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All issues Volume 505 (2024) E3S Web Conf., 505 (2024) 03005 References
Open Access
Issue
E3S Web Conf.
Volume 505, 2024
3rd International Conference on Applied Research and Engineering (ICARAE2023)
Article Number 03005
Number of page(s) 15
Section Modelling and Numerical Analysis
DOI https://doi.org/10.1051/e3sconf/202450503005
Published online 25 March 2024
  1. Jočbalis, G., Kačianauskas, R., Borodinas, S., & Rojek, J. (2023). Comparative numerical study of rate-dependent continuum-based plasticity models for high-velocity impacts of copper particles against a substrate. International Journal of Impact Engineering, 172, 104394. [CrossRef] [Google Scholar]
  2. Isaac, C. W., & Ezekwem, C. (2021). A review of the crashworthiness performance of energy-absorbing composite structure within the context of materials, manufacturing and maintenance for sustainability. Composite Structures, 257, 113081. [CrossRef] [Google Scholar]
  3. Trelewicz, J. R., & Schuh, C. A. (2007). The Hall-Petch breakdown in nanocrystalline metals: a crossover to glass-like deformation. Acta Materialia, 55(17), 5948–5958. [CrossRef] [Google Scholar]
  4. Harničárová, M., Valíček, J., Kušnerová, M., Palková, Z., Kopal, I., Borzan, C., … & Paulovič, S. (2021). A New Method of Predicting the Structural and Mechanical Change of Materials during Extrusion by the Method of Multiple Plastic Deformations. Materials, 14(10), 2594. [CrossRef] [PubMed] [Google Scholar]
  5. Kesharwani, R., Jha, K. K., Imam, M., Sarkar, C., & Barsoum, I. (2024). Correlation of microstructure, texture, and mechanical properties of friction stir welded Joints of AA7075-T6 plates using a flat tool pin profile. Heliyon. [Google Scholar]
  6. Dandekar, T. R., Khatirkar, R. K., Gupta, A., Bibhanshu, N., Bhadauria, A., & Suwas, S. (2021). Strain rate sensitivity behaviour of Fe-21Cr-1.5 Ni-5Mn alloy and its constitutive modelling. Materials Chemistry and Physics, 271, 124948. [CrossRef] [Google Scholar]
  7. Chakraborty, D., Rathi, A., Singh, R., Pathak, V. K., Srivastava, A. K., Sharma, A., … & Kumar, S. (2023). External six-bar mechanism rehabilitation device for index finger: Development and shape synthesis. Robotics and Autonomous Systems, 161, 104336. [CrossRef] [Google Scholar]
  8. Singh, G., Chakraborty, P., & Tiwari, V. (2023). Constitutive Behavior of a Homogenized AT61 Magnesium Alloy under Different Strain Rates and Temperatures: An Experimental and Numerical Investigation. Journal of Materials in Civil Engineering, 35(9), 04023314. [CrossRef] [Google Scholar]
  9. Lv, Y., Wu, H., Dong, H., Zhao, H., Li, M., & Huang, F. (2023). Experimental and numerical simulation study of fiber-reinforced high strength concrete at high strain rates. Journal of Building Engineering, 65, 105812. [CrossRef] [Google Scholar]
  10. Kaatz, L., Schmalholz, S. M., & John, T. (2023). Numerical simulations reproduce field observations showing transient weakening during shear zone formation by diffusional hydrogen influx and H2O inflow. Geochemistry, Geophysics, Geosystems, 24(5), e2022GC010830. [CrossRef] [PubMed] [Google Scholar]
  11. Awasthi, A., Rao, U. S., Saxena, K. K., & Dwivedi, R. K. (2022). Impact of equal channel angular pressing on aluminium alloys: An overview. Materials Today: Proceedings, 57, 908–912. [Google Scholar]
  12. Raj, I. L. P., Valanarasu, S., Hariprasad, K., Ponraj, J. S., Chidhambaram, N., Ganesh, V., … & Khairy, Y. (2020). Enhancement of optoelectronic parameters of Nd-doped ZnO nanowires for photodetector applications. Optical Materials, 109, 110396. [CrossRef] [Google Scholar]
