Work

Turbulence.ai: an end-to-end AI scientist for fluid mechanics

Year: 2025

Type: article

Abstract: Fluid mechanics holds an almost infinite range of unsolved questions whose answers could improve energy efficiency, environmental protection and public health. Yet progress is throttled by scarce resources—human expertise, time cost and research funding. We introduce turbulence.ai , the first fully autonomous AI scientist for fluid mechanics, designed to lift those constraints. A multi-agent architecture unifies hypothesis generation, CFD execution and draft writing. From a single natural-language query the platform (i) formulates testable ideas, (ii) orchestrates a series of numerical experiments, (iii) interprets results and (iv) produces a draft (attached). This advance inaugurates a new chapter in fluid-mechanics research and could expand human’s knowledge base by orders of magnitude.

Source: Theoretical and Applied Mechanics Letters

DOI: 10.1016/j.taml.2025.100620

Authors: Jingsen Feng, Yupeng Qi, Ran Xu, Sandeep Pandey, Xu Chu

Institutions: University of Exeter, University of Stuttgart, Stuttgart Center for Simulation Science, Technische Universität Ilmenau

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funder: Royal Society