Power plant cooling technologies : hybrid cooling systems can save water

In addition to water saving, the hybrid cooling concept presented in this book also has the potential to improve energy efficiency and possibly reduce CO2 emission by recovering and upgrading the 'waste' energy from the cooling water stream.Yilmaz and Kouzani are at Deakin Uni, Hessami is at Monash Uni, Hu is at Uni of Adelaide.

Performance assessment of earth pipe cooling system for low energy buildings in a subtropical climate

Energy consumption in heating and cooling around the world has been a major contributor to global warming. Hence, many studies have been aimed at finding new techniques to save and control energy through energy efficient measures. Most of this energy is used in residential, agricultural and commercial buildings. It is therefore important to adopt energy efficiency measures in these buildings through new technologies and novel building designs. These new building designs can be developed by employing various passive cooling systems. Earth pipe cooling is one of these which can assist to save energy without using any customary mechanical units. This paper investigates the earth pipe cooling performance in a hot humid subtropical climate of Rockhampton, Australia. A thermal model is developed using ANSYS Fluent for measuring its performance. Impacts of air velocity, air temperature, relative humidity and soil temperature on room cooling performance are also assessed. A temperature reduction of around 2 °C was found for the system. This temperature reduction contributed to an energy saving of a maximum of 866.54 kW (8.82%) per year for a 27.23 m3 room.

Designing a low cost solar collector system for process industry applications

New Zealand is a large producer and processor of primary products and has a climate with high levels of solar radiation. However, the use of solar energy for heating and cooling in the processing industries has received limited attention.
For this study, the design of a low cost solar collector is analysed and discussed. Furthermore, the methods for integrating the collector into water heating and cooling systems in a hypothetical processing environment are examined. An F-Chart analysis is used to simulate the performance of large-area arrays of the solar collector and to determine its potential contribution to heating and cooling loads.
The study shows that for a storage-based system, the contribution of solar energy is determined mainly by the collector area to storage volume ratio. It is suggested that this low cost collector could make a significant contribution to energy use in processing plants and may be an attractive future technology.

Exergy applied to lunar base design

This paper explores design considerations for energy efficiency in lunar habitats. It considers several previous lunar energy studies in regards to energy types and stages of energy requirements. If we are to obtain true sustainability in energy processes, we will need to design according to the principles “exergy”, considering both the first and the second laws of thermodynamics in a holistic and thorough evaluation of energy capture, transformation, and use. Such an evaluation will ascertain the source of energy, its processing and energy potential stages, as well as the task required. Traditional designs of facility thermal systems are frequently extremely wasteful: they dramatically increase both first costs and operating costs because they treat heating and cooling systems as separate entities, instead of an integrated energy system. Energy processes, the state of energy required to do a particular task, the embodied energy to complete or manufacture an object, and the wasted energy released are all important to conservation and obtaining an efficient and effective use (quality) of energy. If the regulation of energy processes is a concern in terrestrial habitation, it should be even more so for extra-terrestrial habitation where there is little margin for waste of any sort.

Role assessment of GIS analysis and its reliability while ranking urban sustainability using scenarios specific to regional climate, community and culture

Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban sustainability using different indicator metrics, that implement vector GIS Analysis and Raster GIS analysis as basic tools to assist the evaluation and increase of its reliability besides assessing and decomposing it, after which a hypothetical implementation of the chosen evaluation model represented by various scenarios was implemented on the planned urban sustainability factors for a certain period of time to appraise the expected future grade of urban sustainability and come out with advises associated with scenarios for assuring gap filling and relative high urban future sustainability. The results this paper is reflecting are concentrating on the elements of vector and raster GIS analysis that assists the proper urban sustainability grading within the chosen model, the reliability of spatial data collected; analysis selected and resulted spatial information. Starting from selecting some important indicators to comprise the model which include regional culture, climate and community needs an example of what was used is Energy Demand & Consumption (Cooling systems). Thus, this factor is related to the climate and it‟s regional specific as the temperature varies around 30-45 degrees centigrade in city areas, GIS 3D Polygons of building data used to analyse the volume of buildings, attributes „building heights‟, estimate the number of floors from the equation, following energy demand was calculated and consumption for the unit volume, and compared it in scenario with possible sustainable energy supply or using different environmental friendly cooling systems this is followed by calculating the cooling system effects on an area unit selected to be 1 sq. km, combined with the level of greenery area, and open space, as represented by parks polygons, trees polygons, empty areas, pedestrian polygons and road surface area polygons. (initial measures showed that cooling system consumption can be reduced by around 15 -20 % with a well-planned building distributions, proper spaces and with using environmental friendly products and building material, temperature levels were also combined in the scenario extracted from satellite images as interpreted from thermal bands 3 times during the period of assessment. Other examples of the assessment of GIS analysis to urban sustainability took place included Waste Productivity, some effects of greenhouse gases measured by the intensity of road polygons and closeness to dwelling areas, industry areas as defined from land use land cover thematic maps produced from classified satellite images then vectors were created to take part in defining their role within the scenarios. City Noise and light intensity assessment was also investigated, as the region experiences rapid development and noise is magnified due to construction activities, closeness of the airports, and highways. The assessment investigated the measures taken by urban planners to reduce degradation or properly manage it. Finally as a conclusion tables were presented to reflect the scenario results in combination with GIS data types, analysis types, and the level of GIS data reliability to measure the sustainability level of a city related to cultural and regional demands.

