (e.g., Adam plus L-BFGS-B) for the two-dimensional flow problems considered in our work.

physics.comp-ph↗