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Now showing 1 - 10 of 20
  • Article
    Citation - WoS: 17
    Citation - Scopus: 24
    Optimization 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 Engineering
    Electrical 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: 89
    Citation - Scopus: 99
    Optimization 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 Engineering
    The 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: 24
    Citation - Scopus: 34
    Optimization and Thermal Analysis of Radial Ventilated Brake Disc To Enhance the Cooling Performance
    (Elsevier, 2022) Jafari, Rahim; Akyuz, Recep
    Ventilated 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.
  • Doctoral Thesis
    Yiyecek içecek sektörü için çok ürünlü, çok aşamalı üretim planlamasına yönelik model ve karar destek sistemi önerisi
    (2016) Tirkeş, Güzin; Çelebi, Neşe; Koyuncu, Murat
    Gıda ve içecek endüstrisinde; üretim planlama kararı güvenilir bir talep tahminine bağlıdır. Bu üretim alanlarında -özellikle hammaddelerin bozulabilir olduğu düşünüldüğünde- taleplerin zamanlamasını tahmin etmek; üretimi planlamak ve müşteri gereksinimlerini karşılamak için çok önemlidir. Literatürde gıda ve içecek endüstrisinde talep tahmini yapmak için, otoregresif hareketli ortalama (ARMA), otoregresif entegre hareketli ortalama (ARIMA), doğrusal olmayan ARMA modelleri, Holt-Winters metodları, yapay sinir ağları (ANN), genetik algoritmalar gibi çeşitli istatistiksel modellerin denendiği görülmektedir. Yapılacak tahminler için kullanılacak model verilerin karakteristiğine -'eğilim' veya 'mevsimsellik' özelliklerine- bağlıdır. Bu çalışmada 'gerçel zamanlı, çok aşamalı ve çok hatlı' bir üretim sürdürürken, hem toptan hem de perakende satış yapan bir reçel-şerbet üretim tesisi ele alınmaktadır. Tesisin; kapasite sınırlamaları ve taleplerin belirsizliği gibi sorunların varlığında oluşan üretim zamanlaması problemini çözebilmek için 'zaman serileri analizi' temelli bir talep tahmini yaklaşım modeli kurulmuştur ve bu çalışmada bu model tanıtılmaktadır. Uzun dönem talep tahmini için kullanılan 'zaman serileri modeli işletmenin iki yıllık satış verilerinden elde edilen aylık satış bilgilerinden oluşturulmuştur. Modelde Holt ve Winters'ın üçlü üstel düzleştirme ve mevsimsel düzeltme metotları kullanılarak 2015 yılı için talep tahmini yapılmıştır. Uygulama, gıda ve içecek sektöründe mevsimsel belirsizlikleri ele alabilen ilk çalışmalardan biridir. Modelin tutarlılığında hata ölçütü olarak ortalama mutlak yüzdesel hata (MAPE) kriteri ele alınmıştır. Talep tahmin modelini kurduktan sonra, envanter planlama modülünü de içeren, üretim planlama ve zamanlama modeli olarak karışık tam sayılı programlama modeli kullanılmıştır. Geliştirilen modelin 'belirsizlik' içeren durumlara da kolaylıkla uyum gösterebilir olması, modeli hem şu anki problemin çözümü hem de gelecekteki çalışmalar için en uygun seçenek kılmaktadır. Çalışmanın son kısmında, uç noktalara varan değişken taleplerin olduğu durumlarda kullanıcılara yardımcı olabilecek bir karar destek sistemi önerilmiştir.
  • Article
    Citation - WoS: 15
    Citation - Scopus: 17
    Performance Evaluation of Laser Induced Breakdown Spectroscopy in the Measurement of Liquid and Solid Samples
    (Pergamon-elsevier Science Ltd, 2018) Bilge, Gonca; Sezer, Banu; Boyaci, Ismail Hakki; Eseller, Kemal Efe; Berberoglu, Halil
    Liquid analysis by using LIBS is a complicated process due to difficulties encountered during the collection of light and formation of plasma in liquid. To avoid these, some applications are performed such as aerosol formation and transforming liquid into solid state. However, performance of LIBS in liquid samples still remains a challenging issue. In this study, performance evaluation of LIBS and parameter optimizations in liquid and solid phase samples were performed. For this purpose,milk was chosen as model sample; milk powder was used as solid sample, and milk was used as liquid sample in the experiments. Different experimental setups have been constructed for each sampling technique, and optimizations were performed to determine suitable parameters such as delay time, laser energy, repetition rate and speed of rotary table for solid sampling technique,and flow rate of carrier gas for liquid sampling technique. Target element was determined as Ca, which is a critically important element in milk for determining its nutritional value and Ca addition. In optimum parameters, limit of detection (LOD), limit of quantification (LOQ) and relative standard deviation (RSD) values were calculated as 0.11%, 0.36% and 8.29% respectively for milk powders samples; while LOD, LOQ and RSD values were calculated as 0.24%, 0.81%, and 10.93% respectively for milk samples. It can be said that LIBS is an applicable method in both liquid and solid samples with suitable systems and parameters. However, liquid analysis requires much more developed systems for more accurate results. (C) 2018 Elsevier B.V.All rights reserved.
