4 papers
Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications
Arindam Sengupta, Paul Jeanney, Ricardo Vinuesa +2
Urban flow and air-quality simulations generate high-dimensional datasets describing velocity and pollutant transport across multiple spatial, temporal, and physical-variable dimen…
MoTIF: A Mode-Structured Tensor Framework for Multi-Parametric Approximation, Super-Resolution and Forecasting of Unsteady Systems
Guillermo Barragán, Ashton Hetherington, Arindam Sengupta +3
We introduce MoTIF, a mode-structured tensor framework for multi-parametric approximation, super-resolution, and temporal forecasting of high-dimensional unsteady systems. The meth…
A temporal deep learning framework for calibration of low-cost air quality sensors
Arindam Sengupta, Tony Bush, Ben Marner +2
Low-cost air quality sensors (LCS) provide a practical alternative to expensive regulatory-grade instruments, making dense urban monitoring networks possible. Yet their adoption is…
Hybrid machine learning models based on physical patterns to accelerate CFD simulations: a short guide on autoregressive models
Arindam Sengupta, Rodrigo AbadÃa-Heredia, Ashton Hetherington +2
Accurate modeling of the complex dynamics of fluid flows is a fundamental challenge in computational physics and engineering. This study presents an innovative integration of High-…