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 Erişim2022Scopus SJRQ1Evaluation of the mechanical properties and durability of self-compacting alkali-activated mortar made from boron waste and granulated blast furnace slag
Yön, Merve Şahin; Karataş, Mehmet
The production of high-strength alkali-activated mortar and concrete by using waste materials instead of cement in order to reduce the amount of carbon dioxide released to nature in cement production is an important study that attracts the attention of researchers. In this study, self-compacting alkali-activated mortar samples were produced using boron waste (BW) and granulated blast furnace slag (GBFS). Prismatic samples of 40 × 40 × 160 mm and cubes of 50 × 50 × 50 mm were produced, in which 0%, 5%, 10%, 15%, 20%, 25% of BW were used. To achieve self-compacting alkali-activated mortar (SCAAM) slump-flow test method was conducted by per The European Federation of Specialist Construction Chemicals and Concrete Systems (EFNARC) guidelines. The samples prepared using Na2SiO3 (NS)/NaOH (NH) = 3.0 were exposed to oven curing at 60 °C and 100 °C for 3 days. The flexural and compressive strength (CS) values of 3, 28 and 90 days were obtained for the samples whose curing period was completed. According to the mechanical strength results, influence of capillary water absorption, porosity, water absorption and density and freeze-thaw from durability tests were carried out. After experimental tests, Scanning Electron Microscope (SEM) and Energy-dispersive X-ray Spectroscopy (EDS) images were utilized to determine microstructures of the samples. As a result of the study, it was determined that the highest strengths were obtained at the curing temperature of 60 °C. Also, it was seen that mechanical strengths and durability decreased with the increase in the BW ratio in the mixtures.
AtıfScopus31WoS28OpenAlex33
İncele - MakaleYalnız künye2022Scopus SJRQ1A novel prediction model for durability properties of concrete modified with steel fiber and Silica Fume by using Hybridized GRELM
Cemalgil, Selim; Gül, Enes; Onat, Onur; Yılmaz Aruntaş, Hüseyin
The service life performance of conventional and modified concrete subjected to harsh climatic condition environment is directly related to durability properties of concrete like abrasion, freezing and thawing cycles. These properties are critical issues that should be predicted before performing experimental test. On this basis, the basic purpose of this paper is to predict the abrasion loss, freezing and thawing properties of concrete modified with silica fume (SF) and steel fiber (SFb) by using mix design and additional properties. From this point of view, a conducted experimental study was selected as a case study. In the control concrete (CC) mixtures, Portland cement, crushed stone aggregate, and superplasticizer (SP) were used in the selected experimental study. SP in concrete mixtures was used in the amounts of 1.0%, 1.5%, and 2.0% by weight of cement, and so modified concrete was produced with and without SFb according to the target strength of C25. Furthermore, SF and SFb were used in different amounts to modify the concrete. The SF was replaced with cement in the amounts of 7.5%, 10.0%, and 15.0%. In total, 16 different mix designs were prepared with different SP and SF ratios. In addition, SFb was added to all mixtures of designed concrete at a constant amount of 65 kg/m3. Additionally, a 16-mix design was prepared with SFb. Cumulatively, 32 different mix designs were prepared for the experimental study. Tests on the fresh, hardened, and life-cycle performance properties of the concrete were conducted. As for the metaheuristic part of this study, on the basis of the available experimental data, life-cycle performance parameters of the concrete modified with SF and SFb are predicted by using single and hybrid generalized extreme learning machine methods. Eight different data sets were generated with gradually extended input data. Two different outputs were considered: abrasion resistance (AL) and freezing/thawing (FT). Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) algorithms were used to produce binary and ternary hybrid methods. Four different models were proposed as listed: single use of Generalized Extreme Learning Machine (GRELM), binary use of GRELM-PSO, and GRELM-GWO. Finally, PSO and GWO were hybridized and integrated into GRELM. Two quality indicators, namely Root Mean Square Error (RMSE) and correlation of determination (R2), were considered to see the performance of the prediction. The results showed that the proposed ternary prediction model composed of GRELM-PSO-GWO provided more accurate results in all sets from 74% to 91% by extending input parameters, even if complicated parameters are inserted in as an input to the data set.
