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    Assessment of pipe powder in soil improvement applications: an optimization by response surface methodology
    (Springer Heidelberg, 2020) Bagriacik, Baki; Yildirim, Zeynel Baran; Guner, Esra Deniz; Beycioglu, Ahmet
    Experimental design methods have become very popular approaches in engineering studies thanks to providing some advantages to reduce time period of experiments. In this study, shear strength characteristics of sandy soils were investigated by using central composite design (CCD) approach which is one of the response surface methods. Shear box test results performed at different time intervals were used to design CCD. In model application, the effect of time period under constant load (TPUL) and pipe powder (PP) content (8-12-16%) were used as independent factors to observe shear strength characteristics. Regression equations, variance analysis results, and factor interactions of response variables were used as statistical parameters to analyze CCD performance. Experimental results showed that TPUL is a significant parameter. CCD analysis also determined the importance of TPUL and suggested 14 days as the best time period. CCD results also showed that the optimum PP content can be selected as 12%.
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    Evaluation and Multi-Objective Optimization of Lightweight Mortars Parameters at Elevated Temperature via Box-Behnken Optimization Approach
    (Mdpi, 2021) Kaya, Mehmet; Yildirim, Zeynel Baran; Koksal, Fuat; Beycioglu, Ahmet; Kasprzyk, Izabela
    In this research, the mechanical properties of lightweight mortars containing different percentages of additional powder materials has been investigated using response surface methodology (RSM). Box-Behnken design, one of the RSM techniques, was used to study the effects of silica fume content (5, 10, and 15%), vermiculite/cement (V/C) ratio (4, 6, and 8), and temperature (300, 600, and 900 degrees C) on the ultrasonic pulse velocity (UPV), bending strength, and compressive strength of lightweight mortars. Design expert statistical software was accustomed to determining and evaluating the mix-design of materials in mortar mixtures and temperature effect on mortars. After preliminary experimental research of the relationships between independent and response variables, regression models were built. During the selection of the model parameters, F value, p-value, and R-2 values of the statistical models were taken into account by using the backward elimination technique. The results showed a high correlation between the variables and responses. Multi-objective optimization results showed that the critical temperatures for different levels of silica fume (5-10-15%) were obtained as 371.6 degrees C, 306.3 degrees C, and 436 degrees C, respectively, when the V/C ratio kept constant as 4. According to the results obtained at high desirability levels, it is found that the UPS values varied in the range of 2480-2737 m/s, flexural strength of 3.13-3.81 MPa, and compressive strength of 9.9-11.5 MPa at these critical temperatures. As a result of this research, RSM is highly recommended to evaluate mechanical properties where concrete includes some additional powder materials and was exposed to high temperature.
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    How will autonomous vehicles affect sustainable urban mobility? A decision support framework
    (Elsevier, 2025) Yildirim, Zeynel Baran; Ozuysal, Mustafa
    Autonomous vehicles (AVs) hold immense potential in revolutionizing transportation systems, aiming to boost safety, infrastructure efficiency, and sustainable energy use. However, deploying AVs in cities without seamless integration into transportation systems poses challenges to sustainable urban mobility goals. This research explores the intersection of AVs and sustainable urban mobility, focusing on mixed traffic scenarios and addressing unique challenges. The sustainability measures identified as highly important with the help of Fuzzy Analytic Hierarchy Process (F-AHP) were monitored in dynamic simulations with scenarios focused on autonomy level and induced demand. Critical penetration levels are identified through scoring techniques, and then decision support-based measures are developed. Simulations in urban mobility environments reveal critical autonomy levels requiring preventive measures: 10% for Level 1, 10% for Level 2, 20% for Level 3, 25% for Level 4, and 15% for Level 5, according to Scenario-5 (SCN5). Emphasizing the significance of monitoring and controlling these levels, a scoring system-based linear regression model aids Decision Support Systems (DSS) in overseeing autonomous vehicle (AV) autonomy distribution. As society embraces AV technology, this study supports policymakers, urban planners, and transportation authorities in prioritizing sustainability and optimizing transportation efficiency.
