SUSTAINABLE SCULPTURE DESIGN USING AI OPTIMIZATION
DOI:
https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7103Keywords:
Sustainable Sculpture Design, AI Optimization, Generative Design, Multi-Objective Optimization, Computational ArtAbstract [English]
The necessity to create sustainable sculptures projects is becoming more and more problematic due to the necessity to create a compromise between aesthetic expression, structural integrity, material efficiency, and environmental responsibility. Sculptural traditional practices, rich in cultural and artistic significance, can be based on the initiation of decisions, intuitive in their nature, which contribute to the overuse of materials, an increase in energy use, and reduced flexibility to the requirements of sustainability. In this research, the presented AI-based optimization framework in the field of sustainable sculpture design is suggested as the concept that will combine the principles of computational intelligence with modern artistic processes. The study has used genetic algorithms, multi-objective optimization, and neural network-based evaluation models to maximize sculptural shapes in relation to several sustainability parameters, such as the material usage, stability, carbon footprint, and aesthetic consistency. The main inputs of digital sculptural models are supplemented by material properties and environmental parameters in the form of density, recyclability and energy cost. The AI-optimized sculptures are compared in a systematic approach to traditionally designed sculptures through control experimental design and the use of a set of sculptural case studies. Findings indicate that AI optimization can make dramatic material savings and environmental savings and maintain, or even, improve aesthetic and structural quality. The results point to the ability of AI systems to act as intelligent partners of artists and designers but not the substitutes to make data-driven creative choices.
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Copyright (c) 2026 Rashmi Manhas, Milind Patil, Ram Rameshwar Wayzode, Dr. Gajanan P Arsalwad, Aishwarya Pathak, Dhanalakshmi V
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