AtıfScopus28WoS22OpenAlex25İncele - MakaleAçık Erişim2022Scopus SJRQ3A New Rail Surface Defects Detection Approach Using 3D Laser Cameras Based on ResNet50
Santur, Yunus; Yilmazer, Merve; Karakose, Mehmet; Akin, Erhan
Rail transportation systems, which are used as one of the most common means of transportation worldwide, should be regularly inspected to prevent accidents that may occur. The rail condition monitoring can be performed in high accuracy and real time using computer vision, deep learning algorithms today. In this study, a new deep learning based approach using 3D laser cameras for rail inspection is presented. In the proposed approach, two 3D laser cameras placed on a real train, seeing the rail line from the left and right surfaces were used. These data consisting of sensitive distance value constitute the input data of the ResNet50 transfer learning model. The training was carried out on Nvidia Cuda supported graphics processing units using ResNet50 Convolutional Neural Network. During the test phase, the operation speed and accuracy rate of the method was measured by repeating the process on real-time rail profiles. The accuracy rate was calculated as 94%. As a result a new approach is presented based on deep learning using 3D laser cameras for rail inspection is presented.
AtıfScopus12WoS8OpenAlex9İncele - MakaleAçık Erişim2022Scopus SJRQ3Investigation of rutting, fatigue and cracking resistance parameters of CR modified warm asphalt binders compare with SBS modified binders
Akpolat, Mustafa
This study compares the rutting and cracking resistance and fatigue parameters of crumb rubber (CR) modified warm asphalt binders, which were determined by viscoelastic continuum damage (VECD) theory. The effect of the combination of CR modification and Sasobit, a warm mix additive, was investigated. Performance of CR + Sasobit compound was compared with styrene-butadiene-styrene (SBS) modification. Newly developed rheological tests such as multi stress creep recovery (MSCR), lineer amplitude sweep (LAS) and conventional tests were applied to modified binders. It was determined that the CR + Sasobit modified binders improved the rutting parameter better in comparison to SBS-added binders. Although the CR additive improved the rheological properties of the binder at low and medium temperatures, this effect was reduced when used with Sasobit additive. Sasobit additive increased the stiffness and decreased the fatigue parameter at low temperatures. Besides, the results of the LAS test revealed that at high strain values (i.e.> 6%), the fatigue life of CR and Sasobit modified binders was lower than the fatigue life of the pure binder. In other words, CR and Sasobit modified binders could not preserve material integrity.
AtıfScopus13WoS13OpenAlex12İncele - MakaleYalnız künye2022Scopus SJRQ3The Effect of Using Waste Tire as a Fine Aggregate on Mechanical Properties of Fly Ash-Substituted Self-Compacting Concrete
Cemalgil, Selim
Wasted tyres are commonly used in civil engineering applications for a variety of purposes, including as concrete ingredients. Wasted tires that are mechanically sheared into shreds ranging in size from 25 to 300 mm and intended for use in concrete are called " Waste Shreded Tyre Aggregate" to make a contribution to sustainable waste management. Currently, at this point, the basic philosophy of this study is to investigate the effects of Waste Tire Aggregate (WTA) on the mechanical and durability properties of Self Compacting Concrete (SCC) to provide a contribution to reusing waste tires in the construction industry. WTAs with 5, 10, and 15% volume ratios are substituted for fine aggregate in SCC production. In addition, 15% mixtures with a binder quantity of 550 kg/m3, including 20 and 30% fly ash (FA) were substituted and prepared to be compared with the control concrete. To measure the rheological properties of SCCs, slump flow, V-funnel and L-box tests were performed. Then, the produced concrete samples of different sizes were cured under laboratory conditions for 28 days and then subjected to hardened concrete tests on the 28th, 56th and 90th days. The hardened concrete tests were composed of axial compressive strength, flexural strength, splitting tensile, diagonal tensile, abrasion resistance, modulus of elasticity. Finally, a durability test was performed as chlorine penetration depth. The test results show that WTA positively affects the properties of fresh and hardened SCC. Only, the increase in the substitution rate of WTA in concrete mixtures decreased the hardened state strength of the SCC. However, the addition of WTA to up to 15% of the total fine aggregate volume indicates that it is possible to apply recycled WTA to SCC and successfully satisfy both fresh and hardened SCC specifications.