  13. Liu, Y. A. N. G., Duan, Y. C., & Guan, Y. P. (2023). Ductile fracture prediction of ZK61M high-strength magnesium alloy sheet during hot deformation process. Transactions of Nonferrous Metals Society of China, 33(1), 95–106. [CrossRef] [Google Scholar]
  14. Singh, S., Agrawal, V., Saxena, K. K., & Mohammed, K.A. (2023). Optimization on Manufacturing Processes at Indian Industries Using TOPSIS. Indian Journal of Engineering and Materials Sciences (IJEMS), 30(1), 32–44. [Google Scholar]
  15. Pon, V. D., Wilson, K. J., Hariprasad, K., Ganesh, V., Ali, H. E., Algarni, H., & Yahia, I. S. (2021). Enhancement of optoelectronic properties of ZnO thin films by Al doping for photodetector applications. Superlattices and Microstructures, 151, 106790. [CrossRef] [Google Scholar]
  16. Pantalé, O. (2023). Development and implementation of an ANN based flow law for numerical simulations of thermo-mechanical processes at high temperatures in FEM software. Algorithms, 16(1), 56. [CrossRef] [Google Scholar]
  17. Dinbandhu, and Kumar Abhishek. “Parametric optimization and evaluation of RMDTM welding performance for ASTM A387 Grade 11 steel plates using TOPSIS-Taguchi approach.” In International Conference on Advances in Materials Processing & Manufacturing Applications, pp. 215–227. Singapore: Springer Singapore, 2020. [Google Scholar]
  18. Gaur, B., Patel, M., & Patel, S. (2023). Strain rate effect on CRALL under high-velocity impact by different projectiles. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 45(2), 103. [CrossRef] [Google Scholar]
  19. Deshpande, V. M., & Chakraborty, T. (2023). Experimental and numerical study on the dynamic behavior of a transversely isotropic rock. Engineering Geology, 314, 107016. [CrossRef] [Google Scholar]
  20. Awasthi, A., Saxena, K. K., Dwivedi, R. K., Buddhi, D., & Mohammed, K. A. (2023). Design and analysis of ECAP Processing for Al6061 Alloy: a microstructure and mechanical property study. International Journal on Interactive Design and Manufacturing (IJIDeM), 17(5), 2309–2321. [CrossRef] [Google Scholar]
  21. Vinoth, S., Kanimozhi, G., Hari Prasad, K., Harish, K., Srinadhu, E. S., & Satyanarayana, N. (2019). Enhanced ionic conductivity of electrospun nanocomposite (PVDF-HFP+ TiO2 nanofibers fillers) polymer fibrous membrane electrolyte for DSSC application. Polymer Composites, 40(4), 1585–1594. [CrossRef] [Google Scholar]
  22. Kumar, P., Kumar Jain, A., Srivastava, J. P., Kumar, R., Saxena, K. K., Prakash, C., & Buddhi, D. (2023). Multiphysics Simulation of the Shape Prediction and Material Removal Rate in Electrochemical Machining Process. Advances in Materials and Processing Technologies, 1–13. [Google Scholar]
  23. Yin, X., Li, Q., Xu, X., Chen, B., Guo, K., & Xu, S. (2023). Investigation of continuous surface cap model (CSCM) for numerical simulation of strain-hardening fibre-reinforced cementitious composites against low-velocity impacts. Composite Structures, 304, 116424. [CrossRef] [Google Scholar]
  24. Saffarini, M. H., & Voyiadjis, G. Z. (2023). Atomistic-Continuum Constitutive Modeling Connection for Gold Foams under Compression at High Strain Rates: The Dislocation Density Effect. Metals, 13(4), 652. [CrossRef] [Google Scholar]
  25. Kumari, C. U., Murthy, A. S. D., Prasanna, B. L., Reddy, M. P. P., & Panigrahy, A. K. (2021). An automated detection of heart arrhythmias using machine learning technique: SVM. Materials Today: Proceedings, 45, 1393–1398. [CrossRef] [Google Scholar]
