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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: 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: 3Citation - Scopus: 7Optimization-Based Scheduling of Construction Projects With Generalized Precedence Relationships: a Real-Life Case Study(Sharif University of Technology, 2024) Aminbakhsha, S.; Ahmed, A.Concomitant reduction of cost and duration is recognized as one of the main aspects of construction planning. Expedition of project schedule naturally incurs extra costs due to implementation of more productive and/or high-price construction techniques. Meanwhile, a reduction in time is usually plausible only down to a certain limit, below which renders expeditions either technically or nancially unviable. Thus, striking a reasonable balance between project cost and duration remains a desirable yet challenging task for which there has been a myriad of advancements and literature. Despite the many studies associated with this problem-referred to as Time-Cost Trade-off Problem (TCTP) it is observed that only a few exercise TCTPs with the generalized logical relationships. This observation holds despite the fact that generalized precedence relationships are imperative to introduce parallelism and to secure a realistic overlap among the activities. In this regard, a Simulated Annealing-based (SA-based) Genetic Algorithm (GA) as proposed herein, is specically designed to provide the capability of exerting TCTPs with properly overlapped activities. Eciency of this algorithm is tested over a range of problems and its performance is validated over a large-scale real-case construction project. Results of the hybridized GA indicate fast and robust convergence to high-quality solutions. © 2024, Sharif University of Technology. All rights reserved.Conference Object Citation - WoS: 10Citation - Scopus: 12A Flow Stress Model for Steel in Cold Forging Process Range and the Associated Method for Parameter Identification(Springer London Ltd, 2018) Simsir, Caner; Duran, DenizDetailed thermo-mechanical characterization of DIN 16MnCr5 covering the process range of cold forging applications (0.01 s(-1) 40 s(-1), 25 A degrees C Ta 400 A degrees C) by compression tests revealed flow stress instabilities associated with dynamic strain aging (DSA) which cannot be reproduced by conventional flow stress models. As a remedy, a flow stress model capable of capturing sharp changes in flow stress, strain hardening, and strain rate sensitivity is proposed. Then, a method for parameter identification is presented which can deal with inhomogeneous deformation heating of the specimen at relatively high-strain-rate tests. The presented method involves response surface-based numerical optimization of the flawed compression tests coupled with finite element (FE) simulation. The proposed flow stress model and the extracted parameters are validated in a forward rod extrusion process without using any case-specific determined parameters in FE simulation. A natural agreement is obtained between the experimental and the predicted results in terms of both the force-displacement curve and the part geometry. The authors think that the flow stress instabilities encountered in the cold forging process range may have further consequences in other inverse analysis attempts such as friction coefficient or critical damage parameter determination and that the proper treatment of material data as put forth in this study can improve the predictive capability of process modeling.
