LatentFlow: Cross-Frequency Experimental Flow Reconstruction from Sparse Pressure via Latent Mapping

TL;DR

LatentFlow is a novel framework that reconstructs high-frequency turbulent wake flow fields from sparse pressure data by learning a latent representation and mapping low-frequency flow to high-frequency flow during inference.

Contribution

It introduces a cross-modal autoencoder and a latent mapping network to enable high-frequency flow reconstruction from sparse pressure measurements.

Findings

Successfully reconstructs 512 Hz flow fields from 15 Hz pressure data.

Decouples spatial flow encoding from temporal pressure signals.

Provides a scalable solution for high-frequency flow reconstruction in experiments.

Abstract

Acquiring temporally high-frequency and spatially high-resolution turbulent wake flow fields in particle image velocimetry (PIV) experiments remains a significant challenge due to hardware limitations and measurement noise. In contrast, temporal high-frequency measurements of spatially sparse wall pressure are more readily accessible in wind tunnel experiments. In this study, we propose a novel cross-modal temporal upscaling framework, LatentFlow, which reconstructs high-frequency (512 Hz) turbulent wake flow fields by fusing synchronized low-frequency (15 Hz) flow field and pressure data during training, and high-frequency wall pressure signals during inference. The first stage involves training a pressure-conditioned $\beta$-variation autoencoder ($p$C-$\beta$-VAE) to learn a compact latent representation that captures the intrinsic dynamics of the wake flow. A secondary network maps synchronized low-frequency wall pressure signals into the latent space, enabling reconstruction of the wake flow field solely from sparse wall pressure. Once trained, the model utilizes high-frequency, spatially sparse wall pressure inputs to generate corresponding high-frequency flow fields via the $p$C-$\beta$-VAE decoder. By decoupling the spatial encoding of flow dynamics from temporal pressure measurements, LatentFlow provides a scalable and robust solution for reconstructing high-frequency turbulent wake flows in data-constrained experimental settings.