Professor Andrew Hamilton Sherry
FREng
Professor of Materials and Director of Nuclear Engineering Doctorate, The Dalton Nuclear Institute, University of Manchester , as of 2011
Fellow , Elected 2011 , North West
Listed by the Academy’s directory under National Nuclear Laboratory
Works on corrosion, crack growth and fatigue. Elected a Fellow of the Royal Academy of Engineering in 2011.
Summary generated from the sources below
Expertise
- Corrosion
- Crack Growth
- Fatigue
- Finite Element Analysis
- Finite Element Method
- Fracture
- Fracture Mechanics
- Knowledge Transfer
- Manufacturing
- Manufacturing Processes
- Materials
- Materials Research
- Mechanical Testing
- Mechanics
- Metal Fatigue
- Metallurgy
- Metals
- Nuclear
- Nuclear Accidents
- Nuclear Decommissioning
- Nuclear Energy
- Nuclear Fuel
- Nuclear Marine Propulsion
- Nuclear Safety
- Nuclear Technology
- Numerical Modelling
- Postgraduate Education
- Radioactive Waste
- Radioactive Waste Disposal
- Radioactive Waste Management
- Research and Development
- Residual Stress
- Simulation
- Steel
- Stress
- Stress Analysis
- Structural
- Structural Fatigue
- Structural Fracture
- Structural Integrity
- Structural Mechanics
- Surface Engineering
- Welding
- Advanced Manufacturing
- Advanced Materials
- Policy
- Safety
- Safety Assessment
- Structural Reliability
Sources
- Identity
Likely (grade C) , two independent sources state they are a Fellow, and one source names them with their organisation or field , RAEng citation , 30 Sep 2026 , uknnl.com , 11 Oct 2026 , lastenergy.com , 11 Oct 2026
Why we think this is them
RAEng citation , 30 Sep 2026 , announces their election in 2011
uknnl.com , 11 Oct 2026 , states they are a Fellow
lastenergy.com , 11 Oct 2026 , names them with their organisation or field
- Directory entry, Listed under
RAEng directory , 30 Sep 2026 , read from the page , facts , high confidence
- Role, Organisation
RAEng citation , 30 Sep 2026 , read from the page , facts , low confidence , as of 2011
- Summary
RAEng directory , 11 Oct 2026 , extracted by a language model , facts , high confidence