Yazarlar
- Can, Erol(29)
- Kumbasaroglu, Atila(17)
- Yalciner, Hakan(17)
- Bayata, Halim Ferit(14)
- Ting, Naim Suleyman(14)
- Katipoğlu, Okan Mert(13)
- Bayrak, Osman Ünsal(12)
- Sahin, Yakup(12)
- Turan, Ahmet İhsan(9)
- Baş, Fatih İrfan(8)
- Destek, Mehmet Akif(8)
- Manga, Müge(8)
- Çolak, Muhammed Ali(8)
- Bulut, H. Alperen(6)
- Manga, Muge(6)
- Tastimur, Canan(6)
- Akin, Erhan(5)
- Akoğuz, Harun(5)
- Akın, Fatih(5)
- Balli, Esra(5)
- Dede, Tayfun(5)
- Sarıgöl, Metin(5)
- Sarıçiçek, İnci(5)
- Aka, Salih(4)
- Ayasun, Saffet(4)
- Ayaz, Yaşar(4)
- Celik, Alper(4)
- Demirci, Oğuz Kürşat(4)
- Demirel, Soner(4)
- Kalkan, Orhan(4)
- Keleş, Ömer Faruk(4)
- Tortum, Ahmet(4)
- Tuysuz, Suat(4)
- Yavuz, Selahattin(4)
- Yazici, Ahmet(4)
- Yazıcı, Ahmet(4)
- Yesilyurt, Huseyin(4)
- Yılmaz, Mehmet(4)
- Çabuk, Umut Can(4)
- Özkan, Kemal(4)
Yayınlar
- ArticleAçık Erişim2025Kavşak Geometrilerinin ve Araç Hacimlerinin CO2 Salınımı Üzerindeki Etkilerinin İncelenmesi
Çolak, Muhammed Ali; Deniz, Fatih Ahmet
Ulaşımdan kaynaklanan CO₂ salınımındaki artış; nüfusun büyümesi, teknolojik gelişmeler, bireysel araç sahipliğinin yaygınlaşması ve toplu taşıma ile lojistik sektörlerinde kullanılan otobüs ve kamyon gibi motorlu taşıtların sayısının artmasıyla doğrudan ilişkilidir. Bu bağlamda, şehir içi trafik akışının analizi ve iyileştirilmesi, zararlı salınımların azaltılması için kritik bir öneme sahiptir. Bu çalışmada, Erzincan il merkezindeki en yoğun yedi kavşağın oluşturduğu trafik koridorunun mevcut durumu, kavşak sayımları ve sinyalizasyon verileri kullanılarak Aimsun ortamında modellenmiştir. Kavşaklardaki geometrik düzenlemeler ve araç hacimlerinin farklı kombinasyonlarıyla oluşturulan 2303 alternatif senaryo üzerinde analiz yapılmıştır. Toplam 2304 senaryonun analizinden elde edilen CO2 salınım değerleri, Hafif Gradyan Artırma Makinesi (LightGBM), k-En Yakın Komşular (kNN) ve Bayesian Ridge regresyon algoritmaları kullanılarak modellenmiştir. En iyi CO2 salınım tahmini, LightGBM ile elde edilmiştir. Özellik önem analizi, Dörtyol Kavşağı'nın mevcut durumunun CO2 salınımları üzerinde en büyük etkiye sahip olduğunu, Terzibaba Kavşağı'nın farklı düzeyli kavşak olarak yeniden düzenlenmesinin ise koridor boyunca CO2 salınımların azaltmaya yardımcı olacağını ortaya koymuştur.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Efficient and Real-Time Railway Track Fault Classification Using CNN Integrated with Convolutional Block Attention Module
Tastimur, Canan
The occurrence of various types of faults on railway rail surfaces can lead to accidents such as train derailments. In this study, a new approach that produces very fast and robust results is developed by combining the convolutional neural network and the convolutional block attention module for the classification of rail faults. The dataset used in this study contains four different fault types, and experimental studies were conducted on the public rail dataset. The impact of the convolutional block attention module on the performance of the proposed approach and its contribution to the model's generalization ability are examined, and the performance of the proposed approach increases by approximately 5% compared to the performance of the proposed approach without this module. It has been demonstrated that the proposed approach can be used effectively in railway track fault diagnosis by producing fast and effective results.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Sakaltutan Geçidi Yerine Önerilen Eğimsiz Tünelin Emisyon, Yakıt Tüketimi ve Ekonomik Analizi
Demirci, Oğuz Kürşat
