WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Department: search.filters.department.İzmir Institute of TechnologySubject: search.filters.subject.Uncertainty

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  • Article
    Robust Scheduling of Crude Oil Farming and Processing Under Uncertainty
    (Elsevier, 2026) Şıldır, Hasan; Sildir, Hasan; 03.02. Department of Chemical Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The sulphur content in crude oil has a significant impact on refinery operations, influencing the feasibility of crude blending, the distribution of product yields, and overall economic performance. Variations in sulphur content introduce uncertainty in the short-term scheduling of crude oil loading, blending, and distillation processes. This study introduces a scenario-based stochastic optimization framework in which sulphur uncertainty is treated as a central modeling element, represented through a regression-based relationship with specific gravity (SG). The approach systematically propagates uncertainty through blending decisions, crude distillation unit (CDU) feed composition, and product yields. The problem is modeled as a mixed-integer quadratically constrained programming (MIQCP) formulation within a continuous-time scheduling framework, enabling the simultaneous optimization of timing, blending, and processing strategies. The results indicate that increased sulphur uncertainty adversely affects the distribution of yields for nine end-products, resulting in profit losses. These findings underscore the importance of explicitly managing compositional uncertainty and provide insights into cost-performance trade-offs in refinery scheduling.
  • Article
    Assessment of the Repeatability of Column Experiments Results on the Example of a Conservative Tracer
    (Sciendo, 2025) Baba, Alper; Kania, Jaroslaw; Kmiecik, Ewa; Baba, Alper; 01. Izmir Institute of Technology; 03. Faculty of Engineering; 03.03. Department of Civil Engineering
    Most studies on the behavior of pollutants in the groundwater environment are carried out in laboratories, and the results are then implemented at local and regional levels using model simulations or analytical solutions. Column experiments are used to determine the transport characteristics of inorganic and organic chemicals in the soil and water environment. Although column experiments have been conducted regularly for many years, there is currently no established standard protocol for setting up and conducting them to ensure consistent results. The repeatability of column experiments was evaluated for soils, which differ primarily in the silt and clay content, using a conservative tracer susceptible only to advection and dispersion processes to reduce the number of variables affecting the results of the study which arise in a case of using reactive contaminants. The column experiments performed according to the adopted methodology are characterized by high repeatability of the obtained test results for the transport parameters, regardless of the type of injection or the chosen column length (only a small-scale effect is visible). Based on the results, it can be noticed that for the same soil the values of the pore-water velocity for different types of injections and column lengths are very similar. The percentage difference between the values of pore-water velocity obtained for both tested soils does not exceed 5% and for individual pairs of parallel column experiments it does not exceed 3%.
  • Article
    FW-S3KIFCM: Feature Weighted Safe-Semi Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method
    (Tsinghua Univ Press, 2025) Aghazadeh, Nasser; Aghazadeh, Nasser; Hashemzadeh, Mahdi; Oskouei, Amin Golzari; 04.02. Department of Mathematics; 04. Faculty of Science; 01. Izmir Institute of Technology
    Semi-supervised clustering (SSC) methods have emerged as a notable research area in machine learning. These methods integrate prior knowledge of class distribution into their clustering process. Despite their efficiency and straightforwardness, SSCs encounter some fundamental issues. Generally, the proportion of unlabeled data surpasses that of labeled data. Consequently, handling the uncertainty of unlabeled data becomes difficult. This issue is frequently related to numerous real-world problems. On the other hand, existing SSC techniques fail to differentiate between the varied attributes within the feature space. When forming clusters, they presume uniform significance for all attributes, disregarding potential variations in feature importance. This presumption hinders the creation of optimal clusters. Furthermore, all existing approaches employ the Euclidean distance metric, susceptible to noise and outliers. This paper proposes a robust safe-semi-supervised clustering algorithm to mitigate these shortcomings. For the first time, this approach combines two concepts of Intuitionistic Fuzzy C-Means (IFCM) clustering and Safe-Semi-Supervised Fuzzy C-Means (S3FCM) clustering to address the uncertainty problem in unlabeled data. Also, it uses a kernel function as a distance metric to tackle noise and outliers. Additionally, incorporating a feature weighting parameter in the objective function highlights the importance of significant features in creating optimal clusters. The effectiveness of the proposed method is thoroughly evaluated on various benchmark datasets, and its performance is compared with state-of-the-art methods. The results show the superiority of the proposed method over its competitors.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 5
    Optimization of Tuned Mass Dampers by Considering Soil-Structure Interaction and Uncertainty in Soil Parameters
    (ASCE-Amer Soc Civil Engineers, 2025) Turan, Gürsoy; Turan, Guersoy; Roozbahan, Mostafa; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The tuned mass damper (TMD) is one of the oldest and most widely used passive control devices, designed to absorb lateral energy from structures and mitigate vibrations. Various methods have been proposed for the optimal design of TMDs to minimize structural responses in buildings. However, many of these approaches overlook soil-structure interaction (SSI). Among the few studies that do account for SSI, most rely on certain soil parameter values. In reality, however, soil parameters are uncertain and can vary due to environmental factors such as soil water content. This study introduces an innovative method for optimizing TMDs by incorporating soil parameter uncertainties. The method's effectiveness is evaluated by comparing TMDs optimized using the proposed approach, TMD designed by incorporating soil parameter uncertainties (TMD-UNC) with those optimized using certain soil parameters values (TMD-CRT) and those optimized without SSI consideration (TMD-FB). A 6-story shear building model with 200 uncertain soil scenarios is used for the comparison. The results showed that, on average, TMDs optimized for uncertainty marginally outperformed TMD-CRT-Mid, which is optimized with the midpoint of soil parameter ranges. However, these TMDs outperformed TMDs optimized for stiffest and softest soil conditions in reducing responses of uncertain systems. All these TMDs proved significantly more effective at reducing structural responses than the TMD designed for a fixed-base condition.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Effect of Soil Water Content Changes on the Behavior of Buildings Equipped With Single and Double Tuned Mass Dampers Subjected To Earthquakes
    (Springer Science and Business Media Deutschland GmbH, 2025) Turan, Gürsoy; Turan, G.; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Tuned mass dampers (TMDs) are one of the structural control systems that have been frequently used in the last century. A TMD is designed according to the properties of the main system. In building applications, the substructure’s soil affects the response of buildings, especially in soft-type soils. Therefore, the soil properties should be included in the analysis and design of tuned mass dampers. However, the soil properties are not always identical and vary due to different factor changes such as soil water content changes. Unlike previous research, which typically assumes constant soil properties, this study incorporates the impact of soil water content changes, a key factor that can significantly alter soil behavior. This study aims to evaluate the effectiveness of optimized single and double tuned mass dampers (DTMDs) in response reduction of buildings considering the changes in the water content of soil. In this study, a metaheuristic-based optimization method is programmed to optimize TMDs and DTMDs for low-, mid-, and high-rise buildings considering soil-structure interaction (SSI). The efficiency of the optimized tuned mass dampers on the response reduction of buildings due to changes in soil water content is evaluated. According to the investigated results of 14 near-field earthquake simulations, it is concluded that the efficiency of the TMDs is significantly affected by changes in soil water content. Moreover, according to the result, the DTMD efficiency is slightly better than the TMD-controlled structure. © Springer Nature Switzerland AG 2025.