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    IMPORTANCE OF TEACHING STATISTICAL OPTIMIZATION IN ENGINEERING EDUCATION: A CASE STUDY ON THE CONTRIBUTION OF A PHD STUDENT FOR A GEOTECHNICAL DESIGN
    (Int Council Materials Education, 2020) Bagriacik, Baki; Yildirim, Zeynel Baran; Beycioglu, Ahmet; Cetin, Suna; Guner, Esra Deniz
    In engineering education, the students are often guided by their advisors to take courses related to their areas of expertise. In addition to the courses related to their areas of expertise, especially in the fields of applied engineering, taking math-based statistics or artificial intelligence courses improves students' analytical thinking skills significantly. For this reason, new perspectives for teaching in engineering education are required. In this study, the importance of teaching mathematically based statistical optimization techniques in engineering education has been discussed through an experimental case study. Within the study, the disposal of Drinking Water Treatment Sludge (DWTS) through its use in sandy soil improvement was studied experimentally and it was discussed whether the sludge usage improves the engineering properties of sandy soils. Besides, the experimental process of this research was supported by a Response Surface Methodology (RSM) analysis, thanks to the knowledge of a Ph.D. student. The RSM studied by Ph.D. students aims to suggest a useful approach to decrease laboratory efforts considering the difficulties of laboratory studies. It has been observed that the results found experimentally and calculated by a Ph.D. student are very close to each other, and the approach suggested by a Ph.D. student can be a useful way to decrease laboratory experiments. It can be concluded from this applied research that statistical knowledge gives strong advantages to engineers for reducing labor efforts, gaining time and having economic advantages. As a result, teaching some statistical approaches to engineering students is very useful for their professional lives.
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    Investigation of the effect of geometric irregularities on capacity of traffic circles by using partial least squares regression method
    (Canadian Science Publishing, 2024) Avsar, Yagmur Ozinal; Yildirim, Zeynel Baran; Politi, Ruti R.; Tanyel, Serhan
    This paper examined the impact of geometric irregularities on the intersection capacity at traffic circles. A new empirical capacity relation was proposed to predict the capacity of the traffic circles as a function of geometric elements, exit and circulating flows. Within this scope, first, the relationship between the vehicles entering from the minor approach and the circulating flow from the turning movement in the traffic circle was examined based on the K-Means cluster analysis method. The analysis was created in accordance with an exponential relationship between entry and circulating flow. Second, two clusters were selected by the partial least squares regression method to improve the model's effectiveness. Lastly, to validate the model, leave-one-out cross-validation was used to select the components that maximize the model's predictive ability. The results show that geometric parameters of a traffic circle create different effects on capacity, especially in different circulating flow conditions.
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    Modelling of waste rubber and glass fibber with response surface method in hot mix asphalt
    (Elsevier Sci Ltd, 2019) Yildirim, Zeynel Baran; Karacasu, Murat
    This paper presents the effect of Temperature (100-180 degrees C), Waste Rubber (WR) content (5-25%), Glass Fibber (GF) content (1-4%) and Bitumen content (3-7%) on performance characteristics of hot mix asphalt (HMA). For this purpose, experimental design matrix was generated depending the central composite design (CCD) for four independent variables. Simultaneous optimisation of dependent variables such as practical specific gravity (PSG), voids, voids of filled with asphalt cement (VFA) and Marshall stability (MS) were analysed. Mathematical models were proposed to fit the experimental results, and all models were found to be statistically significant. It was shown that the optimum conditions with desirable levels was achieved at temperature of 160 degrees C, 12.181% WR content, 4% GF content and 4.917% bitumen content. Following the optimum conditions proposed by the model, PSG is estimated to be 2.401 g/cm(3) with voids of 4.60%, VFA of 70%, MS of 1374.43 kgf. Additionally, the adequacy and validity of the predicted models were determined by conducting validation experiments under optimum ambient conditions proposed by the model. (C) 2019 Elsevier Ltd. All rights reserved.
