Yazarlar
- Tozlu, Alperen(13)
- Ergün, Mustafa(11)
- Artar, Musa(10)
- Cuce, Erdem(9)
- Cuce, Pinar Mert(8)
- Yurdakul, Muhammet(8)
- Imamoglu, Ilyas Kays(7)
- Esmer, Yusuf(6)
- Isik, Cem(6)
- Ongan, Serdar(6)
- Can, Ömer(5)
- Guclu, Tamer(5)
- Kahveci, Hakan(5)
- Tayfur, Bilal(5)
- Yilmaz, Fatih(5)
- Ates, Sevket(4)
- Guler, Evrim(4)
- Gökçe, H.S.(4)
- Karakus, Murat(4)
- Tapkın, Serkan(4)
- Tercan, Emre(4)
- Çaglar, Hakan(4)
- Özahi, Emrah(4)
- Abdioglu, Murat(3)
- Abusoglu, Aysegul(3)
- Altuntas, Serkan(3)
- Ateş, Şevket(3)
- Ayberkin, Doruk(3)
- Aydin, Rahman(3)
- Cakici, Ziya(3)
- Cakir, Mehmet(3)
- Carbas, Serdar(3)
- Dereli, Turkay(3)
- Engin, Mustafa Alptekin(3)
- Gökçe, H. Süleyman(3)
- Güngör, Okan(3)
- Kiral, Adnan(3)
- Kuziboev, Bekhzod(3)
- Murat, Yetis Sazi(3)
- Okur, Fatih Yesevi(3)
Yayınlar
- MakaleAçık Erişim2026Role of artificial intelligence in the process of innovation management: dimensions, themes and examples
Esmer, Yusuf
This study aims to discuss the role of artificial intelligence (AI) in innovation management in a conceptual framework. In line with the purpose of the research, the conceptual analysis technique was used within the scope of qualitative research methods. In this context, the effects of AI on innovation management are explained based on relevant scientific research, reports and sectoral examples. How AI is integrated with innovation management processes, its application areas, and its potential future effects are examined. It has been concluded that AI affects important elements of organizations such as knowledge management, organizational flexibility, organizational innovation, decision-making, sustainable growth, organizational culture and strategic human resources management and that AI makes innovation management processes more efficient and effective with the opportunities it offers in areas such as big data analysis, machine learning and automation. The role of AI in innovation management stands out as an important element for modern organizations and reveals that research in this field should be examined in depth. This study examines the role of AI in innovation management processes within a conceptual framework and recommends that future studies conduct empirical research to expand on this topic. This study provides important in terms of revealing the role of AI in innovation management based on the relevant literature and with examples and will contribute to the literature.
- MakaleAçık Erişim2026COVID-19 Sonrası Tedarik Zinciri Gecikmelerine Dair Ampirik Kanıtlar: APEC Ekonomileri Örneği
Okur, Fatih
Bu çalışma, 2015–2023 döneminde APEC ülkelerinde tedarik zinciri gecikmelerinin temel belirleyicilerini analiz etmektedir. Panel veri analizi yoluyla COVID-19 pandemisi, ekonomik gelişmişlik düzeyi ve bölgesel ticaret anlaşmalarının etkileri incelenmiştir. Ayrıca, modelde sanayi üretimi, dış ticaret hacmi, ticaret açıklığı, enflasyon oranı ve doğrudan yabancı yatırımlar gibi kontrol değişkenlerinin de tedarik zinciri gecikmeleri üzerindeki etkileri analiz edilmiştir. Sabit etkiler modeline dayalı analiz sonuçları, ihracat ve ithalat hacmi, sanayi üretimi ve ticaret açıklığının gecikmeleri artırdığını; ekonomik büyüme oranı ile doğrudan yabancı yatırımların ise gecikmeleri azalttığını göstermektedir. Ayrıca, enflasyon oranı ve pandemi dönemi gecikmeler üzerinde anlamlı ve olumsuz etkiler yaratmıştır. Alt grup analizleri, bu ilişkilerin dönemsel ve ülke türüne göre farklılaştığını ortaya koymaktadır. Elde edilen bulgular, tedarik zinciri performansını artırmak isteyen politika yapıcılar için önemli yol göstericidir. Bu bağlamda lojistik altyapının güçlendirilmesi, fiyat istikrarının korunması ve esnek tedarik stratejilerinin geliştirilmesi önerilmektedir.
