Yazarlar
- Gul, Muhammet(16)
- Kahraman, Gökhan(13)
- Onat, Onur(13)
- Yucesan, Melih(12)
- Etli, Serkan(11)
- Mete, Suleyman(11)
- Akkurt, Nevzat(10)
- Karataş, Mehmet(10)
- Utku, Anıl(10)
- Yön, Burak(10)
- Akmaz, Düzgün(8)
- Cemalgil, Selim(8)
- Demir, Yakup(8)
- Ergen, Burhan(8)
- Çil, Zeynel Abidin(8)
- Akgül, Melek(7)
- Doğan, Gürkan(7)
- Gülmez, Nihan(7)
- Xu, Qian(7)
- Yildirim, Ozal(7)
- Yilmaz, Mehmet(7)
- Özceylan, Eren(7)
- Celik, Erkan(6)
- Göçmen, Elifcan(6)
- Orhan, Ahmet(6)
- Ertarğın, Merve(5)
- Serin, Faruk(5)
- Yilmazer, Merve(5)
- Zheng, Qiang(5)
- Akpolat, Mustafa(4)
- Atangana, A(4)
- Baskonus, HM(4)
- Bulut, H(4)
- Ding, Yulong(4)
- Dogan, Akar(4)
- Eristi, Huseyin(4)
- Hammouch, Z(4)
- Işık, Erdem(4)
- Karakose, Mehmet(4)
- Kaya, Sema Kayapinar(4)
Yayınlar
- MakaleAçık Erişim2023Deep Learning-Based Automatic Helmet Detection System in Construction Site Cameras
Korkmaz, Adem; Ağdaş, Mehmet Tevfik
Ensuring worker safety in high-risk environments such as construction sites is of paramount importance. Personal protective equipment, particularly helmets, plays a critical role in preventing severe head injuries. This study aims to develop an automated helmet detection system using the state-of-the-art YOLOv8 deep learning model to enhance safety monitoring in real-time. The dataset used for the study consists of 16,867 images, with various data augmentation and preprocessing techniques applied to improve the model's robustness. The YOLOv8 model achieved a 96.9% mAP50 score, outperforming other deep learning models in similar studies. The results demonstrate the effectiveness of the YOLOv8 model for accurate and efficient helmet detection in construction sites, paving the way for improved safety monitoring and enforcement in the construction industry.
AtıfOpenAlex15TR Dizin3
İncele - MakaleAçık Erişim2023Uluslararası politikada bir etki aracı olarak siber güvenlik ve türkiye’nin siber güvenlik politikası uygulaması: ulusal siber olaylara müdahale merkezi (usom)
Gündoğdu, Serkan
Teknolojik gelişmelere bağlı olarak internetin kullanımı gündelik hayatın her alanında etkin bir şekilde yer almaya başlamıştır. Bu süreç insanların hayatını birçok alanda kolaylaştırdığı gibi bazı sorunları da beraberinde getirmiştir. Bu sorunlardan önemli bir tanesi de güvenlik olmuştur. Uluslararası politika bakımından da yeni güvenlik önemlerine ihtiyaç duyulmuş, uluslararası ilişkiler disiplininde güvenlik kavramının önemli bir kavramı haline gelen siber güvenlik sorunun ortaya çıktığı görülmüştür. Gerek ulusal gerekse uluslararası bir önem taşımaya başlayan siber güvenlik konusunda, devletlerin önlemler alması zorunluluk haline gelmiştir. Bu çerçevede siber tehditlere karşı koyabilmek için savunma sistemlerini içeren siber güvenlik politikaları oluşturulmaya başlanmıştır. Çalışma kapsamında Türkiye’nin siber uzaydaki varlığı ve bu alanda kamu hizmetlerinin nasıl sağlandığı, siber güvenlik politikalarına ilişkin çalışmalarını nasıl planladığı incelenmiştir. Türkiye’nin siber güvenliği sağlama adına yapmış olduğu; politika, strateji ve eylem planları ile araştırma konusu sınırlandırılmıştır. Siber tehditleri azaltmak ve bertaraf etmek amacıyla, Türkiye’nin ulusal siber güvenlik stratejisi açısından önemli olan yapılar çalışma kapsamında verilmiştir. Bu bağlamda Bilgi Teknolojileri ve İletişim Kurumu’nun bir yapısı olan Ulusal Siber Olaylara Müdahale Merkezi’nin siber güvenlik stratejisine ve uluslararası politikada bir etki aracı olması noktasında ne denli bir etkiye sahip olduğu üzerinde durulmuştur.
