Heat transfer analysis of lateral perforated fin heat sinks

In this article fluid flow and conjugate conduction-convective heat transfer from a three-dimensional array of rectangular perforated fins with square windows that are arranged in lateral surface of fins are studied numerically. For investigation, Navier-Stokes equations and RNG based k - [epsilon] turbulent model are used. Finite volume procedure with SIMPLE algorithm is applied to coupled differential equations for both solid and gas phases. Computations are carried out for Reynolds numbers of 2000-5000 based on the fin thickness and Pr = 0.71. Numerical model is first validated with previous experimental studies and good agreement were observed. Based on a valid numerical model, numerical solution is made to find fluid flow and temperature distribution for various arrangements. For each type, fin efficiency of perforated fins is determined and compared with the equivalent solid fin. Results show that new perforated fins have higher total heat transfer and considerable weight reduction in comparison with solid fins.Rectangular perforated fins Turbulent flow Convection heat transfer Fin weight

An intelligent simulation platform for train traffic control under disturbance

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Railway disturbance management is inherently a multi-objective optimization problem that concerns both the operators’ cost and passenger’s service level. This study proposes a multi-objective simulation-based optimization framework to effectively manage the train conflicts after the occurrences of a disturbance caused by a temporary line blockage. The simulation model enhanced with a dynamic priority dispatching rule in order to speed up the optimization procedure. A multi-objective variable neighborhood search meta-heuristic is proposed to solve the train rescheduling model. The obtained Pareto optimal solutions for disturbance management model support the decision maker to find a trade-off between both user and operator viewpoints. The proposed approach has been validated on a set of disruption scenarios covering a large part of the Iranian rail network. The computational results prove that the proposed model can generate good-quality timetables with the minimum passenger delay and deviation from the initial timetable. The outcomes indicate that the developed simulation-based optimization approach has substantial advantages in producing practical solution quickly when compared to currently accepted solutions. Abbreviation: MOVNS: multi-objective variable neighbourhood search; DES: discrete-event simulation; SO: simulation-optimization; AG: Alternative Graph; FCFS: First Come First Served; MIP: mixed integer programming; MILP: mixed-integer linear programming; B&B: branch and bound algorithm; VND: Variable Neighborhood Descent; NSGA-II: Non-dominated Sorting Genetic Algorithm–II; CD: crowding distance; DP: dynamic priority; EDD: earliest due date first; SRTT: shortest remaining traveling time; LST: least slack time first