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.Article Citation - WoS: 2Citation - Scopus: 3High-Pressure Processing of Traditional Hardaliye Drink: Effect on Quality and Shelf-Life Extension(MDPI, 2023) Atmaca, Bahar; Demiray, Merve; Akdemir Evrendilek, Gülsün; Bulut, Nurullah; Uzuner, SibelHardaliye, as one of the oldest and lesser known traditional beverages, is produced using red grape pomace from wine production. This drink production is achieved through lactic acid fermentation, with the addition of sour cherry leaves and mustard seeds-either heat-treated, grinded, or whole-in various concentrations. Hardaliye has a very short shelf life; thus, efforts have recently been made to process hardaliye with novel processing technologies in order to achieve shelf-life extension. Therefore, the high-hydrostatic-pressure (HHP) processing of hardaliye was performed to determine its impact on important properties, including in microbial inactivation and shelf-life extension, with respect to a Box-Behnken experimental design. Maximum log reductions of 5.38 & PLUSMN; 0.6, 5.10 & PLUSMN; 0.0, 5.05 & PLUSMN; 0.2, and 4.21 & PLUSMN; 0.0 with HHP were obtained for Brettanomyces bruxellensis, total mesophilic aerobic bacteria, Lactobacillus brevis, and total mold and yeast, respectively. The processing parameters of 490 MPa and 29 & DEG;C for 15 min were found as the optimal conditions, with the response variables of an optical density at 520 nm and the inactivation of L. brevis. The samples processed at the optimal conditions were stored at both 4 and 22 & DEG;C for 228 d. While the non-treated control samples at 4 and 22 & DEG;C were spoiled at 15 and 3 d, the HHP-treated samples were spoiled after 228 and 108 d at 4 and 22 & DEG;C, respectively.Article Citation - WoS: 4Citation - Scopus: 4Optimizing the Dispersion of Calcium Phosphate Nanoparticles for Cellular Studies Using Statistical Design of Experiments(Elsevier, 2023) Önder, Anıl Can; Tomak, Aysel; Öksel Karakuş, CeydaThe in vitro experimentation of ceramic nanoparticles often requires their dispersion in liquid media without causing particle clumps or deteriorating sample integrity. However, the dispersion of nanoparticles using the available protocols rarely leads to stable and uniform dispersions which, in turn, raises concerns about the validity, repeatability and comparability of the findings observed in vitro. Moreover, the ability to control the final dispersion quality of ceramic nanoparticles is an essential step to obtaining optimized nanoceramic materials with desired functionality and to enhancing their performance in subsequent applications. While the need to have a comprehensive guideline for the dispersion of nanoparticles has led to several published documents and protocols, the dispersion methodology of ceramic nanoparticles and the relative contribution of the experimental parameters to the quality of resulting dispersion are still not clear. Here, we employed the statistical design of experiment (DoE) approach to systematically assess the magnitude and source of variation in dispersion quality of two different ceramic nanoparticles, hydroxyapatite and tricalcium phosphate. Using the first-order Plackett-Burman Design (PBD), nanoparticle concentration, pH and the presence of an additive were identified as the most critical factors influencing the resulting hydrodynamic size and zeta potential of the ceramic nanoparticles. Optimization using a second-order Central Composite Design (CCD) yielded a set of quadratic regression equations that were used to predict the hydrodynamic size or zeta potential of ceramic nanoparticles with high accuracy (R2, 0.88–0.92). The results of PBD screening and CCD optimization experiments were employed to prepare nanoparticle dispersions of different quality, which were then used to compare the effect of aggregation on the viability of human osteosarcoma (SaOS-2) cells. Overall, the results of this study provided insight into the role that various experimental parameters play in the colloidal stability and dispersion of ceramic nanoparticles. © 2023Article Citation - WoS: 11Citation - Scopus: 12An Improved Passive Tuned Mass Damper Assisted by Dual Stiffness(Elsevier, 2023) Roozbahan, Mostafa; Turan, GürsoyA tuned mass damper (TMD) is one of the oldest and most commonly used passive control devices attached to structures to absorb lateral loads of energy from main systems. In the last decades, several novel