AtıfOpenAlex7TR Dizin6İncele - MakaleAçık Erişim2023An integrated Bayesian Best-Worst Method and GIS-based approach for offshore wind power plant site selection: A case study in North Aegean and Marmara Sea (Türkiye)
Gul, Muhammet; Yucesan, Melih; Konurhan, Zekeriya
In today’s world, renewable energy sources are in great demand due to the negative ef- fects of fossil fuels on the environment. Wind power plants are an important renewable energy source alternative to fossil fuel consumption. Offshore wind farms established in coastal areas and seas are used effectively in many parts of the world. The wind power plants, especially in the Northwest region of Turkey and the Aegean coasts, constitute an important potential. This study selects suitable sites for offshore wind farms in the Marmara Sea and North Aegean Coasts of Turkey by integrating the Bayesian Best-Worst method (BWM) and GIS. Bayesian BWM improves the traditional BWM integrating the preferences of multiple experts. In the study, 17 sub-criteria were determined under four main criteria of “technical”, “socio-economic”, “environment,” and “location”. Ex- perts’ judgments through the filled enabled the criterion weights to be obtained. The criteria weights found using the Bayesian-BWM model were integrated into the GIS, and suitable locations for the offshore wind farm were determined. Accordingly, the study area off the coasts of Aliağa, Bozcaada, and Gökçeada on the North Aegean coast, and the part south of the Marmara Sea and the area around Kapıdağ Peninsula are sugges- ted as suitable areas for wind power plants.
AtıfOpenAlex7İncele - MakaleYalnız künye2023Scopus SJRQ4Development of a best-worst method based MCDM approach for solar power plant location selection: an application to Tunceli, Turkey
Aykac, Yunus Emre; Yucesan, Melih; Gul, Muhammet
Solar energy stands out with its increasing potential in the world. The decision to choose the location of a solar power plant is very important due to the investment return. In this study, a solar power plant site selection for Tunceli, Turkey is studied with a two-stage multi-criteria decision-making approach. In the first stage, the importance levels of the determined nine factors are obtained by the best-worst method (BWM). In the second stage, the most appropriate site is selected among the eight districts of Tunceli. As a result of the first stage, solar and fault line emerged as the most and least important factor, respectively. The second stage showed that Pertek district is the most suitable place. A comparative framework has been created including five different MCDM methods, which strengthens the final decision's accuracy and reveals whether each method's results are correlated.
AtıfScopus5OpenAlex3
İncele - Kitap BölümüYalnız künye2023A GIS-Based BWM Approach for the Location Selection of Solar Power Plant in Tunceli Province (Turkey)
Konurhan, Zekeriya; Yucesan, Melih; Gul, Muhammet; Rezaei, J; Brunelli, M; Mohammadi, M
The world has recently tended to turn to renewable energy sources due to the serious negative impact of fossil fuels on the environment. One of the top priorities for solar energy is the selection of the most suitable location of the solar power plant to be established. In this study, the most suitable solar power plant location selection for Tunceli, a province located in the eastern part of Turkey, is studied with an approach based on Geographic Information System (GIS) and the best-worst method (BWM). A weighting was performed using the BWM model for 16 sub-criteria under four the main criteria of “climatic conditions, geographical conditions, land conditions, and location (distance to crucial points)”. Afterward, maps were created for these criteria, and a 6-point scale in the legends of each map for each sub-criteria was applied. Finally, the most suitable locations were determined with GIS-based calculations.
