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Mapping the research landscape of stormwater quality improvement devices: trends, influencers, and thematic evolution (1992-2024)
(MDPI, 2025) Yua, Sesugh; Yıldırım, Gökhan; Morshed, Mohammad Ataul; Anindita, Monisha; Alim, Mohammad A.; Rahman, Ataur
This study presents a comprehensive bibliometric analysis of the research landscape on Stormwater Quality Improvement Devices (SQIDs) covering 1992-2024. Using data from the Web of Science (WoS) and utilizing Bibliometrix R-package 5.1.0 and VOSviewer 1.6.20, this study identifies key trends, influential contributors, and the thematic evolution within SQIDs research. The findings reveal distinct growth phases driven by policy shifts, scientific advancements, and an increasing global emphasis on sustainability. Keyword analysis highlights a significant thematic transition post-2015, with terms like performance, runoff, and management (Keyword Plus), and stormwater management, green infrastructure, and stormwater (Author Keywords) indicating a strong shift toward sustainable, nature-based solutions. Bioretention system has emerged as the most researched SQIDs, reflecting widespread academic and practical interest. The most prolific countries in SQIDs research are the USA, China, and Australia, while prominent thought leaders include Fletcher (Monash University), Wang (Guangzhou University), Shuster (US EPA), and Deletic (UNSW). Leading publication outlets include the Journal of Environmental Management, Science of the Total Environment, Journal of Hydrology, and Water. Overall, this study underscores the field's maturation toward policy-relevant and interdisciplinary innovations, long-term performances and smart SQIDs using artificial intelligence positioning SQIDs as vital tools in addressing urban stormwater management challenges globally.
Structural damages observed in 6 February 2023 Kahramanmaraş earthquakes
(Techno Press, 2025) Bakırcı Er, Şule; Avanoğlu Sıcacık, Eda; Kaya, Mustafa
Turkiye is an earthquake country with active faults. On February 6, 2023, there were two major destructive earthquakes with magnitudes of 7.7 and 7.6, with the epicenters in Kahramanmara & scedil; Pazarc & imath;k and Kahramanmara & scedil; Elbistan, and affected 11 cities. The region has a population of approximately 13.5 million. More than 50000 people lost their lives. It was determined that there were 61772 buildings that were heavily damaged, destroyed or needed to be demolished. Based on this bitter experience, it was desired to take attention to the structural deficiencies and mistakes made. It is thought that the points emphasized will be guiding for new constructions. Selection of unappropriate ground and foundation for construction, low concrete quality used, insufficient and flat reinforcement, errors and deficiencies in project design, application and inspection are the main reasons for demolitions. As a result of investigations, it was observed that the buildings that received adequate engineering services had good material and construction quality, and did not experience any deficiencies in inspection and implementation survived the earthquake without any damage or with very minor damage. It is noteworthy that the residences built by the Public Housing Administration (PHA) in the region did not suffer any catastrophic damage. The most important features of these houses can be listed as: ground surveys before application, raft foundation, tunnel formwork system, use of quality concrete and reinforcement, project implementation and controls during the construction phase. The difficulty of reaching aid due to collapsed buildings blocking the roads after the earthquake once again revealed the importance of planned urbanization.
Data-driven drought prediction by means of machine learning techniques and ıncreasing accuracy with wavelet transform
(Birkhauser Verlag Basel, 2025) Tuğrul, Türker; Selek, Bülent; Hınıs, Mehmet Ali; Selek, Zeliha; Oruç, Sertaç
Drought is not only a problem that challenges scientists but also one of the most difficult natural disasters to combat for local governments and decision-makers. Like many parts of the world suffering from drought, the western Mediterranean region of Turkey is also affected by drought. In this study, innovative drought prediction models were created with different machine learning algorithms and deep learning methods to create a model that will help decision-makers regarding drought. 4 different monthly lagged model structures were established using SPI12 values calculated with precipitation data between 1967 and 2020 for the Acipayam, Bodrum and Fethiye regions located in the west of Turkey. While providing data, attention was paid to the distance between stations and data continuity. The models were analyzed with Long-Short Term Memory (LSTM), Artificial Neural Network (ANN) and Random Forest (RF) algorithms. In addition, Discrete Wavelet Transform (WT) was used to obtain better model results. The hyper-parameters of these algorithms were determined by taking into account the most commonly used parameters in the literature. The analysis results were evaluated by correlation coefficient (R), root mean square error (RMSE), Nash–Sutcliffe Efficiency (NSE), and Combined Accuracy (CA). As a result of the comparison of these methods, the best results were obtained in the M01 model of LSTM, LSTM-WM01, for Acipayam after WT (r: 0.9910, NSE: 0.9733, RMSE: 0.1637, and CA: 0.1030). While the best prediction for Bodrum was obtained in LSTM-WM02 after WT (r:0.9657, NSE:0.9325, RMSE:0.3101, and CA: 0.1929), for Fethiye it was obtained in LSTM-WM02 having performance metrics r:0.9539, NSE:0.8973, RMSE:0.3689, and CA: 0.2359. It is expected that the results obtained with this study will help researchers and decision-making authorities on drought.
