The spatial analysis and speciation of uranium and thorium series radionuclides in the soil of the Cronamuck Valley, County Donegal, Ireland

This thesis details the findings of a study into the spatial distribution and speciation of 238U, 226Ra and 228Ra in the soils of the Cronamuck valley, County Donegal . The region lies on the north-eastern edge of the Barnesmore granite and has been the subject of uranium prospecting efforts in the past. The results of the project provide information on the practicability of geostatistical techniques as a means of estimating the spatial distribution of natural radionuclides and provide insight into the behaviour of these nuclides and their modes of occurrence and enrichment in an upland bog environment. The results of the geostatistical survey conducted on the area indicate that the primary control over the levels of the studied nuclides in the soil of the valley is the underlying geology. Isopleth maps of nuclide levels in the valley indicate a predominance of elevated nuclide levels in the samples drawn from the granite region, statistical analysis of the data indicating that levels of the nuclides in samples drawn from the granite are greater than levels drawn from the non-granite region by up to a factor of 4.6 for 238U and 4.9 for 226Ra. Redistribution of the nuclides occurs via drainage systems within the valley, this process being responsible for transport of nuclides away from the granite region resulting in enrichment of nuclides in soils not underlain by the granite. Distribution of the nuclides within the valley is erratic, the effect of drainage f lows on the nuclides resulting in localized enriched areas within the valley. Speciation of the nuclides within one of the enriched areas encountered in the study indicates that enrichment is as a result of saturation of the soil with drainage water containing trace amounts of radionuclides. 238U is primarily held within the labile fractions (exchangeable cat ions + easily oxidisable organics + amorphous iron oxides ) of the soil , 226Ra being associated with the non- labile fractions, most probably the resistant organic material. 228Ra displays a significant occurrence in both the labile and non- labile fractions. The ability of the soil to retain uranium appears to be affected largely by the redox status of the soil, samples drawn from oxidizing environments tending to have little or no uranium in the easily oxidisable and amorphous iron oxide fractions. This loss of uranium from oxidised soil samples is responsible for the elevated 226Ra /238U disequilibrium encountered in the enriched areas of the valley. Analysis of the data indicates that samples displaying elevated 226Ra/238U ratios also exhibit elevated 228Ra/238U ratios indicating a loss of uranium from the samples as opposed to an enrichment of 226Ra.

Development of a data acquisition system to characterise sustainable energy technologies and to support Web-Based learning (DAQ-WBL)

Driven by concerns about rising energy costs, security of supply and climate change a new wave of Sustainable Energy Technologies (SET’s) have been embraced by the Irish consumer. Such systems as solar collectors, heat pumps and biomass boilers have become common due to government backed financial incentives and revisions of the building regulations. However, there is a deficit of knowledge and understanding of how these technologies operate and perform under Ireland’s maritime climate. This AQ-WBL project was designed to address both these needs by developing a Data Acquisition (DAQ) system to monitor the performance of such technologies and a web-based learning environment to disseminate performance characteristics and supplementary information about these systems. A DAQ system consisting of 108 sensors was developed as part of Galway-Mayo Institute of Technology’s (GMIT’s) Centre for the Integration of Sustainable EnergyTechnologies (CiSET) in an effort to benchmark the performance of solar thermal collectors and Ground Source Heat Pumps (GSHP’s) under Irish maritime climate, research new methods of integrating these systems within the built environment and raise awareness of SET’s. It has operated reliably for over 2 years and has acquired over 25 million data points. Raising awareness of these SET’s is carried out through the dissemination of the performance data through an online learning environment. A learning environment was created to provide different user groups with a basic understanding of a SET’s with the support of performance data, through a novel 5 step learning process and two examples were developed for the solar thermal collectors and the weather station which can be viewed at http://www.kdp 1 .aquaculture.ie/index.aspx. This online learning environment has been demonstrated to and well received by different groups of GMIT’s undergraduate students and plans have been made to develop it further to support education, awareness, research and regional development.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.