Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item A Hybrid Monte Carlo Simulation Risk Model for Oil Exploration Projects(MARINE POLLUTION BULLETIN, 2023) Balas, Egemen AnderA new 3-D Hybrid Monte Carlo Simulation (MCS) Risk Model is proposed in this study. The wind, wave, current, climate change, and tsunami sub-models of the Three-Dimensional Hydrodynamic Transport and Water Quality Model HYDROTAM-3D are interrelated with MCS, to obtain probability distributions for the simulation of environmental conditions. This is the only model that can incorporate the tsunami, storm, and sea level rise risks in oil exploration projects. The spill risk index (SRI) of 50 blue barrels spilled due to a blowout from the rig/port during fuel supply was circa 1 ton/ship as Tier I with an average annual occurrence probability of 1.0 x 10-6. The discharge of 4000 bbls for 6 h was modeled, resulting in the SRI of 546 metric tons from the riser blowout with SRI = 0.2 per meter, indicating a Tier II risk. The mean arrival time of this spill was found by MCS as 145 min.Item Intelligent Optimization Under the Makespan Constraint: Rapid Evaluation Mechanisms Based on the Critical Machine for the Distributed Flowshop Group Scheduling Problem(2023) Wang, Yuhang; Han, Yuyan; Wang, Yuting; Tasgetiren, M. Fatih; Li, Junqing; Gao, KaizhouIn the flowshop scheduling literature, the insertion-based neighborhood search method is often considered to obtain high-quality solutions. It will lead to expending extensive computational effort when evaluating the objective function. Rapid evaluation methods based on Taillard's acceleration can reduce the time complexity of function evaluation. However, existing rapid evaluation methods cannot be applied directly to the distributed flowshop group scheduling problem (DFGSP), especially to minimize the total tardiness time objective. Thus, we first proposed two theorems and their proofs based on the critical machine. Then, two rapid evaluation methods based on these theorems are proposed to accelerate the evaluation of the objective. Considering the multiple coupled sub-problems in the DFGSP, we proposed a cooperative iterated greedy algorithm (CIG) combining two rapid evaluation methods, in which intergroup and intra-group neighborhood search strategies are proposed to enhance the search depth and breadth. Comprehensive statistical experiments show that computational effort is extensively decreased in the calculation of total tardiness time, and the CIG algorithm significantly outperforms the eight compared algorithms.& COPY; 2023 Elsevier B.V. All rights reserved.Item Diver Detection and Tracking with Different Beamforming Algorithms(2023) Sevimli, Rasim A.Diver Detection Sonars (DDS) aim to detect the diver and tracking at the specific distance. At the side of signal processing case, there are bunch of beamforming algorithms to localize the target or diver in our case in the literature. In this paper, some beamforming algorithms are combined and compared via PSNR, time each other. Some algorithms show that the effect of sidelobes and reverberation are clearly decreased. Moreover, detection and tracking algorithms are applied to artificial sonar data created with a specific scenario for this purpose.Item Automatic Brain Tumor Detection and Volume Estimation in Multimodal MRI Scans via a Symmetry Analysis(2023) Ficici, Cansel; Erogul, Osman; Telatar, Ziya; Kocak, Onur; 0000-0002-8240-4046In this study, an automated medical decision support system is presented to assist physicians with accurate and immediate brain tumor detection, segmentation, and volume estimation from MRI which is very important in the success of surgical operations and treatment of brain tumor patients. In the proposed approach, first, tumor regions on MR images are labeled by an expert radiologist. Then, an automated medical decision support system is developed to extract brain tumor boundaries and to calculate their volumes by using multimodal MR images. One advantage of this study is that it provides an automated brain tumor detection and volume estimation algorithm that does not require user interactions by determining threshold values adaptively. Another advantage is that, because of the unsupervised approach, the proposed study realized tumor detection, segmentation, and volume estimation without using very large labeled training data. A brain tumor detection and segmentation algorithm is introduced that is based on the fact that the brain