PapersFlow Research Brief
Marine and Coastal Research
Research Guide
What is Marine and Coastal Research?
Marine and Coastal Research is a field within ocean engineering that examines marine safety, industrial risk management, and accident prevention across sectors including shipbuilding, nuclear power plants, and aquaculture.
The field encompasses 29,488 works with a focus on fire resistance design, human error analysis, wireless sensor networks, and augmented reality in education. Studies address safety enhancements in marine and industrial settings such as shipbuilding and aquaculture production efficiency. Key contributions include trajectory prediction models and risk analysis for ice-covered waters.
Topic Hierarchy
Research Sub-Topics
Marine Accident Analysis
Researchers apply HFACS, fault tree analysis, and Bayesian networks to investigate collision, grounding, and fire causal factors. Studies use accident databases for trend analysis and safety indicators.
Human Error in Maritime Operations
This sub-topic examines cognitive error models, fatigue effects, training interventions, and automation impacts on human performance. Research includes simulator studies and bridge team resource management.
Ship Fire Risk Assessment
Studies develop probabilistic risk assessment models for engine room, cargo, and accommodation fires. Topics include fire spread modeling, detection systems, and suppression effectiveness.
Arctic Marine Safety
Research addresses ice navigation risks, collision with ice features, search-and-rescue challenges, and cold-water survival. Includes risk models for icebreaker operations and polar code compliance.
Maritime Wireless Sensor Networks
Engineers develop WSN applications for structural health monitoring, environmental sensing, and collision avoidance. Studies focus on network reliability, power management, and data fusion algorithms.
Why It Matters
Marine and Coastal Research supports accident prevention in high-risk marine operations, with applications in ship trajectory prediction to manage uncertainty, as shown in "Ship trajectory uncertainty prediction based on a Gaussian Process model" where Rong et al. (2019) developed models for safer navigation. In ice-covered waters, "Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters" by Zhang et al. (2018) identified human and organizational factors reducing collision risks for icebreakers. Root cause analyses like "A root cause analysis for Arctic Marine accidents from 1993 to 2011" by Kum and Şahin (2015) examined 218-cited incidents to inform safety protocols in Arctic shipping, directly impacting industries like shipbuilding and offshore operations.
Reading Guide
Where to Start
"Ship trajectory uncertainty prediction based on a Gaussian Process model" by Rong et al. (2019) serves as the starting point because it provides a clear, applied example of probabilistic modeling for marine safety relevant to ocean engineering fundamentals.
Key Papers Explained
"Ship trajectory uncertainty prediction based on a Gaussian Process model" (Rong et al., 2019; 264 citations) establishes uncertainty modeling foundations, which "Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters" (Zhang et al., 2018; 249 citations) extends to human factors and fault trees for ice navigation risks. "A root cause analysis for Arctic Marine accidents from 1993 to 2011" (Kum and Şahin, 2015; 218 citations) builds further by applying causal analysis to historical Arctic data, linking to trajectory and collision prevention.
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Current efforts center on risk models for extreme environments like Arctic shipping, as seen in analyses from Zhang et al. (2018) and Kum and Şahin (2015), with no recent preprints or news indicating shifts in the past 6-12 months.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | A MODIFIED NINHYDRIN REAGENT FOR THE PHOTOMETRIC DETERMINATION... | 1954 | Journal of Biological ... | 3.0K | ✓ |
| 2 | Effects of Varying the Vehicle for OsO4 in Tissue Fixation | 1957 | The Journal of Cell Bi... | 1.1K | ✓ |
| 3 | A Study on Information Extraction of Water Body with the Modif... | 2005 | National Remote Sensin... | 711 | ✓ |
| 4 | Development of metaverse for intelligent healthcare | 2022 | Nature Machine Intelli... | 383 | ✓ |
| 5 | The Variability of Transfusion Practice in Coronary Artery Byp... | 1991 | JAMA | 290 | ✕ |
| 6 | Ship trajectory uncertainty prediction based on a Gaussian Pro... | 2019 | Ocean Engineering | 264 | ✕ |
| 7 | Use of HFACS and fault tree model for collision risk factors a... | 2018 | Safety Science | 249 | ✓ |
| 8 | Narrative of the surveying voyages of His Majesty's ships Adve... | 1839 | H. Colburn eBooks | 232 | ✓ |
| 9 | Patterns and Structures of the Currents in Bohai, Huanghai and... | 1994 | — | 221 | ✕ |
| 10 | A root cause analysis for Arctic Marine accidents from 1993 to... | 2015 | Safety Science | 218 | ✕ |
Frequently Asked Questions
What methods are used for water body extraction in coastal research?
"A Study on Information Extraction of Water Body with the Modified Normalized Difference Water Index （MNDWI）" by Xu (2005) introduces the MNDWI, which modifies the NDWI by using middle-infrared bands to improve accuracy in extracting water bodies from remote sensing images across various water types. This index outperforms the original NDWI by reducing interference from built-up land shadows.
How is ship trajectory uncertainty modeled in marine safety?
"Ship trajectory uncertainty prediction based on a Gaussian Process model" by Rong et al. (2019) applies Gaussian Process models to predict ship trajectory uncertainties, aiding collision avoidance in ocean engineering. The approach accounts for environmental and operational variabilities to enhance maritime navigation safety.
What frameworks analyze collision risks for icebreakers?
"Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters" by Zhang et al. (2018) combines HFACS for human factors and fault tree analysis to quantify collision risks during icebreaker operations. This identifies key risk contributors like procedural failures in ice-covered environments.
What are common root causes of Arctic marine accidents?
"A root cause analysis for Arctic Marine accidents from 1993 to 2011" by Kum and Şahin (2015) applies root cause analysis to accidents in Arctic waters, highlighting human error and equipment failure as primary factors. The study covers incidents from 1993 to 2011 to guide preventive measures.
How many works exist in Marine and Coastal Research?
The field includes 29,488 works focused on marine safety and industrial risk management. Growth rate over the past 5 years is not available in the data.
Open Research Questions
- ? How can Gaussian Process models be extended to real-time ship trajectory predictions under dynamic weather conditions, building on Rong et al. (2019)?
- ? What integrations of HFACS and fault trees best mitigate emerging collision risks for autonomous icebreakers in changing ice conditions?
- ? Which unaddressed root causes from 1993-2011 Arctic accidents persist in modern operations?
- ? How do MNDWI improvements apply to hyperspectral imagery for coastal monitoring?
- ? What human error patterns in shipbuilding and aquaculture require updated wireless sensor network interventions?
Recent Trends
The field maintains 29,488 works with no specified 5-year growth rate; highly cited papers from 2015-2019, such as "Ship trajectory uncertainty prediction based on a Gaussian Process model" (Rong et al., 2019; 264 citations) and "Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters" (Zhang et al., 2018; 249 citations), reflect sustained focus on probabilistic risk modeling and human factors in marine safety.
No recent preprints or news coverage in the last 6-12 months signals ongoing reliance on established methods.
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