AtıfScopus4WoS5OpenAlex4İncele - MakaleYalnız künye2022Scopus SJRQ2Linear programming with fuzzy parameters for inventory routing problem in effective management of personal protective equipment: a case study of corona virus disease 2019
Göçmen, Elifcan
Coronavirus disease 2019 (COVID-19) brings about severe disruptions for human living, economics, and environmental balance. This pandemic has boosted the demand for personal protective equipment (PPE) and thus, medical wastes. Thus, a research hypothesis is stated whether it would be possible to provide more efficient distribution and inventory planning to optimize the PPE availability in a fuzzy environment. To confirm the hypothesis, in addition to addressing a scientific novelty considering integration of linear programming with fuzzy parameters, named as the Jimenez’s method and clustering heuristic methods, the practicality of these approaches is provided on a real case study and generated instances from Turkey. The computational results reveal that clustering the 32% of the hospitals ensures optimum total cost and solution time while feasibility degree changes between 0, 4, and 1 values of the Jimenez are not more effective on the results. Improved cost results reveal the economic importance of the healthcare supply chain management and optimal PPE distribution and inventory planning can break down the disease propagation and reduce the detrimental impacts on human life. The proposed approach, for the first time, ensures practical and theoretical insights of distribution and storage decisions across disciplines, namely, engineering and health-care organization authorities.
AtıfScopus19WoS12OpenAlex19İncele - MakaleYalnız künye2022Scopus SJRQ1A calibrated Fuzzy Best-Worst-method to reinforce supply chain resilience during the COVID 19 pandemic
López, Cristina; Ishizaka, Alessio; Gul, Muhammet; Yücesan, Melih; Valencia, Daniela
Making decisions require increasingly more sophisticated methods. The Best-Worst method was developed recently to find a good balance between the amount of information required and its consistency. The Fuzzy Best-Worst method was then proposed to integrate the uncertainty and imprecision of evaluations. In this paper, we propose the Calibrated Fuzzy Best-Worst Method, which enables us to define personalized fuzzy numbers. This new method was applied to the real case study of a global fashion supply chain suffering a dramatic drop of demand due to the COVID-19 shocks. Since its upstream was leading to a ripple effect on the rest of the supply chain stages, our study focused on evaluating the viability of its distribution channels based on weighted resilience capabilities and performance indicators. The proposed method allowed being more precise than the traditional Best-Worst method because it personalizes the uncertainty and subjectivity. The results revealed that cash flow, revenues, and inventory turnover were the most important performance indicators in the supply chain resilience. Financial strength, adaptability, and market position were shown to be the most critical resilience capabilities in preserving supply chain survivability with low-demand items and longer disruptions. Their effects explain why e-commerce was the most viable distribution channel.
AtıfScopus26WoS24OpenAlex29İncele - BildiriAçık Erişim2022Railway Condition Monitoring and Fault Detection Based on YOLOv4
Yilmazer, Merve; Karakose, Mehmet
Regular maintenance of the line is critical for safety in railway transportation, which constitutes an important part of the transportation system. Due to the high error rate of manual fault detection methods, non-contact fault detection methods have been developed. Railway switch state and level crossing faults are frequently encountered in the occurrence of train accidents. A new method based on YOLOv4 has been proposed for condition monitoring and fault detection in these rail sections. The YOLOv4 deep neural network was trained using four class label datasets consisting of real railway visual data. Model evaluated using test data. Performance evaluation was made using evaluation metrics. Experimental results showed that the model could detect correctly with 96.8% accuracy.
AtıfScopus8OpenAlex9İncele - MakaleYalnız künye2022Scopus SJRQ2A new signal processing approach/method for classification of power quality disturbances
Akmaz, Düzgün
The disadvantage of conventional signal processing methods used for Power Quality (PQ) classification is that their mathematical calculations are complex. Therefore, it is necessary to develop simple, effective, and fast signal processing tools to analyze the PQ signal. In this study, a new signal processing method with simple mathematical operations based on the Integer Factor (IF) down sampling/Approximation Derivatives (AD) was developed to analyze PQ signals. IF was employed to analyze the signals at various sampling frequencies, while the AD method was employed to obtain different degrees of detail and approximation coefficients for the signals. In order to prove that the IF/AD signal processing method can perform a fast and detailed signal processing analysis, the IF/AD method and the Discrete Wavelet Transforms (DWT)/Multiresolution method, which is one of the basic signal processing methods, were compared. It was determined that the developed signal processing method has analyzed PQ disturbances in a shorter time and in more detail than DWT/Multiresolution method. After it was determined that the IF/AD method was effective in the analysis of PQ signals, a new classification method based on the IF-AD signal processing approach, the Slime Mould feature selection algorithm, and Support Vector Machine was developed. The classification method was applied to synthetic signals with noise, real-time data generated in the laboratory and PQ online data. The results proved that the developed classification method was successful. Therefore, this study will provide a different approach to PQ classification methods and non-stationary signal analysis studies.
