Kranz, Felix (2025): A dataset of energy-optimal driving waveforms in turbulent pipe flow [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.986097
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Published: 2025-10-20 • DOI registered: 2025-11-19
Abstract:
We compute drag- and energy-optimal driving waveforms in turbulent pipe flow using direct numerical simulations combined with a gradient-free, black-box optimisation framework. Our results demonstrate that Bayesian optimisation significantly outperforms conventional gradient-based methods in terms of efficiency and robustness, owing to its ability to handle noisy objective functions that arise from the finite-time averaging of turbulent flows. Optimal waveforms are identified for three Reynolds numbers and two Womersley numbers. At a Reynolds number of 8600 and a Womersley number of 10, the optimal waveforms reduce total energy consumption by up to 22% and drag by up to 37%. This dataset includes the optimal waveforms, instantaneous and time-averaged velocity fields, as well as post-processing scripts.
Related to:
Morón, Daniel; Avila, Marc: Bayesian minimisation of energy consumption in turbulent pipe flow via unsteady driving. https://arxiv.org/pdf/2508.14593
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| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Binary Object | Binary | Kranz, Felix | Numerical simulated | ||
| 2 | Binary Object (File Size) | Binary (Size) | Bytes | Kranz, Felix | Numerical simulated | |
| 3 | Figure | Fig | Kranz, Felix | Numerical simulated | ||
| 4 | Title | Title | Kranz, Felix | Numerical simulated | ||
| 5 | File name | File name | Kranz, Felix | Numerical simulated | ||
| 6 | Variable | Variable | Kranz, Felix | Numerical simulated |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Enhanced curation (CurationLevelC) * Processing Level: PANGAEA data processing level 2 (ProcLevel2)
Size:
59 data points