AtıfScopus6WoS5OpenAlex7
İncele - MakaleAçık Erişim2023Theoretical and Practical Investigation of Stability Performance for Power Regulation in Hydroelectric Power Plants
Kahraman, Gökhan; Işık, Erdem
Hydroelectric power plants are the insurance of the interconnected system in order to provide fast energy to the system compared to other fossil fueled power plants. Hydroelectric power plants control the balance between the energy it supplies to the interconnected system and the pressurized water it uses with a system based on the fully automatic control principle. The quality of the energy supplied to the interconnected system depends entirely on this automatic control mechanism. In this study, mathematical models of the mechanisms that affect the automatic control system during the generation of energy in hydroelectric power plants are formed. Transfer functions of the obtained mathematical models are calculated by laplace transform. With the calculated transfer functions, the responses of the units of a hydroelectric power plant to the change of the amount of energy produced under different operating conditions are determined. The obtained data are compared with the actual conditions in a 1330 MW hydroelectric power plant with 8 Francis turbines. It is seen that the mathematical model and the turbine responses in real conditions are similar. In the calculations made at 115, 125, 135, 145 m. net head, the best stability conditions were obtained at 135 m. In addition, as a result of the calculations obtained under different operating conditions, ideal operating conditions are determined to minimize the fluctuations in energy production.
AtıfScopus2OpenAlex2İncele - MakaleAçık Erişim2023Scopus SJRQ3Performance evaluation of steel-concrete composite structures designed in poorly graded soils
Etli, Serkan
In this study, the seismic behavior of steel concrete composite buildings in a specific region was investigated. For this purpose, 5-, 10-, 15- and 20-storey composite moment-resisting framed structures were designed. Moment-resist-ing composite framed structures are modeled with concrete-filled steel tube columns and designed and modeled using composite beams. The buildings are designed according to ÇYTHYE-2016 and TBEC-2018 regulations at design levels with high ductility. In the design of the designed structures, the peak ground acceleration value is 0.79 g, and the design ground is planned as ZE class. SeismoStruct software was used for the design and performance evaluation of the structures. During the performance evaluations of the structures, nonlinear static pushover and incremental dynamic analyzes were used. Uniform and triangular load distributions are adopted in the static pushover analysis and 16 earthquake ground mo-tions are used in the incremental dynamic analysis. Evaluation of the effect of the number of stories on the earthquake behavior of composite moment-resisting framed structures was investigated using the non-linear analyzes mentioned. Ac-cordingly, lateral response, overstrength factors, ductility, and dynamic behavior factor values for composite frame struc-tures were calculated and presented using the relevant analysis results. It has been calculated that the behavior factor of all moment-resisting composite framed structures can perform well above the design assumptions, whereas moment-resistant composite framed structures absorb seismic energy by using inelastic deformations. Ductility is almost 30% higher than the design assumption for international standards. As a result, it was concluded that these structures could continue to serve theoretically.
AtıfScopus6WoS3OpenAlex9İncele - MakaleAçık Erişim2023Scopus SJRQ1An Integrated Approach for Assessing Suppliers Considering Economic Sustainability Innovation
Ahmadi, Hadi Badri; Pamucar, Dragan; Pourhejazy, Pourya; Kaya, Sema Kayapinar; Liou, James J. H.
Innovation plays a key role for improving the sustainability performance of corporations. A truly sustainable innovative firm needs to take the social, environmental, and economic aspects of sustainable innovation into consideration. However, limited studies have investigated the economic aspect of sustainable innovation, especially in the context of supplier evaluation from emerging economies. To deal with this issue, this manuscript puts forward a criteria decision framework for evaluating economic sustainable innovative suppliers. A new methodology based on fuzzy Full Consistency Method (FFUCOM) and Improved Combinative Distance-based Assessment (ICODAS) is developed and extended using interval rough Dombi-Bonferroni operators. In the developed approach, the FFUCOM is employed to determine the criteria weights, and the ICODAS is responsible for assessing and ranking the suppliers. A case study from the manufacturing sector of an emerging economy is considered for validating the developed framework and decision model. The findings introduce the 'financial resumption of products' as the most critical economic innovation criterion for evaluating suppliers. This article significantly helps decision-makers and practitioners to better comprehend the underpinnings of sustainable innovation economic dimension, particularly when assessing their suppliers. Furthermore, the applicability and validity of the proposed model was confirmed by the results of sensitivity analysis. Findings demonstrated that the proposed method is a solid and useful MCDM framework, and its outputs are precise and acceptable.