- MakaleYalnız künye2026Scopus SJRQ2Analyzing IPO Performance on Borsa Istanbul: A Hybrid Econometric and Machine Learning Framework (2013-2025)
Ayberkin, Doruk
This study examines the determinants of the performance of initial public offerings (IPOs) conducted by 237 firms across 38 sectors on the Istanbul Stock Exchange between 2013 and 2025, using a hybrid analytical framework. To analyze the impact of sector characteristics, firm-level financial indicators, supply structure, and market timing on the returns of USD-denominated IPOs, this study combines heteroskedasticity-resistant ordinary least squares (OLS) regression with tree-based ensemble machine learning algorithms (random forest, XGBoost) and benchmark models (support vector regression, artificial neural network). The distributional characteristics of returns from IPOs highlight the use of nonlinear modelling techniques characterized by high positive skewness (5.12) and excess kurtosis (45.24). Our findings reveal significant sectoral heterogeneity. According to the findings, the Financial Services and Fisheries sectors showed statistically significant superior performance, while the Metal Mining, Insurance, and Construction sectors underperformed. Transportation and Storage exhibited the highest point estimate but did not reach conventional significance levels. The XGBoost machine learning model, with an R 2 of 0.869 and a mean absolute error (MAE) of 17.87, achieved superior single-split prediction accuracy compared to the OLS method, which yielded an R 2 of 0.220. However, cross-validation analyses indicated that all models exhibited limited out-of-sample generalizability (best CV R 2 = 0.04). The Diebold-Mariano test, conducted to compare prediction performance, confirmed that the artificial neural network (ANN) model provided a statistically significant improvement over the OLS method (DM = 2.121, p = 0.034). The SHAP value analysis used in the models reveals how each feature affects the final predictions, the relative importance of each feature, and the model's dependence on feature interactions. It identifies the IPO price (USD), the USD/TRY exchange rate, and the size of the supply as the most effective estimators with economically significant nonlinear interactions. The study aims to demonstrate the comparative advantages and limitations of ensemble learning under abnormal financial data conditions by presenting detailed sectoral evidence across 38 sectors. In this way, it aims to contribute to the IPO literature in emerging market economies by offering viable policy recommendations for investors, issuers, and regulators in Turkish capital markets.
- MakaleYalnız künye2026Scopus SJRQ2Experimental investigation on hybrid parabolic trough collector and thermoelectric generator system for energy, economic, and environmental aspects
Cuce, Pinar Mert; Guclu, Tamer; Cuce, Erdem; Bouabidi, Abdallah; El Hadi Attia, Mohammed
This study experimentally investigates the thermal and electrical performance, economic feasibility, and environmental impacts of a hybrid energy system integrated with a parabolic trough collector (PTC) and thermoelectric generator (TEG). In the established system, solar energy is converted into electrical and thermal energy using a steam turbine and TEG. Experimental data indicate that the system operates with an average efficiency of 71.44%, which varies depending on the intensity of solar radiation. The overall energy efficiency of the system is calculated as 14.51%. In the economic analysis, the payback period of the designed system is approximately 5.4 years, while the levelised cost of energy production (LCOE) is calculated to be 0.075 USD kWh−1. The environmental assessment indicates that the system can prevent 356.18 kg of CO2 emissions annually and save approximately 1499.72 L of water. These findings demonstrate that hybrid systems offer an economically and environmentally sustainable and efficient alternative to energy production.
AtıfScopus1WoS2OpenAlex2
İncele - MakaleAçık Erişim2026Scopus SJRQ1Structural condition assessment of the Bamsı Beyrek observation terrace in Bayburt, Türkiye, on autonomous updated FEMs
Ergün, Mustafa; Tayfur, Bilal; Güneş, Erdi
This study involves detailed numerical and experimental investigations to assess the current structural condition of the Bamsı Beyrek steel observation terrace in Bayburt, Türkiye. The numerical dynamic characteristics of the structure were obtained by free vibration analysis conducted on the preliminary finite element model, while the experimental ones were determined through ambient vibration testing. The ultimate finite element models representing the actual state of the structure were developed through the model updating process based on the principle of minimizing the differences between numerical and experimental dynamic characteristics via the Teaching-Learning Based Optimization Algorithm. Load types and their characteristic values, potentially impacting the observation terrace during its service life, were identified according to national and international code standards. The internal forces obtained from the analysis conducted on the updated model under the influence of these loads were combined using various load combinations. The structure was then statically and dynamically checked based on the most critical responses calculated from these combinations. Structural responses are evaluated based on distributions in PMM ratios on the structure, PMM ratios of all elements according to the combination that causes the most adverse values, and maximum displacements. Consequently, considering all the findings obtained from the assessments conducted on the finite element model, which reflects the current state of the observation terrace under various loads, it has been concluded that the structure is statically and dynamically reliable and does not require any repair or strengthening procedures.
