Presenter: Prof. M. G. H. Zaidi (G.B. Pant University of Agriculture & Technology, India)
Presentation Type: Oral Presentation
Title: Analytical and Computational Framework for Simulation of Composite Structures on Mobile Devices
🔬 Presentation Highlights
∙ Research Focus: Development of an analytical and computational framework that enables efficient simulation of advanced composite structures on mobile devices.
∙ Engineering Challenge: Conventional simulation platforms for fiber-reinforced composites provide high accuracy but require powerful computing resources, limiting accessibility for rapid engineering applications.
∙ Innovative Approach: Introduces a lightweight computational framework capable of predicting the elastic stiffness of complex composite architectures while significantly reducing computational requirements.
∙ Composite Systems Covered: Applicable to a wide range of reinforced composites, including unidirectional laminates, 2D woven fabrics, 2.5D interlock composites, and knitted composite structures.
∙ Mobile Computing Advantage: Enables engineers and researchers to perform fast material simulations on portable devices, supporting real-time design evaluation and decision-making.
∙ Industrial Relevance: Supports applications in aerospace, automotive, renewable energy, civil engineering, and advanced manufacturing where lightweight, high-performance composite materials are essential.
∙ Research Impact: Bridges computational mechanics and mobile engineering technologies, making advanced composite material analysis more accessible, scalable, and cost-effective.
👨🔬 About the Speaker
Prof. M. G. H. Zaidi is an accomplished researcher specializing in computational mechanics, composite materials, and advanced engineering simulations. His research focuses on developing innovative computational methodologies that improve the analysis, design, and optimization of complex composite structures for modern engineering applications.
His work contributes to advancing sustainable materials engineering by combining analytical modeling with practical computational solutions that support both academic research and industrial innovation.
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