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Article Citation - WoS: 17Citation - Scopus: 24Optimization and Energy Analysis of a Novel Geothermal Heat Exchanger for Photovoltaic Panel Cooling(Pergamon-elsevier Science Ltd, 2021) Jafari, Rahim; Jafari, Rahim; Jafari, Rahim; Automotive Engineering; Automotive EngineeringElectrical energy and conversion efficiency of the photovoltaic (PV) solar panels are measured under standard test conditions in some microseconds at the room temperature (25 degrees C). It also is seen that the actual working conditions, on the other hand, with higher ambient temperature and continuous generated heat in the PV cells can lead to reduction in reduce their electricity generation and long-term sustainability. In the current work, the coolant (water + ethylene glycol) circulates between two heat exchangers; the minichannel heat exchanger is bounded to the PV cells and geothermal heat exchanger is buried underground, and it is set to remove the heat from PV cells to the ground. Six control factors of the geothermal cooling system are considered for the purpose of optimization using Taguchi design and main effect analysis. These parameters are pipe length, soil thermal conductivity, coolant flow rate, adjacent coil distance, pipe inner diameter and pipe thickness. The experimental results show that the average net electricity generation of the cooled PV panel is improved 9.8% compared to the PV panel without cooling system. However, with the same geothermal heat exchanger it drops to 6.2% as the cooled panel number is doubled. The simulation results reveal that the optimum configuration of the geothermal cooling system is capable of enhancing the net electricity generation of the twin cooled panels up to 11.6%. The LCOE of the optimized geothermal cooling system was calculated 0.089 euro/kWh versus the reference panel of 0.102 euro/kWh for the case study of 30 kW PV solar plant.Article Citation - WoS: 89Citation - Scopus: 99Optimization of Electric Vehicle Recharge Schedule and Routing Problem With Time Windows and Partial Recharge: a Comparative Study for an Urban Logistics Fleet(Elsevier, 2021) Bac, Ugur; Baç, Uğur; Erdem, Mehmet; Erdem, Mehmet; Baç, Uğur; Erdem, Mehmet; Industrial Engineering; Industrial EngineeringThe use of electric vehicles (EVs) is becoming more and more widespread and the interest in these vehicles is increasing each day. EVs promise to emit less air pollution and greenhouse gas (GHG) emissions with lower operational costs when compared to fossil fuel-powered vehicles. However, many factors such as the limited mileage of these vehicles, long recharging times, and the sparseness of available recharging stations adversely affect the preferability of EVs in industrial and commercial logistics. Effective planning of EV routes and recharge schedules is vital for the future of the logistics sector. This paper proposes an electric vehicle routing problem with the time windows (EVRPTW) framework, which is an extension of the well-known vehicle routing problem (VRP). In the proposed model, partial recharging is considered for the EVRPTW with the multiple depots and heterogeneous EV fleet and multiple visits to customers. While routing a set of heterogeneous EVs, their limited ranges, interdependent on the battery capacity, should be taken into consideration and all the customers' deliveries should be completed within the predetermined time windows. To deal with this problem, a series of neighbourhood operators are developed for the local search process in the variable neighbourhood search (VNS) and variable neighbourhood descent (VND) heuristics. The proposed solution algorithms are tested in large-scale instances. Results indicate that the proposed heuristics perform well as to this problem in terms of optimizing recharging times, idle waiting times, overtime of operators, compliance with time windows, number of vehicles, depots, and charging stations used.Article Citation - WoS: 32Citation - Scopus: 39Backhaul-Aware Optimization of Uav Base Station Location and Bandwidth Allocation for Profit Maximization(Ieee-inst Electrical Electronics Engineers inc, 2020) Cicek, Cihan Tugrul; Gultekin, Hakan; Tavli, Bulent; Yanikomeroglu, HalimUnmanned Aerial Vehicle Base Stations (UAV-BSs) are envisioned to be an integral component of the next generation Wireless Communications Networks (WCNs) with a potential to create opportunities for enhancing the capacity of the network by dynamically moving the supply towards the demand while facilitating the services that cannot be provided via other means efficiently. A significant drawback of the state-of-the-art have been designing a WCN in which the service-oriented performance measures (e.g., throughput) are optimized without considering different relevant decisions such as determining the location and allocating the resources, jointly. In this study, we address the UAV-BS location and bandwidth allocation problems together to optimize the total network profit. In particular, a Mixed-Integer Non-Linear Programming (MINLP) formulation is developed, in which the location of a single UAV-BS and bandwidth allocations to users are jointly determined. The objective is to maximize the total profit without exceeding the backhaul and access capacities. The profit gained from a specific user is assumed to be a piecewise-linear function of the provided data rate level, where higher data rate levels would yield higher profit. Due to high complexity of the MINLP, we propose an efficient heuristic algorithm with lower computational complexity. We show that, when the UAV-BS location is determined, the resource allocation problem can be reduced to a Multidimensional Binary Knapsack Problem (MBKP), which can be solved in pseudo-polynomial time. To exploit this structure, the optimal bandwidth allocations are determined by solving several MBKPs in a search algorithm. We test the performance of our algorithm with two heuristics and with the MINLP model solved by a commercial solver. Our numerical results show that the proposed algorithm