AtıfScopus10WoS8OpenAlex9İncele - MakaleYalnız künye2022Scopus SJRQ2Effect of nonlinear modeling approaches used for composite elements on seismic behavior of composite framed buildings
Etlİ, Serkan; Güneyİsİ, Esra Mete
This study aims to assess the effect of nonlinear modeling approaches used for frame elements while appraising the seismic performance of the composite moment resisting frame (CMRF) buildings. To this, the accuracy and efficiency of two representative numerical models (namely, inelastic force-based frame element-distributed plasticity (DP) and inelastic force-based frame element-plastic hinge length (PHL) (lumped-plasticity)) for the columns and beams of CMRFs are evaluated comparatively. The number of stories of the buildings of the case study ranges from 5 to 15 and consists of columns made of concrete-filled steel tube sections and CMRFs designed with composite beams consisting of a combination of solid reinforced concrete slabs and steel beams. The structures are designed by considering high ductility level. Seismostruct software is used for design and performance analysis. During the performance evaluation of the structures, the nonlinear static pushover analysis is utilized as well as the incremental dynamic analysis. While performing the nonlinear static pushover analysis, the lateral loadings with uniform and triangular load distributions are used, and moreover, a series of earthquake ground motions are used in the incremental dynamic analysis. To evaluate the effect of the modeling approaches, the seismic response of the structures is assessed by comparing the load-displacement response, energy consumption, performance limit. Additionally, the behavior factor, dynamic behavior factor, inherent strength and overstrength factors, ductility factor and global yield value are discussed.
AtıfScopus2WoS2OpenAlex16İncele - MakaleAçık Erişim2022Scopus SJRQ1A new mobile convolutional neural network-based approach for pixel-wise road surface crack detection
Doğan, Gürkan; Ergen, Burhan
In recent years, the worldwide road network has grown rapidly and reached an enormous size. Parallel to this size of the road network, the imperfections on the road surfaces are just as large. This has led to a significant increase in road maintenance costs for traffic management departments. Researchers have proposed methods for automatic flaw detection using deep neural networks to reduce road maintenance costs. However, these methods are insufficient in terms of performance and lightness. In this study, a convolutional neural network-based approach is proposed, which provides more successful road surface crack detection and requires less lightweight compared to other studies. Since the performance of the proposed approach is higher and more lightweight, it can be used more effectively and efficiently in mobile systems.
AtıfScopus60WoS55OpenAlex63İncele - MakaleYalnız künye2022Scopus SJRQ2A mathematical programming model for facility location optimization of hydrogen production from renewable energy sources
Derse, Onur; Göçmen, Elifcan; Yılmaz, Ebru; Erol, Rızvan
Fossil fuels are the primary energy sources and meet the global energy demands. However, environmental and health problems related with these sources boosted the demand for renewable energy sources. Hydrogen, as an energy carrier has a growing potential for solving these problems. In this article, a mathematical programming model that integrates the production, storage and transportation, safety, location, and staff assignment decisions is presented considering minimization of costs. Although most of the studies focus on location, distribution, storage decisions of hydrogen energy networks, the article also includes production, safety and staff assignment decisions to make this problem more practical. Furthermore, we also investigate the set covering constraint will ensure that each region is covered by minimum number of the hydrogen facilities. The developed model ensures a balance between location, distribution, storage, production, safety and staff decisions by installing two production facilities by assigning total 9 warehouses, 22 tank trucks, 12100 km pipeline, 35 staffs under distance constraint 2000 km in regions 1 and 5. The computational results indicate that the proposed model produces effective solutions for the coverage to all region and minimum total cost for real-case situations.