tuned mass dampers have been designed to increase the performance of TMDs in decreasing the structural responses during excitation vibrations. Moreover, several formulations and numerical optimization methods have been developed to optimize the TMDs parameters. This paper proposes a novel passive tuned mass damper with dual stiffness (DSTMD). The DSTMD includes mass, primary and secondary springs, dashpot, and motion limiting chamber. The performance of DSTMDs depends on their properties such as mass, primary and secondary stiffness, damping coefficient, and the length of the motion limiting chamber. Thus, a metaheuristic optimization algorithm, called the Mouth Brooding Fish algorithm, was used to optimize the DSTMDs parameters. The effectiveness of the optimum DSTMD on two different linear ten-story structures under several earthquakes has been studied and compared with the effectiveness of classical optimum TMDs. According to the study, optimum DSTMDs generally show better effects for certain excitations, and as an average performance, they are superior compared to the classical optimum TMDs in reducing maximum displacement of the buildings. At last, structural yielding is considered, and the performance analysis on this structure shows that the DSTMD has a superior effect in reducing the maximum displacement and is among the best methods for the calculated absolute yielding amount.Article Citation - WoS: 22Citation - Scopus: 22Multiparameter-Based Product, Energy and Exergy Optimizations for Biomass Gasification(Elsevier, 2021) Çağlar, Başar; Tavşancı, Duygu; Bıyık, EmrahThe thermodynamic modelling of biomass gasification was studied by using Gibbs free energy minimization approach. Different from the studies using the same approach, the simultaneous presence of all gasifying agents (air, H2O and CO2) was considered and a multiparameter optimization was applied to determine the synergetic effect of gasifying agents for hydrogen, syngas with a specific H2/CO ratio and methane production. The performance of gasification was assessed by using technical and environmental performance indicators such as product yields, cold gas efficiency, exergy efficiency, CO2 emission and the heat requirement of the gasifier. The results show that the simultaneous presence of gasifying agents does not create considerable changes in syngas yield, H2 yield, methane yield, CGE and exergy efficiency while it allows to tune the H2/CO ratio and the heat requirement of the gasifier. The highest syngas yield is observed at T > 1100 K and 1 bar and when SBR > 0.5 and/or CBR > 0.8 with the absence of air, at which CGE changes between 114% and 122% while exergy efficiency is between 77% and 86%. The results prove that CO2 offers several advantages as a gasifying agent and suggests that CO2 recycling from gasifier outlet is a useful option for the biomass gasification.Article Citation - WoS: 16Citation - Scopus: 22Optimum Design of Fatigue-Resistant Composite Laminates Using Hybrid Algorithm(Elsevier Ltd., 2017) Deveci, Hamza Arda; Artem, Hatice SeçilIn this study, a fatigue life prediction model termed as Failure Tensor Polynomial in Fatigue (FTPF) is applied to the optimum stacking sequence design of laminated composites under various in-plane cyclic loadings to obtain maximum fatigue life. The validity of the model is investigated with an experimental correlation using the data available in the literature. The correlation study indicates the reliability of FTPF, and its applicability to different composite materials and multidirectional laminates. In the optimization, a hybrid algorithm combining genetic algorithm and generalized pattern search algorithm is used. It is found by test problems that the hybrid algorithm shows superior performance in finding global optima compared to the so far best results in the literature. After the verifications, a number of problems including different design cases are solved, and the optimum designs constituted of discrete fiber angles which give the maximum possible fatigue lives are proposed to discuss. A comparison study is also performed with selected design cases to demonstrate potential advantages of using non-conventional fiber angles in design.Article Citation - WoS: 126Citation - Scopus: 138Thermal Performance Optimization of Hollow Clay Bricks Made Up of Paper Waste(Elsevier Ltd., 2014) Sütçü, Mücahit; Del Coz Diaz, Juan Jose; Alvarez Rabanal, Felipe Pedro; Gençel, Osman; Akkurt, SedatIn