AtıfScopus9OpenAlex6İncele - MakaleYalnız künye2023Scopus SJRQ1Analysis of the mechanical behavior and prediction of the plastic zone of a large-diameter buried gas pipeline under ground overload
Xu, Qian; Zhong, Liqiong; Shu, Mengjie; Zou, Zhenwei; Yang, Gang; Zheng, Qiang; Chen, Xingli; Akkurt, Nevzat; Zhang, Hui; Qiang, Yujie
Plastic failure of pipelines caused by ground overload is increasing. The one-dimensional model based on mechanical nodal parameters cannot predict the plastic failure characteristics of the three-dimensional structure of the pipeline. In order to predict the evolution of the plastic failure of the pipeline with the yield strength as the evaluation criterion, a multidimensional model is needed to consider the changes in the external loads and the changes in the mechanical properties of the pipeline along the circumferential and axial directions. In this study, a finite element calculation model for a large-diameter gas pipeline underground overload was established to investigate the law of stress change in the plastic zone. The nonlinear surface fitting method was used to establish the angle fitting model of the plastic zone and the depth fitting model of the plastic zone. The variation of the area of the plastic zone was described, and the reliability of the results was verified. In addition, the accuracy of the fitting model and the cost of the finite element calculation were evaluated. The results showed that the pipeline entered plasticity at a ground load of P = 25 MPa, and the plastic zone developed continuously in the axial and circumferential directions as the ground load increased. The angle and depth increased to 36° and 1.8 m, respectively, at P = 50 MPa. The average absolute errors for the plastic zone depth fitting model and the plastic zone angle fitting model were 6.42% and 6.64%, respectively, both of which can provide an accurate description of the plastic zone. The calculation results of the plastic zone angle fitting model could meet requirements of data processing and analysis. The plastic zone depth fitting model could be used to obtain solutions with higher accuracy, but it increases the cost of finite element simulation.
AtıfScopus6OpenAlex6İncele - MakaleYayıncıda açık erişim2023Scopus SJRQ1Evaluation of the effect of silica fume on the fresh, mechanical and durability properties of self-compacting concrete produced by using waste rubber as fine aggregate
Etli, Serkan
The supply of sand, which is obtained by disposing of natural resources for the purpose of concrete production and in accordance with production standards, is increasing rapidly and therefore its amount is rapidly depleted. A study is presented that aims to reduce the aggregate content by using this waste tire aggregate (WTA) in the construction industry, and thus, a sustainable production and conservation of nature is the basis. The water/binder ratio used in the study is kept constant as 0.39 and the binder dosage as 550 kg/m3. WTA and SF are replaced with sand and cement at the ratios of 5%, 10% and 15% by volume, and 5% and %15 b y weight, respectively. The fresh (slump flow, V-funnel, and L-box) and hardened (axial compression, splitting tensile strength, flexural tensile strength, diagonal tensile strength, and modulus of elasticity, chlorine penetration and sorptivity) properties of self-compacting concrete (SCC) mixtures produced in this way are evaluated. For the mechanical and durability tests, a total of approximately 500 SCC (100 × 100 × 500 mm: prism, 100 × 100 × 100 mm: cube and 100 × 200 mm: cylindrical) samples are produced. The mechanical experiments of SCC were carried out at 28-, 56- and 90-days age. The test results have shown that WTA substitute concrete, which can be used in terms of civil engineering in terms of all these features, has shown that it has sufficient performance.
AtıfScopus51WoS43OpenAlex55İncele - Kitap BölümüYalnız künye2023Healthcare Logistics and Digital Transformation
Kaya, Sema Kayapınar
Due to the complex and diverse structure of the healthcare industry, the healthcare industry's logistics practices have lagged far behind sectors such as retail and manufacturing. Therefore, in today's increasingly competitive and risky environment, it is critical for hospitals to improve their logistics management performance, increase the efficiency of health services, and reduce costs. This chapter synthesizes the contributions of healthcare logistics, the impact of medical logistics on healthcare providers, types of healthcare logistics. Addition, this chapter enables us to capture the research challenges associated with the healthcare logistics process, pharma logistics and show how digitalization initiatives can address them.
AtıfScopus2OpenAlex2İncele - BildiriAçık Erişim2023Yolov5 Based Fault Detection Approach in Railway Components
Yilmazer, Merve; Karakose, Mehmet
For safe transportation on the railway, the faults occurring in its components must be detected and repaired. Recently, fault detection methods have been developed on railway visual data using methods such as image processing, machine learning and deep learning. Especially since deep learning-based algorithms have a self-learning structure, the data used in model training and testing significantly affect the performance of the model. In the proposed method within the scope of this study, railway visual data were obtained using autonomous drone. YOLOv5 deep neural network is trained to detect faults that may occur in various components such as rail, fastener, sleeper and ballast in the railway. In order to increase the efficiency of the model, images obtained under different lighting conditions were included in the data set. In addition, by using the OpenCV library, the video stabilization process and the vibrations that occur during data acquisition in the video are eliminated. Thus, with the proposed method, it has been shown that the errors due to many components in the railway can be detected with a mAP rate of 94.5%.