AtıfScopus1WoS1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ1Enhanced Absorption-Dominant EMI Shielding Performance of Pyramidal Cementitious Composites Incorporating Recycled Plastics and Magnetite Minerals for 5G Applications
Cakir, Mehmet; Engin, Mustafa Alptekin; Camuzcuoglu, Murat
In this study, waste polypropylene (PP) and magnetite (Fe3O4) mineral-reinforced cement-based pyramidal composite structures were designed, manufactured, and experimentally characterized to reduce electromagnetic interference (EMI) problems in the 3.3–4.9 GHz frequency band for 5G communication systems. Unlike traditional planar concrete surfaces, the aim was to minimize surface reflections and obtain an absorption-dominant shielding mechanism by providing gradient impedance matching through the pyramidal geometry. Although the use of carbon-based nanomaterials is common in the current literature, their high cost and corrosion risks limit their large-scale applications. This study involves the evaluation of waste polypropylene disposal and self-enriching magnetite mineral together. Theoretical analyses were supported by the Lichtenecker Logarithmic Mixing Rule and the Maxwell–Garnett model, and seven different mixing scenarios (S1–S7) were measured using the free-space method with a Libre vector network analyzer. Experimental results showed that the pure concrete sample exhibited predominantly reflective behaviour, with shielding performance improving significantly as the filler ratio increased. The S4 sample, containing 15% PP and 10% magnetite, offered broadband and balanced absorption performance, while the S7 sample, containing 25% PP and 25% magnetite, provided the highest shielding effectiveness with reflection below −10 dB across the entire band and transmission loss reaching −65 dB.
- MakaleAçık Erişim2026Scopus SJRQ2Analysis of thermal energy storage in batch processes using phase change materials
Kaya, Nur Efşan; Ceviz, Mehmet Akif; Afshari, Faraz; Mandev, Emre; Köksal, Hüseyin
Batch reactors are widely utilized in the chemical, pharmaceutical, and food industries due to their simplicity, ease of operation, and maintenance. However, efficient energy management remains a key challenge, especially for systems operating under intermittent conditions. While phase-change materials (PCMs) offer potential for improving energy efficiency by storing and reusing waste heat, integrating heat storage within reactors can compromise their volume and design. This study introduces a novel approach by designing and experimentally testing a PCM heat battery positioned outside the reactor to reduce energy consumption cost in batch processes. By focusing on peak load shifting, the PCM heat battery stores thermal energy during off-peak periods, reducing operational costs and enhancing energy efficiency. The results indicate that energy operating costs can be significantly reduced with a PCM heat battery. Specifically, utilizing the PCM battery under a three-time tariff allows for the efficient use of energy stored at night, reducing the energy cost per batch process by approximately 8%, from 1.72 TL ($0.041) to 1.59 TL ($0.037) for facilities starting operations at 08:00. Furthermore, the findings suggest potential applications in systems like solar energy and highlight the benefits of peak load shifting, offering a sustainable and cost-effective solution for energy management in batch processing.
