• 482 Citations
  • 15 h-Index
If you made any changes in Pure these will be visible here soon.

Personal profile

External positions

Fingerprint Dive into the research topics where Ming Yang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Risk assessment Engineering & Materials Science
Accidents Engineering & Materials Science
Oils Chemical Compounds
Bayesian networks Engineering & Materials Science
Oil spills Engineering & Materials Science
Radioactive materials Engineering & Materials Science
oil spill Earth & Environmental Sciences
oil Earth & Environmental Sciences

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2011 2019

  • 482 Citations
  • 15 h-Index
  • 41 Article
  • 7 Conference contribution
  • 2 Review article
  • 1 Paper

An integrated framework for subsea pipelines safety analysis considering causation dependencies

Li, X., Yang, M. & Chen, G., May 2019, In : Ocean Engineering. 183, p. 175-186

Research output: Contribution to journalArticle

Decision making

Probabilistic assessment of integrated safety and security related abnormal events: a case of chemical plants

Song, G., Khan, F. & Yang, M., Mar 2019, In : Safety Science. 113, p. 115-125 11 p.

Research output: Contribution to journalArticle

Chemical plants

Quantitative Resilience Assessment for Process Units Operating in Arctic Environments

Zinetullina, A., Yang, M. & Golman, B., Jul 2019, 4th Symposium on Safety and Integrity Management in Harsh Environments.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Risk assessment
Chemical reactions
Bayesian networks
Natural resources
6 Citations (Scopus)

Review of risk-based design for ice-class ships

Kujala, P., Goerlandt, F., Way, B., Smith, D., Yang, M., Khan, F. & Veitch, B., Jan 1 2019, In : Marine Structures. 63, p. 181-195 15 p.

Research output: Contribution to journalReview article

Risk analysis
Oil spills

Risk assessment of process systems by mapping fault tree into artificial neural network

Sarbayev, M., Yang, M. & Wang, H., May 9 2019, In : Journal of Loss Prevention in the Process Industries. 60, p. 203-212 10 p.

Research output: Contribution to journalArticle

risk assessment process
Risk assessment
neural networks
Neural networks
risk assessment