Two natural soils from Bahrain were used in this study to investigate the feasibility of using Arabian oil residue as a means to stabilize collapsible saline soils. Since the presence of oil residue in soils can pose an environmental threat, the high oil retention capability of the stabilized soils is critical to its application. / The behavior of the stabilized soils has been experimentally investigated in the laboratory. This study has concentrated on the evaluation of the mechanical properties of the stabilized soils, the oil retention characteristics and its bonding mechanisms, and the leaching and migration behaviors of oil residue from the stabilized soils. / The geotechnical investigation results indicated that the addition of 4% oil residue, by weight, was sufficient to significantly enhance the strength performance of the tested soils. The geochemical tests showed that the bonds formed between the oil and the soil surfaces were predominantly Van der Waal's attraction, weak hydrogen bonding, and cation and water bridging. These bonds were found to be relatively weak but stable and insensitive to leaching forces. The geo-environmental results revealed good oil retention in these samples, with less than 3% of the oil residue by weight leached from the stabilized soils after 40 days of leaching in distilled water. / The migration of oil from the stabilized soils has also been theoretically evaluated. The theoretical study utilizes the model developed by Yong et al. (1992) with a few modifications made to accommodate this particular situation. The model was solved using an explicit finite difference method, Powell's optimization technique, and experimental results. The predicted oil migration profiles were found to be slightly over-estimated as compared to the experimental profiles.

Environmental awareness and legislative pressures have made manufacturers responsible for the take-back and end-of-life treatment of their products. Therefore, manufacturers are struggling to find ways to recover maximum value from returned products. This goal can best be achieved by promoting multiple reuse programs as reuse is one of the most effective ways to enhance a sustainable engineering economy. Since the essential goal of the reuse strategy is to reuse parts, the reliability of used parts becomes a core issue. Research indicates that reuse is technologically feasible, associated with a significant manufacturing cost saving, and it does not compromise product quality. However, it is not easy to be applied in reality. There are several uncertainties associated with reuse, the most common is the uncertainty of the product???s quality after use. A widespread implementation of the reuse strategy could be triggered, subject to the availability of reliable methods to assess the useful remaining life of parts. The evolution of such a methodology would play a pivotal role in making decisions on the supply chain process and the recovery value of returned products. Reliability assessment by life cycle data analysis is the basis of this research. The proposed methodology addresses the problem of reliability assessment of used parts by considering two important aspects. It performs statistical as well as condition monitoring data analysis for decision-making on reuse. The analysis is carried out in two stages. Firstly, a wellknown reliability assessment procedure, the Weibull analysis, is applied to analyse time-tofailure data to assess the overall reuse potential of components. In the second stage, the used capacity (actual life) of components is determined by analysing their operating history (condition monitoring data). The linear and nonlinear regression analysis, Kriging procedures and artificial neural networks (ANN) are employed in this stage. Finally, the Weibull analysis and ANNs are integrated to estimate the remaining useful life of components/assemblies of a product at the end of its first life cycle. The model was validated by using life cycle data from consumer products.

Environmental awareness and legislative pressures have made manufacturers responsible for the take-back and end-of-life treatment of their products. Therefore, manufacturers are struggling to find ways to recover maximum value from returned products. This goal can best be achieved by promoting multiple reuse programs as reuse is one of the most effective ways to enhance a sustainable engineering economy. Since the essential goal of the reuse strategy is to reuse parts, the reliability of used parts becomes a core issue. Research indicates that reuse is technologically feasible, associated with a significant manufacturing cost saving, and it does not compromise product quality. However, it is not easy to be applied in reality. There are several uncertainties associated with reuse, the most common is the uncertainty of the product???s quality after use. A widespread implementation of the reuse strategy could be triggered, subject to the availability of reliable methods to assess the useful remaining life of parts. The evolution of such a methodology would play a pivotal role in making decisions on the supply chain process and the recovery value of returned products. Reliability assessment by life cycle data analysis is the basis of this research. The proposed methodology addresses the problem of reliability assessment of used parts by considering two important aspects. It performs statistical as well as condition monitoring data analysis for decision-making on reuse. The analysis is carried out in two stages. Firstly, a wellknown reliability assessment procedure, the Weibull analysis, is applied to analyse time-tofailure data to assess the overall reuse potential of components. In the second stage, the used capacity (actual life) of components is determined by analysing their operating history (condition monitoring data). The linear and nonlinear regression analysis, Kriging procedures and artificial neural networks (ANN) are employed in this stage. Finally, the Weibull analysis and ANNs are integrated to estimate the remaining useful life of components/assemblies of a product at the end of its first life cycle. The model was validated by using life cycle data from consumer products.