Bu çalışma, D-100/E-80 üzerindeki 13 km’lik Sakaltutan Geçidi yerine 11,1 km, %0 eğimli bir tünelin çevresel ve ekonomik etkilerini nicel olarak değerlendirmektedir. COPERT 5.8.1 ile 5196 araçlık filo için hız, eğim, soğuk başlatma ve iklim çarpanları kullanılmış; ±%15 genişletilmiş belirsizlik ve 10000 yinelemeli Monte Carlo analizi uygulanmıştır. Tünel senaryosu yakıt tüketimini günde 5041 L (−%34) ve CO2’yi 12,9 t gün-1 (≈4700 t yıl-1) azaltır; NOx emisyonunda −%23, PM’de −%37 düşüş sağlar. Toplam yolculuk süresi 211 saat gün-1 azalır ve ekonomik fayda ≈108 milyon TL yıl-1’dır; karbonun parasal değeri eklendiğinde toplam ≈126,8 milyon TL yıl-1’a çıkar. Net tasarruf olasılığı %99,4’tür. Benzer tünel LCA’larıyla karşılaştırılan yapım aşaması gömülü emisyonları 105 t CO2-eş. mertebesindedir; karbon geri ödeme süresi ≈10–20 yıl olarak öngörülür. Yatırım gideri dâhil basit geri ödeme, varsayılan yatırım gideri (CAPEX)’e bağlı olarak ≈24–39 yıl aralığındadır. Sonuçlar, özellikle ağır hizmet araçları kaynaklı kazanımların belirgin olduğunu ve tünelin iklim/ekonomi açısından güçlü bir seçenek sunduğunu göstermektedir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Üretim Sistemlerinde Dijital İkiz Kullanımına Yönelik Bariyer Analizi
Aka, Salih
Dijital ikiz, gerçek bir nesne, kaynak ya da sürecin sanal ortamda dijital benzerinin oluşturulduğu ve veri bağlantısı yoluyla anlık ve dinamik olarak fiziksel dünya ile sanal dünya etkileşiminin canlı tutulduğu bir platformdur. Yeni gelişen bir sistem olduğundan dijital ikizin üretim sistemlerince uygulanması sırasında ortaya çıkan çeşitli bariyerler, bu platformun benimsenmesini zorlaştırabilmektedir. Dijital ikizin üretim projelerinde başarılı olması için bariyerleri ortadan kaldıracak stratejilere ihtiyaç duyulmaktadır. Bu çalışmada üretim sistemlerinde dijital ikiz kullanımı sırasında ortaya çıkabilecek bariyerler belirlenmiş ve uzman görüşleri doğrultusunda bariyerler birbirleri ile karşılaştırılmıştır. Çalışmanın amacı bariyerler arasındaki göreceli ağırlıkları tespit ederek önem önceliğini ortaya koymaktır. Analiz tekniği olarak uzman görüşlerinin dilsel değişkenler üzerinden modellenmesine imkân sağlayan bulanık Best Worst metodu (BWM) kullanılmıştır. Sonuç olarak “sistemsel ve teknolojik entegrasyon yetersizlikleri" bariyerinin üretimde dijital ikiz uygulamaları için öncelikli olduğu tespit edilmiştir. Çalışma, dijital ikiz ve üretim birlikteliğini inceleyerek birlikteliğe engel olabilecek unsurları ortaya koymakta ve uygulayıcılar için genel bir çerçeve sunmaktadır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Elektrikli Araçların Hava Kalitesi Üzerine Etkisi: PM₁₀, NO₂, SO₂ ve CO Parametreleri Üzerinden Bir Değerlendirme
Seyhan, Aslıhan Kurnuç; Ertugay, Neşe
Hava kirliliği, küresel ölçekte halk sağlığını tehdit eden en önemli çevresel sorunlardan biri olarak öne çıkmaktadır. Bu kirliliğin başlıca kaynaklarından biri olan ulaşım sektörü, artan motorlu taşıt sayısıyla birlikte atmosferdeki zararlı gaz konsantrasyonlarını belirgin şekilde yükseltmektedir. Son yıllarda elektrikli araç teknolojilerinde yaşanan gelişmeler, düşük emisyon profilleri sayesinde hava kalitesinin iyileştirilmesinde etkili bir çözüm olarak değerlendirilmektedir. Bu çalışmada, 2016–2024 yılları arasında Türkiye’de trafiğe kayıtlı motorlu kara taşıtlarının illere göre dağılımı esas alınarak toplam araç sayısının %65’inden fazlasını oluşturan ve taşıt yoğunluğu bakımından en üst sıralarda yer alan iller (örneğin İstanbul, Ankara, İzmir vb.) seçilerek, bu illere ait 2016–2024 yılları arasındaki PM₁₀, NO₂, SO₂ ve CO hava kirletici parametrelerine ilişkin veriler analiz edilmiştir. Aynı dönemde elektrikli ve hibrit araç sayılarındaki değişim göz önünde bulundurularak, araç teknolojilerindeki dönüşümün hava kirliliği üzerindeki etkileri değerlendirilmiştir. Elde edilen bulgular, özellikle PM₁₀, SO₂ ve CO konsantrasyonlarında yıllar içinde belirgin ve kademeli bir azalma olduğunu ortaya koymaktadır. Bu azalma, elektrikli araçların yaygınlaşması, fosil yakıt kullanımının sınırlandırılması, pandemi döneminde sanayi ve ulaşım faaliyetlerinin geçici olarak azalması gibi çok faktörlü yapısal değişimlerle ilişkilendirilmiştir. Ancak bazı illerde NO₂ seviyelerinin artmaya devam ettiği ve ulaşım kaynaklı emisyonların hâlen ciddi bir problem olduğu görülmüştür. Sonuç olarak, elektrikli araçların hava kalitesini iyileştirmede önemli bir potansiyel taşıdığı; ancak bu etkinin sürdürülebilir çevre politikaları, yenilenebilir enerji entegrasyonu ve toplu taşımanın güçlendirilmesi gibi çok boyutlu stratejilerle desteklenmesi gerektiği vurgulanmaktadır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Constraints On Production Scales And Distribution Channels Of Erzincan Tulum Cheese
