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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Item Metadata only On the reliability analysis of C-V2X mode 4 for next generation connected vehicle applications(IEEE, 2022) 0000-0002-7502-3122; 0000-0001-9438-5113; N/A; N/A; N/A; N/A; Karaagac, Sercan; Department of Electrical and Electronics Engineering; N/A; N/A; N/A; N/A; N/A; Ergen, Sinem Çöleri; Turan, Buğra; Kara, Yahya Şükür Can; Kümeç, Feyzi Ege; Kar, Emrah; Reyhanoğlu, Aslıhan; Faculty Member; PhD Student; Researcher; Researcher; Researcher; Researcher; Koc University – Ford Otosan Automotive Technologies Laboratory (KUFOTAL); College of Engineering; Graduate School of Sciences and Engineering; N/A; N/A; N/A; N/A; 7211; N/A; N/A; N/A; N/A; N/AVehicle-to-Everything Communication (V2X) technologies are provisioned to play an important role in increasing road safety by enabling advanced connected vehicle applications such as cooperative perception, cooperative driving, and remote driving. However, the reliability of the technology is limited mainly due to wireless communication channel characteristics. Therefore, investigation of V2X reliability aspects is crucial to utilize the technology efficiently. In this paper, we provide simulation and measurement-based reliability analysis of Cellular Vehicle-to-Everything (C-V2X) Mode 4 technology for various message sizes and Modulation and Coding Schemes (MCS) selections. We demonstrate that the Packet Delivery Ratio (PDR), a key communication performance metric, heavily depends on message size and selected MCS.Item Metadata only Comparison of constant and variable discharge flow and force coefficients for reciprocating compressor(Elsevier Sci Ltd, 2023) 0000-0002-8316-9623; 0000-0002-7638-3189; 0000-0002-3511-3887; Karabay, Ahmet Yasin; Sahin, Caglar; Department of Mechanical Engineering; N/A; N/A; Lazoğlu, İsmail; Pashak, Pouya; Malik, Anjum Naeem; Faculty Member; PhD Student; PhD Student; Manufacturing and Automation Research Center (MARC); College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 179391; N/A; N/AEnhancing the mathematical models always have been a critical issue in every field, and the reciprocating compressors are not exceptional. Flow and force coefficients are two empirical factors that help to calculate the mass flow rate through the valve and gas force, respectively. These coefficients can be considered constant values or valve lift dependent. However, in the discharge process, the piston is close to the top dead center, which may affect the discharge flow field and, subsequently, the coefficients.These coefficients should be determined by experiments or numerical simulations such as computational fluid dynamics (CFD). Experiments are expensive, and the exact geometry may not always be available to perform the CFD analysis. Also, CFD analysis for various valve lifts and piston positions is computationally expensive.This study studied the effect of constant, single variable (valve lift dependent) and double variable (valve lift and piston position dependent) coefficients on compressor performance and discharge valve movement in three operating conditions. A mathematical model was developed for this purpose, and a 3-D CFD simulation was used to compute the coefficients. To validate the results, a strain gauge and a calorimeter were used as measurement tools.The single and double variable models captured the valve behavior, and pressure picks better than the constant model. However, the constant model estimated the indicated power, cooling capacity, and COP with good accuracy. In predicting the discharge losses, the double variable model was the most reliable among the others.Item Metadata only Effect of starting position of crankshaft on transient body vibrations of reciprocating compressor(Elsevier Sci Ltd, 2023) 0000-0002-8316-9623; 000-0002-8383-6000; 0000-0002-9704-3626; Sahin, Caglar; Ul Haque, Umar; Department of Mechanical Engineering; N/A; N/A; Lazoğlu, İsmail; Subaşı, Ömer; Oral, Atacan; Faculty Member; PhD Student; PhD Student; Manufacturing and Automation Research Center (MARC); College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 179391; N/A; N/AThe maximum reciprocating compressor vibrations occur during the startup and shutdown operations and un-derstanding the factors that influence the transient vibrations can help in developing solutions to reduce the excessive displacements. In this study, the effect of crankshaft starting position on the vibration phenomenon is investigated and the optimal starting position to deliver a smooth start is proposed. The structural forces are analytically modeled to estimate the body displacements by considering the system resonance frequencies and modal vectors. An experimental setup is also constructed to validate the prediction model results, with the integration of an encoder to track the crankshaft angular position and transducers to measure the discharge and suction pressures. The transient responses of three different crankshaft