  26. Nair, A., Kumanan, S., Prakash, C., Mohan, D. G., Sxena, K. K., Kumar, S., & Kumar, G. (2023). Research developments and technological advancements in conventional and non-conventional machining of superalloys-a review. Journal of Adhesion Science and Technology, 1–72. [Google Scholar]
  27. Collins, I., Contino, M., Marano, C., Masters, I., & Hossain, M. (2023). On the influence of time-dependent behaviour of elastomeric wave energy harvesting membranes using experimental and numerical modelling techniques. European Journal of Mechanics- A/Solids, 98, 104895. [CrossRef] [Google Scholar]
  28. Maniscalco, J., Elmustafa, A. A., Bhukya, S., & Wu, Z. (2023). Numerical Simulation of the Donor-Assisted Stir Material for Friction Stir Welding of Aluminum Alloys and Carbon Steel. Metals, 13(1), 164. [CrossRef] [Google Scholar]
  29. Kandhare, A. D., Thakurdesai, P. A., Wangikar, P., & Bodhankar, S. L. (2019). A systematic literature review of fenugreek seed toxicity by using ToxRTool: evidence from preclinical and clinical studies. Heliyon, 5(4). [Google Scholar]
  30. Bhukya, M. N., & Kota, V. R. (2019). A quick and effective MPPT scheme for solar power generation during dynamic weather and partial shaded conditions. Engineering Science and Technology, an International Journal, 22(3), 869–884. [CrossRef] [Google Scholar]
  31. Korpi, A. G., Țălu, Ş., Bramowicz, M., Arman, A., Kulesza, S., Pszczolkowski, B., … & Gopikishan, S. (2019). Minkowski functional characterization and fractal analysis of surfaces of titanium nitride films. Materials Research Express, 6(8), 086463. [CrossRef] [Google Scholar]
  32. Varga, M., Cervellón, A. V., Leroch, S., Eder, S. J., Rojacz, H., & Ripoll, M. R. (2023). Fundamental abrasive contact at high speeds: scratch testing in experiment and simulation. Wear, 522, 204696. [CrossRef] [Google Scholar]
  33. Kou, X., Li, L., Du, X., & Zheng, X. (2023). Elastoplastic dynamic constitutive model of concrete with combined effects of temperature and strain rate. Case Studies in Construction Materials, 18, e01905. [CrossRef] [Google Scholar]
  34. Dai, P., Kyaw, P. M., Osawa, N., Rashed, S., Ma, D., Okada, J., & Honnami, M. (2023). Numerical study on local residual stresses induced by high frequency mechanical impact post-weld treatment using the optimized displacement-controlled simulation method. Journal of Manufacturing Processes, 92, 262–271. [CrossRef] [Google Scholar]
  35. Kumar, P. S. S., & Allamraju, K. V. (2019). A review of natural fiber composites [Jute, Sisal, Kenaf]. Materials Today: Proceedings, 18, 2556–2562. [CrossRef] [Google Scholar]
  36. Xu, L., Zhou, D., Xu, C., Zhang, H., Qu, W., Xie, P., & Li, L. (2023). Microstructure evolution, constitutive modeling and forming simulation of AA6063 aluminum alloy in hot deformation. Materials Today Communications, 34, 105138. [CrossRef] [Google Scholar]
  37. Bhadauria, A., Bajpai, S., Tiwari, A., Mishra, S. K., Nisar, A., Dubey, S., … & Balani, K. (2023). Bimodal microstructure toughens plasma sprayed Al2O3-8YSZ-CNT coatings. Ceramics International, 49(8), 12348–12359. [CrossRef] [Google Scholar]
  38. Singh, B., Kumar, I., Saxena, K. K., Mohammed, K. A., Khan, M. I., Moussa, S. B., & Abdullaev, S. S. (2023). A future prospects and current scenario of aluminium metal matrix composites characteristics. Alexandria Engineering Journal, 76, 1–17. [CrossRef] [Google Scholar]