AtıfScopus5OpenAlex3İncele - MakaleAçık Erişim2023A new approach based on convolutional neural network and feature selection for recognizing vehicle types
Doğan, Gürkan; Ergen, Burhan
The number of vehicles used in traffic life has reached enormous dimensions today. The increase in the number of vehicles day by day causes some traffic problems along with it; such as traffic congestion, accidents, pollution, and safety. To overcome all these problems, convolutional neural networks (CNN) methods are one of the trend methods used in recent years due to their success. In this study, a new approach is proposed to use this power of CNN in low-power devices. First of all, MobileNetv1, MobileNetv2, and NASNetMobile models were optimized to increase accuracy performance. Then, an approach is proposed in which these optimized mobile CNN approaches are used only as feature extractors, and methods such as combining, selecting, and classifying the obtained features are used together. As a result of the classification made with this approach, the classification accuracy has increased by approximately 5%.
AtıfScopus10OpenAlex12İncele - MakaleYalnız künye2023Scopus SJRQ1A holistic failure modes and effects analysis for university plastic injection laboratory under Bayesian Network
Yucesan, Melih; Gul, Muhammet; Pamučar, Dragan
University Research & Development (R&D) laboratories are facilities used for research and manufacturing activities in engineering and basic science fields. Various filling materials are used in plastic R&D laboratories to improve the mechanical properties of thermoplastics or to recycle waste materials. The use of filling materials causes changes in plastic production parameters. This study dealt with the risks arising from extrusion, injection and shredder in a plastic injection laboratory, which led to the inability to manufacture the appropriate product under a holistic methodology. The proposed holistic methodology merges the concepts of failure mode and effects analysis (FMEA), fuzzy best-worst method (FBWM), and a rule-based three-hierarchical Bayesian network (RB-THBN). First, 15 root risks have been identified under a three-stage hierarchy with the support of laboratory decision makers. Then, questionnaires were created using the FMEA concept. The importance values (degree of belief-DoB) of three different FMEA parameters (severity, occurrence and detection) by experts for each risk have been calculated with FBWM. And finally, the RB-THBN has been created, and the final risk values have been computed using the linear utility function for the network. The system has been analyzed via a Bayesian modeling software. A validity test and a control measures planning has also been executed. According to the results, the highest root risk has been determined as “E2-The prepared mixture is not homogeneous” with a crisp risk score of 0.639559. In addition, “Failure due to extrusion” has been determined as the highest risk category with a score of 0.564059. It was discussed in detail that these risks arise from homogenization and how the used mixture should be homogenized. A comparative study among traditional FMEA, FMEA extended under FBWM and the proposed approach is performed to observe the differences in final ranking of root risks and to highlight the arguments that strengthen the advantages of the proposed method over the other two.
AtıfScopus7WoS7OpenAlex8İncele - MakaleYalnız künye2023Scopus SJRQ1Analysis of the mechanical characteristics and plasticity-hazardous zones development of natural gas pipeline under overload
Zheng, Qiang; Shu, Zekai; Yang, Gang; Zhang, Hui; AKKURT, Nevzat; Guan, Ben; Chen, Weiwang; Xu, Qian; Zang, Yong; Ding, Yulong
The problem of natural gas pipeline overload failure is of great significance, and the development law of critical mechanical properties of pipelines is of great importance to the safety design of natural gas pipelines. This study establishes a three-dimensional finite element computational model of the pipeline that integrates the changes in axial and circumferential mechanical characteristics, and uses the yield strength, safety factor and ellipticity indexes as criteria to dimensionless the axial depth and circumferential angle of the plastic zone to explore the characteristics of the plastic damage stage of the pipeline. By solving the plastic hazardous zones based on the safety factor, the applicability of the dimensionless parameters is extended to investigate the development laws of the hazardous zones and the correlation mechanism between failure criteria and hazardous zones. The results show that as the ground load increases, the pipeline deformation gradually develops into the plastic stage (P = 16 MPa) and then goes through three deformation stages. With the increase of safety factor, the change trend of the proportion of stage I in the whole loading process decreases to 4 %, the change trend of the proportion of stage III increases significantly to 52 %, while the proportion of stage II shows a change trend of decreasing and then increasing, the proportion of this stage ranges from 30 % to 38 %. Based on the law of variation of axial ellipticity of pipeline section, a high-risk section of pipeline was identified in the range of 0–2 m from the point of maximum local compression strain. The results of the study can serve as a basis for accurate evaluation of the safety status of natural gas pipelines under overload.
