Profile URL: https://hdl.handle.net/20.500.13091/11886
Job Title:Doç. Dr.
Email Address:vyilmaz@ktun.edu.tr
Main Affiliation:02.02. Department of Civil Engineering
Status: Current Staff
ORCID:
0000-0002-5407-860X
0000-0002-5407-860XScopus ID:
57201021510
57201021510YÖK Akademik: 0470D6D5DFB107B1
Google Scholar:
g5I-xS0AAAAJ
g5I-xS0AAAAJWeb of Science ID:
DZF-7400-2022
DZF-7400-2022Name Variants:
Yilmaz, Volkan
21 results
Scholarly Output Search Results
Now showing 1 - 10 of 21
Article Citation - WoS: 2Citation - Scopus: 2Analysis of the Memory Mechanism in the Pan Evaporation Phenomenon by the Band Similarity Method(Springer Wien, 2023-05-29) Yılmaz, VolkanIn this study, band similarity (BS) method as a new approach, which allows investigation of the memory features of the evaporation phenomenon, was applied on 7 different meteorological data in addition to the monthly pan evaporation data of Beysehir district of Konya city, located in the middle regions of Turkey. The models required for BS were generated with the artificial bee colony (ABC) optimization algorithm. As a result of the study, it has been observed that ABC optimization algorithm produced sufficient evaporation models. Subsequently, it was concluded that the BS method significantly improved the ABC results by using the temporal similarity mechanism. In this direction, it has been observed that the evaporation phenomenon studied remembers its own past. As a result of the BS method, it can be mentioned that there is a seasonal effect in the memory properties. While the memory weakens in the months when evaporation is high and low, it gets stronger especially in the spring and autumn months. Therefore, it has been concluded that the changes of the parameters affecting evaporation have a more intense effect on memory compared to their intensities. It is thought that this study differs from other studies in the literature because the pan evaporation phenomenon was evaluated from a different perspective and the BS method, which is a new method, and was applied for the first time on a hydrological parameter.Conference Object Estimation of Position of Hydraulic Jump in an Open Channel by Numerical Modeling and Comparision With Experimental Results(2019) Yıldız, Ali; Martı, Ali İhsan; Yılmaz, VolkanA flow passing under a sluice gate is generally in supercritical regime in open channels. If the regime of the flow is changed from supercritical to subcritical by a step or contraction, a hydraulic jump occurs. Although a hydraulic jump act as an energy dissipater, an uncontrolled or unpredicted hydraulic jump can damage hydraulic structures. Therefore, determination of parameters such as position of hydraulic jump, flow depths at subcritical and supercritical phases has great importance. Computational fluid dynamics are used to predict behavior of flow in open channels, but the accuracy of these results should be tested. In this study, a simple open channel system is used in order to investigate behavior of hydraulic jump and determine position of it. The regime of the flow passing through the sluice gate is changed to subcritical flow by a step which placed after sluice gate and a hydraulic jump is formed. Position of hydraulic jump, flow depths and flow velocities are measured for 2 different gate openings and 40 different discharge values. Numerical model of the physical experiment is created in same dimensions and initial conditions by Ansys-Fluent. Results of numerical and physical models are compared. According to results, CFD programs are sufficiently advanced to simulate a hydraulic jump.Book Part Medium-Term Effects of Covid-19 Pandemic on Domestic Water Consumption: a Case Study(Eğitim Yayınevi, 2024) Yılmaz, Volkan; Kamanlı, MehmetArticle Citation - WoS: 3Citation - Scopus: 3An Approach on the Estimation and Temporal Interaction of Runoff: the Band Similarity Method(Iwa Publishing, 2024-08-30) Yılmaz, Volkan; Koyceğiz, Cihangir; Büyükyıldız, MeralThis study is based on the investigation of the performance of the band similarity (BS) method, which is quite new in the literature, in the prediction of flow and in determining the memory properties of the flow phenomenon. For this purpose, flow prediction models for the monthly flow data of the Sar & imath;z station, located in the Seyhan Basin in T & uuml;rkiye, were produced first with the particle swarm optimization (PSO) algorithm. Second, these models were used in the BS method to create the BSPSO approach. Then, flow prediction was made for the same data set with support vector regression (SVR). In the test period, the standalone PSO, BSPSO, and SVR models achieved the most successful Nash-Sutcliffe efficiency (NSE) values of 0.516, 0.691, and 0.659, respectively. As a result, it was seen that BS increased the success of PSO by approximately 35% and the BSPSO produced the best results (mean absolute error = 1.205 m(3)/s, root mean square error = 1.895 m(3)/s, NSE = 0.691, and R-2 = 0.734). With the BSPSO approach, it has been observed that there is a memory mechanism within the flow phenomenon. It was concluded that the 5-month variation played an important role in the memory and a stronger memory existed especially in water years when low flow values were observed.Master Thesis Şehirsel Su Sarfiyatına Etki Eden Değişkenlerin Konya İline Ait Bazı Mahalleler Üzerinde İncelenmesi(Konya Teknik Üniversitesi, 2020) Ebad, Omidullah Zein; Yılmaz, VolkanSu talebi günümüzde, kentsel alanda içme, bahçe sulama, yangın kontrolü, temizlik ve