Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article AI-Supported Seismic Performance Evaluation of Structures: Challenges, Gaps, and Future Directions at Early Design Stages(Elsevier Sci Ltd, 2026) Ak, Fatma; Ekici, Berk; Demir, UgurThis study reviews 91 journal articles that intersect with earthquake-resistant building design and artificial intelligence (AI)- based modeling, utilizing machine learning, deep learning, and metaheuristic optimization algorithms. Previous reviews on AI applications have examined engineering problems without considering the impact of architectural design parameters and structural irregularities on seismic performance. This review discusses the role of AI in integrating architectural design variables and seismic performance objectives, highlighting challenges, gaps, and future directions in the early design phase. The reviewed articles demonstrate that AI is successful in addressing seismic performance objectives; however, a holistic framework for assessing architectural and structural variables has not been presented. The review highlights key findings, gaps, and future directions for those involved in earthquake-resistant building design utilizing AI.Article Artificial Intelligence for Improving Thermal Comfort through Envelope Design in Residential Buildings: Recent Developments and Future Directions(Elsevier Science Sa, 2026) Bayraktar, Arda; Ekici, BerkEnvelopes are vital components for improving thermal comfort in almost all building typologies. Yet, the design and analysis of envelopes are complex, as they involve multiple aspects and various parameters, ensuring comfort standards. Improving thermal comfort in residential buildings is within the scope of researchers to suggest sustainable design alternatives that consider multiple performance aspects and design parameters. Previous review articles have focused on improving thermal performance in residential buildings from the perspective of envelope technology, materials, and design strategies. However, none of them investigated current developments using artificial intelligence (AI), which inevitably supports decision-making in complex circumstances for a sustainable built environment. This review examines the contribution of AI methods, which consist of metaheuristic optimization and machine learning algorithms as sub-branches, to envelope parameters. The paper systematically reviews 95 relevant works on AI, including early approaches, to provide a comprehensive overview of current developments, following PRISMA guidelines. The results showed that early applications considered conventional approaches to improve thermal comfort and energy performance, which mostly limit the results to specified cases. On the other hand, studies utilizing AI methods dealt with numerous parameters, allowing them to cope with complex envelope systems in a reasonable amount of time. The study addresses relevant research questions related to the trends, research methods, system types, AI methods, data types, and their relation to performance and envelope parameters. The study also provides actionable insight, underlining gaps and future works for utilizing machine learning methods in the reviewed research domain.Conference Object Developing Machine Learning Models to Predict Outdoor Thermal Comfort of Kinetic Shading Devices: An Approach for Global Optimization(Education and Research in Computer Aided Architectural Design in Europe, 2025) Dağlier, Y.; Ekici, B.; Korkmaz, K.Utilizing artificial intelligence (AI) methods in the design process supports the achievement of sustainable alternatives during the conceptual design. In various AI methods, optimization and machine learning (ML) algorithms are the most common methods to develop predictive models and discover favorable design alternatives with significantly reduced computational time. Recent works focused on limited datasets, as well as the evaluation of the developed prediction models based on collected data. During the optimization process of complex design problems, the number of design parameters becomes enormous; thus, search areas contain many design alternatives that might lead the search outside of the collected data. Therefore, evaluating the accuracy of prediction models only based on the collected samples may result in scenarios where the predicted outcome during the optimization process aligns with an unrealistic solution. This study investigates how accurately prediction models developed using different ML algorithms can perform in optimization processes. The proposed framework is used to cope with outdoor thermal performance, considering kinetic shading devices with rigid origami techniques. A parametric shading device model with kinematic principles and 10 design parameters is created in Grasshopper 3d. LadyBug is used to analyze the performance of the universal thermal climate index (UTCI). To minimize the UTCI, the radial basis function optimization (RBFOpt) algorithm in the Opossum plugin is used. To compare the optimization results with the prediction results, multiple linear regression, support vector machines, random forest, polynomial regression algorithms, and artificial neural networks (ANN) are developed