Middle East Technical University Research Information System
Not a member yet
104897 research outputs found
Sort by
A Finite Element Approach to Optimize Fiber Paths of Tow Steered Composites Using Unstructured Mesh Technique
No full textThis study proposes a finite element-based methodology to optimize curvilinear fiber paths in Tow Steered Composites (TSCs) by tuning two governing fiber orientation parameters, T0 and T1. These angles define the spatially varying fiber direction along the lamina, directly influencing structural stiffness and buckling behaviour. MATLAB is employed to extract the complete central fiber path definitions for a flat square plate made up of a single lamina, with parametric sweep of 81 combinations of (T0, T1), the sole parameters which govern the central fiber path. For the purpose of finite element modelling, a novel approach of executing unstructured mesh is adopted in ANSYS Workbench, with an objective to cover the no overlap and overlap regions precisely for each of the combinations of (T0, T1) in the entire plate, subsequently the combinations are evaluated by first conducting simple static structural analysis under axial compression, followed by linear eigenvalue buckling analysis. Buckling load factors are extracted to identify optimal fiber path configurations. While overlap-related defects from fiber placement are acknowledged, the shift distance optimization is discussed as future work. The findings highlight the critical role of fiber orientation tailoring in maximizing structural performance under compressive loads
Implementation of Microfluidic FRAP for Characterization of Nanoparticle Transport in Porous Biopolymer Networks
No full textNanomedicine features nanoparticles (NPs) that can be designed in various sizes, shapes and surface functionalities for therapeutic or diagnosticapplications. Despite the major promise of nanomedicine for targeted drug delivery and patient-specific treatments, its clinical translation remains limiteddue to challenges in its effective delivery to the target tissue [1]. Specifically, the extracellular matrix (ECM), a heterogeneous porous network ofbiopolymers such as collagen, poses a significant barrier against NP transport in the tissue interstitium. Transport of NPs in engineered tissue scaffolds alsoface similar challenges. Unfortunately, the mechanisms behind hinderance of NP transport within ECM are poorly understood, limiting the design ofnanomedicine for delivery. The problem is further complicated by lack of specialized and accessible tools for characterization of diffusive and advectivetransport properties of NPs. This study addresses this gap by implementing Fluorescence Recovery after Photobleaching (FRAP) [2] for use in shallow(<10-50 µm high) microchannels where ECM mimetic hydrogels are injected in and polymerized. In what we refer to as the microfluidic FRAP technique,containment of specimens in shallow microchannels combined with relatively large length and time scales of interstitial transport enable use of wide-fieldfluorescence LED illumination rather than the laser illumination, confocal imaging and specialized modules typically required for FRAP. In addition,hydrogels in microchannels can be precisely perfused to characterize and delineate the diffusive and advective transport properties. In this study, wedevelop and validate this technique by measuring effective diffusivity of fluorescent silica and polymeric NPs up to 400 nm in diameter in nanofibrouscollagen type I hydrogels with collagen concentrations varying between 1.5 mg/ml and 6.0 mg/ml. The microfluidic FRAP measurements are comparedwith those from mean-square displacement analysis of single particle tracking, stochastic simulations based on Brownian dynamics, and measurementsfrom previous studies in the literature. This work provides microfluidic FRAP as an accessible wide-field quantitative microscopy tool for transportcharacterization and lays the groundwork for investigating the role of other NP design features and ECM components in transport. The insights from thisstudy will ultimately help develop a mechanistic understanding of NP transport for rational design of nanomedicine for optimal delivery.This work is supported by grants 118C200 from TÜBİTAK and AGEP-302-2023-11236 from Middle East Technical University</p
GIS-based multi-criteria decision analysis for dam site selection in the Pedieos River basin, Cyprus
No full textClimate change, the expansion of impervious areas, and poorly planned infrastructures have significantly impacted Cyprus, resulting in severe extreme events, such as floods and droughts. Constructing dams in strategically chosen locations is crucial for effective water management, addressing flood control and water scarcity. The Pedieos River basin, characterized by the longest river with the highest flow capacity, is the most critical basin due to its high population density, agricultural and economic activities, and recurring floods. To tackle these challenges, this study aims to create a dam suitability map and identify potential sites for flood mitigation and water storage, utilizing remotely sensed datasets, Geographic Information Systems (GIS), the Analytic Hierarchy Process (AHP), and hydrological models. Initially, the AHP was employed with determined major factors, and a preliminary dam suitability map was produced. The map's accuracy was subsequently evaluated using existing dam locations, revealing that 93.2% of these dams fell within the moderate to very high suitability zones. Furthermore, the map underwent refinement by applying a Boolean approach that considered six environmental and socioeconomic criteria. This refinement process led to the proposal of eight multi-purpose dams in the Kyrenia and Troodos Mountain ranges. These dams varied in size and capacity, with Dam 3 being the smallest (433,179 m3) and Dam 7 the largest (4,367,512 m3). Lastly, hydrological modeling using HEC-HMS evaluated flood retaining capacities, showing that the dams can effectively handle storms up to a 500-year return period, except for Dam 2, which is limited to a 50-year return period