consists of two symmetrical hemispheres. Two main analyses, i.e., histogram and symmetry, were performed to automatically estimate tumor volume. The threshold values used for skull stripping were computed adaptively by examining the histogram distances between T1- and T1C-weighted brain MR images. Then, a symmetry analysis between the left and right brain lobes on FLAIR images was performed for whole tumor detection. The experiments were conducted on two brain MRI datasets, i.e., TCIA and BRATS. The experimental results were compared with the labeled expert results, which is known as the gold standard, to demonstrate the efficacy of the presented method. The performance evaluation results achieved accuracy values of 89.7% and 99.0%, and a Dice similarity coefficient value of 93.0% for whole tumor detection, active core detection, and volume estimation, respectively.Item Calculation of the Phase Diagrams (T - X and T - P) and the Thermodynamic Quantities for the Solid - Liquid Equilibria in n-tridecane(2023) Tari, O.; Yurtseven, H.solid - liquid equilibria in n-tridecane is investigated by calculating phase diagrams and the thermodynamic quantities using the Landau phenomenological model. By expanding the free energy in terms of the order parameter of the solid phase, the phase line equations are fitted to the experimental data for the T - X and T - P phase diagrams from the literature. The temperature dependences of the thermodynamic quantities (order parameter psi, susceptibility chi(psi), free energy F, the heat capacity C, entropy S and the enthalpy H) are predicted for the n-tridecane from this model. Our results give that the slope dT/dP congruent to 2 K/MPa for n-C-13 to n-C-17. psi varies with T as psi similar to(T - T-m)(1/2) above T-m. It is linear for the chi(-1)(psi), S(T) and C(T), and quadratic for the F(T) and H(T) in n-tridecane. This indicates that the Landau model, describes the observed behaviour of the phase diagrams satisfactorily for the solid - liquid equilibria in n-tridecane. Predictions of the thermodynamic quantities can also be compared with the measurements and predictions of some other theoretical models. The pressure effect, in particular, on the solid - liquid equilibria in n-tridecane can also be investigated under the model studied here.Item A Comparative Performance Investigation of Single- and Double-Nozzle Pulse Mode Minimum Quantity Lubrication Systems in Turning Super-Duplex Steel Using a Weighted Pugh Matrix Sustainable Approach(2023) Roy, Soumikh; Kumar, Ramanuj; Panda, Amlana; Sahoo, Ashok Kumar; Rafighi, Mohammad; Das, Diptikanta; 0000-0002-9343-9607; AAQ-7933-2020This study investigates the performance comparison of machining of UNS S32750 super-duplex stainless steel under single- and double-nozzle pulse mode minimum quantity lubrication (MQL) conditions. The pulse mode MQL system delivers lubricant pulses at specific intervals. The Taguchi L9 design, with three factors and their three levels, was taken to perform the CNC turning experiments under both single-nozzle and double-nozzle MQL cooling environments. The surface roughness (Ra), tool-flank wear (VB), tool-flank temperature (Tf), power consumption (Pc), and material removal rate (MRR) are evaluated and compared as performance indicators. In comparison to single-nozzle MQL, the responses of Ra, VB, Tf, and Pc were found to be decreased by 11.16%, 21.24%, 7.07%, and 3.16% under double-nozzle conditions, respectively, whereas MRR was found to be 18.37% higher under double-nozzle conditions. The MQL pulse time was found to be an important variable that affects Ra, VB, Tf, and MRR significantly. Under both cooling scenarios, common wears such as abrasion, built-up edges, adhesion, and notch wear are detected. Furthermore, the Pugh matrix-based sustainability evaluation results revealed that the double-nozzle MQL technique was superior to single-nozzle MQL, achieving improved sustainability for machining super-duplex stainless steel.Item A Stationary Axisymmetric Vacuum Solution for Pure R2 Gravity(2023) Azreg Ainou, Mustapha; Nguyen, Hoang Ky; 0000-0002-3244-7195The closed-form expression for pure R-2 vacuum solution obtained in Phys. Rev. D 107, 104 008 (2023) lends itself to a generalization to axisymmetric setup via the modified Newman-Janis algorithm. We adopt the procedure put forth in Phys. Rev. D 90, 064 041 (2014) bypassing the complexification of the radial coordinate. The procedure presumes the existence of Boyer-Lindquist