Collision Risk Analysis of FPSO-Tanker Offloading Operation

2002 ◽  
Author(s):  
Haibo Chen ◽  
Torgeir Moan
Keyword(s):  
Risk Model ◽  
Human Action ◽  
Near Miss ◽  
Risk Modeling ◽  
Collision Risk ◽  
Forward Movement ◽  
Recovery Stage ◽  
Human Aspects ◽  
Machine Interaction ◽  
Tandem Offloading

Collision between FPSO and shuttle tanker in tandem offloading operation has caused a growing concern in the North Sea. Several recent contact incidents between FPSO/FSU and shuttle tanker have clearly demonstrated a high likelihood of contact between vessels in tandem offloading. The large masses involved, i.e. high potential impact energy, make the collision risk large. Traditional ship/platform collision risk model may not be effective for tandem offloading operation. Further more in a broader sense, offshore quantitative risk analyses generally focus more on technical aspects, little on human aspects. This leads to a hardware-centered risk control approach, which may not be effective in the face of risks in complex marine operations. A collision risk modeling approach for FPSO and tanker offloading operation is presented in this paper. The collision frequency is modeled in the initiating stage and the recovery stage. In the initiating stage, this paper is focused on tanker powered forward movement (PFM) scenarios. The initiation of tanker PFM involves a complex man machine interaction. The risk model is set up which integrates technical events, human actions and their interaction in the initiating stage. This model guides us further to identify the two failure prone situations where man machine interaction happened and resulted in most collision incidents. The study to quantitatively analyze these failure prone situations and minimize their occurrence is presented in a companion paper OMAE 28101. In the recovery stage, this paper is focused on the tanker initiated recovery. Based on the proposed probabilistic model for the recovery stage, possible recovery actions are identified and the event development is modeled from initiation of tanker PFM to the final outcome, i.e. collision or near miss. The success of recovery is analyzed from the human action timing perspective. Based on qualitative and preliminary quantitative analyses, recommendations are made to reduce the failure of recovery in design and operation.

Macroscopic collision risk model based on near miss

2021 ◽  
pp. 1-23
Author(s):  
Yangyu Zhou ◽  
Jiaxuan Yang ◽  
Xingpei Bian ◽  
Lingqi Ma ◽  
Zhen Kang
Keyword(s):  
Geographical Distribution ◽  
Risk Model ◽  
Grid Method ◽  
Near Miss ◽  
Distribution Characteristics ◽  
Data Sampling ◽  
Collision Risk ◽  
Model Based ◽  
Marine Traffic ◽  
The Subject

Abstract Using near miss data detected from non-accident information to analyse marine traffic risk can alleviate some of the limitations of accident-based methods. A model based on an arena for detecting scenes of near miss is proposed to detect comprehensively those ship encounters with potential collision risk. To eliminate the influence of data sampling frequency on the detection of scenes of near miss, a single near miss is defined as the whole progress of traffic state from the time the target ship sails into the arena of the subject ship to the time it leaves the arena of the subject ship. To research the geographical distribution characteristics of marine traffic risk, first, a statistical model for the scenes of near miss based on the water grid method is proposed, and then a macroscopic collision risk model based on near miss is developed. The geographical distribution characteristics of marine traffic risk in the Bohai Sea are analysed, and the water areas of high marine traffic risk are obtained. The findings can provide theoretical support for marine safety management.

scholarly journals Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

2021 ◽  
Vol 9 (2) ◽  
pp. 180
Author(s):  
Lei Du ◽  
Osiris A. Valdez Banda ◽  
Floris Goerlandt ◽  
Pentti Kujala ◽  
Weibin Zhang
Keyword(s):  
Baltic Sea ◽  
Perceived Risk ◽  
Maritime Transportation ◽  
Near Miss ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Ship Collision ◽  
The Impact ◽  
Ship Behavior

Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.

Dynamic collision risk modeling under uncertainty

Robotica ◽  
2012 ◽  
Vol 31 (4) ◽  
pp. 525-537 ◽  
Author(s):  
F. Belkhouche ◽  
B. Bendjilali
Keyword(s):  
Configuration Space ◽  
Collision Detection ◽  
Sensory System ◽  
Dynamic Environment ◽  
Rate Of Change ◽  
Risk Modeling ◽  
Collision Risk ◽  
Moving Vehicles ◽  
Probability Of Collision ◽  
Geometric Variables

SUMMARYThis paper introduces a probabilistic model for collision risk assessment between moving vehicles. The uncertainties in the states and the geometric variables obtained from the sensory system are characterized by probability density functions. Given the states and their uncertainties, the goal is to determine the probability of collision in a dynamic environment. Two approaches are discussed: (1) The virtual configuration space (VCS), and (2) the rates of change of the visibility angles. The VCS is a transformation of observer that reduces collision detection with a moving object to collision detection with a stationary object. This approach allows to create simple geometric collision cones. Error propagation models are used to solve the problem when going from the VCS to the configuration space. The second approach derives the collision conditions in terms of the rate of change of the limit visibility angles. The probability of collision is then calculated. A comparison between the two methods is carried out. Results are illustrated using simulation, including Monte Carlo simulation.

