@article{Chen:2026:10.1080/09544828.2025.2481536,
author = {Chen, L and Cai, Z and Cheang, W and Long, Q and Sun, L and Childs, P and Zuo, H},
doi = {10.1080/09544828.2025.2481536},
journal = {Journal of engineering design},
pages = {238--272},
title = {AskNatureGPT: an LLM-driven concept generation method based on bio-inspired design knowledge},
url = {http://dx.doi.org/10.1080/09544828.2025.2481536},
volume = {37},
year = {2026}
}

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TY  - JOUR
AB  - Concept generation is the early stage in the engineering design process to produce initial design concepts. By applying bio-inspired design (BID) knowledge, designers can employ biological analogies for solution-driven BID concepts. Solution-driven BID starts with knowledge of a specific biological system for technical design. Despite the proven benefits of solution-driven BID, the gap between biological solutions and engineering problems hinders its effective application, with designers frequently encountering misaligned problem-solution pairs and facing multidisciplinary knowledge gaps in concept generation. Therefore, this research proposes a large language model (LLM) based concept generation method – AskNatureGPT – to automatically search for problems, transfer biological analogy, and generate solution-driven BID concepts in the form of natural language. A concept generator and two evaluators are identified and fine-tuned based on the LLM. The method is evaluated by an ablation study, machine-based quantitative assessments, subjective human evaluations, and a case study. The results show our method can generate solution-driven BID concepts with high quality.
AU  - Chen,L
AU  - Cai,Z
AU  - Cheang,W
AU  - Long,Q
AU  - Sun,L
AU  - Childs,P
AU  - Zuo,H
DO  - 10.1080/09544828.2025.2481536
EP  - 272
PY  - 2026///
SN  - 0954-4828
SP  - 238
TI  - AskNatureGPT: an LLM-driven concept generation method based on bio-inspired design knowledge
T2  - Journal of engineering design
UR  - http://dx.doi.org/10.1080/09544828.2025.2481536
UR  - https://www.tandfonline.com/doi/full/10.1080/09544828.2025.2481536#d1e211
VL  - 37
ER  - 

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