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.

Computer integrated testing for the transport refrigeration systems industry.

This is a study of a state of the art implementation of a new computer integrated testing (CIT) facility within a company that designs and manufactures transport refrigeration systems. The aim was to use state of the art hardware, software and planning procedures in the design and implementation of three CIT systems. Typical CIT system components include data acquisition (DAQ) equipment, application and analysis software, communication devices, computer-based instrumentation and computer technology. It is shown that the introduction of computer technology into the area of testing can have a major effect on such issues as efficiency, flexibility, data accuracy, test quality, data integrity and much more. Findings reaffirm how the overall area of computer integration continues to benefit any organisation, but with more recent advances in computer technology, communication methods and software capabilities, less expensive more sophisticated test solutions are now possible. This allows more organisations to benefit from the many advantages associated with CIT. Examples of computer integration test set-ups and the benefits associated with computer integration have been discussed.

A nutrient balance model for typical Irish farming systems

The twin objectives of the work described were to construct nutrient balance models (NBM) for a range of Irish animal production systems and to evaluate their potential as a means of estimating the nutrient composition of farm wastes. The NBM has three components. The first is the intake of nutrients in the animal's diet. The second is retention or the nutrients the animal retains for the production of milk, meat or eggs. The third is the balance or the difference between the nutrient intake and retention. Data on the intake levels and their nutrient value for dairy cows, beef cattle, pigs and poultry systems were assembled. Literature searches and interviews with National experts were the primary sources of information. NBMs were then constructed for each production system. Summary tables of the nutrient values for the common diet constituents used in Irish animal production systems, the nutrient composition of the animal products and the NBMs (nutrient intake, retention and excretion) for a range of production systems were assembled. These represent the first comprehensive data set of this type for Irish animal production systems. There was generally good agreement between the derived NBMs values and those published in the literature. The NBMs were validated on a number of farms. Data on animal numbers, fertiliser use, concentrates inputs and production output were recorded on seven farms. Using the data a nutrient input/output balance was constructed for each farm. This was compared with the NBM estimate of the farm nutrient balance. The results showed good agreement between the measured balance and the NBM estimate particularly for the pig and poultry farms. However, the validation emphasised the inherent risks associated with NBMs. The average values used for feed intake and production parameters in the NEMs may result in the under or over estimate of actual nutrient balances on individual farms where these variables are substantially different. On the grassland farms there was a poor correlation between the input/output estimate and the NBM. This possibly results from the omission of the soil's contribution to the nutrient balance. However, the results indicate that the NBMs developed are a potentially useful tool for estimating nutrient balances. They also will serve to highlight the significant fraction of the nutrient inputs into farming systems that are retained on the farm. The potential of the NBM as a means of estimating the nutrient composition of farm wastes was evaluated on two farms. Feed intake and composition, animal production, slurry production was monitored during the indoor winter feeding period. Slurry samples were taken for analysis. The appropriates NBMs were used to estimate the nutrient balance for each farm. The nutrient content of the slurry produced was calculated. There was a good agreement between the NBM estimate and the measured values. This preliminary evaluation suggests that the NBM has a potential to provide the farmer with a simple means of estimating the nutrient value of his slurry.