Effects of reducing long-term groundwater overdraft in uluova micro-basin
(Springer Science and Business Media Deutschland GmbH, 2025) Şekerci, Kürşat; Tuna, M. Cihat; Doğan, Mustafa Şahin
Recently, groundwater use has increased significantly in response to limited surface water availability in arid and semi-arid regions. This trend has led to increasing concerns about declining groundwater levels and the risk of overdraft. For the above reasons, a hydroeconomic model was developed in this study to evaluate various management scenarios aimed at mitigating the negative impacts of groundwater overdraft. The Uluhem hydroeconomic model focuses on a total of six different water management operations with different physical constraints. The first scenario is a baseline water operation with groundwater pumping (with overdraft), while the next four scenarios cover four different water management operations where groundwater pumping is restricted at different rates (without overdraft). The sixth and final scenario investigates the installation of a solar-powered system to pump water from a nearby surface water reservoir. This last scenario seeks a potential solution to completely eliminate the agricultural water scarcity and associated scarcity costs arising from the first five scenarios. With the Uluhem model, the water deliveries, water scarcity and economic impacts of these six different management scenarios are analyzed. The findings show that the four different scenarios in which groundwater pumping is restricted contribute positively to the groundwater reservoir but increase water scarcity. The solar power plant installation scenario, on the other hand, offers a promising and sustainable solution that not only effectively addresses water scarcity but also eliminates the associated costs. The study investigates the factors contributing to groundwater overdraft and seeks a sustainable solution to current groundwater utilization. The results emphasize the urgent need for effective and sustainable water management strategies to prevent groundwater overdraft. Overall, the study provides valuable insights into groundwater overdraft problems in the Uluova micro-basin and emphasizes the importance of adopting long-term, sustainable groundwater management practices.
Strengthening strategies for unreinforced stone masonry walls using FRP and CFM composites
(Nature Research, 2025) Çelik, Tülin
Recent earthquakes have highlighted the vulnerability of unreinforced masonry (URM) walls particularly those constructed with stone to lateral loads, underscoring the need for effective strengthening against shear failure. In this context, fiber-reinforced polymer (FRP) and carbon fiber mesh (CFM) have been explored as innovative alternatives to traditional reinforcement techniques. This study investigated unreinforced stone masonry walls, a common type of URM, strengthened using FRP and CFM materials in different configurations, focusing on the walls’ in-plane shear behavior under diagonal compression testing. A reference specimen, labeled URM-1, was constructed without reinforcement. FRP materials were applied to two specimens either horizontally or diagonally on both wall surfaces. Similarly, two specimens were strengthened on both surfaces using CFM, applied with either epoxy or repair mortar. Based on experimental and analytical results, the URM-5 specimen (CFM with epoxy) was identified as the most effective strengthening method. It significantly increased maximum load capacity, shear stress, ductility, and elastic stiffness. Additionally, the URM-5 specimen reduced wall fragility and maintained structural integrity during fracture.