to predict outdoor thermal comfort performance targets on each collected data set with 2000 samples. Results showed that ANN models can provide more accurate predictions during the optimization process. The paper aims to discuss the way ML algorithms are applied and evaluated for ML-based optimization domains in design problems. © 2025, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.Article Comparative Optimization of Hot Water and Citric Acid Extraction Methods for Sericin Recovery From Silk Cocoons: In Vitro Antioxidant and Antidiabetic Activities(Springer, 2026) Sincar, Bahar; Ozdemir, Feyza; Bicakci, Beyza Tutku; Erdem, Cansu; Yalcin, Dilek; Alamri, Abdulhakeem S.; Bayraktar, OguzSilk sericin, a hydrophilic protein derived from Bombyx mori cocoons, has attracted increasing interest due to its antioxidant, moisturizing, and enzyme-inhibitory properties. Efficient extraction is essential to preserve its biofunctional potential. In this study, sericin was extracted using hot water and 1.25% (w/v) citric acid using autoclave-based heating to achieve pressurized conditions above 100 degrees C. A Box-Behnken Response Surface Methodology (RSM) was applied to systematically evaluate the effects of extraction parameters (temperature and time) and to optimize five key response variables: yield, purity, molecular weight and polydispersity index (PDI), total antioxidant capacity (ABTS), and alpha-glucosidase inhibition activity. The results revealed that higher temperatures (125 degrees C) produced the maximum sericin yield, while moderate conditions (115 degrees C for 45 min) ensured better preservation of antioxidant and antidiabetic activities. Hot acid extraction resulted in significantly enhanced purity and enzymatic inhibition compared to hot water extraction. Sericin fractions above 7 kDa exhibited the strongest bioactivity, as reflected by lower IC50 values in both ABTS and alpha-glucosidase inhibition assays. The optimized hot water citric acid-based method yielded 24.00% sericin with 100.00% purity and an IC50 of 0.67 mg/mL for alpha-glucosidase inhibition. This study compares hot water and hot acid autoclave extractions using Box-Behnken design and evaluates their effects on sericin yield, purity, and bioactivities. Citric acid-based extraction produced higher purity and stronger alpha-glucosidase inhibition, while hot water extraction preserved antioxidant potential more effectively. These findings support the use of citric acid as an eco-friendly and scalable extraction agent and highlight the potential of sericin in biomedical and nutraceutical applications.Article A Novel ORC-PEM Integrated System for Sustainable Hydrogen Production from Low-Grade Waste Heat in Oil Refineries(Elsevier, 2025) Nazerifard, Reza; Mohammadpourfard, Mousa; Zarghami, RezaThis study presents an integrated multi-generation system for sustainable hydrogen production by harnessing low-grade waste heat from the overhead stream of the NHT unit's stripper column in an oil refinery. The proposed system integrates an ORC with a PEM electrolyzer, forming a novel energy solution that efficiently converts waste heat into clean hydrogen through electricity generation. A detailed model of the proposed system is developed, enabling a comprehensive assessment of its performance from thermodynamic, economic, and environmental viewpoints. At the same time, key operational parameters are optimized using the RSM-BBD method to minimize the hydrogen production cost, thereby enhancing the system's economic viability and practical implementation. The results demonstrated that the system achieves a yearly hydrogen production of 304.53 tons under optimized conditions, for 2.36 $/kg. The integrated system's overall energy and exergy efficiencies are calculated at 8.62 % and 33.43 %, respectively, demonstrating its high thermodynamic performance. Additionally, the system mitigates 3047 tons of CO2 annually by displacing conventional hydrogen production methods.Conference Object Optimized Cooperative Routing for Autonomous Vehicles(Institute of Electrical and Electronics Engineers Inc., 2025) Saydam, B.; Ayav, T.Current traffic control systems - comprising traffic lights, signs, and right-of-way rules - are often inadequate, leading to accidents, excessive fuel consumption, and unnecessary delays. Three key scenarios contribute to these inefficiencies. First, drivers may run red lights due to a lack of traffic signal timing information, leading to indecision when encountering a yellow light, a major cause of accidents. Second, abrupt speed changes in response to traffic signals force drivers to brake suddenly, increasing fuel consumption and travel time. For instance, a driver may accelerate at a green light only to encounter a red light shortly after, resulting in inefficient fuel use. Lastly, vehicles often remain stopped at red lights despite no cross-traffic, leading to wasted fuel and time.This study simulates these scenarios using the Eclipse SUMO tool, with results aligning with expected inefficiencies. The problem is mathematically modeled using Pyomo, and a centralized optimization approach is applied to enhance traffic synchronization and efficiency. By dynamically calculating vehicle