Akın, Mustafa; Tokay, Seher Büşra
This study investigates the challenges and opportunities faced by producers of Erzincan Tulum cheese, a traditional Turkish cheese known for its distinctive flavor and production techniques. Despite its potential for growth and national recognition, Erzincan Tulum cheese remains primarily confined to local markets because of various constraints. Through qualitative research methods, including in-depth interviews with 20 producers, this article explores the underlying factors hindering the scalability, branding, and distribution of Erzincan Tulum cheese nationally and internationally. The findings reveal that producers are predominantly small-scale operators who strongly prefer maintaining traditional production methods, show reluctance towards adopting modern business practices, and express a significant lack of interest in expanding their market reach. The study identifies three main barriers to growth: a knowledge gap in modern production and business management practices, a lack of trust in new market entrants and business partners, and a comfort zone that discourages innovation and expansion. The research highlights a disconnect between Erzincan tulum cheese's rich heritage and its online portrayal, pointing to the untapped potential for engaging wider audiences. Additionally, it addresses the logistical and regulatory obstacles to scaling production and accessing broader markets, emphasizing the need for institutional support and infrastructure improvements. The paper advocates for a collaborative strategy involving producers, government, and marketers to align digital narratives with the cheese's artisanal roots, offering recommendations to enhance digital storytelling, optimize logistics, and create a supportive regulatory framework. This collaborative effort aims to blend tradition with modernity, securing the industry's future in the digital age.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Synchrophasor Estimation Based on Quadrature Amplitude Modulation Using Artificial Ecosystem Optimization Algorithm
Altintasi, Cagri; Şengül, Alperen
The need to monitor power quality and detect faults in the power grid has increased due to diverse generation sources and growing loads, which create supply-demand imbalances. Synchrophasor measurements are used to address these issues and assess system stability. This study proposes using Quadrature Amplitude Modulation (QAM) for synchrophasor measurement. Initially, the power signal’s frequency is estimated using the Artificial Ecosystem Optimization (AEO) algorithm. This estimated frequency serves as a reference for the QAM method. The power signal is then decomposed into positive and negative components based on this frequency. A moving average filter, acting as a low-pass filter, is applied to remove high-frequency noise and retain components aligned with the estimated frequency. As a result, the amplitude and phase of the desired frequency component are extracted. The method’s effectiveness is evaluated based on the IEEE Std. C37.118.1 for both M and P classes. Results show that the proposed approach achieves phasor estimation errors within the acceptable limits defined by the standard. Moreover, its performance at 80 dB SNR is compared with recent methods from literature, demonstrating its superiority in synchrophasor estimation, particularly under steady- state and harmonic conditions.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025An Application on Electric Vehicle Charging Station Site Selection With Multi-Criteria Decision-Making Methods
Sünbül, Seyma; Tortum, Ahmet