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    Optimisation of Marshall Design criteria with central composite design in asphalt concrete
    (Taylor & Francis Ltd, 2020) Yildirim, Zeynel Baran; Karacasu, Murat; Okur, Volkan
    In this study, optimum bitumen content (OBC), an important parameter on Marshall Design is described with a mathematical model by using statistical design method. The effects of independent variables such as number of blows, temperature, additive rate and bitumen content are analysed. The simultaneous optimisation of the dependent variables such as practical specific gravity, voids, voids of filled with asphalt cement, Marshall stability, flow and Marshall coefficient is determined with the central composite design. The optimum conditions are detected with 70 blows, temperature of 160 degrees C, additive amount of 10% and OBC of 4.484%. The desirability function is applied to determine local optimisation points. Following the model application, practical specific gravity is estimated to be 2.418 g/cm(3)with voids of 4%, voids of filled asphalt of 71.74%, Marshall stability of 1138.4 kgf under optimum conditions. While it is necessary to pour 126 samples to achieve a result with these variables in Marshall Design under normal conditions, the results are achieved just by pouring 30 samples thanks to the models established.
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    Travel demand management: a review of recent literature
    (Emerald Group Publishing Ltd, 2025) Yildirim, Zeynel Baran; Ozuysal, Mustafa; Tanyel, Serhan
    Travel demand management (TDM) techniques constitute a critical component of sustainable transportation by mitigating travel demand, optimising existing infrastructure, and promoting multimodal mobility. This literature review synthesises recent findings on the efficacy of TDM interventions, highlighting their capacity to address congestion, minimise environmental impacts, and foster economic vitality. The review emphasises the growing importance of integrating emerging technologies and innovative solutions into TDM practices to address evolving urban mobility challenges and improve policy effectiveness. The results underscore the importance of aligning TDM measures with broader sustainability objectives, including equitable access, public health, and holistic urban planning. Practical policy recommendations emphasise collaborative governance, ensuring that TDM strategies not only enhance operational efficiency but also uphold social and environmental goals. By situating TDM within a comprehensive transport policy context, this review advocates resilient, future-focused solutions contributing to vibrant, low-carbon urban environments.
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    Use of GRP Pipe Waste Powder as a Filler Replacement in Hot-Mix Asphalt
    (Mdpi, 2020) Beycioglu, Ahmet; Kaya, Orhan; Yildirim, Zeynel Baran; Bagriacik, Baki; Dobiszewska, Magdalena; Morova, Nihat; Cetin, Suna
    There is an increasing global trend to find sustainable, environmentally friendly and cost-effective materials as an alternative to limited natural raw materials. Similarly, the use of waste materials has been gaining popularity in the production of hot-mix asphalt (HMA). In this study, the sustainable use of glass-fiber-reinforced polyester (GRP) pipe waste powder (GRP-WP), gathered from the cutting and milling process of GRP pipe production, utilizing it in asphalt mixes as a filler, is evaluated based on lab testing to find out: (i) if it produces similar or better performance compared to the most conventionally available filler material (limestone) and, (ii) if so, what would be the optimum GRP-WP filler content to be used in asphalt mixes. For this reason, an experimental test matrix consisting of 45 samples with three different amounts of binder content (4%, 4.5% and 5.0%), and a 5% filler content with five different percentages of the GRP-WP content (0%, 25%, 50%, 75% and 100% replacement by weight of the filler), was prepared to figure out which sample would produce the similar Marshall stability and flow values compared to the control samples while also satisfying specification limits. It was found that the samples with 4.5% binder content, 3.75% GRP-WP and 1.25% limestone filler content produced the results both satisfying the specification requirements and providing an optimum mix design. It is believed that use of GRP-WP waste in HMA production would be a very useful way of recycling GRP-WP.