velocities based on real-time traffic data, the study proposes an optimized, traffic light-free system. The results demonstrate improved fuel efficiency, reduced accidents, and minimized delays, highlighting the potential of centralized optimization in modern traffic management. © 2025 Elsevier B.V., All rights reserved.Article Citation - Scopus: 8Optimal Design of the Type Iii Hydrogen Storage Tank for Different Carbon/Epoxy Materials by Modified Differential Evolution Method(MIM RESEARCH GROUP, 2019) Ayakdaş,O.; Aydın,L.; Savran,M.; Küçükdoğan,N.; Öztürk,S.In this study, the main objective is to minimize the failure index of a cylindrical laminated composite hydrogen storage tank under internal pressure. The first step is to obtain the distribution of stress components based on Classical Laminated Plate Theory (CLPT). The second is to evaluate the burst pressure of the tank according to three different first ply failure criteria and then to compare the results with the experimental and numerical ones from literature. In the final part of the study, the best possible combination of winding angles, stacking sequences and thicknesses of laminates satisfying minimum possible stress concentration will be obtained for different Carbon/Epoxy materials by Differential Evolution Method. The stress components and, the burst pressures reached according to Hashin-Rotem, Maximum Stress, and Tsai-Wu first-ply failure criteria, have been complied with experimental and numerical results in the literature for Type III pressure vessels. Manufacturable Type-III tank designs have been proposed satisfying the 35 MPa burst pressure for different Carbon/Epoxy materials. © 2019 MIM Research Group. All rights reserved.Book Part Citation - Scopus: 1A New Stable Solar System for Electricity, Cooling, Heating, and Potable Water Production in Sunny Coastal Areas(Springer, 2023) Khani, Leyla; Mohammadpourfard, MousaNowadays, more attention is paid to provide clean energy products with low environmental pollution in a decentralized way. Many coastal rural areas suffer from freshwater and electricity scarcity, especially in hot weather condition. Meanwhile, these regions have a great access to intense solar radiation and seawater. Hence, it seems logical to use the available solar energy in those places to provide to necessities like power, heating, and cooling. A new solar cooling, power, heating, and freshwater production system is designed, evaluated, and optimized in this research. The proposed system is composed of several subsystems to generate each product with high efficiency and reliability. Solar energy is unavailable at night, so molten salt energy storage is used to establish the steady operation of the system. Then, the system is evaluated from thermodynamic and exergoeconomic viewpoints, and a parametric study is accomplished to study the effect on the system performance of key variables. In the end, the system is optimized to determine its best operating condition for different cases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Article Citation - WoS: 1Citation - Scopus: 1Approaches To Optimization for Movable Shading Systems: a Review of Optimization Methods and Tools(Znack Publishing House, 2021) Keskinel, Yeşim; İlal, Mustafa EmreStudies show that movable shading systems have lots of benefits for building performance. Minimizing energy consumption and maximizing daylight usage are natural expectations when using these systems. To find optimal solutions for these systems, different methods have been used. Today, optimization methods are used to solve this problem. In the literature, there are few studies about optimization of movable shading systems. This paper aims to identify different movable shading systems, optimization types, and computational optimization tools that are used. Research findings and future projections based on the reviewed papers are summarized.Article Citation - Scopus: 1Sizing of Autonomous Wind/Solar Hybrid Energy Conversion Systems for Urla, Turkey(ACTA Press, 2009) Özerdem, Barış; Ekren, OrhanIn this paper, an optimum sizing procedure of autonomous hybrid (wind + solar) energy system is presented which can be used to satisfy the requirements of given load distribution. The main purpose of this study is to find out an appropriate wind-photovoltaic hybrid energy system to satisfy electricity consumption of GSM (Global System for Mobile communication) base station at Izmir Institute of Technology Campus Area, Urla, Izmir, Turkey. To do this, monthly average daily solar radiation and wind speed data are collected. The monthly average wind speeds are measured at 10 m height during 3 years period on Izmir Institute of Technology Campus Area. The monthly average wind speed values are obtained between 5.7 and 7.7 m/s, on the other hand, the monthly average daily value of solar radiations on horizontal surfaces are ranged from 1.4 to 6.9kWh/m2 at Izmir Institute of Technology Campus Area. The hybrid system considered in the present analysis consists of one 5kW nominal power wind energy conversion systems (WECS), 21.82 m2 of photovoltaic (PV) panels (18 mono crystal PV panels each having 75 W power output) together with a battery storage system.