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All issues Volume 505 (2024) E3S Web Conf., 505 (2024) 03010 References
Open Access
Issue
E3S Web Conf.
Volume 505, 2024
3rd International Conference on Applied Research and Engineering (ICARAE2023)
Article Number 03010
Number of page(s) 12
Section Modelling and Numerical Analysis
DOI https://doi.org/10.1051/e3sconf/202450503010
Published online 25 March 2024
  1. Buonamici, F., Carfagni, M., Furferi, R., Volpe, Y., & Governi, L. (2020). Generative design: an explorative study. Computer-Aided Design and Applications, 18(1), 144–155. [CrossRef] [Google Scholar]
  2. Basavapoornima, C., Kesavulu, C. R., Maheswari, T., Pecharapa, W., Depuru, S. R., & Jayasankar, C. K. (2020). Spectral characteristics of Pr3+-doped lead-based phosphate glasses for optical display device applications. Journal of Luminescence, 228, 117585. [CrossRef] [Google Scholar]
  3. Torres, A., Mahmoudi, B., Darras, A. J., Imanpour, A., & Driver, R. G. (2021 May) Achieving an Optimized Solution for Structural Design of Single-Storey Steel Buildings Using Generative Design Methodology. In Canadian Society of Civil Engineering Annual Conference (pp. 301–312). Singapore: Springer Singapore. [Google Scholar]
  4. Khan, S., & Awan, M. J. (2018). A generative design technique for exploring shape variations. Advanced Engineering Informatics, 38, 712–724. [CrossRef] [Google Scholar]
  5. Caldas, L. (2008). Generation of energy-efficient architecture solutions applying GENE_ARCH: An evolution-based generative design system. Advanced Engineering Informatics, 22(1), 59–70. [CrossRef] [Google Scholar]
  6. Khetan, A., Lohan, D. J., & Allison, J. T. (2015). Managing variable-dimension structural optimization problems using generative algorithms. Structural and Multidisciplinary Optimization, 52, 695–715. [CrossRef] [Google Scholar]
  7. Kicinger, R. P., Arciszewski, T., & De Jong, K. A. (2005). Generative design in structural engineering. [Google Scholar]
  8. Godavarthi, B., Nalajala, P., & Ganapuram, V. (2017 August) Design and implementation of vehicle navigation system in urban environments using internet of things (IoT). In IOP Conference Series: Materials Science and Engineering (Vol. 225, No. 1, p. 012262). IOP Publishing. [CrossRef] [Google Scholar]
  9. 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]
  10. Saxena, K. K., Srivastava, V., & Sharma, K. (2012). Calculation of Fundamental Mechanical Properties of Single Walled Carbon Nanotube using Non-local Elasticity. Advanced Materials Research, 383, 3840–3844. [Google Scholar]
  11. Tripathi, G. P., Agarwal, S., Awasthi, A., & Arun, V. (2022 August) Artificial Hip Prostheses Design and Its Evaluation by Using Ansys Under Static Loading Condition. In Biennial International Conference on Future Learning Aspects of Mechanical Engineering (pp. 815–828). Singapore: Springer Nature Singapore. [Google Scholar]
  12. Saxena, K. K., & Lal, A. (2012). Comparative Molecular Dynamics simulation study of mechanical properties of carbon nanotubes with number of stone-wales and vacancy defects. Procedia Engineering, 38, 2347–2355. [CrossRef] [Google Scholar]
  13. Reddy, K. S. P., Roopa, Y. M., Ln, K. R., & Nandan, N. S. (2020 July) IoT based smart agriculture using machine learning. In 2020 Second international conference on inventive research in computing applications (ICIRCA) (pp. 130–134). IEEE [Google Scholar]
  14. Agrawal, R., Singh, S., Saxena, K. K., & Buddhi, D. (2023). A role of biomaterials in tissue engineering and drug encapsulation. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 09544089221150740. [Google Scholar]
  15. Arun, V., Shukla, N. K., Singh, A. K., & Upadhyay, K. K. (2015 September) Design of all optical line selector based on SOA for data communication. In Proceedings of the Sixth International Conference on Computer and Communication Technology 2015 (pp. 281–285). [Google Scholar]
  16. SudhirSastry, Y. B., Krishna, Y., & Budarapu, P. R. (2015). Parametric studies on buckling of thin walled channel beams. Computational Materials Science, 96, 416–424. [CrossRef] [Google Scholar]
  17. Ramadugu, S., Ledella, S. R. K., Gaduturi, J. N. J., Pinninti, R. R., Sriram, V., & Saxena, K. K. (2023). Environmental life cycle assessment of an automobile component fabricated by additive and conventional manufacturing. International Journal on Interactive Design and Manufacturing (IJIDeM), 1–12. [Google Scholar]
  18. Shea, K., Aish, R., & Gourtovaia, M. (2005). Towards integrated performance-driven generative design tools. Automation in Construction, 14(2), 253–264. [CrossRef] [Google Scholar]
  19. Regenwetter, L., Nobari, A. H., & Ahmed, F. (2022). Deep generative models in engineering design: A review. Journal of Mechanical Design, 144(7), 071704. [CrossRef] [Google Scholar]
  20. Krish, S. (2011). A practical generative design method. Computer-Aided Design, 43(1), 88–100. [CrossRef] [Google Scholar]
  21. Ajith, J. B., Manimegalai, R., & Ilayaraja, V. (2020 February) An IoT based smart water quality monitoring system using cloud. In 2020 International conference on emerging trends in information technology and engineering (ic-ETITE) (pp. 1–7). IEEE. [Google Scholar]
