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Web and knowledge-based decision support system for measurement uncertainty evaluation
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityIn metrology, measurement uncertainty is understood as a range in which the true value of the measurement is likely to fall in. The recent years have seen a rapid development in evaluation of measurement uncertainty. ISO Guide to the Expression of Uncertainty in Measurement (GUM 1995) is the primary guiding document for measurement uncertainty. More recently, the Supplement 1 to the "Guide to the expression of uncertainty in measurement" – Propagation of distributions using a Monte Carlo method (GUM SP1) was published in November 2008. A number of software tools for measurement uncertainty have been developed and made available based on these two documents. The current software tools are mainly desktop applications utilising numeric computation with limited mathematical model handling capacity. A novel and generic web-based application, web-based Knowledge-Based Decision Support System (KB-DSS), has been proposed and developed in this research for measurement uncertainty evaluation. A Model-View-Controller architecture pattern is used for the proposed system. Under this general architecture, a web-based KB-DSS is developed based on an integration of the Expert System and Decision Support System approach. In the proposed uncertainty evaluation system, three knowledge bases as sub-systems are developed to implement the evaluation for measurement uncertainty. The first sub-system, the Measurement Modelling Knowledge Base (MMKB), assists the user in establishing the appropriate mathematical model for the measurand, a critical process for uncertainty evaluation. The second sub-system, GUM Framework Knowledge Base, carries out the uncertainty evaluation process based on the GUM Uncertainty Framework using symbolic computation, whilst the third sub-system, GUM SP1 MCM Framework Knowledge Base, conducts the uncertainty calculation according to the GUM SP1 Framework numerically based on Monte Carlo Method. The design and implementation of the proposed system and sub-systems are discussed in the thesis, supported by elaboration of the implementation steps and examples. Discussions and justifications on the technologies and approaches used for the sub-systems and their components are also presented. These include Drools, Oracle database, Java, JSP, Java Transfer Object, AJAX and Matlab. The proposed web-based KB-DSS has been evaluated through case studies and the performance of the system has been validated by the example results. As an
established methodology and practical tool, the research will make valuable contributions to the field of measurement uncertainty evaluation.Brunel Universit
Mapping oil spill human health risk in rivers state, Niger Delta, Nigeria
Oil pipelines play a significant role in crude oil transportation and bring danger close to communities along their paths. Pipeline accidents happen every now and then due to factors ranging from operational cause to third party damage. In the Niger Delta pipeline system, interdiction is common; therefore, every length and breadth of land covered by a pipeline is vulnerable to oil pollution, which can pose a threat to land use. Weak enforcement of rights of way led to encroachment by farmers and human dwellings, thereby bringing people in close proximity to pipelines. Considering the impact exposure can have on human health, a method was developed for identifying vulnerable communities within a designated potential pipeline impact radius, and generic assessment criteria developed for assessing land use exposure.
The GIS based model combines four weighted criteria layers, i.e. land cover, population, river and pipeline buffers in a multi-criteria decision making with analytical hierarchy process to develop an automated mapping tool designed to perform three distinct operations: firstly, to delineate pipeline hazard areas; secondly, establish potential pipeline impact radius; and thirdly, identify vulnerable communities in high consequence areas. The model was tested for sensitivity and found to be sensitive to river criterion; transferability on the other hand is limited to similar criteria variables.
To understand spatial distribution of oil spills, 443 oil spill incidents were examined and found to tend towards cluster distribution. Meanwhile, the main causes of spills include production error (34.8%) and interdiction (31.6%); interdiction alone discharged about 61.4% of crude oil. This brings to light the significance of oil pipeline spills and the tendency to increase the risk of exposure. The generic assessment criteria were developed for three land uses using CLEA v 1.06 for aromatic (EC5-EC44) and aliphatic (EC5-EC44) fractions. The use of the model and screening criteria are embedded in a framework designed to stimulate public participation in pipeline management and pipeline hazard mitigation, which policy makers and regulators in the oil industry can find useful in pipeline hazard management and exposure mitigation
Mapping oil spill human health risk in rivers state, Niger Delta, Nigeria
Oil pipelines play a significant role in crude oil transportation and bring danger close to communities along their paths. Pipeline accidents happen every now and then due to factors ranging from operational cause to third party damage. In the Niger Delta pipeline system, interdiction is common; therefore, every length and breadth of land covered by a pipeline is vulnerable to oil pollution, which can pose a threat to land use. Weak enforcement of rights of way led to encroachment by farmers and human dwellings, thereby bringing people in close proximity to pipelines. Considering the impact exposure can have on human health, a method was developed for identifying vulnerable communities within a designated potential pipeline impact radius, and generic assessment criteria developed for assessing land use exposure.
The GIS based model combines four weighted criteria layers, i.e. land cover, population, river and pipeline buffers in a multi-criteria decision making with analytical hierarchy process to develop an automated mapping tool designed to perform three distinct operations: firstly, to delineate pipeline hazard areas; secondly, establish potential pipeline impact radius; and thirdly, identify vulnerable communities in high consequence areas. The model was tested for sensitivity and found to be sensitive to river criterion; transferability on the other hand is limited to similar criteria variables.
To understand spatial distribution of oil spills, 443 oil spill incidents were examined and found to tend towards cluster distribution. Meanwhile, the main causes of spills include production error (34.8%) and interdiction (31.6%); interdiction alone discharged about 61.4% of crude oil. This brings to light the significance of oil pipeline spills and the tendency to increase the risk of exposure. The generic assessment criteria were developed for three land uses using CLEA v 1.06 for aromatic (EC5-EC44) and aliphatic (EC5-EC44) fractions. The use of the model and screening criteria are embedded in a framework designed to stimulate public participation in pipeline management and pipeline hazard mitigation, which policy makers and regulators in the oil industry can find useful in pipeline hazard management and exposure mitigation