The integration of artificial intelligence into experimental fluid mechanics promises to accelerate discovery, yet most AI applications remain narrowly focused on numerical studies. This work proposes an AI Fluid Scientist framework that autonomously executes the complete experimental workflow: hypothesis generation, experimental design, robotic execution, data analysis, and manuscript preparation. We validate this through investigation of vortex-induced vibration (VIV) and wake-induced vibration (WIV) in tandem cylinders. Our work has four key contributions: (1) A computer-controlled circulating water tunnel (CWT) with programmatic control of flow velocity, cylinder position, and forcing parameters (vibration frequency and amplitude) with data acquisition (displacement, force, and torque). (2) Automated experiments reproduce literature benchmarks (Khalak and Williamson [1999] and Assi et al. [2013, 2010]) with frequency lock-in within 4% and matching critical spacing trends. (3) The framework with Human-in-the-Loop (HIL) discovers more WIV amplitude response phenomena, and uses a neural network to fit physical laws from data, which is 31% higher than that of polynomial fitting. (4) The framework with multi-agent with virtual-real interaction system executes hundreds of experiments end-to-end, which automatically completes the entire process of scientific research from hypothesis generation, experimental design, experimental execution, data analysis, and manuscript preparation. It greatly liberates human researchers and improves study efficiency, providing new paradigm for the development and research of experimental fluid mechanics.

翻译：将人工智能融入实验流体力学有望加速科学发现，然而目前大多数人工智能应用仍局限于数值研究。本研究提出了一种人工智能流体科学家框架，能够自主执行完整的实验工作流程：假设生成、实验设计、机器人执行、数据分析和论文撰写。我们通过对串联圆柱体的涡激振动（VIV）和尾流诱导振动（WIV）的研究验证了该框架。本工作的主要贡献包括：（1）开发了一套计算机控制的循环水洞（CWT）系统，可编程调控流速、圆柱体位置及激励参数（振动频率与振幅），并实现数据采集（位移、力与扭矩）。（2）自动化实验复现了文献基准（Khalak与Williamson [1999] 以及Assi等人 [2013, 2010]），频率锁定误差在4%以内，且临界间距变化趋势吻合。（3）结合人在回路（HIL）的框架发现了更丰富的WIV振幅响应现象，并采用神经网络从数据中拟合物理规律，其拟合精度较多项式拟合提升31%。（4）基于虚实交互的多智能体系统框架实现了数百次端到端实验，自动完成从假设生成、实验设计、实验执行、数据分析到论文撰写的完整科研流程。该框架极大解放了科研人员，提升了研究效率，为实验流体力学的发展与研究提供了新范式。