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 Erişim2026Ranking of Foreign Trade Capital Companies in Türkiye Using Critic-Copras Methods
Baysal, Yusuf Volkan
Foreign trade is a key driver of economic growth, reducing external debt dependency, supporting industrial production, creating employment, and stabilizing the current account balance. In this framework, Foreign Trade Capital Companies (FTCCs) act as strategic intermediaries that facilitate SMEs’ access to global markets through financing, logistics, and promotion. Their corporate structures and international networks strengthen the competitiveness of Turkish products and ensure continuity of exports even during crises. The sustainability of FTCC activities is therefore essential not only for expanding trade volume but also for supporting long-term growth. This study evaluates the efficiency of FTCCs in Türkiye using the CRITIC-COPRAS method, which applies an objective weighting system and expresses the relative performance of firms in percentage terms. Seventeen financial ratios across liquidity, activity, financial structure, profitability, and market performance were analyzed for pre-pandemic (2017–2019) and pandemic (2020–2022) periods. The results show that the Leverage Ratio (debt to total assets) was the most influential criterion, while Net Profit to Equity was the least significant. İzmir Demir Çelik ranked highest before COVID-19, whereas Federal Mogul Türkiye led during the pandemic. Findings highlight the importance of leverage management for building resilience in crises and strengthening competitiveness. This study evaluates the efficiency of FTCCs in Türkiye using the CRITIC-COPRAS method, which applies an objective weighting system and expresses the relative performance of firms in percentage terms. Seventeen financial ratios across liquidity, activity, financial structure, profitability, and market performance were analyzed for pre-pandemic (2017–2019) and pandemic (2020–2022) periods. The results show that the Leverage Ratio (debt to total assets) was the most influential criterion, while Net Profit to Equity was the least significant. İzmir Demir Çelik ranked highest before COVID-19, whereas Federal Mogul Türkiye led during the pandemic. Findings highlight the importance of leverage management for building resilience in crises and strengthening competitiveness.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim20262023 Kahramanmaraş Depremleri sonrasında Malatya’daki yığma binaların sismik performansı: Saha incelemesi ve nümerik analizler
Turan, Ahmet Ihsan; Celik, Alper
Türkiye, aktif deprem kuşağında yer almakta olup tarih boyunca yıkıcı depremler yaşamıştır. 6 Şubat 2023 Pazarcık (Mw 7.7) ve Elbistan (Mw 7.6) depremleri, özellikle bölgede yaygın olan mühendislik hizmeti almamış yığma yapılarda büyük hasara yol açmıştır. Bu çalışma, Malatya ilindeki yığma yapı stokunda gözlenen hasar türlerini incelemekte ve saha gözlemlerine dayanarak bu hasarların olası nedenlerini tartışmaktadır. Nitel bulguları desteklemek amacıyla, temsilî az katlı yığma yapı prototiplerinin deprem davranışını karşılaştırmalı olarak değerlendiren sayısal analizler gerçekleştirilmiştir. Doğrusal-elastik yanıt spektrumu analizleri ve modal esaslı yaklaşım kullanılarak iki ana parametre dikkate alınmıştır: taşıyıcı duvar malzemesi türü (dolu kil tuğla, boşluklu kil tuğla ve gazbeton) ve kat sayısı (1–3). Saha gözlemleri, yapı stokunun önemli bir bölümünün yeterli mühendislik hizmeti olmadan inşa edildiğine işaret etmekte; ayrıca katlar arasında farklı yığma birimlerinin kullanılması gibi düzensiz uygulamaların kritik zafiyetlere yol açabildiğini göstermektedir. Sayısal sonuçlar da rijitlik ve deplasman taleplerinin hem yığma birimi türüne hem de yapı yüksekliğine güçlü biçimde bağlı olduğunu ortaya koymakta ve özellikle daha hafif yığma sistemlerde kat sayısı arttıkça daha olumsuz talep eğilimlerinin gelişebileceğine işaret etmektedir.
