Benchmark-Dataset FAN-01: Low pressure Axial Fan in a short Duct

The case consists of a generic axial fan for industrial applications. Provided measurement data include instationary pressure probes in the rotor's tip gap, distributions of velocity and turbulent kinetic energy gained by laser Doppler anemometry, as well as acoustic results gained by microphones and beamforming. A detailed description of the dataset with references can be found in the PDF-File. The rotor geometry is available as IGS or Parasolid file. The measurement data is available, including the ones (LDA-data, pressure probes, acoustic microphones, üerformance) listed in the PDF description file. Citation of the fan and the data: Zenger, Florian, et al. A benchmark case for aerodynamics and aeroacoustics of a low pressure axial fan. No. 2016-01-1805. SAE Technical Paper, 2016. Citation of the microphone array measurements: Krömer, Florian J. Sound emission of low-pressure axial fans under distorted inflow conditions. FAU University Press, 2018. Citation of the python scripts: Junger, Clemens. Computational aeroacoustics for the characterization of noise sources in rotating systems. Diss. Technische Universität Wien, 2019. Related work and existing publications: Schoder, Stefan, Clemens Junger, and Manfred Kaltenbacher. "Computational aeroacoustics of the EAA benchmark case of an axial fan." Acta Acustica 4.5 (2020): 22. https://doi.org/10.1051/aacus/2020021 Schoder, Stefan, and Felix Czwielong. "Dataset fan-01: Revisiting the EAA benchmark for a low-pressure axial fan." arXiv preprint arXiv:2211.12014 (2022). https://doi.org/10.48550/arXiv.2211.12014 Kaltenbacher, Manfred, and Stefan Schoder. "EAA Benchmark for an axial fan." e-Forum Acusticum 2020. 2020. https://hal.science/hal-03221387/document Tieghi, Lorenzo, et al. "Machine-learning clustering methods applied to detection of noise sources in low-speed axial fan." Journal of Engineering for Gas Turbines and Power 145.3 (2023): 031020. https://doi.org/10.1115/1.4055417 Antoniou, E., Romani, G., Jantzen, A., Czwielong, F., & Schoder, S. (2023). Numerical flow noise simulation of an axial fan with a Lattice-Boltzmann solver. Acta Acustica, 7, 65. https://doi.org/10.1051/aacus/2023060 Data curation and Questions about the Dataset Data curated by Stefan Schoder, any questions related to the dataset to [e-mail].本数据集针对一款通用工业应用轴流风机。所提供的测量数据包含转子叶尖间隙处的非定常压力探针数据、通过激光多普勒测速术（Laser Doppler Anemometry，LDA）获取的速度与湍流动能分布，以及通过麦克风阵列与波束成形技术得到的声学测量结果。 本数据集的详细说明及参考文献可查阅配套PDF文件。转子几何模型可通过IGS（Initial Graphics Exchange Specification）或Parasolid格式文件获取。测量数据均已开放获取，包含PDF说明文件中列出的LDA数据、压力探针数据、声学麦克风数据及性能数据。 本风机及数据集的引用规范如下：Florian Zenger 等. 低压轴流风机气动与气动声学基准案例[R]. 编号2016-01-1805, SAE技术论文, 2016. 麦克风阵列测量相关引用规范：Florian J. Krömer. 畸变来流条件下低压轴流风机的声辐射[M]. 德国埃尔朗根-纽伦堡大学出版社, 2018. 配套Python脚本的引用规范：Clemens Junger. 旋转系统噪声源表征的计算气动声学[D]. 维也纳工业大学, 2019. 相关研究及已发表文献： 1. Stefan Schoder, Clemens Junger, Manfred Kaltenbacher. 轴流风机EAA基准案例的计算气动声学[J]. Acta Acustica, 2020, 4(5): 22. https://doi.org/10.1051/aacus/2020021 2. Stefan Schoder, Felix Czwielong. 数据集fan-01：重新审视低压轴流风机的EAA基准案例[EB/OL]. arXiv预印本, arXiv:2211.12014, 2022. https://doi.org/10.48550/arXiv.2211.12014 3. Manfred Kaltenbacher, Stefan Schoder. 轴流风机的EAA基准案例[C]// e-Forum Acusticum 2020, 2020. https://hal.science/hal-03221387/document 4. Lorenzo Tieghi 等. 机器学习聚类方法在低速轴流风机噪声源检测中的应用[J]. Journal of Engineering for Gas Turbines and Power, 2023, 145(3): 031020. https://doi.org/10.1115/1.4055417 5. E. Antoniou, G. Romani, A. Jantzen, F. Czwielong, S. Schoder. 基于格子玻尔兹曼（Lattice-Boltzmann）求解器的轴流风机流动噪声数值模拟[J]. Acta Acustica, 2023, 7: 65. https://doi.org/10.1051/aacus/2023060 数据集管理与咨询 本数据集由Stefan Schoder整理，若有相关疑问请发送邮件至[e-mail]。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于工业应用的通用低压轴流风扇基准测试数据集，包含转子尖端间隙的非稳态压力探头测量、激光多普勒测速仪获得的流速和湍流动能分布，以及麦克风和波束成形技术采集的声学结果。数据集提供了详细的测量数据、几何模型文件和Python脚本，旨在支持气动声学研究和计算验证，由多所大学合作创建并开放共享。