  39. Dikshit, M. K., Singh, S., Pathak, V. K., Saxena, K. K., Agrawal, M. K., Malik, V., … & Khan, M. I. (2023). Surface characteristics optimization of biocompatible Ti6Al4V with RCCD and NSGA II using die sinking EDM. Journal of Materials Research and Technology, 24, 223–235. [CrossRef] [Google Scholar]
  40. Wang, Y., Wang, Z., Ni, P., Wang, D., Lu, Y., Lu, H., … & Chen, Z. (2023). Experimental and numerical study on regulation of cutting temperature during the circular sawing of 45 steel. Coatings, 13(4), 758. [CrossRef] [Google Scholar]
  41. Becerra-Becerra, E., Ojeda, C. A., Saldaña-Robles, A., Reveles-Arredondo, J. F., Barco-Burgos, J., & Vidal-Lesso, A. (2023). A review of numerical simulation of ball burnishing process. Finite Elements in Analysis and Design, 218, 103926. [CrossRef] [Google Scholar]
  42. Gupta, P., Gupta, N., & Saxena, K. K. (2023). Predicting compressive strength of geopolymer concrete using machine learning. Innovation and Emerging Technologies, 10, 2350003. [CrossRef] [Google Scholar]
  43. Pan, L., Hao, H., Cui, J., & Pham, T. M. (2023). Numerical study on dynamic properties of rubberised concrete with different rubber contents. Defence Technology, 24, 228–240. [CrossRef] [Google Scholar]
  44. Ahmad, A. S., Wu, Y., Gong, H., & Alhassan, Y. (2023). Numerical simulation of post- weld shot peening using combined discrete and finite element methods (DEM-FEM). Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 237(1-2), 261–275. [CrossRef] [Google Scholar]
  45. Prateek, Soumy, Rajnish, Garg, Kuldeep Kumar, Saxena, V. K. Srivastav, Hitesh Vasudev, and Nikhil Kumar. “Data-driven materials science: application of ML for predicting band gap.” Advances in Materials and Processing Technologies (2023): 1–10. [CrossRef] [Google Scholar]
  46. Wubuliaisan, M., Wu, Y., Hou, X., Liu, X., & Wu, Y. (2023). Multiscale viscoelastic constitutive modeling of solid propellants subjected to large deformation. International Journal of Solids and Structures, 262, 112084. [CrossRef] [Google Scholar]
  47. Awasthi, A., & Saxena, K. K. (2019). Evaluation of mechanical properties of orange peel reinforced epoxy composite. Materials Today: Proceedings, 18, 3821–3826. [CrossRef] [Google Scholar]
  48. Mahadule, D., Kumar, D., Dandekar, T. R., Khatirkar, R. K., & Suwas, S. (2023). Modelling of flow stresses during hot deformation of Ti-6Al-4Mo-1V-0.1 Si alloy. Journal of Materials Research, 1–14. [Google Scholar]
  49. Sarkhel, P., Dikshit, M. K., Pathak, V. K., Saxena, K. K., Prakash, C., & Buddhi, D. (2023). Robust deflection control and analysis of a fishing rod-type flexible robotic manipulator for collaborative robotics. Robotics and Autonomous Systems, 159, 104293. [CrossRef] [Google Scholar]
  50. Hu, X., Guo, P., Xie, N., Hu, H., Lei, G., Ma, J., & Gong, X. (2023). Creep behavior and associated acoustic characteristics of heterogeneous granite containing a single pre- existing flaw using a grain-based parallel-bonded stress corrosion model. Rock Mechanics and Rock Engineering, 1–34. [Google Scholar]
  51. Sambasivam, S., Abed, A. S., Chopde, S., Patil, P. P., Math, P., Parmar, A., … & Awasthi, A. (2023). Role of processing techniques related to Mg-MMCs for biomedical implantation: An overview. Materials Today: Proceedings. [Google Scholar]
  52. Thakar, H. H., Chaudhari, M. D., Vora, J. J., Patel, V., Das, S., Bandhu, D., … & Reddy, V. S. (2023). Performance optimization and investigation of metal-cored filler wires for high-strength steel during gas metal arc welding. High Temperature Materials and Processes, 42(1), 20220305. [CrossRef] [Google Scholar]

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