  • Article
    Citation - WoS: 32
    Citation - Scopus: 39
    Backhaul-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, Halim
    Unmanned 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: 9
    Citation - Scopus: 12
    The Behavior of Warm Standby Components With Respect To a Coherent System
    (Elsevier Science Bv, 2011) Eryilmaz, Serkan
    This paper is concerned with a coherent system consisting of active components and equipped with warm standby components. In particular, we study the random quantity which denotes the number of surviving warm standby components at the time of system failure. We represent the distribution of the corresponding random variable in terms of system signature and discuss its potential utilization with a certain optimization problem. (C) 2011 Elsevier B.V. All rights reserved.
  • Master Thesis
    Genel Öncüllük İlişkili Zaman-maliyet Ödünleşim Problemi için Genetik Algoritma Tabanlı Optimizasyon Yöntemi
    (2020) Ahmed, Ary Hama Faraj Ahmed; Amınbakhsh, Saman
    Bir projenin süresinin kısaltılarak toplam maliyetin düşürülmesi, bir inşaat projesinin ana hedeflerinden biri olarak düşünülebilir. Daha verimli inşaat tekniklerinin kullanılarak ve inşaat projesini hızlandırarak süre kısaltılabilir. Ek ve / veya daha verimli kaynakların tahsis edilmesiyle süre kısaltılması sağlanabilir. Bununla birlikte proje takviminin hızı, yüksek fiyatlı inşaat tekniklerinin uygulanması nedeniyle, ekstra maliyete neden olacaktır. Ayrıca, zamanın kısaltılması belli bir süreye kadar makul olabilir. Toplam maliyet ve projelerin süresi arasındaki bu denge, işin doğası gereği son derece zorlayıcıyı olup, henüz bununla başa çıkabilecek özelliklere sahip bir planlama yazılım paketi bulunmamaktadır. Bu işlevsellik eksikliği, zaman ve maliyetin çatışan hedefleri arasında bir denge sağlamak için çeşitli araştırmacıları sayısız optimizasyon algoritmasının geliştirilmesine teşvik etmiştir. Büyük bir çabaya rağmen, literatürün büyük çoğunluğu, pratikte sıklıkla dahil edilen çeşitli ilişkilerini göz ardı eder. Bu tezde, inşaat bağlamında zaman-maliyet ödünleşim problemi (TCTP) olarak adlandırılan bu optimizasyon probleminin çözümü için Simüle Tavlama Bazlı Genetik Algoritma önerilmiştir. Önerilen hibrit GA, bulunan çözümlerin kalitesinden ödün vermeden hızlı çözüm sağlayacak şekilde tasarlanmıştır. Önerilen optimizasyon yöntemi TCTP'leri gerçekçi örtüşen aktiviteler ve genel bağımlılık ilişkileriyle çözme yeteneğine sahiptir. Burada önerilen hibrid GA'nın performansı, çokça ve sık kullanılan problemler üzerinde test edilir ve sonuçlar, mevcut çeşitli yöntemlerle karşılaştırılır. Bu algoritmanın pratikliği, modeli büyük ölçekli gerçek durum inşaat projesine oturtarak da doğrulanır. Doğrulamanın bir sonucu olarak, önerilen algoritmanın faydası şudur: hem müşterinin hem de müteahhitin bütçeyi aşmadan projeyi hızlandırmada bu algoritmanın nasıl yardımcı olabileceğini vurgulamaktadır.
  • Article
    Citation - WoS: 25
    Citation - Scopus: 29
    Optimum Design of Steel Braced Frames Considering Dynamic Soil-Structure Interaction
    (Springer, 2019) Bybordiani, Milad; Azad, Saeid Kazemzadeh
    Recent 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: 7
    Citation - Scopus: 12
    Genetic Algorithm and Tabu Search Memory With Course Sandwiching (gats_cs) for University Examination Timetabling
    (Tech Science Press, 2020) Abayomi-Alli, A.; Misra, S.; Fernandez-Sanz, L.; Abayomi-Alli, O.; Edun, A. R.
    University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as tine and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed fora lame public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first and second semesters, respectively. It also automatically sandwiched (scheduled) multiple examinations into single halls with a simulation time in the range of 20-29.5 seconds. The GAT_CS outperformed previous related works on the same timetable dataset. It could, however, be improved to reduce clashes, duplications, multiple examinations and to accommodate more system-defined constraints.