AtıfScopus20WoS16OpenAlex29İncele - MakaleAçık Erişim2022Scopus SJRQ1MULTI-LAYER PERCEPTRON BASED TRANSFER PASSENGER FLOW PREDICTION IN ISTANBUL TRANSPORTATION SYSTEM
Utku, Anıl; Kaya, Sema Kayapınar
Predicting passenger movement in transportation networks is a critical aspect of public transportation systems. It allows for a greater understanding of traffic patterns, as well as efficient system evaluation and monitoring. It could also help with precise timing to emergencies or important events, as well as the improvement of urban transport system weaknesses and service quality. The number of transfer passengers demand in Istanbul, Turkey's biggest and most developed metropolis, was used to construct a real-world forecasting model in this study. The number of transfer passengers has been forecasted using popular machine learning methods such as kNN (k-Nearest Neighbours), LR (Linear Regression), RF (Random Forest), SVM (Support Vector Machine), XGBoost and MLP. The dataset utilized is made up of hourly passenger transfer counts gathered at two public transportation transfer stations in Istanbul in January 2020. Using MSE, RMSE, MAE and R2 parameters, each model's experimental data have been thoroughly evaluated. MLP has more successfully other machine learning algorithms in the majority of transportation lines, according to the experimental results.
AtıfScopus27OpenAlex25İncele - MakaleAçık Erişim2022Effects of single-walled carbon nanotubes and steel fiber on recycled ferrochrome filled electrical conductive mortars
Dehghanpour, Heydar; Doğan, Fatih; Subaşi, Serkan; Maraşli, Muhammed
The production of electrically conductive concrete was introduced years ago among construction materials, generally for anti-icing. The present study investigates the electrical, mechani-cal, dynamic, and microstructural properties of recycled ferrochrome filled cementitious mortars containing single-walled carbon nanotubes (SWCNTs) and steel fiber. Within the scope of the study, a total of 5 different mixtures were obtained. 7, 14, and 28-day non-destructive and 28-day compressive and bending tests of cementitious conductive mortars obtained from five different mixtures were performed. The two-point uniaxial method was used to determine the electrical conductivity properties of the samples. The damping ratio of the samples was obtained by performing dynamic resonance tests. Ultrasound pulse velocity (UPV) and Leeb hardness tests were performed as other non-destructive testing methods. Microstructure analysis at the interfaces of conductive concrete samples was characterized by scanning elec-tron microscopy (SEM), EDS (Energy-Dispersive X-ray Spectroscopy), and X-ray diffraction (XRD). The results showed a logical agreement when comparing their mechanical, physical, and dynamic properties. When SWCNT is used with steel fiber, the conductive mortar samples exhibited good conductivity, while their compressive and bending strengths turned below.
AtıfScopus11OpenAlex13
İncele - MakaleYalnız künye2022Scopus SJRQ2Fault location method on two-terminal transmission line using synchronized time information of traveling waves
Akmaz, Düzgün; Mamiş, Mehmet Salih
In this study, approximate derivative (AD) signal processing method using synchronous voltages data, based on the traveling wave theory, was developed to determine fault locations in transmission lines. The first aerial mode voltage signals were obtained by applying the Clarke transformation to the voltage signals that occur after a short circuit fault. Then, by taking the first AD of the aerial mode voltage signals, the traveling waves were obtained. Finally, the location of the fault was found by using the time difference information of the traveling waves, wave velocity value and transmission line length. The proposed signal processing method was found to be effective in determining the location of faults. It was tested and compared to the discrete wavelet transform (DWT) for various fault conditions. Based on the simulation results, the proposed method was found to have a slightly higher success rate than DWT, in general. Moreover, it can work with low sampling frequencies, and it provides a better resolution than DWT to display the traveling waves in noise conditions.