As the population grows and vehicles are increasingly owned, emissions from fossil fuels are worsening environmental problems. In this context, electric vehicles (EVs) present a significant alternative for the development of sustainable transportation systems. However, for electric vehicles (EVs) to become a prevalent form of transportation, the establishment of an effective and efficient charging infrastructure is imperative. The primary objective of this study is to ascertain the most suitable location for the installation of an electric vehicle (EV) charging station within the Erzincan Binali Y & imath;ld & imath;r & imath;m University Yaln & imath;zbag Campus. During site selection, the analytical hierarchy process (AHP) and TOPSIS methods were used to evaluate the criteria. The study was conducted in two stages. In the first, seven active-use transformers on campus were weighed using the AHP method, then the most suitable one was selected using the TOPSIS method.In the second, seven parking areas were analysed using the same criteria. The parking lot selection used the AHP and TOPSIS methods, considering faculty and campus entrance distance, lot capacity and transformer preference score. The findings of the study demonstrate the efficacy of the AHP and TOPSIS methods in the context of multi-criteria and multi-stage decision-making processes. The integration of these methods has been demonstrated to facilitate the optimisation of EV charging station location selection, both in technical and practical terms.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Earthquake safety in Erzincan City center: strategic analysis of building stock, transportation network, gathering, and temporary shelter areas
Bayata, Halim Ferit; Mazlum, Yunus Emre; Bas, Fatih Irfan; Çolak, Muhammed Ali
The twin earthquakes in Kahramanmara & scedil; in 2023 revealed the necessity of disaster coordination and pre-disaster situation analysis. To cope with such disasters and prevent possible losses, a comprehensive preparation process is required, such as evaluating a city's building stock in terms of earthquake risks and assessing the adequacy of the transportation network, emergency gathering points, and temporary shelter areas. This study selected Erzincan province, which has been destroyed by many major earthquakes, as the study area. It aimed to create risk maps by determining earthquake-risk buildings using rapid visual screening methods based on Geographic Information Systems (GIS), conducting building performance evaluations, and choosing safe transportation routes in case of a possible disaster. A total of 3,199 reinforced concrete and masonry buildings with two or more stories in the city center of Erzincan, constructed before 2000, were identified. In a possible earthquake, transportation infrastructure was analyzed, and maps of traffic density, emergency gathering, and temporary shelter areas were created. The analyses showed that the capacity of emergency gathering, and temporary shelter areas needed to be increased. In the scenarios of increased traffic density, it has been determined that the existing roads in all ten neighborhoods are unsuitable for disaster-emergency situations.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Optimizing Aircraft Operations in Case of Increasing Demand for Limited Airport Capacity
Demirel, Soner; Çınar, Ertan
The purpose of this paper is to minimize the total difference between the requested and assigned departure time of aircraft to enhance the efficiency of using limited airport capacity. The mathematical model was formed by employing mixed integer linear programming. The parameters, decision variables, and constraints were defined to cover the problem. The baseline and alternative scenarios were compared to present the improved results. Sensitivity analysis was performed to test the ability of the model with different parameters. Also, in order to test the mathematical model, distinct from both the baseline and alternative scenarios, CHQ airport was based by using its number of parking positions and taxi-in/out durations in the sensitivity analysis. The proposed model reduced the total difference by 20.78% for 30 aircraft for 5 parking positions in the alternative scenario. The results showed that it may well serve to improve the imbalance regarding operational conditions.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Design, analysis, and implementation of DC-DC boost converter with new active snubber cell
