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Ingrid Bouwer Utne
Researcher at Norwegian University of Science and Technology
Publications - 150
Citations - 3591
Ingrid Bouwer Utne is an academic researcher from Norwegian University of Science and Technology. The author has contributed to research in topics: Computer science & Risk management. The author has an hindex of 31, co-authored 134 publications receiving 2644 citations.
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Building Safety indicators: Part 1 – Theoretical foundation
TL;DR: In this article, the theoretical basis for the development of early warning indicators used as early warnings of major accidents is established. But, the focus of these indicators is on the major hazard indicators, and less on personal safety indicators.
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Human Fatigue’s Effect on the Risk of Maritime Groundings - A Bayesian Network Modeling Approach
TL;DR: In this article, a Bayesian Network (BN) of human fatigue in the bridge management team and the risk of ship grounding is proposed, and the qualitative part of the BN has been structured based on modifying the Human Factor Analysis and Classification System (HFACS).
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Developing safety indicators for preventing offshore oil and gas deepwater drilling blowouts
TL;DR: In this article, the authors present information and indicators from the Risk Level Project (RNNP) in the Norwegian O&G industry related to safety climate, barriers and undesired incidents, and discuss the relevance for deepwater drilling.
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A method for risk modeling of interdependencies in critical infrastructures
TL;DR: A method for assessing interdependencies of critical infrastructures, as part of a cross-sector risk and vulnerability analysis, based on a relatively simple approach applicable for practitioners but may be extended for more detailed analyses by specialists.
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Collision avoidance on maritime autonomous surface ships: Operators’ tasks and human failure events
TL;DR: This paper presents a task analysis for collision avoidance through Hierarchical Task Analysis and making use of a cognitive model for categorizing the tasks, and identifies human failure events in future MASS operations.