Soğukta şekil verilmiş çelik gövde delikli kesitlerin burkulma kapasitelerinin farklı yaklaşımlarla incelenmesi
(Kahramanmaraş Sütçü İmam Üniversitesi, 2025) Oruç, Ramazan
Bu çalışma, gövde delikli soğukta şekil verilmiş çelik kesitlerin eğilme etkisi altındaki burkulma davranışını incelemektedir. Delikli kesitler, elektrik, su ve havalandırma sistemleri için gerekli boşlukları sağlamak amacıyla yapısal uygulamalarda yaygın olarak kullanılmaktadır. Ancak bu delikler, kesitin mekanik özelliklerini ve burkulma davranışını önemli ölçüde etkilemektedir. Bu kapsamda, delik yüksekliği, delik uzunluğu ve kesit yüksekliği gibi değişkenler dikkate alınarak, CUFSM programı kullanılarak deliksiz ve delikli kesitler için elastik burkulma analizleri gerçekleştirilmiştir. Ayrıca, farklı yaklaşımların lokal ve distorsiyonel burkulma kapasitelerini tahmin etmedeki etkinliği karşılaştırılmıştır. Elde edilen sonuçlar, delik yüksekliği ve delik uzunluğunun burkulma kapasitesi üzerinde önemli bir etkisi olduğunu göstermektedir. Özellikle delik uzunluğunun 80 mm’yi aşması durumunda, lokal burkulma kapasitesinin arttığı, ancak distorsiyonel burkulma kapasitesinin azaldığı belirlenmiştir. Ayrıca, farklı yöntemlerin karşılaştırılması sonucunda, Moen ve Schafer tarafından geliştirilen yaklaşımının standart hesaplamalarla benzer sonuçlar verdiği, buna karşın bazı diğer yöntemlerin lokal burkulma kapasitesini yüksek, distorsiyonel burkulma kapasitesini ise düşük tahmin ettiği tespit edilmiştir.
Su tutma modelinin parametrelerinin yapay zeka optimizasyon algoritmaları ile tahmin edilmesi
(Gazi Üniversitesi, 2025) Özsoy, Mürüvet
İnşa edilen mühendislik tasarımlarında su varlığının neden olabileceği olumsuz etkileri ortadan kaldırmak ya da minimum seviyeye indirebilmek amacıyla yapının konumlandığı zeminlerdeki su miktarının optimum seviyede olması gerekmektedir. Ancak bazı durumlarda su seviyesi optimum değerden daha yüksek olabilmekte ve deprem dalgalarının etkisiyle daha fazla artan boşluk suyu basıncı üst yapıda ciddi hasarlara yol açmaktadır. Bu yüzden zeminde yer alan su içeriğini optimum seviyede tutabilmek için zemin su ilişkisi sürekli izlenmesi gerekmektedir. Gözenekli ortamın hidrolik karakterizasyonunda önemli bir role sahip olan su tutma eğrisi zeminde bulunan su miktarı ile zemin su potansiyeli arasındaki ilişkiyi göstermektedir. Bu eğri zeminin yapısı ve gözenekliliği gibi zeminin fiziksel özellikleriyle ilişkili olduğu için parametrelerinin doğru bir şekilde tahmin edilmesi gerekmektedir. Doğrusal olmayan bir fonksiyon olan su tutma eğrisinin parametrelerini tahmin etmek için Van Genuchten modeli kullanılmıştır. Geleneksel optimizasyon yöntemlerinin yeterli olmaması nedeni ile yapay zeka optimizasyon algoritmalarından simbiyotik organizma arama algoritması ile dünyanın altı farklı noktasından elde edilen toprakların fiziksel özelliklerine ilişkin veriler kullanılarak parametreler tahmin edilmiştir. Elde edilen bulgular R2 değerlerinin %99’un üzerinde olduğunu göstermekte olup θr, θs, α ve n parametrelerin gerçek değerlerine oldukça yakın tahmin edilmiştir.