Gecmez, Hilal Sebnem; Ting, Naim Suleyman; Sahin, Yakup
In this paper, a new active snubber cell for DC-DC boost converters is introduced for the purpose of soft switching. The introduced snubber cell ensures lossless turning-on by zero-voltage transition (ZVT) and turning-off by zero-voltage switching (ZVS) of the main switch. Besides, it enables turning-on by ZVS and turning-off by zero current switching (ZCS) of the main diode. None of the semiconductor power devices are subjected to extra voltage stress, and all of them operate by soft switching (SS). The converter can successfully maintain the SS even under light loads. Furthermore, the proposed converter structure is advantageous in terms of simplicity and low cost. The operating modes and theoretical analysis of the introduced converter are presented and it is validated using a prototype with a 500 W output power and at the 100 kHz switching frequency. Owing to the proposed active snubber cell, the converter efficiency is achieved as 97.2%.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Intercomparison of sediment transport curve and novel deep learning techniques in simulating sediment transport in the Wadi Mina Basin, Algeria
Achite, Mohammed; Katipoğlu, Okan Mert; Elshaboury, Nehal; Tuğrul, Türker; Pandey, Kusum
The accurate estimation of sediment discharge is crucial for the design and operation of engineering structures such as dams, water treatment facilities, and erosion control systems. This study evaluates the performance of various machine learning (ML) and deep learning (DL) models in predicting sediment transport in the Mina Basin, Algeria, at two stations: Oued Abtal and Sidi Abdelkader Djillali. The models include the sediment rating curve, category boosting, convolutional neural network, deep neural network (DNN), gated recurrent unit, and multilayer perceptron. Among these, the DNN model consistently demonstrated superior performance. For Oued Abtal station, the DNN achieved RMSE = 243.72 kg/s, MAE = 102.17 kg/s, NSE = 0.99, and PBIAS = 6.81%. At Sidi Abdelkader Djillali station, it recorded RMSE = 91.27 kg/s, MAE = 46.51 kg/s, NSE = 0.99, and PBIAS = 38.06%. Error analysis revealed that the DNN model offers the most reliable predictions, outperforming both traditional and other ML/DL methods. This study underscores the potential of deep learning models in advancing sediment transport prediction, particularly in semi-arid regions, and highlights their implications for sustainable water resource management.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Evaluating membranes for hydrogen storage and utilization in next-generation aviation systems
Ayar, Murat; Cinoglu, Bahadır; Iulianelli, Adolfo; Karakoc, T. Hikmet
This study aims to provide a comprehensive evaluation of membrane technologies for hydrogen-related processes in aviation, specifically focusing on hydrogen production, hydrogen separation, and fuel cells. As aviation seeks to transition to cleaner energy solutions, the selection of appropriate membranes is critical for ensuring efficiency and sustainability. The research utilizes the Analytic Hierarchy Process (AHP) to systematically assess membrane alternatives based on key criteria: economic factors, environmental impact, technical performance, and technological maturity. By conducting pairwise comparisons and detailed matrix calculations, this study establishes the relative importance of sub-criteria and ranks membrane types for each hydrogen-related application. The analysis identifies Nonporous Dense Films as the most effective membrane for hydrogen production, due to their balance of cost and technical performance. For hydrogen separation, Ceramic and Metal Membranes