Effect of Gap Length and Partition Thickness on Thermal Boundary Layer in Thermal Convection.

Two-dimensional direct numerical simulations of partitioned thermal convection are performed using the thermal lattice Boltzmann method for the Rayleigh number () of 10 and the Prandtl number () of 7.02 (water). The influence of the partition walls on the thermal boundary layer is mainly focused on.

Simulation of Cardiac Flow under the Septal Defect Based on Lattice Boltzmann Method.

In this paper, the lattice Boltzmann method was used to simulate the cardiac flow in children with aseptal defect. The inner wall model of the heart was reconstructed from 210 computed tomography scans. By simulating and comparing the cardiac flow field, the pressure field, the blood oxygen content, and the distribution of entropy generation before and after an operation, the effects of septal defect on pulmonary hypertension(PH), cyanosis, and heart load were analyzed in detail.

Small-scale fluctuation and scaling law of mixing in three-dimensional rotating turbulent Rayleigh-Taylor instability.

The effect of rotation on small-scale characteristics and scaling law in the mixing zone of the three-dimensional turbulent Rayleigh-Taylor instability (RTI) is investigated by the lattice Boltzmann method at small Atwood number. The mixing zone width h(t), the root mean square of small scale fluctuation, the spectra, and the structure functions are obtained to analyze the rotating effect. We mainly focus on the process of the development of plumes and discuss the physical mechanism in the mixing zone in rotating and nonrotating systems.

PINE: Universal Deep Embedding for Graph Nodes via Partial Permutation Invariant Set Functions.

Graph node embedding aims at learning a vector representation for all nodes given a graph. It is a central problem in many machine learning tasks (e.g.

Time Evolution Features of Entropy Generation Rate in Turbulent Rayleigh-Bénard Convection with Mixed Insulating and Conducting Boundary Conditions.

Time evolution features of kinetic and thermal entropy generation rates in turbulent Rayleigh-Bénard (RB) convection with mixed insulating and conducting boundary conditions at = 10 are numerically investigated using the lattice Boltzmann method. The state of flow gradually develops from laminar flow to full turbulent thermal convection motion, and further evolves from full turbulent thermal convection to dissipation flow in the process of turbulent energy transfer. It was seen that the viscous, thermal, and total entropy generation rates gradually increase in wide range of /τ < 32 with temporal evolution.

Study on Bifurcation and Dual Solutions in Natural Convection in a Horizontal Annulus with Rotating Inner Cylinder Using Thermal Immersed Boundary-Lattice Boltzmann Method.

A numerical investigation has been carried out to understand the mechanism of the rotation effect on bifurcation and dual solutions in natural convection within a horizontal annulus. A thermal immersed boundary-lattice Boltzmann method was used to resolve the annular flow domain covered by a Cartesian mesh. The Rayleigh number based on the gap width is fixed at 10.

Numerical Study on Entropy Generation in Thermal Convection with Differentially Discrete Heat Boundary Conditions.

Entropy generation in thermal convection with differentially discrete heat boundary conditions at various Rayleigh numbers () are numerically investigated using the lattice Boltzmann method. We mainly focused on the effects of and discrete heat boundary conditions on entropy generation in thermal convection according to the minimal entropy generation principle. The results showed that the presence of the discrete heat source at the bottom boundary promotes the transition to a substantial convection, and the viscous entropy generation rate () generally increases in magnitude at the central region of the channel with increasing .

Gene Regulatory Network Inference from Perturbed Time-Series Expression Data via Ordered Dynamical Expansion of Non-Steady State Actors.

The reconstruction of gene regulatory networks from gene expression data has been the subject of intense research activity. A variety of models and methods have been developed to address different aspects of this important problem. However, these techniques are narrowly focused on particular biological and experimental platforms, and require experimental data that are typically unavailable and difficult to ascertain.