AtıfScopus1WoS1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ1Optimizing Budget Allocation for Digital Health Investments Using Metaheuristic Algorithms: A Cost–Impact Analysis for Public Health Systems
Dayi, Faruk; Erdogdu, Aylin; Esmer, Yusuf; Yildiz, Ferah; Ganji, Farshad
Background: In the era of digital transformation, public health systems increasingly rely on digital technologies to improve accessibility, efficiency, and patient outcomes. However, policymakers face significant challenges in allocating limited resources across competing digital health investments characterized by uncertainty and dynamic impacts. Methods: This study introduces the Adaptive Impact–Cost Optimization Theory (AICOT), a hybrid framework integrating fuzzy logic and genetic algorithms to optimize digital health investment portfolios. The model defines the Investment Priority Score (IPS) as a function of cost, expected impact, and implementation feasibility, enabling structured evaluation under uncertainty. A fuzzy inference system with centroid-based defuzzification is used to convert qualitative assessments into quantitative scores, while optimization techniques identify optimal portfolios across different fiscal scenarios. The empirical analysis covers 15 OECD countries (2018–2024) using publicly available datasets. Sensitivity analyses assess robustness under inflation, cost shocks, and changing system priorities. Results: The findings show that blended investment strategies combining routine digital health tools with pandemic-oriented infrastructures yield the highest resilience-adjusted efficiency. Results remain stable across sensitivity scenarios, with pandemic surveillance consistently ranking as a top priority even under increased cost conditions. The model effectively captures cross-country heterogeneity, demonstrating adaptability to different levels of digital maturity. Conclusions: AICOT provides a transparent and policy-relevant decision-support framework that improves resource allocation efficiency and reduces unnecessary expenditures. These contributions support long-term financial sustainability and align with global health objectives, including Universal Health Coverage and Sustainable Development Goal 3 (Good Health and Well-being).
AtıfScopus1WoS1OpenAlex1
İncele - MakaleYalnız künye2026Scopus SJRQ1Resilience-oriented seismic retrofit of heritage masonry minarets using hybrid base isolation and supplemental damping
Ergun, Mustafa; Tonyali, Zeliha; Kiral, Adnan; Elias, Said
Historic masonry mosques represent a highly vulnerable class of cultural heritage structures whose seismic fragility stems from their complex geometries, heterogeneous material composition, and rigid load-transfer mechanisms. This study presents a resilience-oriented seismic performance improvement of the historic masonry minaret of the Bayburt Grand Mosque, a structure with limited lateral deformation capacity that challenges the applicability of conventional strengthening measures. To address this limitation, a hybrid retrofitting strategy is introduced, integrating lead rubber bearings (LRBs) with supplemental viscous dampers (VDs) at the foundation level. This combined system—implemented for the first time in a historic masonry minaret—aims to enhance energy dissipation and displacement control through a minimally invasive and architecturally compatible approach. Finite element analyses (FEA), coupled with MATLAB-supported optimization routines, were used to calibrate isolator stiffness and damper coefficients. Three configurations were evaluated: fixed-base, LRB-isolated, and hybrid LRB–VD systems. Nonlinear time-history analyses (NTHAs) using the 1992 Erzincan (Otlukbeli) earthquake record quantified displacements, stress–strain responses, and damage progression. Results show that while base isolation mitigates seismic demand, it remains insufficient under restricted deformation capacity. The proposed hybrid system reduces peak horizontal displacements from 22 cm to 12 cm, limits drift ratios below 0.17 %, and lowers maximum tensile stresses from 4.890 MPa to 0.490 MPa—well below the masonry tensile strength of 0.880 MPa. Two iterative analytical design methodologies are additionally introduced to derive effective isolator stiffness and viscous damping coefficients, enabling systematic integration into resilience-focused evaluation frameworks. Overall, the study advances reliability-based, conservation-compatible retrofitting practices for historic masonry minarets and supports sustainable strategies for seismic risk mitigation.
AtıfScopus8WoS7OpenAlex6İncele - MakaleAçık Erişim2026Scopus SJRQ1The effect of existing damage on the seismic performance of a historical masonry structure: a site-specific assessment
Tayfur, Bilal; Tunca, Osman; Artar, Musa; Çarbaş, Serdar
This study comprehensively evaluates the structural integrity and seismic performance of a historic masonry mosque, exhibiting significant settlement cracks, through an integrated approach combining field measurements and advanced numerical analyses. The Operational Modal Analysis (OMA) conducted to determine the dynamic characteristics of the structure. Field measurements revealed that the environmental vibrations originating from a nearby tram line causes significant amplitude incrase in one of the main columns. The dynamic characteristics of the structure obtained from field experiments are used to calibrate the numerical model via the Particle Swarm Optimization Algorithm. The calibrated numerical model, taking into account the existing cracks in the structure using contact elements, was subjected to nonlinear analysis in the time domain under 11 site-specific ground motion records selected in accordance with the procedures of the Turkish Building Seismic Code. This analysis examined the seismic performance and damage mechanisms of the structure. The findings revealed that while existing settlement cracks contribute to seismic energy dissipation through frictional sliding and gap opening mechanisms, they may also serve as potential failure initiation points under strong ground motions. This study’s integrated approach, combining dual-purpose OMA application and explicit crack modeling with contact elements, constitutes a novel methodological framework for the realistic seismic assessment of historic masonry structures with pre-existing damage.
