Mohammad Yazdani-Asrami

University of Glasgow

United Kingdom

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Research Interests

Condensed Matter Physics

100%

Hardware Engineering

80%

Superconducting Technology

100%

Superconductivity

80%

Electrical Engineering

70%

Semiconductor Physics

50%

Neuromorphic Engineering

50%

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Positions1

Mohammad Yazdani-Asrami

University Name

University of Glasgow

1 year ago

Protection models for superconducting fusion magnets

No summary provided for this position.

1 year ago

Articles30

Intelligent estimation of critical current density of ReBCO superconductors exposed to irradiation: first machine learning study

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Year:

2025

Physics-informed neural network model for transient thermal analysis of superconductors

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Year:

2025

Data-driven thrust prediction in applied-field magnetoplasmadynamic thrusters for space missions using artificial intelligence-based models

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Year:

2025

Intelligent predictor model for critical current density of MgB2 superconducting bulks

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Year:

2025

Preliminary Assessment of a Highly Flexible HTS Drive for Electric Aircraft

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Year:

2025

Degradation modeling of polymer electrolyte membrane water electrolyzers for hydrogen production: motivation, status, and strategies

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Year:

2025

Fast-Recovery Superconducting Fault Current Limiter Based on a Novel Skeleton Topology for Future Cryo-Electric Aircraft: Reclosing and Repetitive Fault Cases

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Year:

2025

Intelligent and Application-Oriented Optimal Design of Travelling Field Flux Pumps

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Year:

2025

Artificial intelligence models for predicting the performance of proton exchange membrane water electrolyzers under steady and dynamic power

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Year:

2025

Advanced intelligent quench diagnostics for high temperature superconducting coils based on principal component analysis of voltage harmonic ratios and Support Vector Machine

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Year:

2025

Artificial-Intelligence-Driven Model for Resistive Superconducting Fault Current Limiter in Future Electric Aircraft

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Year:

2024

Intelligent surrogate model of a high-temperature superconducting cable for reliable energy delivery: short-circuit fault performance

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Year:

2024

Enhancing the Predictive Modeling of n-Value Surfaces in Various High Temperature Superconducting Materials Using a Feed-Forward Deep Neural Network Technique

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Year:

2024

Estimation of magnetic levitation and lateral forces in MgB2 superconducting bulks with various dimensional sizes using artificial intelligence techniques

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Year:

2024

A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes

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Year:

2024

Machine learning-based model for the intelligent estimation of critical heat flux in nanofluids

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Year:

2024

Intelligent estimation of critical current degradation in HTS tapes under repetitive overcurrent cycling for cryo-electric transportation applications

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Year:

2024

Short circuit analysis of a fault-tolerant current-limiting high temperature superconducting transformer in a power system in presence of distributed generations

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Year:

2024

Digital Twins for Condition and Fleet Monitoring of Aircraft: Toward More-Intelligent Electrified Aviation Systems

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Year:

2024

Roadmap on Artificial intelligence and big data techniques for superconductivity

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Year:

2023

The TRV Improvement of Fast Circuit Breakers Using Solid-State Series Superconducting Reactor

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Year:

2023

AC Loss Analysis in Superconducting Cables Carrying Characteristic and Noncharacteristic Harmonic Currents

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Year:

2023

Artificial intelligence, machine learning, deep learning, and big data techniques for the advancements of superconducting technology: a road to smarter and intelligent superconductivity

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Year:

2023

Smart fault detection of HTS coils using artificial intelligence techniques for large-scale superconducting electric transport applications

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Year:

2023

A Fast Numerical Modeling Approach Based on Boundary Field Method for Calculating AC Losses in Superconducting Motors

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Year:

2023

Ultra-fast Surrogate Model for Magnetic Field Computation of a Superconducting Magnet Using Multi-layer Artificial Neural Networks

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Year:

2023

Role of Insulation Materials and Cryogenic Coolants on Fault Performance of MW-Scale Fault-Tolerant Current-Limiting Superconducting Transformers

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Year:

2023

A New Intelligent Estimation Method Based on the Cascade-Forward Neural Network for the Electric and Magnetic Fields in the Vicinity of the High Voltage Overhead Transmission Lines

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Year:

2023

Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring

Article Link

Year:

2022

Artificial intelligence-based models for reconstructing the critical current and index-value surfaces of HTS tapes

Article Link

Year:

2022

Collaborators14

Stefano Diciotti

ALMA MATER STUDIORUM UNIVERSITY OF BOLOGNA

ITALY

Amir Heidary

Delft University of Technology

NETHERLANDS

Paolo Bellavista

Full Professor

University of Bologna

ITALY

Vitor Fernao Pires

Professor Coordenador

Instituto Politécnico de Leiria Escola Superior de Tecnologia e Gestão

PORTUGAL

Maciej Wielgosz

Assistant Professor

AGH University of Science and Technology

POLAND

Giacomo Russo

University of Bologna

ITALY

Dominic Moseley

Victoria University of Wellington

NEW ZEALAND

Andrzej Skoczen

assistant professor

POLAND

Antonio Morandi

University of Bologna

ITALY

Dr Wenjuan Song

Lecturer/Assistant Professor

University of Glasgow

UNITED KINGDOM

Anabela Pronto

Universidade de Aveiro

PORTUGAL

Shahin Alipour Bonab

University of Glasgow

UNITED KINGDOM

Dimitrios Tzelepis

University Of Strathclyde

UNITED KINGDOM

Yao Wang

Assistant Professor

Clemson University

UNITED STATES

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