Drought analysis with two different ındices in yeşilırmak basin
(Tokat Gaziosmanpaşa Üniversitesi Ziraat Fakültesi Dergisi Yayın Ofisi, 2022) Geyikli, Mehmet Selim; Hınıs, Mehmet Ali; Yürekli, Kadri
Reducing the negative effects of drought disaster, which is one of the most important parameters affecting the planning and management of water resources, has become very important today. Many methods have been proposed in the literature for the calculation of drought, which is used to express the periods when precipitation is significantly less than the average, and two of these methods, "Standardized Precipitation Index (SPI)" and "Reconnaissance Drought Index (RDI)" were applied to the Yeşilırmak basin in this study.12-month SPI and RDI analyzes were made and compared by using the monthly precipitation and evapotranspiration totals of 8 stations in the Yeşilırmak Basin for the period 1991-2020. The results show us that the SPI and RDI methods generally give similar signals for wet periods, but the RDI method defines more extreme dry periods than the SPI method in extreme dry periods. While the RDI method defines more extreme dry periods than the SPI method; It was observed that the SPI method defined more extreme wet periods than the RDI method. In drought analysis, using an index based on more than one meteorological parameter (such as the RDI) will give more reliable results instead of using an index based on a single parameter (i.e, SPI). It has shown in this study that the effect of evapotranspiration values in drought calculation is very important by comparing it with RDI analysis and SPI analysis.
Kenet genişliğinin yığma taş bloklarının kayma davranışı üstündeki etkisinin incelenmesi
(Düzce Üniversitesi, 2022) Tanrıverdi, Şükran; Çelik, Tülin; Ural, Ali; Fırat, Fatih Kürşat
Tarihi yapılarda geleneksel yapı malzemesi olarak taş, tuğla türü malzemeler kullanılmıştır. Bu malzemelerin harç ile birleştirilmesiyle yığma duvarlar inşa edilmiştir. Yığma yapı birimlerinin çekme dayanımı oldukça düşüktür. Yığma yapıların kayma gerilmelerine karşı dayanım sağlaması ve yapı sisteminin birlikte hareket etmesi istenmektedir. Tarihi yapı duvarlarının, birleşim ve kesişim bölgelerinde elemanların birbirine kenetlenerek bütünleşmesini sağlamak gerekmektedir. Geçmişte tarihi yapıların bu bütünlüğünü koruyabilmek amacıyla çeşitli metal bağlantı elemanları kullanılmıştır. Bu bağlantı elemanları olarak kenetler ve zıvanalar ön plana çıkmıştır. Yapılan deneysel çalışmada, genişlikleri farklı olan kenet elemanların yığma taş blokların kayma dayanımına etkisi araştırılmıştır. Bu amaçla farklı kenet genişliklerde 18 adet deney numunesi üretilerek kayma dayanım testine tabi tutulmuştur. Elde edilen sonuçlar grafikler ve tablolar ile karşılaştırılmalı olarak sunulmaktadır. Bu çalışma ile kenet genişlikleri farklı olan numunelerin, kırılma yüklerine ve kayma dayanımlarına göre değerlendirmeleri yapılmıştır.
Determination of tire contact stress and deflection distributions in a layered half-space using 3-d boundary element method
(Osmaniye Korkut Ata Üniversitesi, 2022) Deneme, İbrahim Özgür; Severcan, Metin Hakan
In this study, the Boundary Element Method (BEM) was employed for the numerical determination of the response of a layered half-space. The material behaviour of the soil was assumed to be isotropic and linear elastic. The BEM was used in the Fourier transform space (FTS). The focus of this paper is to determine the stress and deflection distributions of interior points of a layered half-space. To achieve this aim, in this study, a computer program is developed for three-dimensional elastic or visco-elastic problems. The results of stress and deflection distributions in a layered half-space determined using boundary element formulation are presented in figures.