AtıfScopus1WoS1OpenAlex2İncele - MakaleAçık Erişim2026Scopus SJRQ1A novel passive cooling configuration for photovoltaic panels based on bio-inspired heatsinks and nanoparticle-enhanced PCM
Cuce, Erdem; Cuce, Pinar Mert; Guclu, Tamer
This study presents the design, fabrication, and experimental evaluation of a novel passive thermal management system for photovoltaic (PV) modules that integrates a bio-inspired aluminium heatsink with a nanoparticle-doped phase change material (PCM). The proposed configuration aims to regulate the temperature of the PV module under real outdoor conditions without any external energy input. The bio-inspired heatsink was designed based on coral-like branching geometry to enhance natural convection and heat distribution within the PCM. The PCM, doped with metal-oxide nanoparticles (Al2O3, SiO2, TiO2) at a 2% mass fraction, provided additional latent-heat storage capacity and improved thermal conductivity. Experimental tests were conducted using two identical monocrystalline PV panels. The results demonstrated that the bio-inspired-cooled PV module effectively reduced surface temperature fluctuations by 8–15 °C and achieved a maximum efficiency improvement of 9.2% compared to the uncooled configuration. The integration of the PCM layer with the bio-inspired heatsink maintained a more stable operating temperature throughout the day, particularly during high-irradiance conditions. Hourly I-V and P-V analyses confirmed that the hybrid module consistently exhibited higher maximum power and efficiency values. Furthermore, the estimated energy yield analysis revealed that the average efficiency gain of 5.6% achieved under outdoor conditions could lead to a substantial increase in annual energy production. Overall, the hybrid bio-inspired fins + PCM system offers a sustainable, self-regulating, and energy-free cooling solution that enhances both the performance and durability of PV modules.
AtıfScopus8WoS7OpenAlex11İncele - MakaleYalnız künye2026Scopus SJRQ2Frequency-Based Damage Detection with ANN and Seismic Behaviour Assessment of a Historical Masonry Tower
Demirtaş, Betül; Türker, Temel; Yanik, Yusuf; Dede, Tayfun
Nowadays, Artificial Neural Networks (ANNs) are widely used in damage detection because of their powerful computational and exceptional ability to recognize patterns in historical structures. This paper presents the seismic behaviour assessment and structural damage detection performance of the ANN trained with natural frequencies to identify the damage on the Hagia Sophia Bell Tower in Trabzon, Türkiye. Reduction in the stiffness of the structures causes changes in the structural dynamics. Natural frequencies, being key indicators in damage detection, were utilized as input parameters to train the ANN in this study. The study’s scope included updating of the initial finite element (FE) model constituted with SAP2000 software according to the experimental dynamic characteristics obtained from the Civil Engineering Vibration System developed by our work team. The seismic behaviour of the tower was also examined through time history analyses under the effect of strong earthquakes. The required data for the ANN analyses was obtained from the FE modal analysis of the tower. The ANNs dataset was generated separately by simulating both single and double damage scenarios. Possible twelve damage zones were determined according to the places where the highest stresses occurred in the earthquake analysis of the tower. The reduction in the elasticity modulus of each region defined on the tower was considered as damaging effect and used as ANN output parameter. It was shown that ANN trained with natural frequencies can effectively identify the location and severity of damage.
