SIMULATION

The present work provides a detailed comparative study of the hypersonic flow past spherically blunted and parabolic nose cones at a Mach number of 5.8, numerically. The main focus of the paper is to determine the geometry and parameters of the nose cones that provide minimum aerodynamic drag and heating. Studies on spherically blunted and parabolic nose cones are performed for different fineness ratios at zero angle of attack. It is observed that for fineness ratio <1.2, blunted cones provide minimum drag, whereas at higher values of fineness ratios >1.2, parabolic nose cones provide superior drag reduction. Detailed comparison of the flow/shock features in the vicinity of the blunted and parabolic nose cones for different fineness ratios is also shown in order to determine its influence on aerodynamic drag. An empirical correlation developed for the total drag coefficient based on regression analysis for a parabolic nose cone reveals that it is mainly a function of the maximum pressure coefficient and fineness ratio. In general, the present study reveals that parabolic nose cones at higher fineness ratios are preferred over spherically blunted ones for achieving higher drag reductions and lower heating in hypervelocity vehicles.

Nowadays, seaports seek to achieve a better massification (massive transportation of containers) share of their hinterland transport by promoting rail and river connections in order to more rapidly evacuate increasing container traffic shipped by sea and to avoid landside congestion. The attractiveness of a seaport to shipping enterprises depends not only on its reliability and nautical qualities but also on its massified hinterland connection capacity. Contrary to what has been observed in Europe, the massification share of Le Havre seaport has stagnated in recent years. To overcome this situation, Le Havre Port Authority is putting into service a multimodal hub terminal linked only with massified modes. In this study, we focus on rail–rail transshipment of this new terminal, specifically on minimizing unproductive situations of cranes to improve crane productivity and to speed up freight train processing. To this end, an improving agent-based engineering strategy called the “crane anti-collision strategy” is proposed and tested using multi-method simulation software (Anylogic). In a numerical study, the simulation results reveal that our developed model is very satisfactory and outperforms other existing simulation models.

The present study numerically investigates the effect of a partially covered cylindrical shield on the flow/shock oscillation characteristics of a Hartmann whistle when the pulsating jet exits through the two small openings, (a) close to the cavity inlet, and (b) away from the cavity inlet, of the cylindrical shield. The relevant parameters that modify the flow/shock oscillations of the Hartmann whistle are the stand-off distance, nozzle pressure ratio, cavity length, cavity shield, jet diameter, etc. The pulsating nature of flow in a partially shielded Hartmann whistle is investigated for various stand-off distances to understand its effect in achieving effective flow control. The velocity vectors indicate that the partly shielded Hartmann whistle operates in the jet regurgitant mode with different regurgitant phases. It also shows that some amount of the jet near the cavity inlet gets diverted towards the shield and gets attached to it, whereas some exits out through the two shield openings which can be injected into the flow to be controlled. The Mach number contours indicate the flow deceleration/reacceleration zones, shock-cell structures as well as fluid column oscillations in shock-cells/cavity regions. The present study reveals that the stand-off distance and the jet diameter are the crucial parameters, which control the oscillation mechanisms in a partially covered Hartmann whistle for achieving effective flow control. Thus, this paper sufficiently demonstrates the role of stand-off distances, openings in the shield as well as jet diameter in modifying the flow/shock oscillation characteristics of a partially shielded Hartmann whistle in achieving the finest flow control.

In this paper, we investigate the effect of emergency signs on evacuation dynamics under smoke conditions. We assume that in a smoky hall the visual field of pedestrians is limited to a certain range, and they do not know the exact location of the exit. In this kind of evacuation process, we analyze the influence of emergency signs on movement direction and speed, and the herd behavior of pedestrians. In the analysis, we divide the emergency signs into two types: the wall signs (WS) and the ground signs (GS). Then, we analyze the variation of pedestrian behavior when they encounter the WS, the GS, and the exit in the evacuation process. Combined with the analysis results, we build our improved model based on the social force model. In the simulation, we study the evacuation process in the case of WS and GS. According to the result of the simulation, we consider that the effect of the emergency signs on herd behavior and the desired speed is an important factor to improve evacuation efficiency. We find that, from the perspective of evacuation time, the evacuation in the case of WS is more efficient, but from the perspective of the interaction between pedestrians, the evacuation in the case of GS presents less security risk. Finally, we explore how to design a mixed layout scheme of WS and GS.

Oil reservoir history matching is a well-known inverse problem for predicting production by optimizing enormous unknown parameters with numerical simulation. Typically it can be formulated in a Bayesian framework with geological priors. Instead of gradient-based optimization with the possibility of converging to a local minimum, evolutionary algorithms have been introduced to globally find optimal parameters. Due to the high-dimensional parameters, the optimization could become inefficient; therefore, many dimensionality reduction algorithms have been applied in history matching. However, these methods suffer from the linear assumption or the pre-image problem, which could affect the model optimization. In this paper, based on the evolutionary algorithm termed Multi-objective Evolutionary Algorithm Based on Decomposition, which is capable of simultaneously optimizing the parameters with respect to the data of several oil wells, we propose history matching with dimensionality reduction by explicitly utilizing the nonlinear dimensionality reduction model Auto-Encoder to reduce the number of unknown parameters, which can naturally handle the pre-image problem and then improve model performance in terms of precision and complexity. Experimental results based on PUNQ-S3 data verify the efficiency of the newly proposed methods.

Time Petri nets (TPNs) have been widely used for modeling discrete event systems such as manufacturing, supply chain, and military systems. However, TPNs still have many drawbacks in some scenarios where an operation or process is associated with probability, and also lack appropriate simulation algorithms for analyzing different types of systems. In this paper, we address these two issues by proposing a class of extended time Petri nets (ETPNs) and presenting an appropriate simulation algorithm. We illustrate and validate our approach using a hypothetic command and control system, which shows that this approach could be a powerful tool for modeling and analyzing discrete event systems.