  22. Swapna Sri, M. N., Anusha, P., Madhav, V. V., Saxena, K. K., Chaitanya, C. S., Haranath, R., & Singh, B. (2023). Influence of Cu particulates on a356mmc using frequency response function and damping ratio. Advances in Materials and Processing Technologies, 1–9. [CrossRef] [Google Scholar]
  23. Han, L., Du, W., Xia, Z., Gao, B., & Yang, M. (2022). Generative design and integrated 3D printing manufacture of cross joints. Materials, 15(14), 4753. [CrossRef] [PubMed] [Google Scholar]
  24. Lohan, D. J., Dede, E. M., & Allison, J. T. (2017). Topology optimization for heat conduction using generative design algorithms. Structural and Multidisciplinary Optimization, 55, 1063–1077. [CrossRef] [Google Scholar]
  25. Telagam, N., Kandasamy, N., & Nanjundan, M. (2017). Smart sensor network based high quality air pollution monitoring system using labview. International Journal of Online Engineering (iJOE), 13(08), 79–87. [CrossRef] [Google Scholar]
  26. Arora, G. S., & Saxena, K. K. (2023). A review study on the influence of hybridization on mechanical behaviour of hybrid Mg matrix composites through powder metallurgy. Materials Today: Proceedings. [Google Scholar]
  27. Abrishami, S., Goulding, J., Pour Rahimian, F., & Ganah, A. (2015). Virtual generative BIM workspace for maximising AEC conceptual design innovation: A paradigm of future opportunities. Construction Innovation, 15(1), 24–41. [CrossRef] [Google Scholar]
  28. Wang, Y., Du, W., Wang, H., & Zhao, Y. (2021). Intelligent generation method of innovative structures based on topology optimization and deep learning. Materials, 14(24), 7680. [CrossRef] [PubMed] [Google Scholar]
  29. Awasthi, A., Saxena, K. K., & Arun, V. (2020). Sustainability and survivability in manufacturing sector. In Modern Manufacturing Processes (pp. 205–219). Woodhead Publishing. [CrossRef] [Google Scholar]
  30. Walke, S., Kale, V. M., Patil, P. P., Giri, J. M., Kumar, H., Kumar, M., & Arun, V. (2023). Effects of alloying element on the mechanical behavior of Mg-MMCs: A review. Materials Today: Proceedings. [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. Singh, B., Saxena, K. K., Dagwa, I. M., Singhal, P., & Malik, V. (2023). Optimization Of Machining Characteristics of Titanium-Based Biomaterials: Approach to Optimize Surface Integrity for Implants Applications. Surface Review and Letters, 2340008. [CrossRef] [Google Scholar]
  33. Arun, V., Singh, A. K., Shukla, N. K., & Tripathi, D. K. (2016). Design and performance analysis of SOA- MZI based reversible toffoli and irreversible AND logic gates in a single photonic circuit. Optical and quantum electronics, 48, 1–15. [CrossRef] [Google Scholar]
  34. Monizza, G. P., Bendetti, C., & Matt, D. T. (2018). Parametric and Generative Design techniques in mass- production environments as effective enablers of Industry 4.0 approaches in the Building Industry. Automation in Construction, 92, 270–285. [CrossRef] [Google Scholar]
  35. Walia, K., Khan, A., & Breedon, P. (2021). The generative design process for robotic design applications. Journal of Additive Manufacturing Technologies, 1(2), 528–528. [Google Scholar]
  36. Gupta, T. K., Budarapu, P. R., Chappidi, S. R., Yb, S. S., Paggi, M., & Bordas, S. P. (2019). Advances in carbon based nanomaterials for bio-medical applications. Current Medicinal Chemistry, 26(38), 6851–6877. [CrossRef] [PubMed] [Google Scholar]
  37. Awasthi, A., Saxena, K. K., Dwivedi, R. K., Buddhi, D., & Mohammed, K. A. (2022). Design and analysis of ECAP Processing for Al6061 Alloy: a microstructure and mechanical property study. International Journal on Interactive Design and Manufacturing (IJIDeM), 1–13. [Google Scholar]
  38. Urquhart, L., Wodehouse, A., Loudon, B., & Fingland, C. (2022). The application of generative algorithms in human-centered product development. Applied Sciences, 12(7), 3682. [CrossRef] [Google Scholar]
  39. Liao, W., Lu, X., Huang, Y., Zheng, Z., & Lin, Y. (2021). Automated structural design of shear wall residential buildings using generative adversarial networks. Automation in Construction, 132, 103931. [CrossRef] [Google Scholar]
  40. Balguri, P. K., Samuel, D. H., & Thumu, U. (2021). A review on mechanical properties of epoxy nanocomposites. Materials Today: Proceedings, 44, 346–355. [CrossRef] [Google Scholar]
  41. Awasthi, A., Saxena, K. K., & Arun, V. (2021). Sustainable and smart metal forming manufacturing process. Materials Today: Proceedings, 44, 2069–2079. [CrossRef] [Google Scholar]
  42. Gero, J. S., & Kazakov, V. A. (1996). An Exploration-Based Evolutionary Model of a Generative Design Process. Computer-Aided Civil and Infrastructure Engineering, 11(3), 211–218. [CrossRef] [Google Scholar]
  43. Singh, V., & Gu, N. (2012). Towards an integrated generative design framework. Design studies, 33(2), 185–207. [CrossRef] [Google Scholar]
  44. Kazi, R. H., Grossman, T., Cheong, H., Hashemi, A., & Fitzmaurice, G. W. (2017 October) DreamSketch: Early-Stage 3D Design Explorations with Sketching and Generative Design. In UIST (Vol. 14, pp. 401–414). [Google Scholar]
  45. McKnight, M. (2017). Generative Design: What it is? How is it being used? Why it’sa game changer. KnE Engineering, 176–181. [CrossRef] [Google Scholar]

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