are determined to be the optimal choice, offering superior durability, hydrogen permeability, and thermal stability. In fuel cell applications, Electrically Charged Membranes are found to be the most suitable for Proton Exchange Membrane Fuel Cells (PEMFCs), while Ceramic and Metal Membranes excel in Solid Oxide Fuel Cells (SOFCs). The outcomes of this study not only highlight the most suitable membranes for different aviation hydrogen processes but also offer a strategic framework for decision-makers. By identifying the key factors driving membrane selection, this research contributes to advancing hydrogen adoption in aviation, facilitating the development of efficient, low-emission technologies for the future of sustainable air travel.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Exploring the role of voluntary business associations on borrowed institutionalism in regional development: insights from the case of Kayseri in Türkiye
Tuysuz, Suat; Varol, Cigdem; Çiçek, Ihsan
Institutional and cultural traditions, usually shaped by non-economic factors, help to reduce the transaction costs of firms, particularly the costs of knowledge transfer. This study attempts to explain the effects of non-economic factors over voluntary business associations (BAs) and highlight the concept of “borrowed institutionalism” to illustrate the constructive and destructive power of BAs in their use of their relationships with the political establishment for their members. In Türkiye, BAs are not only economic actors but are also embedded in social forms that contain secular or conservative characteristics. While, the structures of these associations that operate within various ideologies can contribute to the institutional setting, they can also hinder the economic potential of a region by developing love or hate relations with the respective political structures. This forms the basis of the concept of “borrowed institutionalism” introduced in this study. Kayseri, which is one of Türkiye’s successful production centers with its unique socio-political characteristics, and predominantly home to small- and medium-sized enterprises (SMEs) appears to be a critical case to analyze the role of BAs. The findings from Kayseri case study support the idea that both secular and conservative forms of BAs can cyclically be constructive or destructive for their members and create borrowed institutionalism based on non-inclusive institutionalism.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Integrated risk management in construction project: utilizing NDSII-BMR and NDSII-BWR for time-cost-safety trade-offs
Dede, Tayfun; Sin, Theint Shwe; Yılmaz, Mehmet; Uçan, Hacı Abdullah; Rao, Ravipudi Venkata
Purpose – This research introduces novel algorithms (NDS-II-BMR and NDS-II-BWR) that combine the simplicity of best-mean-random (BMR) and best-worst-random (BWR) approaches with the opting mechanisms of NDS-II. Design/methodology/approach – This study expands on earlier comparison assessments by adding a broader range of algorithms, including MOPSO, NSGAII, PESA2 and WOA, to provide a more comprehensive evaluation approach for the proposed NDSII-BMR and NDSII-BWR algorithms. In addition to typical performance measurements, this study utilizes sophisticated statistical validation through the Wilcoxon signed-rank test to determine the statistical significance of performance differences across this varied range of multi-objective optimization approaches. Findings – The results demonstrate the effectiveness of NDSII-BMR and NDSII-BWR in optimizing costs and decreasing safety risks while minimizing time efficiency. These outcomes underscore the applicability of these models for managing complex construction projects in real-world scenarios. Originality/value – This study employs multi-objective functions to minimize the total project time and cost while reducing overall safety risks. The proposed model integrates the NDS-II framework with innovative strategies, best-mean-random (BMR) and best-worst-random (BWR).