AtıfScopus6OpenAlex7İncele - MakaleAçık Erişim2026Scopus SJRQ1Performance level controlled efficiency of graphene nanoplatelets in cementitious composites
Şahin, Yaren; Öksüzer, Nurullah; Kütük, Sezai; Gökçe, Hacı Süleyman
Graphene nanoplatelets (nGP) have been widely reported as effective nano-reinforcements for cementitious composites; however, their optimal dosage remains inconsistent across existing studies. This variability is commonly attributed to nanomaterial-related parameters, whereas the influence of the cementitious matrix’s inherent performance is rarely systematically examined. In this study, cementitious matrices with distinct performance levels were designed by varying water-to-binder ratios (0.55, 0.40, and 0.30) and incorporating silica fume. Their interaction with nGP was experimentally investigated, with contents up to 2.4% being used. A total of 25 mix designs were evaluated for fresh-state behavior, mechanical performance, transport properties, and microstructural characteristics. The results indicate that the efficiency and optimal utilization of nGP are strongly governed by the matrix performance level. High-performance matrices (water-to-binder (w/b) = 0.30, 11% silica fume) achieved peak performance at 1.2% nGP, yielding compressive strength of 118.2 MPa and up to 50% reduction in capillary water transport, whereas low-performance matrices (w/b = 0.55) exhibited limited sensitivity to nGP incorporation. Microstructural observations confirmed that matrix densification improved nGP integration and hierarchical pore refinement by enhancing interfacial bonding, thereby restricting capillary water transport. The findings demonstrate that optimal nGP dosage cannot be treated as an intrinsic material parameter and should instead be defined in relation to matrix performance level, enabling performance-based dosage guidelines for nano-engineered composites in high-durability applications.
AtıfWoS1OpenAlex1İncele - MakaleAçık Erişim2026Scopus SJRQ2Experimental Electromagnetic Shielding Analysis of a Square-Resonator-Integrated Double-Concrete Structure Using Explainable Machine Learning
Cakir, Mehmet
Electromagnetic shielding has become a practical concern in buildings and structures exposed to persistent interference. This paper reports experimental measurements of the frequency-dependent shielding properties of a square-resonator-integrated double-concrete structure, using a free-space S-parameter setup built around WR229 waveguide adaptors and horn antennas. Three variables were tested: concrete thickness D, relative permittivity εr, and relative magnetic permeability μr. Both εr and μr were characterized experimentally from carbon-fibre- and copper-slag-modified concrete rather than taken from standard tables. The novelty of the study lies in combining experimentally characterized concrete electromagnetic properties, an embedded square-resonator geometry, and explainability-driven machine learning analysis within a single experimental framework for cement-based EMI shielding design. A total of 96 parameter combinations were evaluated using calibrated S11 and reference-corrected S21 responses across 3.3–4.9 GHz. Thickness and electromagnetic material properties interacted—neither governed shielding performance on its own. The strongest transmission attenuation occurred at D = 5, εr = 7, and μr = 1.2, where minimum S21 reached approximately −62.98 dB at 3.6392 GHz. S11 varied considerably less than S21 across the tested combinations, suggesting transmission suppression is the dominant mechanism rather than reflection enhancement. A machine learning analysis confirmed that nonlinear ensemble models outperformed the linear baseline and identified thickness as the most influential predictor of minimum S21.
- MakaleAçık Erişim2026Scopus SJRQ1Effect of fiber architecture and CNT reinforcement on the mechanical behavior and formability of thermoplastic PE composites
Gavgali, Esma; Dilmec, Murat
Lightweight thermoplastics with improved mechanical performance and formability are critical for aerospace, defense, and automotive applications. Despite this, the coupled effects of nanoscale carbon nanotube (CNT) reinforcement and fiber architecture on formability-dominated deformation remain insufficiently explored. This study investigates polyethylene (PE) matrix fiber-reinforced composites manufactured with and without CNT modification to clarify these effects. Mechanical behavior was evaluated through tensile, flexural, hardness tests, while biaxial formability was assessed using the Erichsen test. Fracture mechanisms were analyzed by scanning electron microscopy (SEM). The results indicate that CNT addition significantly improved glass fiber laminates, with peak forming loads increasing by up to 152% for plain weaves and 211% for twill weaves. In contrast, carbon fiber laminates showed only marginal improvements (≤5%), attributed to their inherently high interfacial efficiency. The CNT-reinforced twill carbon fiber composite achieved the highest tensile strength (240.32 MPa) and hardness (66.8 Shore D), while the CNT-reinforced plain glass composite exhibited the highest flexural strength (43.19 MPa). SEM observations revealed composites predominantly failed through fiber–matrix debonding, matrix plastic deformation, and fiber pull-out. Overall, the results show that optimizing fiber type, textile architecture, and CNT reinforcement enables PE-based composites with balanced strength, stiffness, and formability for multiaxial loading applications.