RDL Kalıcı Kaydıİncele - Review ArticleAçık Erişim2026Dijital Yönetimlerin Siber Güvenlik Stratejileri: AB ve Finlandiya İncelemesi
Ekinci, Elif
Bu çalışma, dijital dönüşüm süreciyle birlikte karmaşıklaşan siber tehditlerin kamu yönetimi ve politika yapım süreçleri üzerindeki etkilerini Avrupa Birliği (AB) ve Finlandiya örnekleri üzerinden incelemektedir. AB, siber güvenlik alanında normatif bir liderlik hedefiyle hareket etmekte; yasal düzenlemeler, kurumsal koordinasyon ve dayanıklılık politikalarıyla, bütünleşik bir güvenlik kültürü oluşturmaya çalışmaktadır. NIS2 Direktifi, Siber Dayanıklılık Yasası, Dijital Hizmetler Yasası, Genel Veri Koruma Tüzüğü (GDPR) ve Yapay Zekâ Yasası, birliğin dijital güvenliği kapsamlı bir normatif çerçeveye oturtma girişimlerinin temelini oluşturmaktadır. Ancak üye devletler arasındaki uygulama farklılıkları, AB düzeyinde siber güvenlik stratejilerinin etkinliğini ve sürdürülebilirliğini sınırlandırmaktadır. Finlandiya ise 2024–2035 Ulusal Siber Güvenlik Stratejisi kapsamında katılımcı yönetişim, kamu–özel iş birliği, kriptografi, yapay zekâ uygulamaları ve ulusal izleme mekanizmalarını bütünleştirerek operasyonel düzeyde güçlü bir model ortaya koymuştur. Ülkenin stratejisi, siber güvenliği yalnızca teknik bir savunma aracı olarak değil, ekonomik kalkınma, demokratik yönetişim ve ulusal egemenliğin dijital boyutu olarak ele almaktadır. Çalışma sonucunda, sürdürülebilir siber güvenliğin sadece teknolojik kapasiteyle değil, aynı zamanda kurumsal dayanıklılık, uluslararası iş birliği, insan kaynağının niteliği ve toplumsal farkındalık düzeyine bağlı olduğu kanısına varılmıştır. AB’nin normatif düzenleme kapasitesi ile Finlandiya’nın uygulama disiplini birlikte değerlendirildiğinde, Avrupa’nın bütüncül ve dirençli bir dijital güvenlik ekosistemi oluşturma potansiyeli giderek güçlenmektedir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Kamu Malları Bağlamında Hidroelektrik Santraller
Gürbüz, Abdulsamet
Devlet kamu hizmetlerini yerine getirirken kamu kaynaklarını ve kamu mallarını kullanmaktadır. Ülkemizde kamu malları kapsamında değerlendirilen akarsular üzerinde hidroelektrik santrallerin inşası uzun yıllardır sürdürülüyor olsa da bu konu ancak 2000’li yıllardan itibaren kamuoyunun gündeminde belirgin bir yer edinmeye başlamıştır. Bunun bir nedeni daha önce devlet eliyle kurulan ve işletilen bu tesislerin 2000’li yılların başından itibaren özelleştirilmesidir. Bu yıllardan itibaren konuya ilişkin yasal değişikliklerin özel sektörün isteklerine göre gerçekleştirildiği, kurulan hidroelektrik santrallerin ise kurulma ve işletilme aşamalarında idare tarafından etkin bir denetime ve yaptırıma tabi kılınmadığı görülmektedir. Böylece santrallerin yapıldığı yerlerde yöre halkının menfaatini ve kamu yararını dışlayan uygulamalar söz konusu olmaktadır. Bu çalışmanın konusu hidroelektrik santrallerin yapımında özel şirketlerin istekleri ile kamunun beklentilerinin uyum içinde olup olmadığının araştırılmasıdır. Çalışmada, konuya ilişkin yaşanan sorunların çözülmesine ilişkin faydalı sonuçlara varılması amaçlanmaktadır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026COVID-19 Pandemi Döneminde Erzincan Kent Merkezinde Trafik Kazalarının Zaman-Mekân Küpü Yöntemiyle Zamansal – Mekânsal Analizi (2020-2023)
Kesik, Ozan Arif; Güney, Ertuğrul
Bu çalışma, 2020-2023 döneminde Erzincan kent merkezinde meydana gelen ölümlü ve yaralanmalı trafik kazalarının zamansal ve mekânsal dinamiklerini, COVID-19 pandemisinin etkileri bağlamında incelemektedir. Erzincan, Doğu Anadolu Bölgesi’nde bin kişi başına düşen araç sayısında birinci sırada yer alması ve düşük nüfusuna rağmen yüksek kaza istatistikleri göstermesi nedeniyle çalışma alanı olarak seçilmiştir. Araştırmada; Sıcak Nokta Analizi (Getis-Ord Gi*), Kernel Yoğunluk Analizi ve Zaman-Mekân Küpü Analizi yöntemleri kullanılarak kazaların dağılımı haritalanmıştır. Ayrıca, Analitik Hiyerarşi Süreci (AHP) ile kaza risk faktörleri ağırlıklandırılmıştır. Bulgular, COVID-19 kısıtlamalarının yaşandığı 2020 yılında kaza sayılarında belirgin bir düşüş yaşandığını, ancak normalleşme süreciyle birlikte 2023 yılında kaza ve yaralı sayılarının pandemi öncesi seviyeleri aşarak zirve yaptığını ortaya koymuştur. Mekânsal analizler, kaza riskinin Dörtyol kavşağı ve ana arterler üzerinde "yoğunlaşan sıcak nokta" karakteri sergilediğini; AHP sonuçları ise trafik yoğunluğu (%46) ve hızın (%33) temel risk faktörleri olduğunu kanıtlamıştır. Çalışma, elde edilen bulgular ışığında, riskli kavşaklar ve trafiğin zirve yaptığı saatler için yerel ölçekte uygulanabilir trafik güvenliği stratejileri sunmaktadır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Comparison of Financial Performance of Logistics Companies During and Before COVID-19 Period via CILOS-ARAS Method
Baysal, Yusuf Volkan
