AI-DRIVEN SIMULATION OF MATERIAL BEHAVIOR IN SCULPTURAL ARTS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6897Keywords:
AI-Driven Simulation, Sculptural Arts, Material Behavior Modeling, Physics-Informed Neural Networks, Digital Fabrication, Deformation Prediction, Creative ComputingAbstract [English]
The arts of sculpture are adopting digital design and creation, although sculptors are still struggling to anticipate the behaviour of complicated materials like deformation, stress distribution, fracture, and surface reaction during modeling and post-processing. The main goal of the study is to create an AI-based simulation platform that should be able to predict the behavior of materials used in sculptural artworks with high precision to make informed decisions regarding both art and architecture during the design process. The method that has been proposed combines physics-informed neural networks, deep learning-based regression models with data-driven material embeddings trained on datasets with multi-modality containing mechanical properties, sculptural geometries as well as historic fabrication outcomes. Results of the Finite element simulation are combined with learning based predictors in an effort of capturing linear and nonlinear material responses to sculpting forces. The evaluation on clay, plaster, and polymer-based sculptural materials is performed experimentally and compared to ground-truth simulation and physical experiments of deformation and stress field prediction by AI. It has been found that the suggested framework reaches a median prediction accuracy of 92.4% on deformation prediction, and the decrease in simulation error (RMSE) is 38 percent smaller than that of traditional physics-only models. Also, theoretical time is cut down by about 45 percent, which means that artists can get close to real-time responses. The results reveal the opportunities of the creative control, material waste reduction, and the support of creative sculptural methods by AI-based material simulation, making intelligent simulation one of the primary support tools in the future of digital and physical sculpture.
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Copyright (c) 2025 Dr. Mukesh Patidar, Om Prakash, Gopal Goyal, Suhas Gupta, Anupama Abhijeet Deshpande, Dr. M. Maheswari
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