Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Hydrogen Susceptibility of Al 5083 Under Ultra-High Strain Rate Ballistic Loading(Walter de Gruyter Gmbh, 2024-09-25) Baltacioglu, Mehmet Furkan; Mozafari, Farzin; Aydin, Murat; Cetin, Baris; Oktan, Aynur Didem; Teoman, Atanur; Bal, BurakThe effect of hydrogen on the ballistic performance of aluminum (Al) 5083H131 was examined both experimentally and numerically in this study. Ballistics tests were conducted at a 30 degrees obliquity in accordance with the ballistic test standard MIL-DTL-46027 K. The strike velocities of projectiles were ranged from 240 m s-1 to 500 m s-1 level in the room temperature. Electrochemical hydrogen charging method was utilized to introduce hydrogen into material. Chemical composition of material was analyzed using energy dispersive X-ray (EDX) analysis. Instant camera pictures were captured using high-speed camera to compare H-uncharged and H-charged specimen ballistics tests. The volume loss in partially penetrated specimens were assessed using the 3D laser scanning method. Microstructural examinations were conducted utilizing scanning electron microscopy (SEM). It was observed that with the increased deformation rate, the dominance of the HEDE mechanism over HELP became evident. Furthermore, the experimental findings were corroborated through numerical methods employing finite element analysis (FEM) along with the Johnson-Cook plasticity model and failure criteria. Inverse optimization technique was employed to implement and fine-tune the Johnson-Cook parameters for H-charged conditions. Upon comparing the experimental and numerical outcomes, a high degree of consistency was observed, indicating the effective performance of the model.Article Citation - WoS: 10Citation - Scopus: 10FEA Based Fast Topology Optimization Method for Switched Reluctance Machines(Springer, 2022-01-04) Tekgun, Didem; Tekgun, Burak; Alan, IrfanIn this paper, a finite element analysis (FEA) based fast optimization method to optimize a lightweight in-wheel switched reluctance machine is presented. This method speeds up the switched reluctance machine optimization procedure by running the FEA simulations with single-phase constant current excitations for half electrical cycle and estimating the machine performance metrics using the gathered FEA data. Hence, the machine`s dynamic performance estimation process takes shorter for each design candidate. The optimization algorithm employs designs of experiments (DOE), response surface (RS) analysis method, and differential evolution algorithm (DE). Here, the DOE method is used to reduce the search space by narrowing down the upper and lower boundaries of each design variable based on the RS analysis. Although this process does not guarantee getting the Pareto front, it places the search space close to the actual one. Hence, the multi-objective DE optimization finds the Pareto optimal solution set without requiring a large number of iterations as well as a large number of candidate designs for each iteration. The method is applied to a 24/16 SRM that is intended to be used in a lightweight race car as a hub motor. Six dimensionless geometric variables are optimized to satisfy three objective functions, namely torque ripple, motor mass, and copper loss. While the conventional DE takes at least 3000 candidate designs, the proposed method considers only 559 designs to reach a similar Pareto front. It is observed that the proposed method takes about 6 h 30 min compared to the conventional method that takes 32 h 50 min using the same computer. Therefore, the computation time is reduced almost five times with the proposed method.Article Citation - WoS: 4Citation - Scopus: 2Development of High-Performance Nanostructured Aluminum and Its Constitutive Modeling(Taylor & Francis inc, 2023-10-11) Deka, Surja; Mozafari, Farzin; Mallick, Ashis; Thamburaja, Prakash; Gupta, ManojA new technique, an in-situ hot-extrusion-based synthesizing process, is proposed to develop high-performance nanocrystalline aluminum (nc-Al) with an optimally tuned strength-to-ductility ratio suitable for various technologically relevant applications. Comprehensive investigations are conducted by characterizing mechanical and microstructural properties to realize the influence of various synthesizing variables on the properties of the bulk nc-Al. Furthermore, a continuum-scale constitutive modeling approach is proposed based on dominant microstructural mechanisms of plastic deformation and implemented into a finite element solver using a user-defined material interface. It is shown that the proposed theory can provide a versatile platform to predict the nanocrystalline aluminum mechanical response quite well.