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Investigating the effects of glass fiber in enhancing concrete pavement performance
Baş, Fatih İrfan
Flexible pavements are considered more sustainable than concrete pavements primarily due to the higher long-term maintenance and rehabilitation costs associated with concrete pavements. Concrete pavements possess a higher modulus of elasticity, which allows them to distribute vehicle loads over a larger area, thereby enhancing the strength of the pavement. However, despite this advantage, their flexural strength is relatively low. As a result, there has been a growing focus on research to improve the flexural strength of concrete pavements to increase their overall performance and sustainability. This study aimed to reveal the effects of enhanced mechanical properties of concrete reinforced with glass fiber on concrete pavements, specifically under heavy vehicle loading as in real-world conditions. The impact of glass fiber on the thickness of both the concrete and base layers, as well as the quality of the base layer material and transverse joint spacing, was assessed. For this purpose, 3D finite element models were developed using ANSYS software, considering concrete thicknesses of 100, 150, and 200 mm, glass fiber ratios of 0%, 0.5%, and 1%, base layer elastic moduli of 100, 200, and 300 MPa, and transverse joint spacings of 300, 450, and 600 mm. It was determined that the concrete thickness and the base layer modulus of elasticity were the most influential factors in minimizing flexural stress, total deformation, and equivalent total strain. The glass fiber addition had a more notable impact on maximum principal stress, especially at the 1% ratio, but had a minimal effect on total deformation and strain. Transverse joint spacing had the least effect, although shorter spacings are still recommended to reduce the risk of transverse cracking in stiffer base layers.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025A Reinforcement Learning-Based Solution for the Capacitated Electric Vehicle Routing Problem from the Last-Mile Delivery Perspective
Aslan Yıldız, Özge; Sarıçiçek, İnci; Yazıcı, Ahmet
The growth of the urban population and the increase in e-commerce activities have resulted in challenges for last-mile delivery. On the other hand, electric vehicles (EVs) have been introduced to last-mile delivery as an alternative to fossil fuel vehicles. Electric vehicles (EVs) not only play a pivotal role in reducing greenhouse gas emissions and air pollution but also contribute significantly to the development of more energy-efficient and environmentally sustainable urban transportation systems. Within these dynamics, the Electric Vehicle Routing Problem (EVRP) has begun to replace the Vehicle Routing Problem (VRP) in last-mile delivery. While classic vehicle routing ignores fueling, both the location of charging stations and charging time should be included in the Electric Vehicle Routing Problem due to the long recharging time. This study addresses the Capacitated EVRP (CEVRP) with a novel Q-learning algorithm. Q-learning is a model-free reinforcement learning algorithm designed to maximize an agent’s cumulative reward over time by selecting optimal actions. Additionally, a new dataset is also published for the EVRP considering field constraints. For the design of the dataset, real geographical positions have been used, located in the province of Eskisehir, Türkiye. It also includes environmental information, such as streets, intersections, and traffic density, unlike classical EVRP datasets. Optimal solutions are obtained for each instance of the EVRP by using the mathematical model. The results of the proposed Q-learning algorithm are compared with the optimal solutions of the presented dataset. Test results show that the proposed algorithm provides remarkable advantages in obtaining routes in a shorter time for EVs.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Transportation Mode Selection Using Reinforcement Learning in Simulation of Urban Mobility
Taş, Mehmet Bilge Han; Özkan, Kemal; Sarıçiçek, İnci; Yazici, Ahmet
