Mohammad Yazdani-Asrami

University of Glasgow

United Kingdom

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Positions (1)

Mohammad Yazdani-Asrami

University of Glasgow

No summary provided for this position.

Articles (30)

Collaborators (14)

Stefano Diciotti

ALMA MATER STUDIORUM UNIVERSITY OF BOLOGNA

Amir Heidary

Delft University of Technology

Paolo Bellavista

Full Professor

University of Bologna

Vitor Fernao Pires

Professor Coordenador

Instituto Politécnico de Leiria Escola Superior de Tecnologia e Gestão

Maciej Wielgosz

Assistant Professor

AGH University of Science and Technology

Giacomo Russo

University of Bologna

Dominic Moseley

Victoria University of Wellington

Andrzej Skoczen

assistant professor

Antonio Morandi

University of Bologna

Dr Wenjuan Song

Lecturer/Assistant Professor

University of Glasgow

UNITED KINGDOM

Anabela Pronto

Universidade de Aveiro

Shahin Alipour Bonab

University of Glasgow

UNITED KINGDOM

Dimitrios Tzelepis

University Of Strathclyde

UNITED KINGDOM

Yao Wang

Assistant Professor

Clemson University

UNITED STATES

Mohammad Yazdani-Asrami

Research Interests

Explore related searches

Contact this professor

Positions (1)

Protection models for superconducting fusion magnets

Articles (30)

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

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

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

Intelligent predictor model for critical current density of MgB2 superconducting bulks

Preliminary Assessment of a Highly Flexible HTS Drive for Electric Aircraft

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Roadmap on Artificial intelligence and big data techniques for superconductivity

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

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

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

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

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

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

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

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

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

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

Collaborators (14)

Stefano Diciotti

Amir Heidary

Paolo Bellavista

Vitor Fernao Pires

Maciej Wielgosz

Giacomo Russo

Dominic Moseley

Andrzej Skoczen

Antonio Morandi

Dr Wenjuan Song

Anabela Pronto

Shahin Alipour Bonab

Dimitrios Tzelepis

Yao Wang

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