Asset integrity case development for normally unattended offshore installations: Bayesian network modelling

This research proposes the initial stages of the application of Bayesian Networks in conducting quantitative risk assessment of the integrity of an offshore system. The main focus is the construction of a Bayesian network model that demonstrates the interactions of multiple offshore safety critical elements to analyse asset integrity. A NUI (Normally Unattended Installation) - Integrity Case will enable the user to determine the impact of deficiencies in asset integrity and demonstrate that integrity is being managed to ensure safe operations in situations whereby physical human to machine interaction is not occurring. The Integrity Case can be said to be dynamic as it shall be continually updated for an installation as the Quantitative Risk Analysis (QRA) data is recorded. This allows for the integrity of the various systems and components of an offshore installation to be continually monitored. The Bayesian network allows cause-effect relationships to be modelled through clear graphical representation. The model accommodates for continual updating of failure data

Launching Systems for Unmanned Vehicles Onboard Naval Vessels

Unmanned vehicles can replace humans in humanitarian and military operations, requiring ships to have innovative capabilities for launching and recovering them. However, the variety of unmanned vehicles makes it difficult to create standardized interfaces, and their development often outpaces the lifespan of ships. Integrating unmanned vehicles on naval vessels is complex due to technical requirements and limited space. Engineers must consider cost efficiency, flexibility, and operational impact. This paper presents technologies and solutions for launching unmanned aerial vehicles (UAVs) from front-line ships, with their pros and cons. To this end, Fuzzy Analytic Hierarchy Process (F AHP) has been here employed to rank the main options. Among them, the electromagnetic catapult is the most promising option for launching UAVs from front-line naval ships and it is worthy of further development. Besides, despite having limited capacity, bungee cords can be used until the technology of the electromagnetic catapult is tested and ready to take the place of the former

Groundwater potential mapping using GIS and remote sensing with multi-criteria decision-making in Shinile sub-basin, eastern Ethiopia

The main challenge for water resources development as well as food security in arid and semi-arid regions of Ethiopia is the hydroclimatic variability. Groundwater resources are largely the main sources of water supply in such regions, alleviating the pressure of hydroclimatic variability on water resources. The present study delineated the potential groundwater zones in the Shinile sub-basin by using geospatial techniques. The criteria used were: geology, geomorphology, slope, soil, lineament density, drainage density, land use land cover, topographic wetness index, topographic roughness index, and rainfall. The relative weights were given by the analytic hierarchy process. A validation was done using the area under the curve (AUC=0.941) of the receiver operating curve (ROC) from borehole data. The study region was partitioned to low, moderate, and high potential groundwater zones having respectively 1.5%, 43%, and 55% of the total area. The high potential areas are concentrated in the central part where alluvial and lacustrine sediment is the dominant geologic unit. The validation results suggest that the geospatial identification of groundwater potential zones effectively performed well in the study area. This study is very important for water management experts as well as for stakeholders and policymakers in the study region

Deriving consistent pairwise comparison matrices in decision making methodologies based on linear programming method

International audiencePairwise comparison matrix (PCM) with crisp or fuzzy elements should satisfy consistency requirements when it is used in analytic hierarchy process (AHP) or in fuzzy AHP methodologies. An algorithm has been presented to obtain a new modified consistent PCM for the corresponding inconsistent original one. The algorithm sets a linear programming problem based on all of the constraints. To obtain the optimum eigenvector of the middle value of the new PCM, segment tree is used to gradually approach the greatest lower bound of distance with the original PCM. As to obtain the lower value and upper value of the new PCM, a theory is proposed to reduce adding uncertainty factors and could maximum maintain the similarity with original PCM. The experiments for crisp elements show that the proposed approach can preserve more the original information than references. The experiments for fuzzy elements show that our method can effectively reduce inconsistency and obtain suitable modified fuzzy PCMs

Bayesian network modelling of an offshore electrical generation system for applications within an asset integrity case for normally unattended offshore installations

This article proposes the initial stages of the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore system. The main focus is the construction of a Bayesian network model that demonstrates the interactions of multiple offshore safety critical elements to analyse asset integrity. The majority of the data required to complete the Bayesian network was gathered from various databases and past risk assessment experiments and projects. However, where data were incomplete or non-existent, expert judgement was applied through pairwise comparison, analytical hierarchy process and a symmetric method to fill these data gaps and to complete larger conditional probability tables. A normally unattended installation–Integrity Case will enable the user to determine the impact of deficiencies in asset integrity and demonstrate that integrity is being managed to ensure safe operations in situations whereby physical human-to-machine interaction is not occurring. The Integrity Case can be said to be dynamic as it shall be continually updated for an installation as the quantitative risk analysis data are recorded. This allows for the integrity of the various systems and components of an offshore installation to be continually monitored. The Bayesian network allows cause and effect relationships to be modelled through clear graphical representation. The model accommodates for continual updating of failure data

Asset integrity case development for normally unattended offshore installations

This thesis proposes the initial stages of the development of a NUI – Asset Integrity Case (Normally Unattended Installation). An NUI – Asset Integrity Case will enable the user to determine the impact of deficiencies in asset integrity and demonstrate that integrity is being managed. A key driver for improved asset integrity monitoring is centred on the level of accurate reporting of incidents. This stems from incidents to key offshore systems and areas. For example, gas turbine driven generators where 22% of fuel gas leaks were undetected with 60% of these 22% having been found to have ignited. Accordingly, there is a need for dynamic risk assessment and improved asset integrity monitoring. The immediate objective of this research is to investigate how a dynamic risk model can be developed for an offshore system. Subsequently, two dynamic risk assessment models were developed for an offshore gas turbine driven electrical power generation system. Bayesian Networks provided the base theory and algorithms to develop the models. The first model focuses on the consequences of one component failure. While the second model focuses on the consequences of a fuel gas release with escalated fire and explosion, based upon several initiating failures. This research also provides a Multiple Attribute Decision Analysis (MADA) to determine the most suitable Wireless Sensor Network (WSN) configuration for asset integrity monitoring. The WSN is applied to the same gas turbine system as in the dynamic risk assessment models. In the future, this work can be expanded to other systems and industries by applying the developed Asset Integrity Case framework and methodology. The framework outlines the steps to develop a dynamic risk assessment model along with MADA for the most suitable remote sensing and detection methods