The logistics sector has a critical position in economies in terms of the continuity of global trade and the effective functioning of supply chains. The role of this sector, with the COVID-19 pandemic, has become even more evident and measuring the financial resilience of businesses has gained importance. In this study, the financial performances of the companies in the BIST transportation and logistics index were analyzed comparatively for the pre-pandemic (2017-2018-2019) and pandemic period (2020-2021-2022). A total of 21 financial ratios were grouped under five groups: liquidity, activity, profitability, financial structure and market performance and they were used in the study, Criteria weights were determined using the CILOS method, and then the financial performance rankings of the companies were created using the ARAS method. The results showed that the main factors determining performance in the pre-pandemic period were profitability and asset utilization efficiency; however, during the pandemic period, cost control, debt management, and market value preservation became more decisive. In addition, it was found that companies focusing on road transportation rose in the rankings during the pandemic period, while companies that operate passenger-focused experienced a loss in performance. The study revealed that crisis periods in the logistics sector reshaped financial decision variables and served as a guide for future studies.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Erzincan Ham Perlit Agregası Kullanılarak Taşıyıcı Hafif Beton Üretilebilirliğinin Araştırılması
Gül, Rüstem; Ulusu, İsmet
Maksimum agrega tane çapı 12.5 mm olan ve granülometrisi Fuller denklemine uygun olan ham perlit agregası kullanılarak taşıyıcı hafif beton üretimi üzerine bir çalışma gerçekleştirilmiştir. Bu amaçla; 150, 200, 250, 300 ve 350 kg/m³ olmak üzere beş farklı çimento dozajında ve iki farklı çökme (slump) değerinde beton numuneleri hazırlanmıştır. Taze betonun işlenebilirliğini düzenlemek amacıyla, tüm karışımlara çimento ağırlığının %1’i oranında akışkanlaştırıcı katkı ilave edilmiştir. Taze ve sertleşmiş betonun fiziksel ve mekanik özellikleri ASTM standartlarına göre belirlenmiştir. Araştırma sonuçlarına göre; perlit agregası kullanılarak 1600 ile 1900 kg/m³ birim hacim ağırlığı arasında taşıyıcı hafif beton üretiminin mümkün olduğu görülmüştür. En yüksek basınç dayanımı, 350 kg/m³ bağlayıcı miktarıyla 90 gün sonunda 35 MPa olarak elde edilmiştir. Araştırma sonuçlarına göre; betonun mekanik ve fiziksel özellikleri üzerinde en etkili iki parametre çökme değeri ile bağlayıcı miktarıdır. Üretilen betonların yarmada çekme dayanımı, basınç dayanımının %11’i olarak belirlenmiş ve su emme oranı %8 olarak tespit edilmiştir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Base station selection with 3GPP tr 38,901 channel model based multiobjective nsga-ii algorithm
Çelik, Hüsamettin
The increase in data demand in mobile communication systems, parallel to the increase in the number of users, has led to serious problems encountered in the base station selection processes in 5G and beyond wireless networks. The distance between the base station and the user, and the signal attenuation caused by this distance, lead to poor signal quality and interference. Effective base station selection plays a critical role in improving the overall performance of communication networks. In traditional base station selection, the desired performance cannot be achieved because the maximum Received Signal Strength Indicator (RSSI) cannot optimize interference and load balancing. Based on these problems, this study created a realistic channel model for the 5G system using the 3GPP TR 38.901 channel model and addressed base station selection. This selection process was formulated using a multi-objective optimization method and solved with the Non-dominated Sorting Genetic Algorithm (NSGA-II). The simulation solution was obtained by considering the maximization of signal quality and the minimization of the distance between the base station and the user as the objective functions used in the NSGA-II algorithm. The results obtained showed that the proposed method provides more balanced and efficient solutions and increases the performance rate.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Heterogeneous Effects of Green Technology Innovations on Renewable Energy Supply Share: A Dynamic Panel Evidence
Balkar, Oğuz Emre; Özenoğlu, Yunus Emre; Alkan, Okan
This study examines the determinants of renewable energy efficiency (REE) in a balanced panel of 17 countries (1995–2021), focusing on green technology innovations (GTI), economic growth (EG), and energy taxation (ET). The analysis accounts for heterogeneity, common shocks, and dynamic adjustment by combining two-way fixed effects with dependence-robust and dynamic common correlated effects (CCE) estimators using Driscoll–Kraay inference. The results show strong persistence in REE and a robust positive association between GTI and REE in the preferred common-factor framework, while the average effects of EG and ET are weaker and model-sensitive. Dumitrescu–Hurlin panel causality tests indicate feedback between REE and EG and bidirectional linkages between REE and ET at the level, whereas innovation dynamics are asymmetric. Overall, the evidences support innovation-centered transition strategies and emphasizes evaluating policy instruments over multi-year horizons given strong persistence and cross-country heterogeneity.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Machine Learning-Based Modeling and Performance Analysis of a Novel Battery Thermal Management System with a Ternary Periodic Minimal Surface Porous Structured Liquid Cooling Channel
