Mohammad Sheikholeslami

Doctoral Student at Marine Technology

The main aim of Mohammad’s project is to exploit the recent developments in machine learning and multi-fidelity deep learning algorithms to accelerate and improve the efficiency of physics-informed neural networks (PINN). This study will answer the research question of how to efficiently and accurately solve PDEs that describes fluid dynamics and wave evolutions by combining PINNs and multi-fidelity algorithms.

Source: chalmers.se
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Showing 1 publications

2024

Physics-Informed Neural Networks for Modeling Linear Waves

Mohammad Sheikholeslami, Saeed Salehi, Wengang Mao et al
Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering - OMAE. Vol. 9
Paper in proceeding

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Showing 2 research projects

2023–2027

Artificial intelligence for enhanced hydraulic turbine lifetime

Håkan Nilsson Fluid Dynamics
Mohammad Sheikholeslami Marine Technology
Saeed Salehi Fluid Dynamics
Wengang Mao Marine Technology
Energiforsk AB
Swedish Energy Agency

6 publications exist
2023–2027

PINNs -- Multi-Fidelity Physics-Informed Neural Network to Solve Partial Differential Equations

Wengang Mao Marine Technology
Håkan Nilsson Fluid Dynamics
Mohammad Sheikholeslami Marine Technology
Arash Eslamdoost Marine Technology
Saeed Salehi Fluid Dynamics
Chalmers

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