At no point in history have we demanded so much from our agricultural land whilst simultaneously leaving so little room for management error. Of the many possible environmental impacts from agriculture, soil and water salinisation has some of the most long-lived and deleterious effects. Despite its importance, however, land managers are often unable to make informed decisions of how to manage the risk of salinisation due to a lack of data. Furthermore, there remains no universally agreed method for salinity risk mapping. This thesis addresses these issues by investigating new methods for producing high-resolution predictions of soil salinity, soil physical properties and groundwater depth using a variety of traditional and emerging ancillary data sources. The results show that the methodologies produce accurate predictions yielding natural resource information at a scale and resolution not previously possible. Further to this, a new methodology using fuzzy logic is developed that exploits this information to produce high-resolution salinity risk maps designed to aid both agricultural and natural resource management decisions. The methodology developed represents a new and effective way of presenting salinity risk and has numerous advantages over conventional risk models. The incorporation of fuzzy logic provides a meaningful continuum of salinity risk and allows for the incorporation of uncertainty. The method also allows salinity risk to be calculated relative to any vegetation community and shows where the risk is coming from (root-zone or groundwater) allowing more appropriate management decisions to be made. The development of this methodology takes us a step closer to closing what some have called our greatest gap in agricultural knowledge. That is, our ability to manage the salinity risk at the subcatchment scale.

At no point in history have we demanded so much from our agricultural land whilst simultaneously leaving so little room for management error. Of the many possible environmental impacts from agriculture, soil and water salinisation has some of the most long-lived and deleterious effects. Despite its importance, however, land managers are often unable to make informed decisions of how to manage the risk of salinisation due to a lack of data. Furthermore, there remains no universally agreed method for salinity risk mapping. This thesis addresses these issues by investigating new methods for producing high-resolution predictions of soil salinity, soil physical properties and groundwater depth using a variety of traditional and emerging ancillary data sources. The results show that the methodologies produce accurate predictions yielding natural resource information at a scale and resolution not previously possible. Further to this, a new methodology using fuzzy logic is developed that exploits this information to produce high-resolution salinity risk maps designed to aid both agricultural and natural resource management decisions. The methodology developed represents a new and effective way of presenting salinity risk and has numerous advantages over conventional risk models. The incorporation of fuzzy logic provides a meaningful continuum of salinity risk and allows for the incorporation of uncertainty. The method also allows salinity risk to be calculated relative to any vegetation community and shows where the risk is coming from (root-zone or groundwater) allowing more appropriate management decisions to be made. The development of this methodology takes us a step closer to closing what some have called our greatest gap in agricultural knowledge. That is, our ability to manage the salinity risk at the subcatchment scale.

At no point in history have we demanded so much from our agricultural land whilst simultaneously leaving so little room for management error. Of the many possible environmental impacts from agriculture, soil and water salinisation has some of the most long-lived and deleterious effects. Despite its importance, however, land managers are often unable to make informed decisions of how to manage the risk of salinisation due to a lack of data. Furthermore, there remains no universally agreed method for salinity risk mapping. This thesis addresses these issues by investigating new methods for producing high-resolution predictions of soil salinity, soil physical properties and groundwater depth using a variety of traditional and emerging ancillary data sources. The results show that the methodologies produce accurate predictions yielding natural resource information at a scale and resolution not previously possible. Further to this, a new methodology using fuzzy logic is developed that exploits this information to produce high-resolution salinity risk maps designed to aid both agricultural and natural resource management decisions. The methodology developed represents a new and effective way of presenting salinity risk and has numerous advantages over conventional risk models. The incorporation of fuzzy logic provides a meaningful continuum of salinity risk and allows for the incorporation of uncertainty. The method also allows salinity risk to be calculated relative to any vegetation community and shows where the risk is coming from (root-zone or groundwater) allowing more appropriate management decisions to be made. The development of this methodology takes us a step closer to closing what some have called our greatest gap in agricultural knowledge. That is, our ability to manage the salinity risk at the subcatchment scale.

Doctor of Philosophy / This research aimed to develop new cooling methods to replace, or at least minimise, the use of currently used grinding coolants which are known to be harmful to the environment. The methods used involved the application of a cold air and vegetable oil mist mixture (CAOM), and the use of liquid nitrogen as cooling media. Allied research focused on the development of a segmented grinding wheel equipped with a coolant chamber. The feasibility of a grinding system using CAOM was assessed on the surface grinding of plain carbon steel 1045. It was found that at low material removal rates, ground surfaces were obtained with a quality comparable to that from grinding with a conventional coolant in association with a reduction of grinding forces. There was no significant difference in the subsurface hardness of the components using CAOM, although the latter method showed a stronger dependence of surface residual stresses on the depth of cut due to the limit in cooling capacity of CAOM. The effects of using liquid nitrogen as a cooling medium on the microstructure of quenchable steel were explored. It was found that a martensite layer was induced on the ground surface. The microstructure featured a dispersion of very fine carbides within the martensite lattice, resulting in a remarkable increase in hardness and high compressive residual stresses within the layer. The topography of the ground surfaces indicated that the material was predominantly removed by brittle fracture. Furthermore surface oxidisation was suppressed. In the interest of coolant minimisation, a segmented wheel equipped with a pressurized coolant chamber was developed. A higher quality ground surface was obtained in conjunction with a coolant saving of up to 70%. In addition, the adhesion of ground chips on the wheel surface largely disappeared. Furthermore, surface tensile residual stresses caused by thermal deformation were minimised. The mechanism of coolant disintegration to form mists using this type of wheel system was studied. The Weber theory for Newtonian jet instability was applied to quantitatively determine the contribution of coolant flow rate to mist and ligament modes. A semi-analytical model was then developed to predict the mist flow rate by taking into account both grinding parameters and coolant properties. The model prediction was in agreement with experimental measurements. Based on the principles of fluid motion and the mechanisms of spin-off and splash, analytical models for both conventional and segmented wheels were established to provide a physical understanding of the mechanisms of coolant penetration into the grinding zone. Coolant minimisation was evident using the segmented wheel where the coolant pumping power into the grinding zone increased with wheel speed, but for the conventional wheel it decreased. A quantitative analysis was developed that accounted for the coolant properties and system design characteristics governing the penetration mechanism revealed by the theory established above. In conjunction with the mist formation analysis, the developed model offers a practical guideline for the optimal use of grinding coolants in achieving a balance between the demands of productivity and care for the environment.

Thesis (Ph.D.)--RAND Graduate School, 2005. / Includes bibliographical references. Also available online.

Thesis (Ph.D.)--University of Western Australia, 2007.

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 114-123). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 114-123). Also available on the Internet.

Thesis (Ph. D.)--Colorado State University, 2004. / Includes bibliographical references.

Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2010. / Committee Chair: Mark Costello; Committee Member: Eric Johnson; Committee Member: Frank Fresconi; Committee Member: Olivier Bauchau; Committee Member: Peter Plostins. Part of the SMARTech Electronic Thesis and Dissertation Collection.