Related Experiment Video
Updated: Mar 16, 2026
05:37
An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
2.7K
Advanced uncertainty modelling for container port risk analysis
Hani Alyami1, Zaili Yang1, Ramin Riahi1
1Liverpool Logistics Offshore and Marine (LOOM) Research Institute, Liverpool John Moores University, Liverpool, UK.
Accident; Analysis and Prevention
|August 18, 2016
Summary
This study introduces a new Failure Mode and Effects Analysis (FMEA) method for Container Terminal Operational Systems (CTOS). It enhances safety performance assessment by integrating Fuzzy Rule-Based Bayesian Networks (FRBN) and Evidential Reasoning (ER) for dynamic risk analysis.
Area of Science:
- Maritime Safety
- Risk Management
- Systems Engineering
Background:
- Globalization increases container traffic in seaports, heightening the need for robust safety measures.
- Effective Container Terminal Operational System (CTOS) safety is crucial for economic prosperity, operational efficiency, and personnel security.
- Traditional risk analysis methods struggle with the dynamic nature of port operations.
Purpose of the Study:
- To propose a novel Failure Mode and Effects Analysis (FMEA) approach for assessing CTOS safety performance.
- To develop a dynamic risk assessment model adaptable to changing port conditions.
- To introduce a sensitivity analysis method for ranking hazardous events based on local and global risk impact.
Main Methods:
- Integration of Fuzzy Rule-Based Bayesian Network (FRBN) for detailed failure information.
- Application of Evidential Reasoning (ER) for aggregating hazardous event (HE) risk estimates.
- Development of a dynamic model to handle evolving operational scenarios in ports.
- Implementation of a novel sensitivity analysis for ranking HEs by local estimation and global Risk Influence (RI).
Main Results:
- The proposed FRBN-ER method provides a flexible framework for estimating risks of individual hazardous events.
- The Evidential Reasoning (ER) component enables systematic aggregation of HE risks for decision support.
- The dynamic model effectively addresses the complexities of real-time port operations.
- A new sensitivity analysis method successfully ranks hazardous events by their local and global impact on port safety.
Conclusions:
- The novel FRBN-ER approach offers a dynamic and systematic method for CTOS safety performance assessment.
- This approach enhances risk management by providing real-time risk ranking and sensitivity analysis.
- The methodology is generalizable to various safety and reliability engineering applications requiring dynamic risk assessment.
Related Concept Videos
00:59Uncertainty: Overview
1.8K
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
1.8K
00:59Propagation of Uncertainty from Random Error
2.1K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
2.1K
01:14Multicompartment Models: Overview
683
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
683
01:17Design Example: Analyzing Capacity Contours for Flood Risk Assessment
348
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
348
00:54Uncertainty: Confidence Intervals
11.9K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
11.9K
01:21Mechanistic Models: Overview of Compartment Models
461
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
461