AtıfScopus9WoS8OpenAlex7İncele - MakaleYalnız künye2022Scopus SJRQ2Corrosion potential and electromagnetic shielding effectiveness of geopolymer tiles produced with waste metal particles
Gülmez, Nihan; Koçkal, Niyazi Uğur; Özen, Şükrü; Ateş, Kayhan
This study is related to the production of special geopolymer specimens, where high effectiveness is provided in terms of electromagnetic interference (EMI) shielding and corrosion resistance. The study is important for the preparation of silica fume/slag based geopolymers by using waste steel and iron powder as a partial substitute for slag aggregate and thus to provide an effective solution to the disposal problems of waste metals. The electromagnetic interference shielding effectiveness (SE) of geopolymer tiles of 7.6 ± 0.1 mm thickness with different metal contents was measured at 4.9–7.05 GHz. Corrosion activity was monitored by measuring the half-cell potential of copper/copper sulphate (Cu/CuSO4) on specimens kept under controlled laboratory conditions for a period of 90 days at %60 relative humidity according to ASTM C876. In addition, anextensive evaluation of the optimization research on the design and proportion of mortar mixtures is presented here. EMI shielding effectiveness of slag based geopolymer tile with 10% steel particles has been determined as 26.1 dB in the frequency range 4.9–7.05 GHz. The results show that the shielding effectiveness reached a maximum of 23.1 decibels (dB) for geopolymer tiles in 40% iron powder content. Also, from experimental results, it was learned that geopolymer specimens with high slag content as binders in the mixtures showed better corrosion resistance.
AtıfScopus10WoS10OpenAlex10İncele - MakaleAçık Erişim2021Beton Dayanımının ve Kirişlerdeki Çekme Donatısı Oranının Orta Yükseklikli Betonarme Binaların Sismik Davranışı Üzerine Etkisinin Belirlenmesi için Artımsal Dinamik Analiz
Onat, Onur; Yön, Burak
Artımsal Dinamik Analiz (ADA), sismik yükler altında yapısal performansı değerlendirmek için birkaç farklı biçimde yaygın olarak kullanılan parametrik bir sonuç analizi yöntemidir. Bu yöntem, seçilmiş olan bir grup sismik kayıtın ölçeklenerek yapısal sisteme etki ettirilerek, bu etki altında, elastik tepkiden genel dinamik yapısal stabiliteye ulaşmayı öneren bir analiz türüdür. Bu çalışmada çekme donatısı oranı ve beton dayanımının orta yükseklikli betonarme yapıların sismik davranışı üzerine etkisi incelenmiştir. Sayısal çalışma olarak 5 açıklıklı, 5 ve 7 katlı iki farklı sayısal model oluşturulmuştur. Her bir model için üç farklı çekme donatısı oranı ve iki farklı beton sınıfı seçilmiştir. Çekme donatısı oranları, basınç bölgesindeki donatının yarısı, bir katı ve iki katı olarak belirlenmiştir. Sayısal modeller artımsal dinamik yük altında analiz edilmiştir. Bu analiz için on bir farklı sismik kayıt kullanılmıştır. Bu kayıtlar 0.2g’den 1.2g’ye kadar 0.2g artımlar ile ölçeklenmiştir. Yapılan artımsal dinamik analizler sonucunda yapısal sistemlerin taban kesme kuvvetleri ve karşılık gelen çatı katı deplasmanları karşılaştırılmıştır. Elde edilen analiz sonuçlarına göre kirişlerde çekme donatısı oranını arttırmak çatı katı deplasmanını düşürmese de katlar arası göreli ötelenmeyi azaltmıştır, böylelikle hasar seviyesini azaltacağı için hasar oranını düşürmektedir.
AtıfOpenAlex2TR Dizin1İncele - MakaleAçık Erişim2021A novel inter-story drift limit proposal for TBEC2018 and fragility prognosis with TSC2007
Onat, Onur; Yön, Burak
The basic purpose of this paper is to investigate and propose a novel inter-story drift limits for the currentTurkish Seismic Code to get easy structural assessment by using software. For this aim, numerical analysiswas performed by modeling two types of RC frame structures. One of them is 5 stories, the other of them is7 stories. Two different concrete classes, C20 and C25, were considered and three tension reinforcementratios were considered for analysis. Tension reinforcement ratios were determined by half of the compressivereinforcement, equal to compressive reinforcement and double the compressive reinforcement ratio.Incremental dynamic analyses (IDA) were performed on these buildings. In this study to execute IDA, elevenseismic acceleration benchmark records were multiplied with various scaling factors from 0.2 to 1.0.Maximum base shear and corresponding roof displacement responses obtained from IDA curves weregenerated according to these responses. IDA curves were compared with each other by deriving fragilitygraphs. According to results, proposed limits for the current Turkish seismic code (TBEC-2018) provide,0.6%, 2.4% and 3.3% respectively for MN, GV and GC, rather safe limits compared to drift limits presentedin the foredate seismic code (TSC-2007).
