activity
20222025
most citedAssessment of URANS and LES Methods in Predicting Wake Shed Behind a Vertical Axis Wind Turbine

62 citations · 76 across the 8 of their papers we have counts for

collaborators

8 papers

physics.flu-dyn2025

Dual guidance: ROM-informed field reconstruction with generative models

Sajad Salavatidezfouli, Henrik Karstoft, Alexandros Iosifidis +1

We present a dual-guided framework for reconstructing unsteady incompressible flow fields using sparse observations. The approach combines optimized sensor placement with a physics…

math.NA2024★ 1 cited

Stochastic Parameter Prediction in Cardiovascular Problems

Kabir Bakhshaei, Sajad Salavatidezfouli, Giovanni Stabile +1

Patient-specific modeling of cardiovascular flows with high-fidelity is challenging due to its dependence on accurately estimated velocity boundary profiles, which are essential fo…

physics.med-ph2024

Mesh-Informed Reduced Order Models for Aneurysm Rupture Risk Prediction

Giuseppe Alessio D'Inverno, Saeid Moradizadeh, Sajad Salavatidezfouli +2

The complexity of the cardiovascular system needs to be accurately reproduced in order to promptly acknowledge health conditions; to this aim, advanced multifidelity and multiphysi…

math.NA2024★ 1 cited

A Predictive Surrogate Model for Heat Transfer of an Impinging Jet on a Concave Surface

Sajad Salavatidezfouli, Saeid Rakhsha, Armin Sheidani +2

This paper aims to comprehensively investigate the efficacy of various Model Order Reduction (MOR) and deep learning techniques in predicting heat transfer in a pulsed jet impingin…

math.NA2023★ 2 cited

Modal Analysis of the Wake Shed Behind a Horizontal Axis Wind Turbine with Flexible Blades

Sajad Salavatidezfouli, Armin Sheidani, Kabir Bakhshaei +4

The proper orthogonal decomposition has been applied on a full-scale horizontal-axis wind turbine to shed light on the wake characteristics behind the wind turbine. In reality, the…

math.NA2023★ 8 cited

Deep Reinforcement Learning for the Heat Transfer Control of Pulsating Impinging Jets

Sajad Salavatidezfouli, Giovanni Stabile, Gianluigi Rozza

This research study explores the applicability of Deep Reinforcement Learning (DRL) for thermal control based on Computational Fluid Dynamics. To accomplish that, the forced convec…