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Bibliography: p. 343-355. / xxiv, 355 p. : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Based on a comprehensive review of past techniques and power combining structures, a class of spatial power combiners compatible with the requirements of millimetre wave operation are identified. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1999?

186, iv leaves : ill. ; 26 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Physics, 1972

xiv, 200 leaves : ill., appendices / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.1971) from the Dept. of Organic Chemistry, University of Adelaide

Title page, table of contents and abstract only. The complete thesis in print form is available from the University of Adelaide Library. / One of the main limitations to current wave data assimilation systems is the lack of an accurate representation of the structure of the background errors. For example, the current operational wave data assimilation system at the Australian Bureau of Meteorology (BoM) prescribes globally uniform background error correlations of Gaussian shape with a length scale of 300 km and the error variance of both the background and observation errors is defined to be 0.25 m². This thesis describes an investigation into the determination of the background errors in a global wave model. There are two methods that are commonly used to determine background errors: the observational method and the 'NMC method'. The observational method is the main tool used in this thesis, although the 'NMC method' is considered also. The observational method considers correlations of the differences between observations and the background, in this case, the modelled Significant Wave Height (SWH) field. The observations used are satellite altimter estimates of SWH. Before applying the method, the effect of the irregular satellite sampling pattern is examined. This is achieved by constructing a set of anomaly correlations from modelled wave fields. The modelled wave fields are then sampled at the locations of the altimeter observations and the anomaly correlations are recalculated from the simulated altimeter data. The results are compared to the original anomaly correlations. It is found that in general, the altimeter sampling pattern underpredicts the spatial scale of the anomaly correlation. Observations of SWH from the ERS-2 altimeter are used in this thesis. To ensure that the observations used are of the highest quality possible, a validation of the European Remote Sensing Satellite 2 (ERS-2) SWH observations is performed. The altimeter data are compared to waverider buoy observations over a time period of approximately 4.5 years. With a set of 2823 co-located SWH estimates, it is found that in general, the altimeter overestimates low SWH and underestimates high SWH. A two-branched linear correction to the altimeter data is found, which reduces the overall rms error in SWH to approximately 0.2 m. Results from the previous sections are then used to calculate the background error correlations. Specifically, correlations of the differences between modelled SWH and the bias-corrected ERS-2 data are calculated. The irregular sampling pattern of the altimeter is accounted for by adjusting the correlation length scales according to latitude and the calculated length scale. The results show that the length scale of the background errors varies significantly over the globe, with the largest scales at low latitudes and shortest scales at high latitudes. Very little seasonal or year-to-year variability is detected. Conversely, the magnitude of the background error variance is found to have considerable seasonal and year-to-year variability. By separating the altimeter ground tracks into ascending and descending tracks, it is possible to examine, to a limited extent, whether any anisotropy exists in the background errors. Some of the areas on the globe that exhibit the most anisotropy are the Great Australian Bight and the North Atlantic Ocean. The background error correlations are also briefly examined via the 'NMC method', i.e., by considering differences between SWH forecasts of different ranges valid at the same time. It is found that the global distribution of the length scale of the error correlation is similar to that found using the observational method. It is also shown that the size of the correlation length scale increases as the forecast period increases. The new background error structure that has been developed is incorporated into a data assimilation system and evaluated over two month-long time periods. Compared to the current operational system at the BoM, it is found that this new structure improves the skill of the wave model by approximately 10%, with considerable geographical variability in the amount of improvement. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1113813 / Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2004

Title page, table of contents and abstract only. The complete thesis in print form is available from the University of Adelaide Library. / One of the main limitations to current wave data assimilation systems is the lack of an accurate representation of the structure of the background errors. For example, the current operational wave data assimilation system at the Australian Bureau of Meteorology (BoM) prescribes globally uniform background error correlations of Gaussian shape with a length scale of 300 km and the error variance of both the background and observation errors is defined to be 0.25 m². This thesis describes an investigation into the determination of the background errors in a global wave model. There are two methods that are commonly used to determine background errors: the observational method and the 'NMC method'. The observational method is the main tool used in this thesis, although the 'NMC method' is considered also. The observational method considers correlations of the differences between observations and the background, in this case, the modelled Significant Wave Height (SWH) field. The observations used are satellite altimter estimates of SWH. Before applying the method, the effect of the irregular satellite sampling pattern is examined. This is achieved by constructing a set of anomaly correlations from modelled wave fields. The modelled wave fields are then sampled at the locations of the altimeter observations and the anomaly correlations are recalculated from the simulated altimeter data. The results are compared to the original anomaly correlations. It is found that in general, the altimeter sampling pattern underpredicts the spatial scale of the anomaly correlation. Observations of SWH from the ERS-2 altimeter are used in this thesis. To ensure that the observations used are of the highest quality possible, a validation of the European Remote Sensing Satellite 2 (ERS-2) SWH observations is performed. The altimeter data are compared to waverider buoy observations over a time period of approximately 4.5 years. With a set of 2823 co-located SWH estimates, it is found that in general, the altimeter overestimates low SWH and underestimates high SWH. A two-branched linear correction to the altimeter data is found, which reduces the overall rms error in SWH to approximately 0.2 m. Results from the previous sections are then used to calculate the background error correlations. Specifically, correlations of the differences between modelled SWH and the bias-corrected ERS-2 data are calculated. The irregular sampling pattern of the altimeter is accounted for by adjusting the correlation length scales according to latitude and the calculated length scale. The results show that the length scale of the background errors varies significantly over the globe, with the largest scales at low latitudes and shortest scales at high latitudes. Very little seasonal or year-to-year variability is detected. Conversely, the magnitude of the background error variance is found to have considerable seasonal and year-to-year variability. By separating the altimeter ground tracks into ascending and descending tracks, it is possible to examine, to a limited extent, whether any anisotropy exists in the background errors. Some of the areas on the globe that exhibit the most anisotropy are the Great Australian Bight and the North Atlantic Ocean. The background error correlations are also briefly examined via the 'NMC method', i.e., by considering differences between SWH forecasts of different ranges valid at the same time. It is found that the global distribution of the length scale of the error correlation is similar to that found using the observational method. It is also shown that the size of the correlation length scale increases as the forecast period increases. The new background error structure that has been developed is incorporated into a data assimilation system and evaluated over two month-long time periods. Compared to the current operational system at the BoM, it is found that this new structure improves the skill of the wave model by approximately 10%, with considerable geographical variability in the amount of improvement. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1113813 / Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2004