Çolak, Andac Batur; Kilinç, Cuma
This article examines the fundamental requirements for effective thermal management of batteries, particularly in high-energy density applications such as electric vehicles and energy storage systems. A unique method is introduced that utilizes a triple periodical minimal surface pore structure in liquid cooling channels to improve heat dissipation and temperature homogeneity in battery packs. Experimental validation and optimization via artificial neural networks are used to evaluate and improve thermal performance, focusing on critical metrics such as maximum temperature and temperature difference within the battery system. Artificial neural network models demonstrated model reliability, exhibiting ideal prediction accuracy with low mean square error values of 1.29E-05 and 9.87E-06, and a correlation coefficient of 0.99999. AThis work builds upon previous attempts by combining an innovative structural design with machine learning, aiming to provide a robust and data-driven solution that aligns cooling efficiency with structural integrity. The novelty of the study lies in its dual experimental machine learning approach, which provides a foundation for improved predictive control in battery temperature management systems with high accuracy and minimal resource requirements.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026Adaptive hybrid control algorithm for integrated wind-solar energy systems: Enhancing efficiency and minimizing environmental impact
Can, Erol
This study introduces a three-tier adaptive control strategy designed for hybrid wind - solar energy systems, with the goal of optimizing energy capture, stabilizing the DC bus voltage, and enhancing overall system performance under varying environmental conditions. The control framework incorporates a TSR-based Maximum Power Point Tracking (MPPT) method for the wind turbine, a temperature-sensitive Perturb-and-Observe (P&O) MPPT for the photovoltaic array, and a real-time energy coordination system that dynamically adjusts the power allocation between wind and solar sources based on their instantaneous availability. A conventional Proportional-Integral (PI) controller manages the DC bus voltage, minimizing fluctuations and ensuring seamless integration with energy storage or the grid. The proposed approach is adaptable to both off-grid and grid-connected microgrids and is computationally efficient for real-time application. Simulation results from four typical scenarios - including high wind/low solar, low wind/high solar, intermittent generation, and balanced generation - show system efficiencies consistently exceeding 92%, along with a substantial reduction in voltage ripple when compared to traditional MPPT techniques. These findings validate the effectiveness of the coordinated control strategy in maintaining power quality, system reliability, and stable energy output, offering a scalable and practical solution for integrating renewable energy into microgrid systems.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026A new full insulated multi output DC-DC converter for photovoltaic energy regulation and multi-battery charging
Can, Erol
The integration of solar energy into electronic devices and battery-charging systems is highly valued due to its status as a clean, environmentally friendly power source. To satisfy energy demands while minimising environmental impact, it is essential to adopt efficient, sustainable technologies. This study introduces a multi-output (dual-inductor, single-capacitor) LLC DC-DC converter designed for battery charging applications, capable of independently charging multiple batteries while reducing input voltage fluctuations from photovoltaic (PV) sources. The proposed converter features independently operated coils for each output channel, preventing long-duration short circuits in the inductors. It achieves high-voltage conversion with reduced output voltage variation, offering greater safety and stability compared to conventional converter designs. A key advantage of this system is its ability to deliver different voltage levels across outputs, enabling flexible, simultaneous charging of various batteries and loads. Initially, circuit modelling and system definition are performed to illustrate these benefits. The dual-inductor, dual-output converter is then evaluated under varying temperatures and irradiance levels during the application phase. Results show reduced ripple levels and increased PV output voltage with lower oscillation while maintaining electrical isolation between batteries and loads.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026UAV DC Motor behaviors control using new hybrid PSO-fuzzy logic with a dynamic error based optimization