endüstriyel kullanım için ihtiyaç duyulan su miktarı olarak tanımlanabilir. Su talepleri oldukça değişken olup, şehir büyüklüğü, nüfus özellikleri, iklim ve doğa şartları, ekonomik faktörler, gelişmişlik düzeyi gibi faktörlerden oldukça etkilenmektedir. Ayrıca insanların su kullanım davranışlarının da su tüketimi üzerinde büyük bir etkisi vardır. Bilindiği gibi gün geçtikçe endüstriyel büyüme, nüfus artışı, teknolojinin ilerlemesi ve yaşam standartlarının yükselmesinden dolayı suyun önemi ve tüketim miktarı artmaktadır. Su kaynaklarının sınırlı olmasından dolayı su sistemlerinin tasarımı ve planlanması ve su talebinin tahmini daha dikkatli bir şekilde yapılmalı ve su kaynakları daha verimli bir şekilde kullanılmalıdır. Bunun için su talebine etki eden faktörlerin incelenmesi oldukça önemlidir. Mevcut çalışmada öncelikle su tüketimine etki eden faktörler hakkında daha önce literatürde yapılmış olan çalışmalar incelenmiş ve ardından Konya iline ait farklı özelliklere sahip olan dört farklı mahalle üzerinde Faktör Analizi, Çok Değişkenli Lineer Regresyon yöntemi ve Yapay Sinir Ağları yöntemleri kullanılarak meteorolojik verilerin birim su sarfiyatı üzerindeki etkisi incelenmiştir. Sonuç olarak iklim faktörlerinin Saraçoğlu Mahallesi için etkili olduğu, Lalebahçe ve Gödene Mahalleleri için kabul edilebilir düzeyde ve Yazır Mahallesinde su tüketimine etkisinin olmadığı görülmüştür. Bir genelleme yapılacak olursa mevcut mahallelerin birim su sarfiyatının tahmini için iklim dışında diğer faktörlerin araştırılması gerektiği söylenebilir.Article Citation - WoS: 2Citation - Scopus: 3An Investigation of the Temporal Interaction of Urban Water Consumption in the Framework of Settlement Characteristics(Springer, 2023-02-02) Yılmaz, Volkan; Alpars, MehmetCan a natural or artificial phenomenon remember its past just like a human? and what are the factors affecting this memory mechanism? This study is designed to find answers to these two questions in the field of urban water consumption within the framework of the settlement characteristics. For this purpose, four different districts with different settlement characteristics belonging to the city of Konya, located in the central part of Turkey, were studied. In the study, firstly the monthly urban water consumption, population, per capita income and the different meteorological variables were used to determine the most influential parameters on water consumption with the help of Factor Analysis. Subsequently, the nonlinear water consumption models were produced with Artificial Bee Colony and Particle Swarm Optimization algorithms. In the last part of the study, the temporal interaction mechanisms were examined with the Band Similarity (BS) method, a novel approach using the model information. As a result of the study, it was observed that the phenomenon of water consumption in the studied districts remembers its own history together with the input parameters. In addition, it was concluded that there is a strong relationship structure between the population density in the settlement and the memory mechanism, and that the memory becomes stronger as the population density increases. Strong memory properties were accepted as a positive outcome, and accordingly, it was suggested by the authors that high-density residential areas are a more sustainable solution in terms of urban water management.Conference Object Investigation of Variables That Affect the Urban Water Consumptıon Over Some Districts of Konya City(2019) Ebad, Omidullah Zein; Yılmaz, VolkanAs it is known, the importance and consumption of water are increasing day by day due to industrial growth, population growth, advancement of technology and increasing living standards. Because of the limited water resources, the design, planning, forecasting of water transmission and distribution systems should be made more carefully and the water resources should be used more efficiently. In this context, the importance of the factors affecting water demand is increasing day by day. Population, economic cycles, education, technology, climatic conditions, price, and many other factors have their effects on water consumption. By designating these effects in a healthy and reliable way, it is possible to design systems that are more reliable and to use water resources more efficiently. In the present study, by using water consumption data of 4 different neighborhoods of the central districts of Konya with different characteristics, the effects of meteorological variables on water consumption according to the characteristics of neighborhoods were investigated by using Multiple Regression Analysis.Article Cost Optimization of Hanoi Water Distribution Netvvork With Meta- Heuristic Optimization Algorithms(2019) Yılmaz, Volkan; Büyükyıldız, Meral; Baykan, Ömer KaanWater transfer and distribution systems have high-cost values in a process from the collection of required water to the delivery by end-users. Besides the existence of few options for water transmission systems, there are more possible Solutions for water distribution systems which have to require necessary conditions. Defining the best system which has minimum cost value for a water distribution system has been an optimization problem in time. Different optimization algorithms have been revealed with the help of the innovation of Computer technologies and these algorithms were used in cost optimization of water distribution network field and performance of algorithmshave been evaluatednearly for 50 years. Inthis