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Biomimicking Nature-Inspired Design Structures-An Experimental and Simulation Approach Using Additive Manufacturing.
Arun Y Patil1, Chandrashekhar Hegde1, Guruprasad Savanur1
1School of Mechanical Engineering, KLE Technological University, Hubballi 580031, India.
Biomimetics (Basel, Switzerland)
|November 22, 2022
Summary
Nature-inspired designs offer optimal solutions for automotive impact resistance. This study tested seven bio-inspired structures for load-bearing capacity, identifying the best-performing concept for enhanced safety and performance.
Area of Science:
- Biomimetics and Materials Science
- Mechanical Engineering and Design
- Automotive Safety Engineering
Background:
- Bio-inspired design leverages natural structures for engineering solutions.
- Nature provides optimal, economically viable, and sustainable design principles.
- Automotive components require robust impact resistance for safety and performance.
Purpose of the Study:
- To evaluate seven plant- and animal-derived bio-inspired structures for automotive impact resistance.
- To identify the most effective bio-inspired design for load-bearing capacity.
- To compare simulation and experimental results for optimized automotive components.
Main Methods:
- Algorithm-based generative shape designs created in CATIA V6.
- Optimization using Rhino 7 software and simulation in ANSYS Workbench.
- Experimental validation through fused deposition modeling (3D printing) and comparative analysis.
Main Results:
- Evaluation of compressive, flexural, and fatigue load conditions for all structures.
- Analysis of key performance indicators including life cycles, safety factor, and damage tolerance.
- Comparative study to determine the optimal bio-inspired structure for automotive applications.
Conclusions:
- Bio-inspired structures show promise for enhancing automotive impact resistance.
- Novel materials with multifunctional properties (softness, stiffness, lightweight) are suitable for automotive, aerospace, and medical sectors.
- The study provides a framework for selecting optimal bio-inspired designs through simulation and experimentation.