outperforms the alternative solution approaches and would be a promising tool to improve the total network profit.Article Citation - WoS: 24Activity Uncrashing Heuristic With Noncritical Activity Rescheduling Method for the Discrete Time-Cost Trade-Off Problem(Asce-amer Soc Civil Engineers, 2020) Sonmez, Rifat; Aminbakhsh, Saman; Atan, TankutDespite intensive research efforts that have been devoted to discrete time-cost optimization of construction projects, the current methods have very limited capabilities for solving the problem for real-life-sized projects. This study presents a new activity uncrashing heuristic with noncritical activity rescheduling method to narrow the gap between the research and practice for time-cost optimization. The uncrashing heuristic searches for new solutions by uncrashing the critical activities with the highest cost-slope. This novel feature of the proposed heuristic enables identification and elimination of the dominated solutions during the search procedure. Hence, the heuristic can determine new high-quality solutions based on the nondominated solutions. Furthermore, the proposed noncritical activity rescheduling method of the heuristic decreases the amount of scheduling calculations, and high-quality solutions are achieved within a short CPU time. Results of the computational experiments reveal that the new heuristic outperforms state-of-the-art methods significantly for large-scale single-objective cost minimization and Pareto front optimization problems. Hence, the primary contribution of the paper is a new heuristic method that can successfully achieve high-quality solutions for large-scale discrete time-cost optimization problems.Article Citation - WoS: 24Citation - Scopus: 34Optimization and Thermal Analysis of Radial Ventilated Brake Disc To Enhance the Cooling Performance(Elsevier, 2022) Jafari, Rahim; Akyuz, RecepVentilated brake discs are preferable to automobile application because of their higher heat dissipation ability than solid discs. The shape, geometry and number of the cooling fins are interested parameters to be investigated to improve the cooling performance of the discs. In the present study, the optimum design of the brake disc with radial vanes is investigated numerically using the Taguchi design of experiments with taking into account nine design parameters. Finite element method is employed to simulate the detailed airflow and temperature distribution in the disc considering adjoined components as pads, rim, tire and dust shield. It has been found that the ventilation gap width has the highest impact on the brake disc cooling. The cooling time of the disc decreases 21% as the ventilation gap increases from 8 mm to 14 mm. In addition, it reduces about 10% with the increment of the channel width between two adjacent vanes (inverse of vane numbers from 43 to 30) and the twist point from 225 mm to 266 mm. In a decreasing order of importance, fin angle, inner and outer diameters of fin, dust shield, bell link and disc material affect the cooling performance of the ventilated disc.Article Citation - WoS: 25Citation - Scopus: 29Optimum Design of Steel Braced Frames Considering Dynamic Soil-Structure Interaction(Springer, 2019) Bybordiani, Milad; Azad, Saeid KazemzadehRecent studies on design optimization of steel frames considering soil-structure interaction have focused on static loading scenarios, and limited work has been conducted to address the design optimization under dynamic soil-structure interaction. In the present work, first, a platform is developed to perform optimization of steel frames under seismic loading considering dynamic soil-structure interaction (SSI) in order to quantify the effects of earthquake records on the optimum design. Next, verification of the adopted modeling technique is conducted using comparison of the results with the reference solution counterparts in frequency domain. For time history analyses, records from past events are selected and scaled to a target spectrum using simple scaling approach as well as spectrum matching technique. For sizing of the steel frames, a recently developed metaheuristic optimization algorithm, namely exponential big bang-big crunch optimization method, is employed. To alleviate the computational burden of the optimization process, the metaheuristic algorithm is integrated with the so-called upper bound strategy. Effects of factors such as the building height, presence of soil domain, and the utilized ground motion scaling technique are investigated and discussed. The numerical results obtained based on 5- and 10-story steel braced frame dual systems reveal that, although dynamic SSI reduced the seismic demands to some extent, given the final design pertains to different load combinations, the optimum weight difference is not considerable.Article Citation - WoS: 2A Generic, Multi-Period and Multi-Partner Cost Optimizing Model for Cloud-Based Supply Chain(Igi Global, 2016) Akyuz, Goknur Arzu; Rehan, MohammadCloud technology in a multi-enterprise, collaborative context is one of the most promising topics at IT-Supply Chain (SC) intersection. Cloud comes with well-proven advantages and cost savings; enabling collaboration and business intelligence. Cloud transition is still on-going with individual enterprise-level transitions. However, collaborative paradigm dictates that entire network well-being is to be considered over enterprise-level concerns. Thus, handling the transition of a single enterprise is not sufficient for strategic network leverage. Planning and managing across multiple enterprises is required, taking into consideration various cost items and budget constraints. In this study, a multi-period multi-partner cost-optimizing model is developed for network-level management of cloud transition for a SC. The model produces an optimal transition plan, indicating timing of the transition for each partner to obtain the maximum cost savings across network over a specified planning horizon. The model proposed is generic, flexible and customizable for different sectors/settings.
