Humanity's Last Peer Review

turbulence.ai

Introducing the first fully autonomous AI scientist for fluid mechanics. From a single natural-language query, turbulence.ai formulates testable ideas, orchestrates numerical experiments, and produces publication-level manuscripts. Here we present turbulence.ai's autonomous research findings - as we advance toward infinite discovery, human expertise in peer review remains the final frontier.

Development Team

Jingsen Feng (冯晶森)*, Yupeng Qi (亓宇鹏)*, Ran Xu (徐冉)*, Xu Chu (初旭)†

University of Exeter • University of Stuttgart
* Equal contribution † Corresponding author

The first manuscript

Flow Regime Transitions in Dense Parallel Microfracture Systems: Energy Conversion Analysis and Critical Capillary Number

Understanding flow regime transitions in multiphase displacement processes has emerged as a fundamental challenge in fluid mechanics with profound implications for subsurface energy applications. This study investigates flow regime transitions that fundamentally differ from those in conventional porous media due to the unique characteristics of dense parallel microfracture systems.

The classical framework for characterizing these transitions relies on the dimensionless capillary number Ca = μv/σ, which quantifies the relative importance of viscous forces to surface tension forces. Our AI research analysis reveals novel insights into energy conversion mechanisms and critical capillary number thresholds in microfracture networks.

Keywords: Multiphase Flow Microfracture Systems
Discovered: May 2025
Research by turbulence.ai

The World's First AI Research PhD Thesis

PhD Thesis

Pore-Scale Insights into Multiphase Displacement in Porous and Fractured Media: Regime Transitions for Oil, CO₂, and Hydrogen

by turbulence.ai University of AI June 24, 2025

This cumulative thesis presents a comprehensive investigation of fundamental physics governing multiphase displacement processes through systematic computational and theoretical analysis. The research encompasses four interconnected studies spanning oil recovery, carbon sequestration, and hydrogen storage technologies.

Research Scope

Contact Angle Effects Microfracture Systems CO₂ Trapping Hydrogen Storage

Key Contributions

  • Critical capillary numbers (Ca ≈ 5.5 ×10⁻⁵) for optimal displacement efficiency
  • Universal scaling relationships for multiphase flow regime transitions
  • Wettability-controlled CO₂ storage optimization frameworks
  • Hydrogen plume dynamics with 15–30% saturation improvement
4 research papers
Doctor of Philosophy
Computational Analysis

Peer Review

As we stand at the threshold of AI research, human expertise in peer review becomes more crucial than ever.

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The Technology Behind turbulence.ai

turbulence.ai builds upon groundbreaking advances in AI-driven computational fluid dynamics, representing the culmination of years of research in automated simulation workflows.

1

OpenFOAMGPT 2.0

The 1st AI Engineer

The first multi-agent framework for computational fluid dynamics enabling fully automated, end-to-end simulations. Four specialized agents work collaboratively to achieve 100% success and reproducibility rates across 450+ simulations.

Pre-processing Agent

Mesh generation and geometry setup

Prompt Generation Agent

Converts cases into templated prompts

Core Simulation Engine

Configuration, execution, and error handling

Post-processing Agent

Data analysis and visualization

100% Reproducibility Zero-tolerance Reliability Multi-case Studies Error-driven Refinement
Academic Publications:
OpenFOAMGPT: A retrieval-augmented LLM agent for CFD LLM Cost-Effectiveness Study: ChatGPT vs. Qwen vs. Deepseek OpenFOAMGPT 2.0: end-to-end, trustworthy automation
2

turbulence.ai

The AI Scientist

The world's first fully autonomous AI scientist for fluid mechanics. Beyond simulation automation, turbulence.ai generates hypotheses, designs experiments, interprets results, and writes publication-level manuscripts—completing the entire research cycle autonomously.

Idea Generation
→
Simulation
→
Paper Writing
Autonomous Research Hypothesis Generation Literature Integration Publication-level Output
Academic Publications:
turbulence.ai: an end-to-end AI Scientist for fluid mechanics

Impact & Vision

Infinite Discovery

Removing traditional bottlenecks of time, expertise, and funding to enable boundless research terrain

Democratized Research

Making advanced fluid mechanics research accessible to researchers worldwide

Accelerated Innovation

Expanding humanity's knowledge base by orders of magnitude through AI-driven research

About turbulence.ai

Pioneering the Future of Scientific Discovery

turbulence.ai represents a paradigm shift in scientific research—the world's first fully autonomous AI scientist capable of conducting complete research cycles in fluid mechanics. Built upon the proven foundation of OpenFOAMGPT technology, we've created a system that doesn't just simulate, but truly discovers.

Here we present turbulence.ai's autonomous research findings - spanning the vast landscape of fluid mechanics and computational engineering. Our AI scientist explores fundamental phenomena in turbulence modeling, multiphase flows, heat and mass transfer, aerodynamics, and hydrodynamics, while tackling real-world engineering challenges in energy systems, environmental flows, biomedical applications, and industrial processes. This represents just the beginning of our journey toward infinite discovery across the entire spectrum of fluid dynamics.

As we stand at the threshold of infinite discovery, human expertise in peer review becomes more crucial than ever. You are witnessing—and participating in—the last peer review, where human insight remains the final arbiter of scientific truth in an age of AI research knowledge.

1st
AI Scientist for Fluids
100%
turbulence.ai Research
∞
Discovery Potential