Transportation mode selection is pivotal for navigating through cities plagued by heavy traffic congestion. This plays a crucial role in ensuring the efficient utilization of time and resources to achieve the desired objectives. Given the complex dynamics of urban mobility, strategically selecting a transportation mode can significantly mitigate delays and enhance overall productivity in densely populated areas. The objective of this study is to find the most efficient result among various transportation modes to make deliveries from different points on a university campus. To solve this problem, reinforcement learning was used and tested on the simulation environment SUMO. Traffic density was increased by using an equal number of different transportation modes, such as driving, cycling, motorbiking, and walking. Various traffic densities were generated, and different reward models were applied to select the best means of transportation. Various probability distributions were used as reward models to avoid the unfair distribution caused by how near or how far the road is when moving from random points to the destination region. As a result of the models created using the applied reward–penalty functions, it was determined that the best means of transportation in areas with a low traffic density is cycling, and in areas with high traffic density, the optimal mode of transportation is motorbiking.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Learning-Augmented IDA–PBC for Underactuated Mechanical Systems with Unmeasured Actuator Dynamics and Unmatched Disturbances
Can, Erol
Abstract: Underactuated mechanical systems (UMSs) present significant challenges in control design due to limited actuation, nonlinear coupling, and susceptibility to unmatched and time-varying disturbances. Traditional passivity-based methods often assume full state availability and matched disturbances, limiting their applicability in uncertain, sensor-constrained environments. This study proposes a learning-augmented interconnection and damping assignment passivity-based control (iIDA–PBC) framework that enhances robustness and adaptability for UMSs. The approach integrates real-time disturbance estimation using Gaussian Math. Comput. Appl. (GPR) and Math. Comput. Appl. (LSTM) networks, alongside nonlinear observer designs for reconstructing unmeasured actuator states. The overall control architecture preserves the port-Hamiltonian structure while enabling adaptive compensation for unknown external perturbations. Theoretical analysis ensures Math. Comput. Appl. (ISS) under bounded estimation errors. Simulation results on a benchmark underactuated system demonstrate improved disturbance rejection, tracking accuracy, and robustness compared to conventional adaptive and passivity-based controllers. The proposed method is suitable for complex, partially observable systems such as aerial vehicles, autonomous robots, and marine platforms.
RDL Kalıcı Kaydıİncele - Book ChapterAçık Erişim2025Innovative Ways of Cooperating with Public Administration for Gender Equity in Informatics
Caner-Yıldırım, Sonay; Harizaj, Miranda; Shakarishvili, Salome
Gender inequity in informatics remains a persistent global challenge, with women significantly underrepresented in both educational and professional domains. This disparity not only constrains diversity and innovation but also hinders the achievement of the United Nations Sustainable Development Goal 5 (SDG 5), which endeavors to achieve gender equity and empower all women and girls. This chapter explores innovative strategies for public administration to foster gender equity in informatics. It aims to analyze the current challenges, develop a transformative vision for a supportive ecosystem, and propose concrete actions and innovative instruments to empower women in the field. A comprehensive methodological approach was applied, encompassing an in-depth literature review, policy analysis, and the assessment of best practices and case studies from diverse organizations and countries. The analysis revealed several barriers to achieving gender equity in informatics, including pervasive stereotypes, gaps in digital literacy, and underrepresentation in decision-making and entrepreneurial roles. To address these challenges, the chapter proposes targeted actions and innovative tools, including integrating gender considerations into legislation, the promotion of professional networks, the establishment of equitable care systems, the provision of equal opportunities for skills development, the increased representation of women in AI, the advancement of gender-inclusive AI research, and the facilitation of strategic partnerships. By adopting gender-responsive policies, encouraging collaboration with academia, the private sector, and civil society, and promoting inclusive practices, public administration can foster a more equitable and innovative informatics sector. These strategies not only enhance diversity and problem-solving capabilities but also contribute to broader societal and economic progress in the future.
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