A computational approach to biologically inspired design

Author:

Nagel Jacquelyn K.S.,Stone Robert B.

Abstract

AbstractThe natural world provides numerous cases for analogy and inspiration in engineering design. During the early stages of design, particularly during concept generation when several variants are created, biological systems can be used to inspire innovative solutions to a design problem. However, identifying and presenting the valuable knowledge from the biological domain to an engineering designer during concept generation is currently a somewhat disorganized process or requires extensive knowledge of the biological system. To circumvent the knowledge requirement problem, we developed a computational approach for discovering biological inspiration during the early stages of design that integrates with established function-based design methods. This research defines and formalizes the information identification and knowledge transfer processes that enable systematic development of biologically inspired designs. The framework that supports our computational design approach is provided along with an example of a smart flooring device to demonstrate the approach. Biologically inspired conceptual designs are presented and validated through a literature search and comparison to existing products.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering

Cited by 30 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Understanding inspiration: Insights into how designers discover inspirational stimuli using an AI-enabled platform;Design Studies;2023-09

2. Free-text inspiration search for systematic bio-inspiration support of engineering design;Artificial Intelligence for Engineering Design, Analysis and Manufacturing;2023

3. BERT and Pareto dominance applied to biological strategy decision for bio-inspired design;Advanced Engineering Informatics;2023-01

4. A Preliminary Performance Analysis of A Bio-Inspired Antenna on a Glossy Paper Substrate;2022 International Conference on Green Energy, Computing and Sustainable Technology (GECOST);2022-10-26

5. Exploring Visual Cues for Design Analogy: A Deep Learning Approach;Journal of Mechanical Design;2022-10-06

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