AtıfScopus3WoS3OpenAlex3İncele - MakaleYalnız künye2023Scopus SJRQ2New Deep Learning-Based Passenger Flow Prediction Model
Utku, Anıl; Kaya, Sema Kayapinar
The ability to predict passenger flow in transport networks is an important aspect of public transport management. It helps improve transport services, aids those responsible for management to obtain early warning signals of emergencies and unusual circumstances and, in general, makes cities smarter and safer. This paper develops a long short-term memory-based (LTSM-based) deep learning model to predict short-term transit passenger volume on transport routes in Istanbul. This prediction model has been created using a dataset that included the number of people who used different transit routes in Istanbul at one-hour intervals between January and December 2020. The proposed multilayer LSTM-based deep learning model has been compared with popular models such as random forest (RF), support vector machines, autoregressive integrated moving average, multilayer perceptron, and convolutional neural network. The experimental findings showed that the proposed multilayer LSTM-based deep learning model outperformed the other models with regard to prediction for each transfer route. Furthermore, RF, one of the machine learning models used, produced remarkably successful results.
AtıfScopus19WoS12OpenAlex16İncele - Derleme MakaleYalnız künye2023Scopus SJRQ1A review of advances in mechanical behaviors of the underground energy transmission pipeline network under loads
Zheng, Qiang; Xu, Qian; Shu, Zekai; Yang, Di; Chen, Weiwang; Akkurt, Nevzat; Zhang, Hui; Lin, Lin; Zhang, Xinxin; Ding, Yulong
The safety of underground energy transmission pipeline network is threatened by traffic, earthquakes, explosions, and other stresses. To solve the problem of damage to the underground energy transmission pipeline networks by external loads, this study analyzed the mechanical properties of the Pipe-Soil Coupling System (PSCS) under external loads from a mechanical perspective. The pipeline constitutive model, the soil constitutive model, the internal effect of the PSCS, the influence of external stresses on the PSCS, and the dynamic response of the PSCS under various research methodologies were all studied. First, different mechanical features of the pipes and soil were employed to investigate the pipe and soil constitutive models. Second, based on the different force directions within the PSCS, the earth pressure and axial friction of the PSCS were investigated to clarify the interaction between the pipe and soil. For the purpose of to better understand the degradation of the underground pipeline state, the impacts of man-made and natural stresses on the PSCS failure were explored. Finally, the results of the investigation of the dynamic response of the PSCS were examined for their applicability using three research methods: theoretical analysis, numerical simulation, and experimental analysis. It is found that the existing constitutive models of pipeline and soil are lack of basis, which increases the difficulty of the selection of constitutive models in the process of research. In the analysis of load effect, earth pressure plays a dominant role in affecting the local stability of pipeline, but the calculation accuracy of soil pressure needs to be improved. Due to the lack of experimental guidance for complex damage phenomena under external loads, it is impossible to accurately determine the limit state parameters of pipelines under complex damage modes. It is critical to create and refine the theory underpinned by numerous experimental data in order to address the issue of pipeline dynamic response under multi-field coupling, including explosion and earthquake. This work is critical for analyzing existing research findings, identifying future research problems, and enhancing buried pipeline safety management.
AtıfScopus15WoS13OpenAlex14İncele - MakaleAçık Erişim2023Scopus SJRQ2Investigation on application of plate-tube evaporative condensating technology for data centres in the northwest of China
Wu, Xueyuan; Shao, Shuangquan; Akkurt, Nevzat
The rapid development of data center leads to a rapid increase in energy consumption. In this paper, the plate and tube evaporative condenser is proposed for the water-cooled chiller and the data center cooling system to improve the energy efficiency in hot and dry summer and avoid icing in cold winter. The chiller can operate in the wet mode for compressor refrigeration and the dry mode for free cooling with the coefficient of performance (COP) of 5.2 in wet mode and up to 33.3 in dry mode. Furthermore, the system is applied in a data center in Ulumiqi, which is located in the dry and cold region and its ambient air temperature can vary from −32 °C to 45 °C throughout the year. The actual operation results show that the power usage effectiveness (PUE) value of the whole data centre is 1.349 in June, 1.229 in December, and 1.320 as the annual average, which is stable and efficient for five consecutive years. These results ensure the proposed system is an important technical solution for energy saving and emission reduction in data centres in cold regions.