Research Doctorate - Doctor of Philosophy (PhD) / The impact of a small particle with a wear surface can lead to very high strain-rates in the material being encountered. Often predictive erosion models are based on material property parameters taken from quasistatic test conditions. However, the material properties of the impacted wear surface can change dramatically with strain and strain-rate, leaving some doubt as to the validity of an erosion model based on quasistatic parameter values. In this study, a new stress-wave monitoring process is developed for the study of material characteristics and erosion phenomena, at strain-rates approaching 10e6s-1. For this study a newly designed piezo-electric transducer was used to monitor the stress-waves produced by small erosive particle impact events. A computational study was also conducted to aid in the transducer design and location distance from the impact source by considering the effects caused by spatial averaging. Spatial averaging affects the recorded stress-wave signal and is caused by the curvature of the stress-wave as the wave passes through the flat piezo-electric sensing element. This study was conducted using a computational and experimental approach. The joint study allowed significant knowledge to be gained for the study of elasto-plastic impact and stress-wave motion. Finite element analysis (FEA) was used to model the experimental system in detail. The stress-waves produced by the experimental process were directly compared to the FEA model. Once the FEA model was validated, detailed information from the impact event at the surface could be obtained from the model, which would otherwise be difficult if not impossible to obtain experimentally. The issues of wave dispersion have been an underlying problem in the correct interpretation of stress-wave phenomena for many years. The impact of the wear surface causes stress-waves with many frequency components, each component propagating through the wear material at distinct wave velocities. Wave dispersion causes the initial stress-wave pulse to be dispersed into many waveforms. In this study the longitudinal stress-wave was the main waveform studied. FEA simulations were conducted for a purely elastic impact and an impact causing significant plastic deformation of the surface. A comparison between these waveforms showed that in the case of impacts causing plastic deformation, the initial part of the stress-wave, measured from the time of arrival to the first peak, corresponded to the elastic stress component of the impact event at the surface. The characterisation of the waveform in regards to elastic and plastic stress components at the surface was significant for validating model parameters of the Johnson-Cook material model. The stress-wave monitoring process was applied in the first instance to erosive particle impacts to AISI 1020 steel at impact velocities up to 104m/s. A specially designed erosion apparatus, fitted with a modified double disc system was used to impact the 10mm thick steel plate. The piezo-electric transducer was firmly clamped to the rear surface, directly behind the point of impact to obtain the stress-wave signals produced by impacts of 0.4mm zirconia spheres. The study showed that the contact interface of the wear material and the piezo-electric transducer could cause a phase change and amplitude reduction of the stress-wave transmitted to the transducer at wave frequencies above 0.9MHz. The results showed that the most likely cause for the phase shift to occur was the restriction of tensile stresses across the contact interface. For wave frequencies below 0.9MHz, no phase shift or amplitude reduction was apparent in the experimental stress-wave recordings. The combined experimental / FEA study was shown to be able to validate the strain-rate parameter of the Johnson-Cook model. The parameters, which could not be validated by the stress-wave monitoring process, were the parameters relating to plastic deformation of the surface, which were the strain-hardening terms of the Johnson-Cook model. These terms were later validated by studying the extent of plastic deformation at the surface, which occurred in the form of impact craters. By comparing the predicted impact crater depths from the FEA model with the experimental results, the strain-hardening parameters of the Johnson-Cook model could be validated. The robustness of the stress-wave monitoring process was proven for the impact study of ultra high molecular weight polyethylene (UHMWPE) and vinyl ester resin (VER). Unlike AISI 1020 steel, little is know about the high strain-rate response of these polymers. Initial estimates of material property parameters were made by applying computational curve fitting techniques to the stress-strain curves of similar polymers, which were from published results obtained from split Hopkinson’s pressure bar method. The impact and stress-wave study showed UHMWPE and VER to be highly sensitive to strain-rate effects. The main effect was a substantial increase in hardness with increasing strain-rate and it was considered that the hydrostatic stress component contributed to the strain hardening of the polymers. The stress-wave monitoring and FEA computational techniques developed in this study were implemented in the development of an improved erosion model. The model form is similar to that of the well-known Ratner-Lancaster model. The Ratner-Lancaster model assumes wear rate to be proportional to the inverse of deformation energy, where deformation energy is approximated as the product of the ultimate stress and ultimate strain. The improved Ratner-Lancaster model uses the Johnson-Cook model to obtain the von-Mises stress as a function of strain. The area integral of the stress-strain curve is used to derive the deformation energy capacity of the material in the deformed zone close to the surface. The model accounts for strain, strain-rate and thermal effects and is therefore more soundly based on material deformation characteristics valid for erosion events than the Ratner-Lancaster model assumptions. The model developed in this work was applied to the erosion study of 1020 steel, UHMWPE and VER, with good correlation being obtained between experimental erosion rates and model predictions.

Thesis (Ph. D.)--Ohio University, March, 1982. / Title from PDF t.p.