Can, Erol
This study introduces a novel and comprehensive control architecture for DC motor speed regulation in unmanned aerial vehicles (UAVs), leveraging a hybrid Particle Swarm Optimization-Fuzzy Logic (PSO-FL) strategy. UAV platforms inherently exhibit highly nonlinear, time-varying, and uncertain dynamics, which often challenge the efficacy of traditional control techniques such as Proportional-Integral-Derivative (PID) controllers and conventional fuzzy logic systems. To overcome these limitations, a dual-layer PSO-FL controller is proposed, wherein the PSO algorithm is utilized to optimize both fuzzification and defuzzification parameters, thereby enhancing controller adaptability and precision. Moreover, a Centralized Agent Optimization (CAO) framework is integrated to accelerate convergence and improve overall computational efficiency. The proposed controller dynamically adjusts membership functions and rule weights in real time, enabling robust, stable, and rapid system responses even under sudden aerodynamic perturbations and variable payload conditions. Extensive simulation and experimental validations confirm the superior performance of the proposed method over classical PID, PSO-tuned PID, and conventional fuzzy logic controllers, demonstrating faster rise times, reduced overshoot, and minimized steady-state error. These findings significantly advance the development of intelligent UAV control systems by effectively combining swarm intelligence with human-like reasoning methodologies.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026Adaptive Vibration Suppression in High-Speed Precision Drives Using Multi-Modal Sensor Fusion and Actuator Parameter Tuning
Can, Erol
Background High-speed precision drive systems, such as servo motors and fast-steering platforms, are often affected by coupled torsional and bending vibrations. These vibrations reduce system stability, prolong settling time, and limit achievable control bandwidth, particularly in applications requiring high precision and rapid response. Purpose This study aims to develop a simulation-based adaptive vibration suppression approach capable of simultaneously mitigating torsional and bending vibrations while enhancing dynamic performance and control accuracy in high-speed precision drive systems. Methods A simulation model of a high-speed precision drive system was developed by integrating a distributed multi-modal sensor network with an adaptive control strategy. The system incorporates fiber Bragg grating (FBG) strain sensors, piezoelectric torque sensors, and MEMS accelerometers to monitor vibration modes. A real-time sensor-fusion algorithm identifies dominant vibration frequencies and modes, and an adaptive PD controller dynamically adjusts actuator parameters-such as torque limits, damping coefficients, and phase compensation-based on the simulated structural response under different disturbance scenarios. Results Simulation results clearly demonstrate the effectiveness of the proposed method. Time-domain analysis shows that peak torsional vibration amplitudes are reduced by 65%, while bending vibration amplitudes are reduced by 58%. RMS analysis indicates that torsional vibrations decrease from 0.021 rad to 0.008 rad, and bending vibrations decrease from 0.018 m to 0.007 m. In addition, the adaptive control strategy improves settling time by 40% and provides a more stable steady-state response compared to conventional fixed-gain controllers. Conclusions The results confirm that the proposed simulation-based adaptive vibration suppression system effectively reduces multi-mode vibrations and enhances system stability. By combining distributed sensing, real-time modal analysis, and adaptive actuator tuning within a simulation framework, the approach provides a robust and efficient solution, demonstrating strong potential for the development of self-sensing and self-tuning high-speed precision drive systems.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026A New High Gain Single-Switch Quadratic Boost Converter with Low Voltage Stress
Ting, Naim Suleyman; Ipek, Asli Seyda
