Group-walking effect on bidirectional pedestrian flow in a corridor

Groups are commonly found in general crowds and their behaviors are distinguished from that of isolated pedestrians. Thus, in recent five years researchers have started to investigate pedestrian group movement. In this paper, we considered group walking effect and introduced group floor field to the traditional floor field model. Furthermore, two different methods of generating group floor field were put forward, i.e. group center generation (method 1 for short) and group leader generation (method 2 for short), and we applied the proposed group model to simulate bidirectional pedestrian flow in a corridor. No matter which method of generating group floor field is adopted, the simulation results show that group members walk slower than singles, and with the group size increasing the transition point from the free flow phase to the jamming has a decrease trend. In addition, it seems that method 2 of generating group floor field makes group more cohesive and stable at the same crowd density than method 1. Afterwards it is found that the crowd with large group size is more easily affected by asymmetric injection rate. At last, people’s walking preference is shortly discussed, and it is obtained that people’s walking preference is also good for group movement from the perspective of movement efficiency.

Enhancement of cerebrovascular 4D flow MRI velocity fields using machine learning and computational fluid dynamics simulation data

Blood flow metrics obtained with four-dimensional (4D) flow phase contrast (PC) magnetic resonance imaging (MRI) can be of great value in clinical and experimental cerebrovascular analysis. However, limitations in both quantitative and qualitative analyses can result from errors inherent to PC MRI. One method that excels in creating low-error, physics-based, velocity fields is computational fluid dynamics (CFD). Augmentation of cerebral 4D flow MRI data with CFD-informed neural networks may provide a method to produce highly accurate physiological flow fields. In this preliminary study, the potential utility of such a method was demonstrated by using high resolution patient-specific CFD data to train a convolutional neural network, and then using the trained network to enhance MRI-derived velocity fields in cerebral blood vessel data sets. Through testing on simulated images, phantom data, and cerebrovascular 4D flow data from 20 patients, the trained network successfully de-noised flow images, decreased velocity error, and enhanced near-vessel-wall velocity quantification and visualization. Such image enhancement can improve experimental and clinical qualitative and quantitative cerebrovascular PC MRI analysis.

Capillary equilibrium of bubbles in porous media

In geologic, biologic, and engineering porous media, bubbles (or droplets, ganglia) emerge in the aftermath of flow, phase change, or chemical reactions, where capillary equilibrium of bubbles significantly impacts the hydraulic, transport, and reactive processes. There has previously been great progress in general understanding of capillarity in porous media, but specific investigation into bubbles is lacking. Here, we propose a conceptual model of a bubble’s capillary equilibrium associated with free energy inside a porous medium. We quantify the multistability and hysteretic behaviors of a bubble induced by multiple state variables and study the impacts of pore geometry and wettability. Surprisingly, our model provides a compact explanation of counterintuitive observations that bubble populations within porous media can be thermodynamically stable despite their large specific area by analyzing the relationship between free energy and bubble volume. This work provides a perspective for understanding dispersed fluids in porous media that is relevant to CO2 sequestration, petroleum recovery, and fuel cells, among other applications.

Numerical Study on Powder Stream Characteristics of Coaxial Laser Metal Deposition Nozzle

A 3D model was established to accurately simulate the internal and external powder stream characteristics of the coaxial discrete three-beam nozzle for laser metal deposition. A k-ε turbulence model was applied in the gas flow phase, and powder flow was coupled to the gas flow by a Euler-Lagrange approach as a discrete phase model. The simulated powder stream morphology was in good agreement with the experimental results of CCD and high-speed camera imaging. The simulation results showed that the length, diameter and shrinkage angle of the powder passage in the nozzle have different effects on the velocity and convergence characteristics of the powder stream. The influence of different particle size distribution and the inner laser shielding gas on the powder stream were also discussed in this study. By analyzing the powder stream caused by different incident directions of powder passage, and the collision process between powder and the inner wall, the basic principle of controlling powder stream convergence was obtained.

Geochronology of volcanically associated hydrocarbon charge in the pre-salt carbonates of the Namibe Basin, Angola

In volcanic rifted margins, the timing of hydrocarbon charge is difficult to predict, but is important in understanding fluid genesis. We investigated whether igneous activity was linked to hydrocarbon charge in the prolific South Atlantic pre-salt petroleum system. To do this, we applied in situ carbonate U-Pb geochronology, a relatively novel tool for dating hydrocarbon migration, to bituminous veins in pre-salt travertines from the rifted onshore Namibe Basin (Angola). To test if fluid flow was synchronous with known volcanic pulses, we also obtained new 40Ar/39Ar geochronology from a nearby volcanic complex. Bitumen is associated with calcite in a first generation of veins and vugs, and with dolomite in younger veins. The dated calcite veins yielded a pooled U-Pb age of 86.2 ± 2.4 Ma, which overlaps the volcanism 40Ar/39Ar age of 89.9 ± 1.8 Ma. The overlapping dates and the localized bitumen occurrence around the dated volcanic center show a clear genetic relationship between Late Cretaceous igneous activity and hydrocarbon charge. The dolomite was dated at 56.8 ± 4.8 Ma, revealing a previously unknown Paleocene/Eocene fluid-flow phase in the basin.

KAHN-HILLIARD MODEL FOR MIXTURES OF BINARY LIQUIDS

This article presents a model that is suitable for modeling changes in the chemical potential and the rate of attraction of phases, taking into account thermal effects, by solving the Kahn-Hilliard equation under various initial conditions. Thermal radiation is solved in the framework of the Kahn-Hilliard equation, which has been applied to many physical applications, such as two - and three-phase fluid flow, phase separation, flow visualization, and quantum dot formation. In this article, the numerical solution of the Kahn-Hilliard equation is made on a spaced grid, where the scalar values (pressure, phase function, density, viscosity) are determined in the center of the cell, and the velocity components are at a distance of half a step. Numerical research has shown that the use of a spaced grid avoids the appearance of a so-called staggered oscillating pattern for pressure. An additional advantage of using a spaced grid is that the discrete pressure field automatically satisfies the discrete representation of the integral boundary condition.