activity
20182024
most citedFlow based features and validation metric for machine learning reconstruction of PIV data

18 citations · 21 across the 4 of their papers we have counts for

collaborators

4 papers

physics.flu-dyn2024★ 1 cited

Trade-off between reconstruction accuracy and physical validity in modeling turbomachinery PIV data by Physics-Informed CNN

Maryam Soltani, Ghasem Akbari, Nader Montazerin

Particle Image Velocimetry (PIV) data is a valuable asset in fluid mechanics. It is capable of visualizing flow structures even in complex physics scenarios, such as the flow at th…

physics.app-ph2021★ 2 cited

Numerical study on the performance of a glazed photovoltaic thermal system integrated with phase change material (GPVT/PCM): on the contribution of PCM volumetric fraction and environmental temperature

Ali Naghdbishi, Mohammad Eftekhari Yazdi, Ghasem Akbari

In the present article, performance of a glazed photovoltaic thermal system integrated with phase change materials (GPVT/PCM) is numerically examined based on both energy and exerg…

physics.flu-dyn2021★ 18 cited

Flow based features and validation metric for machine learning reconstruction of PIV data

Ghasem Akbari, Nader Montazerin

Reconstruction of flow field from real sparse data by a physics-oriented approach is a current challenge for fluid scientists in the AI community. The problem includes feature reco…

physics.flu-dyn2018

On the Role of Low Energy Modes of the Flow on Sub-Grid Scale Parameter Prediction

Hossein Rahmani, Hamid Kalaei, Ghasem Akbari +1

Large Eddy Simulation is based on decomposition of turbulent flow structures to large energy containing scales and small subgrid scales. The present study captures all flow low ene…