- MakaleAçık Erişim2026Scopus SJRQ3Low-Data Modeling of Shallow Foundations on Cohesive Slopes: A Comparison between Hybrid FEM–RSM and ML Models*
Kâmiloğlu, Hakan Alper; Gücüyener, Alper
In geotechnical engineering, accurately predicting the seismic bearing capacity of shallow foundations on cohesive slopes requires proper consideration of nonlinear effects and parameter interactions. However, most studies in the literature address these complex effects inadequately, either with numerical methods that demand a large number of analyses or with machine learning (ML) models that require large and heterogeneous data sets. In this study, it is aimed to propose an approach that allows for a robust analysis of the system and at the same time provides accurate forecasting for situations where working with small and homogeneous data sets is mandatory. Within the scope of the study, seismic bearing capacity analyses were performed using Plaxis 2D for 273 cases where eight independent variables took different values according to the Face Centered Composite Design (FCCD), and a database was created. Multiple Linear (MLR), Multiple Nonlinear (MNLR) Regression Models were established, and ML models, such as Support Vector Regression (SVR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), were trained. The models were compared with both in-sample and out-of-sample estimation performance, and parametric sensitivity analyses were evaluated by methods such as ANOVA and SHAP. The results show that the MNLR model with natural logarithmic transformation is the most successful method in terms of both accuracy (R² ≈ 0.98) and reflecting parameter interactions, while the SVR algorithm demonstrates the best generalization ability among ML models under low-data conditions. The results also confirm that the ML models effectively capture the parameter effects.
- MakaleYalnız künye2026Scopus SJRQ1Upcycling marble waste into construction materials and heavy metal adsorbents via hot-pressed geopolymerization technique
Öksüzer, Nurullah; Uslu, Emin; Gökçe, H. Süleyman
This study presents a sustainable approach to utilizing marble dust waste by producing bifunctional metakaolin-based geopolymers via a synchronized hot-pressing technique. In this study, the environmental footprint was minimized by designing mixtures in which marble waste constituted 50% of the total volume. Three stoichiometric series were investigated by varying the activator modulus (SiO2/Na2O = 3 and 4) and the Si/Al ratio (2 and 3) under two curing temperatures (150 and 300 °C) and three compaction stresses (5, 25, and 50 MPa). Thus, a high-volume industrial byproduct was transformed into a functional component. In this context, it investigated the transformation of industrial products into next-generation materials by using them to produce cementless composite geopolymers for civil engineering and to adsorb heavy metal (Cu2+). As a result of the research, an early compressive strength of 58 MPa was obtained through heat treatment and pressing applied at 300 °C and 50 MPa. This optimum strength was achieved in the SiO2/Na2O = 3, Si/Al = 3 series, whereas excess silica (SiO2/Na2O = 4) and excess aluminum (Si/Al = 2) limited the strength to 16.8 and 35.2 MPa, respectively. Microstructural analyses (SEM/EDS and FT-IR) revealed that marble dust was used as a filler material in the microstructure to produce an N-A-S-H-containing matrix. The produced materials were then ground after their service life and used to purify water containing heavy metals. More than 99.75% of Cu2+ was removed through ion exchange between copper ions used as heavy metals. The residual Cu2+ concentration fell below 0.25 mg/L from an initial concentration of 100 mg/L, and the released Na+-to-adsorbed Cu2+ molar ratio of approximately 1.8–2.3 confirmed an ion-exchange-dominated uptake mechanism. This structural and environmental impact demonstrates that marble waste, which is otherwise discarded as waste, is considered inert, offering an alternative model for the circular economy and environmental applications.
- Derleme MakaleAçık Erişim2026Environmental and economic analysis of industrial waste heat recovery with hybrid heat pump application
Kazici, Halil İbrahim; Tozlu, Alperen
Today, increasing energy demands and environmental concerns have made energy efficiency a necessity from both economic and ecological perspectives. High energy consumption in industrial facilities increases costs and raises CO2 emissions. Therefore, waste heat recovery and the use of renewable energy are among the fundamental goals of sustainable production. Energy efficiency is important not only for reducing consumption but also for lowering greenhouse gas emissions, protecting the environment, and strengthening the economics of the business. In this context, heat pump technologies, which extract energy from low-temperature sources and make it reusable, stand out as effective, environmentally friendly, and efficient systems in both heating and cooling applications. In this study, waste heat from a cooling tower generated during the production process in an industrial facility was recovered through a water-source heat pump and integrated into the facility's heating system. The heat pump increased the heat energy by using low-temperature water and reused it in the process. During periods when the waste heat was insufficient, the system was supported by natural gas boilers, thus creating a hybrid operating model between the heat pump and the boiler. As a result of the implementation, natural gas consumption and electricity usage were significantly reduced, leading to lower energy costs and a substantial decrease in CO2 emissions, thereby providing notable environmental benefits. The findings indicate that the proposed system achieves an annual natural gas saving of 6,788,251 kWh and a net financial gain of 5,703,864 TL. Additionally, the payback period of the investment is calculated as 2.41 years, demonstrating the economic feasibility of the system. Overall, this case study highlights that the widespread adoption of hybrid heat pump systems in the industrial sector can make significant contributions to Türkiye’s energy transition and carbon emission goals.
