Does a physics digital twin beat black-box models on a real two-tank rig? 0.53 V test RMSE with 8 parameters vs 0.66 V for the best black box

What it found

Fits a two-tank Torricelli twin, with and without an overflow path, to the real Cascaded Tanks benchmark measurements (Schoukens et al. 2016) and scores free-run simulation on the held-out experiment against linear ARX and quadratic NARX models. The 8-parameter overflow twin reaches 0.53 V test RMSE (0.51 V with the sensor’s 10 V saturation applied); the best black box, a 9-parameter linear ARX, gets 0.66 V, tied with the twin without overflow, so the gain comes from the overflow term. Quadratic NARX models are worse and the 3/3 and 4/4 fits diverge in free run (7.4 and 42 V) after a one-step fit. One rig, one split, no confidence interval; the spill gain sits near its fit bound; no published number is reproduced. Data are measured; no input is invented.

A figure from its own output

Paper, code and results

• README and method
• Experiments and results
• Tests

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Other research topics

Proper scoring & elicitation28Effort & peer prediction9Verification games & slashing19Detection & tolerances14Markets as routers13Prediction-market design9Paying contributors8Decentralised training systems23Digital twins & sim-to-real164LLM chip design loops40Robot manufacturing loops53Ambient AI assistant46Self-replicating manufacturing34Simulation-first design64Engineered clothing45Task-specific AI accelerators40Algorithmic chip-design loops42Open-source purpose-built robots44The software-engineering loop43Adversarial human imitation41Open-source residential construction41Autonomous multi-angle capture34Sensing, imaging and 3D31Energy supply and dense energy storage39Robot societies among people31Agentic co-design of low-cost robots27Laundry-hanging robots25Machine learning on qualitative data23Robots on the building site27Civilizations & group psychology1History & human sciences1

Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.