M
Mario Brito
Researcher at University of Southampton
Publications - 63
Citations - 785
Mario Brito is an academic researcher from University of Southampton. The author has contributed to research in topics: Risk management & Risk analysis. The author has an hindex of 13, co-authored 57 publications receiving 610 citations. Previous affiliations of Mario Brito include National Oceanography Centre, Southampton & University of Bristol.
Papers
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Journal ArticleDOI
Clean access, measurement, and sampling of Ellsworth Subglacial Lake: A method for exploring deep Antarctic subglacial lake environments
Martin J. Siegert,Rachel J. Clarke,Matthew C. Mowlem,Neil Ross,Christopher S. Hill,Andrew Tait,Dominic A. Hodgson,John Parnell,Martyn Tranter,David A. Pearce,Michael J. Bentley,Charles S. Cockell,Maria-Nefeli Tsaloglou,Andrew Smith,John Woodward,Mario Brito,Edward M. Waugh +16 more
TL;DR: In this paper, the authors summarize the scientific protocols and methods being developed for the exploration of Ellsworth Subglacial Lake in West Antarctica, planned for 2012-2013, which they offer as a guide to future subglacial environment research missions.
Journal ArticleDOI
Risk analysis for autonomous underwater vehicle operations in extreme environments.
TL;DR: A risk management process tailored to AUV operations, the implementation of which requires the elicitation of expert judgment is described, and the aggregated risk estimates obtained from the expert judgments were used to create a risk model.
Journal ArticleDOI
A Bayesian approach for predicting risk of autonomous underwater vehicle loss during their missions
Mario Brito,Gwyn Griffiths +1 more
TL;DR: This work proposes and explores a solution founded on a Bayesian Belief Network (BBN), where the results of the expert judgment elicitation are taken as the initial prior probability of loss due to failure.
Journal ArticleDOI
A critique of the use of domain analysis for spatial collision risk assessment
Andrew David Rawson,Mario Brito +1 more
TL;DR: The results suggest that the strength of the relationship between collisions and encounters is varied both between vessel types and the spatial scale of assessment, and provides research direction for practical applications of domain analysis on collision risk assessments.
Journal ArticleDOI
A Markov Chain State Transition Approach to Establishing Critical Phases for AUV Reliability
Mario Brito,Gwyn Griffiths +1 more
TL;DR: In this paper, the authors present a state transition approach, in the form of a Markov chain, which models step sequence from pre-launch to operation to recovery, to identify states and state transitions presenting high risk to the vehicle and hence to the mission.