Recent progress in DC microgrids necessitates high gain DC-DC converters for effective energy conversion. In this regard, this paper introduces a new high gain single-switch quadratic boost converter (HGS2QBC). This converter, comprising a switch, two inductors, four capacitors, and five diodes, incorporates a voltage multiplier cell (VMC) that provides an 8-times voltage gain at a 0.5 duty cycle. The salient features of the proposed converter are its high voltage gain, having only one switch, low voltage stress across semiconductor devices, and non-pulsating input source current. In addition to its high voltage gain, one of the most significant added-value features of the proposed converter is the presence of a single switch in its structure and the fact that the voltage stress on this switch is half of the output voltage. Furthermore, a 100 W, 200 V, and 20 kHz laboratory prototype is constructed to assess practical viability, and the related experimental results are provided. Experimental analysis confirms the converter's effectiveness in managing voltage and current waveforms across its components, reducing stress on the semiconductor elements and minimizing voltage levels across the diodes. Such design optimizations not only provide superior performance but also offer cost advantages that make the converter economically viable.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026Prediction of dimensional deviation and quality tolerance class in the production of AlSi10Mg alloy parts with laser powder bed fusion using machine learning algorithms
Siyambaş, Yusuf; Turgut, Yakup; Akdulum, Aslan
Metal-based workpieces can be produced additively with the selective laser melting (SLM) technique, which is one of the laser powder bed fusion (LPBF) methods. However, due to complex production parameters, the dimensional deviation and quality tolerance class of the produced parts cannot be predicted. This situation causes the need for secondary operations such as turning, milling, grinding, or polishing after production and even increases the amount of scrap. These processes are quite costly as they require extra time, labor, and machinery. This study aims to clarify complex manufacturing parameters, predict dimensional deviation with a high success rate before production, and categorize part quality tolerance classes with high accuracy. To examine the effect of manufacturing variables using dimensional accuracy, parts were produced at various laser power and scanning speeds, and features like length, width, thickness, and radius were measured. Dimensional changes were more significant at extreme parameter values and minimized at medium values. Additionally, extensive datasets were generated using manufacturing parameters and physics knowledge, and various machine learning models were applied and analyzed in detail. As a result of exploratory data analysis, dimensional deviation is estimated with a high success rate, while the part quality tolerance class can be categorized with a high precision rate. With the proposed method, proactive measures can be taken for possible errors before production. By effectively determining production parameters during the process planning phase, the part qualification process will become more efficient. Therefore, advantages such as reducing the cost of scrap parts, the absence of secondary processes, and saving cost and time will be achieved, and production comparable to traditional production methods will be possible.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026Automated fabric defect inspection with fuzzy c-means, conditional random fields and refined U-Net
Tastimur, Canan
In this study, multiple segmentation methods were applied sequentially to enhance the classification for fabric data. First, fuzzy c-means (FCM) segmentation was employed on fabric images, effectively separating in homogeneous regions. Subsequently, these results were refined using conditional random fields (CRF), which provided sharper and more accurate delineation of pixel boundaries. In the final stage, I applied the refined U-Net model to the segmentation results enhanced by CRF, ensuring the preservation of small details in complex and irregularly structured fabric images. In industrial applications such as fabric flaw identification, the distinct contribution of categorizing based on the segmentation results significantly enhanced classification capabilities, particularly in low-quality images. This innovative hybrid strategy serves as an effective technique for improving outcomes, especially in images with uneven textures. Compared to the original dataset, the results are markedly better and pave the way for future advancements in industrial fabric analysis procedures.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2026National-Scale Estimation of Brake-Wear Particulate Emissions From On-Road Vehicles in Türkiye: A 2024 Inventory with Uncertainty and Mitigation Scenarios
Demirci, Oğuz Kürşat
