Radiation Damage of TiC and TiN during Microanalysis in the Electron Microscope

The work presented in this thesis is concerned with the preferential mass loss observed during high spatial resolution micro-analysis of ceramic materials such as TiC and TiN. Electron energy loss spectroscopy (EELS) was used to investigate the preferential loss of the light elements as a function of dose incident upon the specimen. This thesis is primarily concerned with the characterisation of the knock-on displacement damage mechanism thought to be responsible for the mass loss. Chapter 1 gives a general introduction to these knock-on damage processes with particular emphasis on radiation damage observed in the electron microscope. To perform quantitative EELS microanalysis without the use of standard specimens it is necessary to have an accurate knowledge of the cross-sections relevant to the inelastic scattering of electrons. Chapter 2 outlines the development of partial cross-sections required for EELS analysis and discusses other processes which may contribute to the EELS spectrum. Chapter 3 develops two radiation damage mechanisms as possible explanations for the depletion of the light elements in Tic and TiN during electron irradiation: a forward knock-on displacement model and an isotropic radiation induced diffusion model. In chapter 4 a brief description is given of the scanning transmission electron microscope (STEM) used to carry out the high current density radiation damage experiments described in this thesis. The discussion includes a description of two specimen preparation techniques developed to provide electron transparent samples with a plentiful supply of uniform thin areas, suitable for radiation damage experiments. The reduced dose rate incident upon the specimen during radiation damage experiments results in statistically poor EEL spectra. Often, the accuracy with which quantitative data can be extracted from these "noisy" spectra is limited by the accuracy of the background stripping routines. Chapter 5 compares and contrast three such background fitting routines using both experimental and theoretically generated spectra in an attempt to assess which, if any, is more reliable in the presence of noise. The experimental results are presented in chapter 6 and 7 for the TiC and TiN materials. Comparison of the rate of loss of C and N with respect to dose at various specimen thicknesses is carried out to establish which, if either, of the two radiation damage mechanisms considered in chapter 3 is applicable to the data. Other considerations such as dose rate effects, channeling effects and the loss of Ti from the sample are considered in more detail in chapter 7 and their effect on the measured rate of loss of N is established. Some high angle ADF images are presented in chapter 6 as a possible method of following the radiation damage process and to highlight the inhomogeneous nature of the damage processes in TiC and TiN

Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the upper Medway catchment of southeast England using the UK NIMROD radar rainfall estimates, using three hydrological models based upon three very different structures (e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF). We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study

Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

International audienceAdvances in meso-scale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system

Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study

Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2–3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part

Radar hydrometeorology using a vertically pointing radar

International audienceA Vertically Pointing Radar (VPR) has been commissioned and deployed at a number of sites in southern England, to investigate numerically spatial and temporal variations in the vertical reflectivity profile (Zvp); particularly those associated with the intersection by the radar beam of a melting layer ? the bright band. Comparisons with data from other instrumentation, notably with the S-band research radar at Chilbolton, but also with disdrometer data and rainfall measurements from a number of sophisticated rain gauges, show that VPR scans of the atmosphere provide detailed and reliable quantitative measurements of the Zvp. Analysis of a three year archive of Zvp data for Manchester has shown a bright band to be present in over 80% of rainfall events, highlighting the extent of the problem of bright band errors in scanning weather radar data. The primary characteristics of the bright band such as the height and magnitude (in dBZ) of the top, bottom and peak are identified objectively from VPR Zvp data by an automatic bright band recognition algorithm. It is envisaged that this approach could form the basis of an objective, automatic real time correction procedure for scanning weather radars. Keywords: Vertically Pointing Radar, weather radar, hydrometeorology, bright-band, melting-layer, vertical radar reflectivity</p

Developing A High Performance Computing (HPC) Based Hydrological Modelling Framework To Support Extreme Weather Impact Studies

Computer based modelling has long been an established norm in hydrological studies. The demand of computing power in hydrological modelling domain, although keep steadily growing over past decades, it has never been higher as we now look into many impact studies due to climate change. While HPC has long been a major player in the neighbouring field of climate sciences, its role has yet to be defined when the resources become increasingly accessible to hydrological modellers attempting to address the impact of climate change in terms of extreme weather events. In this paper, we present a framework of HPC based hydrological modelling approach that can utilize and maximize the HPC power to support the study on extreme weather impact due to climate change. The framework is intended to achieve 1) seamlessly coupling of the hydrological models with the climate/numerical weather models that are supported by the same HPC platform; 2) supporting large-scale hydrological modelling in greater details; 3) conducting joint ensemble runs of coupled modelling systems so as to account for the modelling uncertainty; 4) supporting multi-model ensembles to identify potential extreme storms with certain climate projections; 5) the ability of processing large volume of data (terabyte level). An example of such system is also discussed with the implementation using Fujitsu’s HPC platform, the UK Unified Model (as the climate model backend) and a versatile interface to a number of preferred hydrological models

Appendix: Data management and data archive for the HYREX Programme

International audienceSince the mid 1980s, changes in political imperatives plus technological changes in computer hardware and software have heightened the awareness of the economic value and importance of quality datasets to scientific research. The Natural Environment Research Council's (NERC) interdisciplinary Thematic and Special Topic Programmes have highlighted the need for a coherent data management policy to provide and preserve these quality datasets for posterity. The Hydrological Radar EXperiment (HYREX) Special Topic Programme brought together multi-disciplinary researchers from UK public sector laboratories and universities. In this paper, the HYREX data management strategy, its problems and its solutions are discussed. The HYREX data archive, situated at NERC's British Atmospheric Data Centre, is described. Keywords: radar, data, archive, web, storm, flood</p