Türkiye’de yüksek hızlı trenlerin önemi ve diğer ulaşım türleri arasındaki tercih nedenleri
(Düzce Üniversitesi Fen Bilimleri Enstitüsü, 2021) Bolakar Tosun, Hümeyra
Türkiye de ulaşım altyapısı ve ağı kurgularken uzun yıllar demiryolu yatırımları ihmal edilmiştir. Bu durum ulaşım ağı içerisinde türel dağılımı olumsuz etkileyen sonuçlar doğurmuştur. Karayolları ağırlıklı oluşturulan planlamaların çevresel olumsuzlukları ve havayollarının hızlılık avantajına rağmen bu ulaşım türlerinin her noktaya taşımacılık hizmetinin bulunmaması, ulaşım araçlarında yenilikleri beraberinde getirmiştir. Güvenli, hızlı ve konforlu bir seyahat kapsamında geliştirilen yüksek hızlı trenler Türkiye’de yeni bir ulaşım türü olarak karşımıza çıkmaktadır. Ankara, İstanbul, Eskişehir, Konya arasında ulaşıma açılan hatların yanı sıra yapımı devam eden ve yeni oluşturulacak hatlar ile bölgeler ve şehirlerarasında hızlı, güvenli ve konforlu bir seyahat oluşturulması hedeflenmektedir. Bu çalışmada yüksek hızlı trenlerin; güvenlik, konfor, seyahat süresi, ulaşım maliyetleri gibi etkileri incelenmiştir. Mevcut hatlar arasında faaliyet gösteren ulaşım türleri kıyaslamış ve sonuç olarak yüksek hızlı trenlerin birçok etki açısından daha avantajlı ulaşım sağladığı belirlenmiştir.
Türkiye demiryolu yolcu taşıma talebinin tahmini
(Düzce Üniversitesi Fen Bilimleri Enstitüsü, 2021) Çakır, Fatma; Bolakar Tosun, Hümeyra
Günümüzde yolcu taşımacılığında demiryollarının payı giderek artmaktadır. Yolcu talebinin karşılanması için uygun planlamaların belirlenmesi gereklidir. Kapasiteyi karşılayacak planlamaların oluşturulması hem talebi karşılayacak hem de yatırımlarda uygun kararların alınmasını sağlayacaktır. Bu çalışmada, demiryolu yolcu taşımacılığı üzerinde etkili olan değişkenler kullanılarak demiryolu yolcu sayısının tahmin edilmesi amaçlanmıştır. Yolcu talebinin belirlenmesi için Çok Değişkenli Regresyon (ÇDR) analizi ve Yapay Sinir Ağları (YSA) ile iki farklı model oluşturulmuştur. İki model içinde tahmin değerleri belirlenmiştir. Hata kareleri ortalaması (MSE) ve belirleme katsayısı (R 2 ), performans kriterlerini, dikkate alarak en uygun tahmin YSA ile elde edilmiştir. Talep tahmininde YSA kaynak olarak kullanılabileceği görüşüne varılmıştır
The effects of infill wall on dynamic characteristics of reinforced concrete frame systems
(Golden Light Publishing, 2019) Kömür, Mehmet Aydın; Deneme, İ. Ö.; Kara, M. A.
This study presents an experimental investigation on the dynamic characteristics of infilled Reinforced Concrete (RC) frames. For this purpose, a 1/3-scaled, one-bay, three-storey RC frame was produced and tested by using ambient vibration test. The experiments were performed on sequentially produced three specimens which use the same single reinforced frame. The infill walls were made of hollow clay brick. The frequency, mode shapes and damping ratios in the in-plane direction of patterns were obtained by six accelerometers. Fifteen-minute records under ambient vibration were taken for each model, and the dynamic characteristics were determined using the ambient response testing and modal identification software (ARTeMIS) program. The experiments showed that the infill walls significantly affected the frequency values and damping ratios of the frame system. As a result of this study, the presence of damaged/undamaged infill walls lead to an increase in the frequency values and the damping ratios for the first three modes of the frame systems. On the other hand, the natural frequency of the first three modes of with undamaged infill walls is more than those with damaged ones. While the damping ratios for undamaged infill walls were increased at first two modes and it was decreased at the third mode.
Seismic response of fixed-base and LRB base-isolated RC framesystems under NF and FF excitations
(Golden Light Publishing, 2019) Kömür, Mehmet Aydın; Oruç, Ramazan; Deneme, İbrahim Özgür
Seismic isolation systems can be used in new structures to reduce the negative effects of the earthquake on the building. The lead rubber bearing (LRB) is one of the most commonly used seismic isolators. This study focused on the behavior of Reinforced Concrete (RC) frame systems with fixed-base and Lead Rubber Bearing systems under Near-Fault (NF) and Far-Fault (FF) records. For this purpose, two-plane frame systems with 4 and 8 story were designed. Nonlinear behavior of both superstructure and isolation system was taken into consideration in modeling. The nonlinear time history analysis method was used in the seismic analysis of reinforced concrete frame systems. Finally, story acceleration, interstory drift ratio, base shear force and distribution of plastic hinges and their damage conditions were evaluated. The results of the analysis showed that the effects of the NF earthquake record on the frame system had generally greater according to the effects of the FF earthquake records.