this paper, the thermal behavior of hollow clay bricks made up of paper waste has been studied and their thermal performance has been optimized. On the one hand, both strength and thermal properties of different paper waste concentrations have been obtained by means of laboratory tests. Thermal conductivity of the microporous brick materials with additives produced in this study reduced from 0.68 W/m K to 0.39 W/m K compared with that of the sample without additives. On the other hand, the finite element method (FEM) has been applied to the nonlinear numerical thermal analysis of three different hollow bricks, including radiation and convection phenomena inside holes. Next, using the design of experiments (DOE) over the FEM models, several parameters such as the material conductivity, the convection and radiation properties and the mean brick temperature have been studied. In general, the thermal resistance is a nonlinear function that depends on the geometry of the recesses, the material properties and the temperature distribution. In all analyzed cases, minimizing the material thermal conductivity of bricks and decreasing the recesses surface radiation emissivity caused a lower thermal transmittance in the brick. Finally, the most important conclusions and the main findings of this research are exposed.Article Citation - WoS: 69Citation - Scopus: 89Joint Optimization for Object Class Segmentation and Dense Stereo Reconstruction(Springer Verlag, 2012) Ladicky, Lubor; Sturgess, Paul; Russell, Chris; Sengupta, Sunando; Baştanlar, Yalın; Clocksin, William; Torr, Philip H.S.The problems of dense stereo reconstruction and object class segmentation can both be formulated as Random Field labeling problems, in which every pixel in the image is assigned a label corresponding to either its disparity, or an object class such as road or building. While these two problems are mutually informative, no attempt has been made to jointly optimize their labelings. In this work we provide a flexible framework configured via cross-validation that unifies the two problems and demonstrate that, by resolving ambiguities, which would be present in real world data if the two problems were considered separately, joint optimization of the two problems substantially improves performance. To evaluate our method, we augment the Leu-ven data set (http://cms.brookes.ac.uk/research/visiongroup/ files/Leuven.zip), which is a stereo video shot from a car driving around the streets of Leuven, with 70 hand labeled object class and disparity maps. We hope that the release of these annotations will stimulate further work in the challenging domain of street-view analysis. Complete source code is publicly available (http://cms.brookes.ac.uk/ staff/Philip-Torr/ale.htm). © 2011 Springer Science+Business Media, LLC.Article Citation - WoS: 103Citation - Scopus: 132Break-Even Analysis and Size Optimization of a Pv/Wind Hybrid Energy Conversion System With Battery Storage - a Case Study(Elsevier Ltd., 2009) Ekren, Orhan; Yetkin Ekren, Banu; Özerdem, BarışThis paper aims to show an optimum sizing procedure of autonomous PV/wind hybrid energy system with battery storage and a break-even analysis of this system and extension of transmission line. We use net present value (NPV) method for the comparison of autonomous hybrid energy system and extension of transmission line cases. The case study is completed for the satisfaction of the electricity consumption of global system for mobile communication base station (GSM) at Izmir Institute of Technology Campus Area, Urla, Izmir, Turkey. First, we optimize the PV/wind energy system using response surface methodology (RSM) which is a collection of statistical and mathematical methods relying on optimization of response surface with design parameters. As a result of RSM, the optimum PV area, wind turbine rotor swept area, and battery capacity are obtained as 3.95 m2, 29.4 m2, 31.92 kW h, respectively. These results led to $37,033.9 hybrid energy system cost. Second, break-even analysis is done to be able to decide the optimum distance where the hybrid energy system is more economical than the extension of the transmission line. The result shows that, if the distance between national electricity network and the GSM base station location where the hybrid energy system is assumed to be installed is at a distance more than 4817 m, the installation of hybrid energy system is more economical than the electricity network.