coordinates. Using the Event Horizon Telescope Collaboration results, we model the central black hole M87* by the thus obtained exact rotating metric, depending on the mass, rotation parameter and a third dimensionless parameter. The latter is constrained upon investigating the shadow angular size assuming mass and rotation parameters are those of M87*. Stability is investigated.Item A Preliminary Study on OSA Severity Levels Detection by Evaluating Speech Signals Nonlinearities With Multi-Class Classification(2023) Ugur, Tugce Kantar; Yilmaz, Derya; Yildiz, Metin; Yetkin, SinanDiagnosis of obstructive sleep apnea (OSA) from speech has become a popular research area in recent years, which can be an alternative way to the application difficulties in polysomnography (PSG). The promising results obtained in our previous study, in which we tried to detect apnea using nonlinear analysis of speech, gave rise to the thought that it is possible to detect OSA and OSA severity by diversifying speech samples and nonlinear features. The principal aim of this study, for the first time in the literature, is to detect the OSA severity levels as mild, moderate, and severe as in the clinic use (multi-class classification) using nonlinear analyses of speech while the patient is awake. In addition, healthy/OSA classification (binary classification) was also carried out. The feature selection method of ANOVA was applied to 336 features (28 voices x 12 features) for each subject, 14 and 5 features were used in multi-class and binary classifications, respectively. As a result of the classifications made with various KNN and SVMs models, the best results were obtained by SVMs in both classifications for OSA severities (with one-vs-all classification scheme and the Gaussian kernel) and OSA detection (with the quadratic kernel) as 82% and 95.1% accuracies, respectively. The proposed study showed that OSA and OSA severity can be determined with the small number of nonlinear features calculated from a few different speech samples, in nearly 15 minutes, consistent with PSG results (simple snorer, mild, moderate, and severe OSA). In conclusion, the highest OSA/healthy classification accuracy rate in the literature was achieved. Furthermore, OSA severity detection in four-class performed quite well as a preliminary study.Item Mechanical and Morphological Investigation of Laminated Composite Polymers Depending on Increasing Vibration Cycle(2023) Kemiklioglu, Ugur; 0000-0002-5597-1256Composite polymers are widely used in vibrating environments such as the aerospace, automotive, marine, and sports industries. Accordingly, composite materials are exposed to vibration at various periods. In this study, the effect of the vibration cycle on the mechanical properties of composite plates was investigated. The plates were vibrated at different revolutions. The tensile strength of these plates after vibration was examined, and these effects were compared with each other. As the vibration cycle increased, it was observed that tensile damage gradually occurred at different angles, and scanning electron microscopy (SEM) analysis revealed that the fibers were damaged at different angles. Accordingly, it was observed that the increased vibration cycle caused an angular fracture in the composite plates and decreased the tensile strength from 9.7 to 7.9 kN by nearly 23% as well as the elongation from 3.4 to 2.76 mm.Item PRI Deinterleaving with Connected Component Labeling-Based Clustering(2023) Fisne, Neslihan; Pakfiliz, Ahmet Gungor; 0000-0002-5901-228X; HSH-4659-2023Air platforms use radar warning receiver systems to detect threat radars in military operations. It is critical for an aircraft operating in a hostile environment to detect and classify radar signals and determine radar emitters' identity and capability. This study proposes an innovative solution to the signal separation problem for pulse radar signals by the computer vision-based connected component labeling method. With the proposed solution, clustering is performed automatically on the three-dimensional image matrix created by using the parameters of the arrival angle, radio frequency, pulse width of the signals. After clustering, the pulse repetition interval (PRI) deinterleaving is provided by the time of arrival analysis in each cluster. Also, various simulations were carried out using different synthetic radar datasets containing pulse-on-pulse states. In the simulations, PRI accuracy analyzes were performed.