Environmental awareness and legislative pressures have made manufacturers responsible for the take-back and end-of-life treatment of their products. Therefore, manufacturers are struggling to find ways to recover maximum value from returned products. This goal can best be achieved by promoting multiple reuse programs as reuse is one of the most effective ways to enhance a sustainable engineering economy. Since the essential goal of the reuse strategy is to reuse parts, the reliability of used parts becomes a core issue. Research indicates that reuse is technologically feasible, associated with a significant manufacturing cost saving, and it does not compromise product quality. However, it is not easy to be applied in reality. There are several uncertainties associated with reuse, the most common is the uncertainty of the product???s quality after use. A widespread implementation of the reuse strategy could be triggered, subject to the availability of reliable methods to assess the useful remaining life of parts. The evolution of such a methodology would play a pivotal role in making decisions on the supply chain process and the recovery value of returned products. Reliability assessment by life cycle data analysis is the basis of this research. The proposed methodology addresses the problem of reliability assessment of used parts by considering two important aspects. It performs statistical as well as condition monitoring data analysis for decision-making on reuse. The analysis is carried out in two stages. Firstly, a wellknown reliability assessment procedure, the Weibull analysis, is applied to analyse time-tofailure data to assess the overall reuse potential of components. In the second stage, the used capacity (actual life) of components is determined by analysing their operating history (condition monitoring data). The linear and nonlinear regression analysis, Kriging procedures and artificial neural networks (ANN) are employed in this stage. Finally, the Weibull analysis and ANNs are integrated to estimate the remaining useful life of components/assemblies of a product at the end of its first life cycle. The model was validated by using life cycle data from consumer products.

Thesis (M. Env. St.)--University of Adelaide, Mawson Graduate Centre for Environmental Studies, 1998. / Australian/New Zealand Standard Environmental management systems papers AS/NZS ISO 14001:1996, AS/NZS14004:1996 inserted. Includes bibliographical references (leaves 162-168).

Thesis (Ph.D.)--University of California, Berkeley, 2006. / (UMI)AAI3254111. Source: Dissertation Abstracts International, Volume: 68-02, Section: B, page: 0763. Adviser: Jillian F. Banfield.

Thesis (M.Sc. Earth and Ocean Sciences)--University of Waikato, 2008. / Title from PDF cover (viewed September 18, 2008) Includes bibliographical references (p. 121-123)

Thesis (Ph. D.)--Pennsylvania State University, 1994. / Vita. Includes bibliographical references (leaves 150-155).

Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6121. Adviser: Peter James Garlick. Includes bibliographical references (leaves 72-89) Available on microfilm from Pro Quest Information and Learning.

Submitted in partial fulfilment of the requirements for the Degree of Masters of Technology: Chemical Engineering, M.L. Sultan Technikon, 1999. / An environmental problem facing the textile industry is the coloured effluent from the dyeing of cellulosic fibres with reactive dyes. Reactive dye loss during dyeing operations is about 10 to 40 %, indicating the need to learn more about the fate of these dyes. Increasing environmental regulations are driving technical innovation to manage this problem. Good analytical techniques for the separation and detection of reactive dyes and their derivatives are necessary for monitoring dye-house effluent, as well as in the optimisation of dye synthesis, purification, formulation and application. / M