Analyzing temperature trends using innovative trend analyses in certain regions of Norway
(Springer Science and Business Media Deutschland GmbH, 2025) Tuğrul, Türker; Oruç, Sertaç; Hınıs, Mehmet Ali
A number of methods are used in the literature to track and monitor meteorological events in a region and make future predictions. Temperatures are one of the most important parameters that trigger changes in meteorological events. In this study, the trends in temperatures, which are a type of indicator of natural disasters in the Norwegian region, were examined. As trend analysis methods, the Innovative Trend Analysis (ITA), the Innovative Polygon Trend Analysis (IPTA), the Innovative trend pivot analysis method (ITPAM), and the Mann–Kendall Trend Test (MK) were preferred and data of monthly average temperature were collected from 4 different stations (Bodo, Karasjok, Oslo, and Tromsø) between 1948 and 2023. The results indicate the existence of increasing trends in all regions. This does not represent a risk or negativity for the region, but an advantage for this region. Furthermore, the results indicated that MK, in contrast to the other methods, was inadequate for identifying the specific trend and non-monotonic trend. Besides, in the annual MK analysis, Bodo, Oslo and Tromso displayed significant trends (p value < 0.05) with z-scores of 2.64, 2.48 and 2.07, respectively while with a z-score of 1.45, Karasjok did not exhibited a significant trend. In addition, one of the notable findings in this study is the demonstrated effectiveness of the graphical methods (ITA, ITPAM, and IPTA), as reflected in the trend results. The findings of this study are expected to support institutions or organizations in executing measures for natural disaster mitigation.
Comparison of LSTM and SVM methods through wavelet decomposition in drought forecasting
(Springer Science and Business Media Deutschland GmbH, 2025) Tuğrul, Türker; Hınıs, Mehmet Ali; Oruç, Sertaç
Many researchers are working to prevent, monitor and identify drought, which is one of the most insidious and dangerous natural disasters that negatively affects life. For this purpose, various drought indices are developed and new methods are proposed. One of the most widely used of these indexes is the Standard Precipitation Index (SPI). Since it is not known when the drought will begin, taking preventive measures is a difficult and challenging task. In the last decade, machine learning techniques have been preferred to increase success in predicting droughts. In this study, SPI was used as the drought index and Support Vector Machine (SVM) and Long-Short Term Memory Network (LSTM) methods, which are increasingly reliable among the most preferred machine learning and deep learning methods in drought predictions, were used as the prediction method, and furthermore, to increase the prediction power of these methods, new powerful models have been proposed using Wavelet transform and Variational mode transform. Support Vector Machines with Wavelet decomposition (SVM-W), Long-Short Term Memory Networks with Wavelet decomposition (LSTM-W), and Long Short Term Memory Networks with Variational Mode Decomposition (LSTM-VMD) were used as prediction models for drought analysis and the performances of these models were compared.
Performance enhancement of models through discrete wavelet transform for streamflow forecasting in Çarşamba River, Türkiye
(IWA Publishing, 2025) Tuğrul, Türker; Hınıs, Mehmet Ali
Streamflow forecasts play an active role in hydrological planning and taking precautions against natural disasters. Streamflow prediction models are frequently used by scientists, especially in dam management, sustainable agriculture, flood control, and flood mitigation. Hence, streamflow prediction modeling was performed in this study, and six models were employed through four different machine learning (ML) algorithms, namely, the artificial neural network (ANN), random forest (RF), support vector machine (SVM), and decision tree (DT) that are well known in the literature, in order to predict the monthly streamflow of Çarşamba River, Türkiye. To further enhance model performance, wavelet transform (WT) was applied to ML algorithms. In this study, monthly average streamflow and precipitation data between 1974 and 2015 was used, and the minimum redundancy maximum relevance method (MRMR) and the cross-correlation method were performed to determine model input data. Results of this study revealed that RF had superiority over the other models before WT, followed by the SVM model. The SVM after WT (W-SVM), M04 (r: 0.9846, NSE: 0.9695, and RMSE: 0.3536) gave the most effective performance results, while the W-ANN model (r: 0.9797, NSE: 0.9588, and RMSE: 0.4108) showed the second best performance.