start positions are then compared using the experimental setup and the analytical model. The results indicate that if the crankshaft starts to rotate from positions close to the bottom dead center, a higher amount of startup vibrations is observed, revealing the optimal starting position zone. The magnetization effect can potentially be addressed by the sensorless starting strategy developed by Lee et al. (2008) that implements a phase current controller for a smoother startup. While out of scope for this study, shutdown strategies can also be devised to have the piston consistently land at the favorable SAP range. By separately investigating the instances when the 'stop' command is provided to the steady-state operating compressor, solutions that attempt to replicate the conditions that lead to the favorable stop position can be developed; a limiting factor in mass production will be implementing the encoder for continuous position tracking and an accompanying undesirable cost increase in manufacturing. Nevertheless, the investigation of passive and active strategies is ripe for research in literature.Item Metadata only Regulating the generation of reactive oxygen species for photocatalytic oxidation by metalloporphyrinic covalent organic frameworks(Elsevier Science Sa, 2023) 0000-0003-1622-4992; Suleman, Suleman; Guan, Xinyu; Zhang, Yi; Waseem, Amir; Meng, Zheng; Jiang, Hai -Long; Department of Chemistry; Metin, Önder; Faculty Member; College of Sciences; 46962Regulating the generation of reactive oxygen species (ROS) impacts the selectivity and activity of photocatalytic oxidation, but the frequently concurrent formation of different types of ROS makes this process rather challenging. This study demonstrates the regulated production of two important ROS, O-1(2) and O-2(center dot-), using a covalent-organic framework (COF) array with three members, which are made up of metalloporphyrin cores with embedded center metal ions from d-block transition metals sequentially arranged in the periodic table. Due to the evolution of the electronic structures in this COF array, the production of O-1(2) and O-2(center dot-) is controlled, which successively leads to distinct performance in photocatalytic aerobic oxidations. The electronic property study and density-functional theory (DFT) calculations revealed that the distinct excitonic behavior of three COFs in regulated O-1(2) and O-2(center dot-) generation is rooted in their different band energy levels and O-2 adsorption ability. Our work presents an effective approach to the controlled production of ROS for improved photocatalytic performance.Item Metadata only Acausal modelling of advanced-stage heart failure and the Istanbul heart ventricular assist device support with patient data(Springer, 2023) 0000-0002-8316-9623; 0000-0001-5969-3823; 0000-0001-9034-9350; Kucukaksu, Deniz Sueha; Department of Mechanical Engineering; N/A; N/A; Lazoğlu, İsmail; Mehmood, Khunsha; Arshad, Munam; Faculty Member; PhD Student; Researcher; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 179391; N/A; N/ABackgroundIn object-oriented or acausal modelling, components of the model can be connected topologically, following the inherent structure of the physical system, and system equations can be formulated automatically. This technique allows individuals without a mathematics background to develop knowledge-based models and facilitates collaboration in multidisciplinary fields like biomedical engineering. This study conducts a preclinical evaluation of a ventricular assist device (VAD) in assisting advanced-stage heart failure patients in an acausal modelling environment.MethodsA comprehensive object-oriented model of the cardiovascular system with a VAD is developed in MATLAB/SIMSCAPE, and its hemodynamic behaviour is studied. An analytically derived pump model is calibrated for the experimental prototype of the Istanbul Heart VAD. Hemodynamics are produced under healthy, diseased, and assisted conditions. The study features a comprehensive collection of advanced-stage heart failure patients' data from the literature to identify parameters for disease modelling and to validate the resulting hemodynamics.ResultsRegurgitation, suction, and optimal speeds are identified, and trends in different hemodynamic parameters are observed for the simulated pathophysiological conditions. Using pertinent parameters in disease modelling allows for more accurate results compared to the traditional approach of arbitrary reduction in left ventricular contractility to model dilated cardiomyopathy.ConclusionThe current research provides a comprehensive and validated framework for the preclinical evaluation of cardiac assist devices. Due to its object-oriented nature, the featured model is readily modifiable for other cardiovascular diseases for studying the effect of pump operating conditions on hemodynamics and vice versa in silico and hybrid mock circulatory loops. The work also provides a potential teaching tool for understanding the pathophysiology of