AtıfOpenAlex2TR Dizin2İncele - MakaleAçık Erişim2021İMobileNet CNN Yaklaşımları ve Özellik Seçme Yöntemleri Kullanarak Araç Türlerini Sınıflandırma
Ergen, Burhan; Doğan, Gürkan
Günümüzde, trafik hayatında seyreden araç yoğunluğu ciddi boyutlara ulaşmıştır. Bu nedenle, mevcut ulaşım ağlarının kullanım kapasitesi maksimum seviyelere çıkmakta ve trafik sıkışıklığına yol açmaktadır. Akıllı Ulaşım Sistemlerinin bir çözümü olan Görsel Trafik Gözetleme Sistemleri trafik sıkışıklığını azaltmak için kullanılan alternatif yöntemlerden biridir. Görsel Trafik Gözetleme Sisteminin temel görevlerinden biri; video veya görüntülerden algılanan araç türlerini doğru bir şekilde sınıflandırmaktır. Bu çalışma, Görsel Trafik Gözetleme Sisteminin araç türlerini sınıflandırma doğruluğunu arttıracak yeni yöntemler sunmayı amaçlamaktadır. Çoğu görüntü sınıflandırma doğruluğunu arttıran çalışmalarda geleneksel yöntemler kullanılırken bu çalışmada günümüzde trend olan mobil evrişimli sinir ağları (MCNN) iki farklı yaklaşımla ele alınmaktadır. İlk olarak, MobileNetv1 ve MobileNetv2 modelleri optimize edilerek İMobileNetv1 ve İMobileNetv2 yaklaşımları önerildi. İkinci olarak, bu önerilen MCNN yaklaşımları sadece özellik çıkarıcı olarak kullanıldığı ve elde edilen özelliklerin birleştirilmesi, seçilmesi ve sınıflandırılması gibi yöntemlerin birlikte kullanıldığı bir yaklaşım önerildi. Önerilen yaklaşımlarla yapılan sınıflandırma sonucunda, %85,05 oranında çok yüksek bir sınıflandırma başarısı elde edilmiştir.
AtıfOpenAlex3TR Dizin2İncele - MakaleAçık Erişim2021Atık lastiklerden elde edilen siyah karbonun asfaltın işlenebilirlik özelliklerine etkisi
Geçkil, Tacettin; İnce, Ceren Beyza; Aksağan, Zülfükar
Bu çalışmada, atık lastiklerden elde edilmiş olan siyah karbon (SK) katkısının asfaltın orta ve yüksek sıcaklıklardaki işlenebilirlik özellikleri üzerindeki etkisi araştırılmıştır. Bu amaçla, penetrasyon sınıfı B 160/220 olan saf asfalta ağırlıkça %5, 10, 15 ve 20 oranlarında SK eklenerek modifiye asfaltlar elde edilmiştir. Saf ve modifiye asfaltların fiziksel özellikleri penetrasyon, yumuşama noktası ve düktilite testleri ile belirlenmiştir. Ayrıca, bağlayıcıların sıcaklık hassasiyetlerinin bir ölçüsü olarak kabul edilen penetrasyon indeksi (PI) değerleri de hesaplanmıştır. Daha sonra, saf ve modifiye bağlayıcıların yüksek sıcaklıklarda bünyelerinde meydana gelen uçucu madde kaybı dönel ince film etüvü deneyi (RTFOT) ile, bağlayıcıların işlenebilirlik özellikleri ise dönel viskozimetre (RV) deneyi ile belirlenmiştir. Fiziksel test sonuçlarına göre, SK katkısıyla bağlayıcıların sertleşme eğiliminin arttığı ve penetrasyon sınıfının B 100/150 olarak değiştiği görülmüştür. Ayrıca, SK katkısıyla bağlayıcıların sıcaklık hassasiyetlerinin azaldığı bu bakimdan en uygun oranın %15SK olduğu görülmüştür. RV sonuçlarına göre, SK katkısıyla bağlayıcıların işlenebilirliklerinin azalarak karıştırma ve sıkıştırma sıcaklıklarının yükseldiği görülmüştür.
