| 000 | 02402nam a22001577a 4500 | ||
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| 082 | _a621 | ||
| 100 |
_aSajjad, Muhammad Uzair _9124016 |
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_aChip Formation Analysis and Machining Optimization of Titanium Ti6Al4V / _c Muhammad Uzair Sajjad |
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| 264 |
_aIslamabad : _bSMME- NUST; _c2024. |
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| 300 |
_a75p. _bSoft Copy _c30cm |
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| 500 | _aThe advancement in the materials science domain has led to the development of many robust composite alloys yielding high tensile strength, low density, and good corrosion resistance. One of such materials is the Titanium-Aluminum-Vanadium Alloy TI6Al4V. The addition of Aluminum and Vanadium compounds enhances the overall material hardness in the alloy matrix, thus improving its physical and mechanical properties. During Orthogonal cutting, the flow stress distribution, cutting forces, and surface finish of the working material play a vital role in predicting the material response via utilizing the Finite Element Analysis (FEA) methodology coupled with the Arbitrary Eulerian-Lagrangian (ALE) meshing during simulations performed in ABAQUS platform in orthogonal cutting analysis. The Johnson-Cook (J-C) model is utilized in finite element analysis of metal cutting as it can efficiently model considerations for temperature-dependent visco-plasticity, higher material strain rates, and larger von mises stresses, while incorporating key features including strain hardening of material, strain rate sensitivity, and heat softening. Our Research aims to formulate a Numerical Finite Element Analysis (FEA) based Model which incorporates a wider range of Johnson-Cook (JC) model test sets totaling to 32 simulated sets of JC Parameters (A, B, C, m, and n) in order to identify the optimum JC test set which would allow us to confirm the model characteristics including Cutting Force, Chip Morphology and Surface Finish, Feed Force/Reaction Force, and Von Mises Stress Distribution during the orthogonal cutting of the Ti6Al4V material. Furthermore, the analysis will provide insights into optimizing machining parameters to enhance productivity, minimize tool wear, and improve surface quality in Ti6Al4V machining operations. | ||
| 650 |
_aMS Mechanical Engineering _9119495 |
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| 700 | _aSupervisor : Dr. Syed Hussain Imran Jaffery | ||
| 856 | _uhttp://10.250.8.41:8080/xmlui/handle/123456789/44429 | ||
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_2ddc _cTHE |
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_c609994 _d609994 |
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