heart failure, diagnosis rationale, and degree of assist requirements.Item Metadata only In-silico hemodynamic ramp testing of ventricular assist device implanted patients using acausal cardiovascular-VAD modeling(Wiley, 2023) 0000-0002-8316-9623; 0000-0001-5969-3823; Kuçukaksu, Deniz Suha; Bakuy, Vedat; Department of Mechanical Engineering; N/A; Lazoğlu, İsmail; Mehmood, Khunsha; Faculty Member; PhD Student; College of Engineering; Graduate School of Sciences and Engineering; 179391; N/ABackground: While cardiovascular system and mechanical circulatory support devices are efficiently model the effect of disease and assistance, they can also lend valuable insights into clinical procedures. This study demonstrates the use of a CVS-VAD model for an invasive procedure; hemodynamic ramp testing, in-silico.Methods: The CVS model is developed using validated models in literature, using Simscape (TM). An analytically derived pump model is calibrated for the HeartWare VAD. Dilated cardiomyopathy is used as an illustrative example of heart failure, and heart failure patients are created virtually by calibrating the model with requisite disease parameters obtained from published patient data. A clinically applied ramp study protocol is adopted whereby speed optimization is performed following clinically accepted hemodynamic normalization criteria. Trends in hemodynamic variables in response to pump speed increments are obtained. Optimal speed ranges are obtained for the three virtual patients based on target values of central venous pressure (CVP), pulmonary capillary wedge pressure (PCWP), cardiac output (CO), and mean arterial pressure (MAP) for hemodynamic stabilization.Results: Appreciable speed changes in the mild case (300 rpm), slight changes in the moderate case (100 rpm), and no changes in the simulated severe case are possible.Conclusion: The study demonstrates a novel application of cardiovascular modeling using an open-source acausal model, which can be potentially beneficial for medical education and research.Item Metadata only Ultra-broadband integrated optical filters based on adiabatic optimization of coupled waveguides(IEEE-Inst Electrical Electronics Engineers Inc, 2023) 0000-0001-7680-6818; N/A; Department of Electrical and Electronics Engineering; N/A; Mağden, Emir Salih; Görgülü, Kazım; Faculty Member; PhD Student; College of Engineering; Graduate School of Sciences and Engineering; 276368; N/ABroadband spectral filters are highly sought-after in many integrated photonics applications such as ultra-broadband wavelength division multiplexing, multi-band spectroscopy, and broadband sensing. In this study, we present the design, simulation, and experimental demonstration of compact and ultra-broadband silicon photonic filters with adiabatic waveguides. We first develop an optimization algorithm for coupled adiabatic waveguide structures, and use it to design individual, single-cutoff spectral filters. These single-cutoff filters are 1 x 2 port devices that optimally separate a broadband signal into short-pass and long-pass outputs, within a specified device length. We control the power roll-off and extinction ratio in these filters using the adiabaticity parameter. Both outputs of the filters operate in transmission, making it possible to cascade multiple filters in different configurations. Taking advantage of this flexibility, we cascade two filters with different cutoff wavelengths on-chip, and experimentally demonstrate band-pass operation. The independent and flexible design of these band edges enables filters with bandwidths well over 100 nm. Experimentally, we demonstrate band-pass filters with passbands ranging from 6.4 nm up to 96.6 nm. Our devices achieve flat-band transmission in all three of the short-pass, band-pass, and long-pass outputs with less than 1.5 dB insertion loss and extinction ratios of over 15 dB. These ultra-broadband filters can enable new capabilities for multi-band integrated photonics in communications, spectroscopy, and sensing applications.Item Metadata only Embryonic aortic arch material properties obtained by optical coherence tomography-guided micropipette aspiration(Elsevier Sci Ltd, 2023) 0000-0001-7637-4445; 0000-0002-9731-7199; Coban, Gursan; Siddiqui, Hummaira Banu; Yap, Choon Hwai; Department of Mechanical Engineering; Department of Mechanical Engineering; Pekkan, Kerem; Lashkarinia, Seyedeh Samaneh; Faculty Member; Researcher; College of Engineering; College of Engineering; 161845; N/AIt is challenging to determine the in vivo material properties of a very soft, mesoscale arterial vesselsof size similar to 80 to 120 mu m diameter. This information is essential to understand the early embryonic cardiovascular development featuring rapidly evolving dynamic microstructure. Previous research efforts to describe the properties of the embryonic great vessels are very limited. Our objective is to measure the local material properties of pharyngeal aortic arch tissue of the chick-embryo during the early Hamburger-Hamilton (HH) stages, HH18 and HH24. Integrating the micropipette aspiration technique with optical coherence tomography (OCT) imaging, a clear vision of the aspirated arch geometry is achieved for an inner pipette radius of Rp = 25 mu m. The aspiration of this region is performed through a calibrated negatively pressurized micro-pipette. A computational finite element model is developed to model the nonlinear behaviour of the arch structure by considering the geometry-dependent constraints. Numerical estimations of the nonlinear material parameters for aortic arch samples are presented. The exponential material nonlinearity parameter (a) of aortic arch tissue increases statistically significantly from a = 0.068 +/- 0.013 at HH18 to a = 0.260 +/- 0.014 at HH24 (p = 0.0286). As such, the aspirated tissue length decreases from 53 mu m at HH18 to 34 mu m at HH24. The calculated NeoHookean shear modulus increases from 51 Pa at HH18 to 93 Pa at HH24 which indicates a statistically significant stiffness increase. These changes are due to the dynamic changes of collagen and elastin content in the media layer of the vessel during development.Item Metadata only A mechanical property prediction system for G-Lattices via machine learning(Taylor and Francis Ltd, 2024) 0000-0002-8316-9623; Armanfar, Arash; Tasmektepligil, A. Alper; Ustundag, Ersan Gunpinar, Erkan; Department of Mechanical Engineering; Lazoğlu, İsmail; Faculty Member; Manufacturing and Automation Research Center (MARC); College of Engineering; 179391G-Lattices-a novel family of periodic lattice structures introduced by Arash Armanfar and Erkan Gunpinar-demonstrate diverse mechanical properties owing to their generatively designed shapes. To assess the properties of lattice structures effectively, experimental tests and finite element analysis (FEA) are commonly used. However, the complex nature of these structures poses challenges, leading to high computation time and costs. This study proposes a machine learning (ML) approach to predict the mechanical properties of G-Lattices quickly under defined loading conditions. G-Lattice training data is generated through a sampling technique, and voxelized data is employed as ML feature vectors for predicting properties determined by FEA. To address the uneven distribution of target values, samples are clustered and utilized to train a classification model. This two-step process involves the classification of G-Lattices, followed by the application of specific regression models trained for each cluster for precise predictions. According to experiments, the ML model obtained, which predicts stiffness-over-volume ratios for G-Lattices, achieved a mean absolute percentage error of 6.5% for 1600 G-Lattices in a few seconds. Furthermore, approximately 70% of the 40,000 G-Lattices exhibited errors within 5%. The ML model's rapid predictions and acceptable accuracy make it useful for quick decision-making and seamless integration into optimization processes.Item Metadata only Antibacterial type-II INP/ZNO quantum dots via multimodal reactive oxygen species(Elsevier B.V., 2024) 0000-0003-0394-5790; N/A; 0000-0003-3682-6042; N/A; N/A; 0000-0002-2376-1246; 0000-0003-4284-9734; 0000-0002-1336-4650; 0000-0003-4162-5587; 0000-0001-9387-2526; Department of Electrical and Electronics Engineering; N/A; N/A; N/A; N/A; N/A; N/A; Department of Chemistry; Department of Chemistry; N/A; Nizamoğlu, Sedat; Khan, Saad Ullah; Önal, Asım; Eren, Güncem Özgün; Ataç, Nazlı; Qureshi, Mohammad Haroon; Cooper, Francis Korshe; Almammadov, Toghrul; Kölemen, Safacan; Can, Füsun; Faculty Member; PhD Student; PhD Student; PhD Student; PhD Student; PhD Student; Master Student; Researcher; Faculty Member; Faculty Member; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Health Sciences; Graduate School of Sciences and Engineering; Graduate School of Health Sciences; College of Sciences; College of Sciences; School of Medicine; 130295; N/A; N/A; N/A; N/A; N/A; N/A; N/A; 272051; 103165The emergence of multidrug-resistant bacteria as a global health threat has necessitated the exploration of alternative treatments to combat bacterial infections. Among these, photocatalytic nanomaterials such as quantum dots (QDs) have shown great promise and type-I QDs have been investigated thus far. In this study, we introduce type-II InP/ZnO core/shell QDs that are ligand-exchanged with a short-chain inorganic sulfide ion (S2−) for antibacterial activity. Interestingly, InP/ZnO QDs simultaneously generate reactive oxygen species (ROS) including hydroxyl (•OH) and superoxide (O2•−) radicals, while only O2•− radicals can be released by the type-I sulfide-capped InP/ZnS QDs. The optimized nanostructure achieved effective inhibition of Pseudomonas aeruginosa and Escherichia coli bacteria growth to the level of 99.99% and 70.31% under low-intensity green light illumination of 5 mW.cm−2. Our findings highlight the importance of type-II QDs as a new avenue for developing effective antibacterial agents against drug-resistant pathogens. © 2023 Elsevier B.V.