- MakaleYalnız künye2026Scopus SJRQ1Experimental 4E analysis (energy-exergy-economic-environmental) of hybrid parabolic trough collector-thermoelectric generator-phase change material cogeneration system
Guclu, Tamer; Cuce, Pinar Mert; Cuce, Erdem
Hybrid solar cogeneration systems are critical for enhancing energy utilisation and mitigating the intermittency of solar resources. This study presents a comprehensive 4E (Energy-Exergy-Economic-Environmental) experimental analysis of a novel hybrid system that uniquely integrates a Parabolic Trough Collector (PTC), a small-scale steam turbine, a Thermoelectric Generator (TEG) assembly, and a Phase Change Material (PCM) thermal storage unit. The system's performance was investigated under 15 distinct operating conditions, varying initial water masses (0.1, 0.15, 0.2 kg) and operating pressures (6, 8, 10, 12, and 14 bar). Experimental results demonstrated the system's adaptive cogeneration capabilities. At 14 bar and 0.2 kg, the system achieved its maximum Solar-to-Electricity efficiency of 0.42%. At this operating condition, the highest collector thermal efficiency was 25.25% (at 6 bar), and the maximum overall energy and exergy efficiencies were 8.43% and 1.45%, respectively. A key finding was the system's adaptive electrical output: at low pressures (6 bar), the TEG acted as a crucial co-generator, supplying up to 55% of the electricity, whereas at high pressures (14 bar), the turbine dominated, accounting for 88-90% of the output. Furthermore, the study experimentally confirmed that latent heat transfer was the dominant heat transfer mechanism for the PCM, with latent heat contributing ∼445 kJ (55%) of the 805 kJ total energy stored. The thermo-economic analysis confirmed the system's viability, yielding a Simple Payback Period (Spp) of 6.9 years and a competitive Levelised Cost of Energy (LCOE) of $0.101/kWh. The system is projected to save 118.8 kg of CO2 and 660 L of water annually. The results validate the thermodynamic and economic feasibility of the integrated PTC-Turbine-TEG-PCM concept as a flexible solution for small-scale solar cogeneration.
AtıfScopus3WoS2OpenAlex6İncele - MakaleAçık Erişim2026Scopus SJRQ4Effect of Seismic Isolation on Earthquake Behavior of Mid-Rise Reinforced Concrete Building Systems
Delikkaya, Uğur; Karabulut, Pembe Merve; Ergün, Mustafa
When the latest updated Türkiye Earthquake Hazard Map and Active Fault Maps are examined, it is seen that a large part of Türkiye's surface area is at earthquake risk. With increasing urbanization, the majority of the population lives in cities built on active earthquake faults. The 7.8 and 7.5 magnitude earthquakes centered in Kahramanmaraş, Pazarcık, and Elbistan occurred in Türkiye on February 6, 2023, and caused significant loss of life and major damage in 10 provinces. In the damage assessment studies conducted after the earthquakes, it was determined that the damage in structures constructed with tunnel formwork systems was less than the damage in other structural systems. The importance of seismic isolators in such a severe earthquake was once again revealed. Within the scope of this study, the earthquake performance of mid-rise buildings constructed with tunnel formwork systems and mid-rise buildings constructed with reinforced concrete carcass construction systems was compared with and without isolators for different soil classes. When the obtained results were examined, it was observed that the earthquake performance of the structures constructed with the tunnel formwork system was better than that of the structures constructed with the reinforced concrete frame structure system and that in cases where a seismic isolator was used, the isolator positively affected the forces acting on the structure and the structure displacements.