This research article develops a screening-level national inventory of airborne brake-wear particulate emissions from on-road vehicles in Türkiye for the year 2024. The scope is limited to brake wear only and does not include tyre wear, road wear, resuspension, or concentration and exposure modelling. The inventory combines TurkStat vehicle-kilometre statistics with EMEP/EEA Tier-2 brake-wear emission factors, including passenger-car powertrain differentiation to reflect regenerative-braking effects. Under nominal baseline assumptions, annual emissions are estimated at 5.67 kt•y-1 for PM10 and 2.26 kt•y-1 for PM2.5. Monte Carlo framework that propagates bounded uncertainty in total activity, vehicle-category composition, passenger-car powertrain shares, guidebook-anchored emission factors, and particle-size fractions, the national totals are characterised by a median (95% interval) of 5.67 (4.87-7.19) kt•y-1 for PM10 and 2.26 (1.87-2.90) kt•y-1 for PM2.5 Passenger cars account for approximately 45% of national PM10 emissions, followed by light commercial vehicles and tractor units. Illustrative, assumptiondependent scenario analysis indicates that PM10 could decrease to 4.95 kt•y-1 under partial uptake of low-emission brake technologies, to 5.28 kt•y-1 with greater use of auxiliary braking in heavy-duty vehicles, and to 5.47 kt•y-1 under a passenger-car fleet share of 10% HEV and 10% BEV. These scenario outcomes should be interpreted as indicative screening-level projections rather than empirical or policyevaluation results. Overall, the study provides a transparent brake-wear-only national baseline and a comparative framework for examining how selected assumptions influence estimated PM emissions in Türkiye.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026A Cost-Effective Ultra-High-Gain Single-Switch DC–DC Converter with Direct Power Transfer for Low-Voltage PV Applications
Sahin, Yakup; Ozgenel, Mehmet Cihat; Ting, Naim Suleyman
This paper presents a novel cost-effective, nonisolated ultra-high-gain single-switch DC–DC converter (UHGS2C) employing a voltage lift (VL) cell and a direct power transfer (DPT) mechanism, specifically designed for low-voltage photovoltaic (PV) applications. The proposed topology achieves an 8× voltage gain at a duty cycle of 0.5 using only a single active switch, three inductors, three capacitors, and five diodes, thereby reducing component count and control complexity compared with conventional high-gain converters. Through the DPT mechanism, a portion of the input energy is transferred directly to the load during the switch-on interval, thereby reducing the energy processed by the magnetic elements and lowering both switch current stress and capacitor voltage ratings. The steady-state analysis confirms that the maximum capacitor voltage is limited to half of the output voltage (VCmax = VO/2), enabling the use of compact, low–voltage-rated capacitors that improve power density and reduce cost. Both continuous and discontinuous conduction modes (CCM/DCM) are analyzed in detail, and a systematic design procedure, along with a comprehensive power loss model, is provided. To validate the theoretical analysis, a 200-W experimental prototype operating at 25-V input, 200-V output, and 50-kHz switching frequency was implemented. The prototype achieves a peak efficiency of 96.4%, while the closed-loop PI control verifies stable line- and load-regulation performance. Comparative results demonstrate that the proposed UHGS2C provides a favorable trade-off among voltage gain, efficiency, component stress, and compactness, making it a strong candidate for renewable energy applications such as PV systems.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2026An adaptive hybrid energy management system for UAVs integrating fuzzy logic, solar forecasting and real-time control
Can, Erol
This study presents a hybrid energy management system (EMS) for unmanned aerial vehicles (UAVs), integrating flexible photovoltaic (PV) panels with a high-capacity lithium-polymer (Li-Po) battery to enhance flight endurance and energy resilience. The proposed EMS features a multi-layered adaptive control architecture, combining fuzzy logic-based decision-making, short-term solar irradiance prediction using machine learning and closed-loop proportional-integral-derivative (PID) motor control. This architecture dynamically allocates power based on real-time solar irradiance, battery state of charge (SOC) and propulsion load. The approach aims to minimise battery stress while ensuring stable UAV operation under variable environmental conditions. Simulation results indicate that, without PV support, the UAV battery depletes in approximately 28 min. However, incorporating an 80 W PV panel extends the endurance to 37 min, and a 160 W effective PV configuration increases the flight time to over 50 min, while maintaining the SOC above 20%. This corresponds to a 79% improvement in endurance and nearly a 50% reduction in net battery energy consumption. The EMS effectively mitigates deep discharge cycles, improving battery health and operational lifespan. These findings demonstrate that the proposed hybrid EMS provides a scalable, adaptive and computationally efficient solution for balancing renewable and stored energy. It outperforms conventional static or single-source control strategies, particularly under fluctuating solar conditions.
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