Kolon Sistemlerinde Sıfır Değerlikli Demir (SSD) ve Manyetit/İndirgenmiş Grafen Oksit (MiGO) Kaplı Kum Kullanılarak İçme Suyundan Arsenik Gideriminin Karşılaştırmalı Bir Çalışması
No full textArsenic contamination in drinking water is a pressing global issue, with over 250 million individuals lacking access to water that meets the World Health Organization's recommended limit of 10 µg/L. Arsenic, a confirmed carcinogen, poses significant health risks, necessitating efficient and cost-effective removal strategies. Adsorption remains one of the most prevalent methods for arsenic removal, employing materials such as metal oxides, graphene-based metal oxides, nanocomposites, and carbonaceous materials and organic-metallic frameworks. One of the most researched materials for the removal of arsenic from drinking water is Zero-Valent Iron (ZVI). However, ZVI, while widely utilized, exhibits limitations including reduced efficacy for As(III), extended reaction times, sensitivity to competing ions, narrow operational pH and DO range, and iron leaching into the water. This study explores the potential of magnetite/reduced graphene oxide (MrGO)-coated sand as an advanced alternative. MrGO's structural synergy, combining highly adsorptive magnetite nanoparticles with the enhanced stability and properties of reduced graphene oxide, addresses many of ZVI’s shortcomings. However, its application in column studies as a fixed nanoparticle remains underexplored, limited to theoretical and batch studies and pelletized or layered column studies. A novel approach to arsenic removal by integrating MrGO-coated sand and ZVI in column systems is presented in this work. The study evaluates their performance independently and in combination, focusing on removal efficiency, operational range, and cost-effectiveness. This includes the development of MrGO-coated sand for enhanced applicability in column systems and the optimization of MrGO-to-ZVI ratios to achieve maximum removal efficiency under conditions representative of real-world groundwaters. Preliminary findings suggest that MrGO-coated sand demonstrates the ability of the material to adequately remove arsenic while maintaining a broader operational conditions compared to ZVI. By investigating optimal ratios and conditions, this study aims to balance performance with economic feasibility, providing a scalable solution for arsenic-contaminated water treatment, contributing to the advancement of arsenic removal technologies and highlighting the potential of reduced-graphene-oxide-based materials in addressing critical water quality challenges.Acknowledgement: This study is supported by TUBITAK (The Scientific and Technological Research Council of Turkey) 1001 Project with Grant Number 123Y025 and Research Fund of the Middle East Technical University, Research Universities Support Program (ADEP) with Grant Number ADEP-311-2022-11172</p
Clutter-aware Precoder Design for Integrated Sensing and Communication Systems
No full textIt is envisaged that next-generation wireless networks will provide integrated sensing and communication (ISAC) functions. Clutter is one of the major factors that degrade the performance of sensing, whereas inter-user interference degrades communication capacity. Thus, this study proposes two clutter-aware precoder designs for ISAC systems that maximize the sensing accuracy and communication sum rate by minimizing the clutter and inter-user interference. The first precoder aims to maximize the network's sum rate while maintaining a desired signal-to-clutter-plus-noise ratio (SCNR) for sensing. On the other hand, the second precoder proposed endeavors to maximize the SCNR while ensuring a desired data rate for each communication user equipment (UE). Both precoders need to deal with non-convex optimization problems, which are solved via sequential quadratic programming and block coordinate descent in this study. The performance of the proposed precoding schemes is verified via extensive simulations and compared to linear and optimization-based communication-only benchmarking precoders
On Rational-Type Contractive Mappings in Bi-Complex Valued Control Metric Spaces and Applications
No full textThis manuscript studies some unique and common fixed point results in the context of bi-complex valued control metric space(BVCMS) using rational-type inequalities. The presented work explains the idea of BVCMS and then shows the necessary criteria for a pair of contractive type mappings in this space to have common fixed points. To show how applicable our results are, we also give an example. Finally, the existence of solutions of a system of fractional differential equations has been studied using the obtained results
Cross-Band Correlation-Aware Interactive Fusion for Multispectral Images
No full textMultispectral homogeneous bands capture distinct and complementary spectral characteristics; therefore, fusing multiple bands has the potential to increase semantic segmentation performance. However, the fusion of highly correlated homogeneous bands [i.e., RGB, near-infrared (NIR), and short-wave infrared (SWIR)] remains underexplored. We hypothesized that using correlation representations between highly correlated homogeneous spectral bands at higher level feature stages may improve segmentation accuracy. Therefore, we propose a novel semantic segmentation architecture that combines homogeneous modalities with a shared latent representation that exploits their intrinsic correlations. We also introduce interactive feature (IF) fusion blocks at early encoder stages to extract better cross-band correlations (CBCs). Our experiments on two different remote sensing image sets, both UAV-based and satellite-based, show that our correlation-driven fusion among homogeneous bands can enhance segmentation accuracy over state-of-the-art unimodal and multimodal models