Towards a Model of Regional Vessel Near-miss Collision Risk Assessment for Open Waters based on AIS Data

2019 ◽  
Vol 72 (06) ◽  
pp. 1449-1468 ◽  
Author(s):  
Weibin Zhang ◽  
Xinyu Feng ◽  
Yong Qi ◽  
Feng Shu ◽  
Yijin Zhang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Safety Management ◽  
Open Water ◽  
Water Area ◽  
Assessment System ◽  
Near Miss ◽  
Collision Risk ◽  
Accurate Analysis ◽  
Open Water Area ◽  
Temporal Features

The absence of a regional, open water vessel collision risk assessment system endangers maritime traffic and hampers safety management. Most recent studies have analysed the risk of collision for a pair of vessels and propose micro-level risk models. This study proposes a new method that combines density complexity and a multi-vessel collision risk operator for assessing regional vessel collision risk. This regional model considers spatial and temporal features of vessel trajectory in an open water area and assesses multi-vessel near-miss collision risk through danger probabilities and possible consequences of collision risks via four types of possible relative striking positions. Finally, the clustering method of multi-vessel encountering risk, based on the proposed model, is used to identify high-risk collision areas, which allow reliable and accurate analysis to aid implementation of safety measures.

scholarly journals Improving conflicts detection in maritime traffic: Case studies on the effect of traffic complexity on ship collisions

2019 ◽  
Vol 234 (1) ◽  
pp. 209-222 ◽  
Author(s):  
Fulko van Westrenen ◽  
Michael Baldauf
Keyword(s):  
Near Miss ◽  
Traffic Density ◽  
Decision Making Process ◽  
High Complexity ◽  
Collision Risk ◽  
Maritime Traffic ◽  
Open Sea ◽  
Reliable Detection ◽  
Human Operators ◽  
Actual Geometry

In shipping, collision risk is a serious safety threat. Risk probability estimations used for policymaking are derived from traffic density statistics, largely ignoring the decision-making process on board. Conflict detection and resolution on board is done using rather rudimentary but effective mental-model-based techniques. In this article, the authors analyse traffic using the concept of complexity. The actual geometry of the ships involved in the conflict defines how well the crews on board can resolve the conflict. This geometry is transformed into a complexity value. A reliable detection and resolution of conflicts by human operators decreases in certain situations. A previous study has shown that when complexity reaches a threshold, the risk of a near miss increases significantly. In this study, three actual collisions at open sea are analysed. It will be shown that situations of high complexity, which decreases human reliability, can be predicted well in advance, allowing for a safe resolution. The technique also allows for alerting and a decision support for the crew.

Collision Risk Modeling in the Northern Pacific Airspace under Separation Reduction and Improvements in Navigational Performance

2006 ◽  
Vol 14 (4) ◽  
pp. 257-282 ◽  
Author(s):  
Theresa Brewer-Dougherty ◽  
Brian Colamosca ◽  
Christine Gerhardt-Falk ◽  
Dale Livingston ◽  
Lauren Martin ◽  
...  
Keyword(s):  
Risk Modeling ◽  
Collision Risk ◽  
Northern Pacific

Collision risk modeling of air traffic

2003 ◽  
Author(s):  
Henk Blom ◽  
Bert Bakker ◽  
Mariken Everdij ◽  
Marco van der Park
Keyword(s):  
Air Traffic ◽  
Risk Modeling ◽  
Collision Risk

scholarly journals Heterogeneity of COVID-19 Risk Perception: A Socio-Mathematical Model

2021 ◽  
Vol 18 (21) ◽  
pp. 11007
Author(s):  
Alfonso Gastelum-Strozzi ◽  
Claudia Infante-Castañeda ◽  
Juan Guillermo Figueroa-Perea ◽  
Ingris Peláez-Ballestas
Keyword(s):  
Risk Perception ◽  
Conceptual Model ◽  
Risk Model ◽  
Secondary Analysis ◽  
Principal Component ◽  
The Body ◽  
Risk Modeling ◽  
Sources Of Information ◽  
Perception Of Risk ◽  
Methodological Aspects

The perception of risk has been a key element in the experiences, containment and differential impact of the COVID-19 pandemic worldwide. The complexity of this phenomenon requires the interdisciplinary integration of theoretical and methodological aspects, as this integration informs the objective of developing a mathematical proposal based on a conceptual model located within the social theory of risk at the micro-social level. The mathematical risk model used here was developed from a secondary analysis of a study of 12,649 individuals on the experiences of the COVID-19 pandemic in a population in which the quantity and quality of the information made it possible to define a risk factor and its relationship to emotions and the sources of information used. Four sequential strategies were used to construct the model: choosing the variables for the questionnaire that theoretically corresponded to the conceptual model, constructing the risk vector and initial grouping of individuals by perception of risk, modeling by using principal component analysis and applying network methods. The theoretical model of risk, proposed and constructed through the analysis of groupings by quartiles and by networks in the studied population from a social and mathematical perspective, demonstrates the heterogeneity of risk perception as manifested by differences in perception by age, gender, expression of feelings and media consulted in a university community. The knowledge and methodology generated in these analyses contribute to the body of knowledge informing the response to future epidemiological contingencies.

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