study, Partide Swarm Optimization (PSO) and Genetic Algorithm (GA) methods, commonly used in the literatüre, and recently revealed Artificial Bee Colony (ABC) algorithm method were applied to Hanoi water distribution network for the purpose of cost optimization. T o determine the bestperforming algorithm for this case study; the comparative performance analysis of convergence velocity, stability, and distribution of results were evaluated.Article Citation - WoS: 5Citation - Scopus: 5Performance of Data-Driven Models Based on Seasonal-Trend Decomposition for Streamflow Forecasting in Different Climate Regions of Türkiye(Pergamon-Elsevier Science Ltd, 2024-12-01) Yılmaz, Volkan; Koyceğiz, Cihangir; Buyukyıldız, MeralThis study examines the ability of different methods such as machine learning, ensemble models, and meta- heuristic algorithms to predict streamflow. For this purpose, five different methods were used: Artificial Neural Networks (ANN), Support Vector Machines (SVM), Adaptive Boosting, Particle Swarm Optimization (PSO), and BSPSO hybridized with Band Similarity (BS), a relatively new method. Additionally, the impact of seasonality and trend components obtained through Seasonal-Trend decomposition using LOESS (locally weighted regression and scatterplot smoothing) (STL) data decomposition technique on prediction success was investigated. Models were developed in three basins with three different climate characteristics: continental, temperate, and arid. The results showed higher prediction success in input structures including seasonality and trend components. While higher prediction successes were achieved at Karasu in the continental climate class and Kork & uuml;n in the temperate climate class, model performances were lower at K & uuml;& ccedil;& uuml;k Muhsine in the arid climate class. While the most successful modeling for K & uuml;& ccedil;& uuml;k Muhsine (NSE = 0.696) and Karasu stations (NSE = 0.811) was obtained with the BSPSO method, the SVM method produced the best results for Kork & uuml;n station (NSE = 0.818). Moreover, BSPSO models outperformed the prediction successes obtained by using PSO alone for each scenario at all three stations. The percentages of the BSPSO method improving the prediction success according to the NSE metric ranged from 3.53% to 17.40% at K & uuml;& ccedil;& uuml;k Muhsine, 0.49%-3.72% at Karasu, and 1.24%-7.24% at Kork & uuml;n. The competitive results achieved by the BSPSO approach compared to ANN and SVM in flow prediction constitute the innovative aspect of this study.Article Particle Swarm Optimization-Based Determination of Hydraulic Jump Location in Sluice Gate Flows(Konya Teknik University, 2025-09-01) Yilmaz, Volkan; Yıldız, AlıThe hydraulic jump is a critical phenomenon in open channel hydraulics, and understanding its behavior is essential for the design and safety of hydraulic structures. In this study, 96 experiments were conducted using five different gate openings to model the location of hydraulic jumps in an open channel. The Particle Swarm Optimization (PSO) algorithm, a metaheuristic optimization technique, was employed to develop both linear and nonlinear predictive models. Experimental data from gate openings (e) of 2.5 cm, 3.5 cm, 4 cm, and 5 cm were used to train the models, while data from a e=6 cm gate opening were used for testing. The results demonstrated that the PSO algorithm effectively modeled the hydraulic jump location, yielding high accuracy and consistency with experimental observations. Model performance was evaluated using the Coefficient of Determination (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Squared Error (MSE). The linear model outperformed the nonlinear model, achieving NSE = 0.954, R² = 0.983, and MSE = 0.022. Furthermore, the upstream total head (H) and gate opening (e) were identified as the most influential parameters affecting the hydraulic jump location.
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Research Topics
Domains
Physical Sciences
Fields
EngineeringEnvironmental Science
Subfields
Civil and Structural EngineeringEnvironmental EngineeringOcean EngineeringElectrical and Electronic EngineeringWater Science and Technology
Specific Research Areas
Water Systems and Optimization
Hydrological Forecasting Using AI
Water resources management and optimization
Energy Load and Power Forecasting
Hydrology and Watershed Management Studies
Sustainable Development Goals
11SUSTAINABLE CITIES AND COMMUNITIES
4
Research Products
6CLEAN WATER AND SANITATION
2
Research Products
3GOOD HEALTH AND WELL-BEING
1
Research Products
Documents
8
Citations
117
h-index
4
Documents
9
Citations
109
Publication Collaboration
| Affiliation Name | Count |
|---|---|
| Konya Technical University | 8 |
| Ondokuz Mayıs University | 1 |
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Data obtained from OpenAlex
| Journal | Count |
|---|---|
| Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi | 2 |
| Konya Journal of Engineering Sciences | 1 |
| Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi | 1 |
| Physics and Chemistry of The Earth | 1 |
| Romanian Journal of Ecology & Environmental Chemistry | 1 |
Current Page: 1 / 3
Scholarly Output
21
Articles
12
Views / Downloads
49/48
Supervised MSc Theses
2
Supervised PhD Theses
0
WoS Citation Count
19
Scopus Citation Count
20
Patents
0
Projects
0
WoS Citations per Publication
0.90
Scopus Citations per Publication
0.95
Open Access Source
13
Supervised Theses
2
Scopus Quartile Distribution
Competency Cloud