AtıfScopus9WoS5OpenAlex8İncele - MakaleYalnız künye2023Scopus SJRQ2An Estimation Proposal for Engineering Properties of Modified Concrete by using Standalone and Hybrid GRELM
Cemalgil, Selim; Onat, Onur; Aruntaş, Hüseyin Yılmaz
The presented study pertains to an attempt to propose a novel prediction model to predict the flexural and compressive strengths of concrete modulated using steel fiber (SFb) and silica fume (SF). A completed experimental investigation is adopted for the current study, and a research plan is employed. Three different superplasticizers amount (SP), different SF replacement ratios, and a constant amount of SFb were used by the weight of cement to meet the C25 target strength. A sum of 16 distinct mixtures designed by changing SP and SF ratios were developed. Furthermore, SFb was added at a fixed rate of 65 kg/m3 to all planned concrete mixes. In addition, SFb was used to create a 16-mix design. Finally, a total of 32 distinct mix designs were created. Produced, hardened specimens were exposed to two different curing conditions. This research uses the mechanical characteristics of concrete treated with SF, SP, and SFb to estimate by conducting standalone and hybridized generalized extreme learning machine (GRELM) algorithms based on available experimental data in terms of the metaheuristic aspects of this work. With continuous input data, four separate data sets were constructed. Compressive strength and flexural strength were estimated separately. With the aid of the Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms, binary and ternary hybrid approaches were developed and tested on the data. Four distinct estimation models were suggested. Two quality metrics were used to evaluate the estimation performance: Root Mean Square Error (RMSE) and correlation of determination (R2). The estimation results showed that the hybridized GRELM-PSO-GWO estimation model that was built for prediction was relatively successful in all sets.
AtıfScopus4WoS3OpenAlex2İncele - MakaleAçık Erişim2023Scopus SJRQ1Physical-Mechanical and Electrical Resistivity Properties of Cementitious Mortars Containing Fe3O4-MWCNTs Nanocomposite
Selen, Veyis; Guler, Omer; Nodehi, Mehrab; Sarı, Ahmet; Yaras, Ali; Gencel, Osman; Gholampour, Aliakbar; Ozbakkaloglu, Togay
Recent growth in materials science and engineering technologies has pushed the construction industry to engage in new applications, such as the manufacturing of smart and electrically conductive products. Such novel uses of conductive construction materials would potentially allow their use in conjunction with various fields, such as those referred to as “Industry 4.0.” The following study uses iron oxide (Fe3O4)-multi-walled carbon nanotubes (MWCNTs) nanocomposites synthesized by chemical vapor deposition (CVD) and incorporated into the cementitious mortars as a substitute for sand at 1, 2, and 3% ratios to enhance the electrical conductivity. Results reveal that the electrical resistivity of cementitious composites decreases (due to the increase in electrical conductivity) from 208.3 to 61.6 Ω·m with both the Fe3O4-MWCNTs nanocomposites ratio and the increasing voltage. The lowest compressive strengths at 7 and 28 days are 12.6 and 17.4 MPa for specimens with 3% Fe3O4-MWCNTs and meet the standards that comply with most applications. On the other hand, the highest porosity was reached at 26.8% with a Fe3O4-MWCNTs rate of 3%. This increase in porosity caused a decrease in both the dry unit weight and ultrasonic pulse velocity (from 5156 to 4361 m/s). Further, it is found that the incorporation of Fe3O4-MWCNT nanocomposites can have a negative effect on the hardening process of mortars, leading to localized air cavities and an inhomogeneous development of cementing products. Nonetheless, the improvement of the electrical conductivity of the samples without significantly compromising their physico-mechanical properties will allow their use in various fields, such as deicing applications with low-voltage electric current.
AtıfScopus7OpenAlex7İncele