Transforming Wind Data into Insights: A Comparative Study of Stochastic and Machine Learning Models in Wind Speed Forecasting
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Tuğrul, Türker; Oruç, Sertaç; Hınıs, Mehmet Ali
Wind speed is a critical parameter for both energy applications and climate studies, particularly under changing climatic conditions and has attracted increasing research interest from the scientific comunity. This parameter is of interest to both researchers interested in climate change and researchers working on issues related to energy production. Based on this, in this study, prospective analyses were made with various machine learning algorithms, the long-short term memory (LSTM), the artificial neural network (ANN), and the support vector machine (SVM) algorithms, and one of the stochastic methods, the seasonal autoregressive integrated moving average (SARIMA), using the monthly wind data obtained from Bodo. In these analyses, five different models were created with the assistance of cross-correlation. The models obtained from the analyses were improved with the wavelet transformation (WT), and the results obtained were evaluated for the correlation coefficient (R), the Nash–Sutcliffe model efficiency (NSE), the Kling–Gupta efficiency (KGE), the performance index (PI), the root mean standard deviation ratio (RSR), and the root mean square error (RMSE). The results obtained from this study unveiled that LSTM emerged as the best performance metric in the M04 model among other models (R = 0.9532, NSE = 0.8938, KGE = 0.9463, PI = 0.0361, RSR = 0.0870, and RMSE = 0.3248). Another notable finding obtained from this study was that the best performance values in analyses without WT were obtained with SARIMA. The results of this study provide information on forward-looking modeling for institutions and decision-makers related to energy and climate change.
The investigation of drum height effects on masonry domes
(Techno-Press, 2025) Fırat, Fatih K.; Tanrıverdi, Şükran
In this study, the effects of drum height on masonry dome behavior were examined experimentally and numerically by taking into account the domes with and without windows. Within the scope of the study, a total of eight domes, two of which were references (without drums) and six with different drum heights, were tested. One of the references was produced without windows and the other with windows. With window dome test elements having a drum height of 300 mm and 400 mm and windowless dome test elements with a drum height in the range of 100 mm, 200 mm, 300 mm, and 400 mm were examined. Numerical modeling of experimentally tested dome elements using the LUSAS analysis program was also examined and the experimental results were compared with the numerical results. As a result of the study, it was observed that the height of the drum significantly affected the load carrying capacity and horizontal displacement of the domes. It was determined that the lowest height drum application increased the load-carrying capacity of the dome by about 30% according to the drum-free reference test element. As the drum height increased, the load-carrying capacity and rigidity of the dome increased significantly, and the horizontal displacements decreased.
Web crippling of cold-formed steel with offset holes under ITF loading: Experimental, numerical study and new design equation
(Elsevier Ltd, 2025) Bölükbaş, Yakup; Oruç, Ramazan
This study investigates the web crippling behavior of cold-formed steel members with offset holes experimentally and numerically, proposing a new design equation. The experimental study includes a total of seven tests under the ITF loading condition, examining the parameters of hole size and distance from the holes to the loading plate. It was determined that hole size and the hole's distance from the loading plate play a significant role in determining web crippling capacity. To validate the experimental data and examine the effects of variables such as hole diameter to web depth, hole diameter to thickness, and distance from the holes to the loading plate to web depth on web crippling capacity, a total of 157 finite element models were developed. The results indicate that an increase in the hole size to web depth ratio and an increase in hole diameter leads to a reduction in web crippling capacity. When the hole is close to the loading point, an increase in hole diameter significantly affects the load-bearing capacity, whereas, at relatively greater distances, its effect is less pronounced. Based on experimental and numerical studies, a new design equation has been proposed, and its accuracy was evaluated through a reliability analysis, which revealed a mean deviation of just 0.2 %. The results indicate that the proposed equation provides consistent and reliable predictions for the web crippling capacity of members with holes. This work fills critical gaps in current design standards, which lack comprehensive guidelines for perforated CFS members under ITF loading.

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