Performance of ventilated hollow core concrete panel systems in Australia

Performance of advanced fabric energy storage systems has not been reported for Australian conditions. The influence pf slab thickness and air flow rate on the annual thermal load, and maximum heating and cooling demands for a typical office module using a ventilated hollow core concrete slab system has been investigated by simulation. Performance results for Melbourne are presented and comments made on other locations.

Advanced fabric energy storage systems in Australia

There is a growing interest in the use of advanced fabric energy storage (FES) systems in Australia. The influence of slab thickness and ventilation rate on the annual thermal load, and maximum heating and cooling demands for an office module using a ventilated hollow core concrete slab system has been investigated by simulation. Airflow through the panels was set at 1, 2 or 4 air changes per hour (ACH) for slab thicknesses of 205, 220 and 300 mm. These configurations were simulated using two different FES operational strategies for six capital cities in mainland Australia. The simulations show that FES systems can offer either energy and/or peak load savings in almost all locations investigated. Overall, compared to a conventional AC system, the tempering of incoming fresh air combined with night flushing of the FES system appears to be the most successful operational strategy.

Seasonal storage for solar thermal systems in Australia?

Seasonal storage systems have been operating in various European countries since 1985. Combined with solar collectors, these systems are known as ‘central solar heating plants with seasonal storage’ (CSHPSS). While these systems have been shown to be technically feasible, their cost is still too high to make them competitive with fossil fuels.

In Australia, we have quite different conditions to those countries where CSHPSS have been trialled. In general, we experience higher radiation levels, ambient temperatures and cooling loads. Our heating loads and energy prices are also usually lower. As a result, any evaluation of CSPSS operating in a European context may not be valid for Australian conditions. To the authors’ knowledge, no evaluation of these systems has been carried out for Australia.

This paper therefore attempts an initial assessment of these systems and their viability for Australia. The paper first describes the various types of CSHPSS and then reviews their current status. The performance of one type of CSHPSS operating in several locations of Australia has been predicted using a TRNSYS model. The simulations indicated that the design guidelines for Europe are inappropriate for Australia and would result in greatly over-sized systems.

An indication of the financial viability of the system was determined by calculating a simple payback period for a variety of fossil fuels. This type of seasonal storage systems appears to be financially attractive in areas of southern Australia where the solar system is displacing LPG.

Fuzzy neural networks for control of dynamic systems

This thesis provides a unified and comprehensive treatment of the fuzzy neural networks as the intelligent controllers. This work has been motivated by a need to develop the solid control methodologies capable of coping with the complexity, the nonlinearity, the interactions, and the time variance of the processes under control. In addition, the dynamic behavior of such processes is strongly influenced by the disturbances and the noise, and such processes are characterized by a large degree of uncertainty. Therefore, it is important to integrate an intelligent component to increase the control system ability to extract the functional relationships from the process and to change such relationships to improve the control precision, that is, to display the learning and the reasoning abilities. The objective of this thesis was to develop a self-organizing learning controller for above processes by using a combination of the fuzzy logic and the neural networks. An on-line, direct fuzzy neural controller using the process input-output measurement data and the reference model with both structural and parameter tuning has been developed to fulfill the above objective. A number of practical issues were considered. This includes the dynamic construction of the controller in order to alleviate the bias/variance dilemma, the universal approximation property, and the requirements of the locality and the linearity in the parameters. Several important issues in the intelligent control were also considered such as the overall control scheme, the requirement of the persistency of excitation and the bounded learning rates of the controller for the overall closed loop stability. Other important issues considered in this thesis include the dependence of the generalization ability and the optimization methods on the data distribution, and the requirements for the on-line learning and the feedback structure of the controller. Fuzzy inference specific issues such as the influence of the choice of the defuzzification method, T-norm operator and the membership function on the overall performance of the controller were also discussed. In addition, the e-completeness requirement and the use of the fuzzy similarity measure were also investigated. Main emphasis of the thesis has been on the applications to the real-world problems such as the industrial process control. The applicability of the proposed method has been demonstrated through the empirical studies on several real-world control problems of industrial complexity. This includes the temperature and the number-average molecular weight control in the continuous stirred tank polymerization reactor, and the torsional vibration, the eccentricity, the hardness and the thickness control in the cold rolling mills. Compared to the traditional linear controllers and the dynamically constructed neural network, the proposed fuzzy neural controller shows the highest promise as an effective approach to such nonlinear multi-variable control problems with the strong influence of the disturbances and the noise on the dynamic process behavior. In addition, the applicability of the proposed method beyond the strictly control area has also been investigated, in particular to the data mining and the knowledge elicitation. When compared to the decision tree method and the pruned neural network method for the data mining, the proposed fuzzy neural network is able to achieve a comparable accuracy with a more compact set of rules. In addition, the performance of the proposed fuzzy neural network is much better for the classes with the low occurrences in the data set compared to the decision tree method. Thus, the proposed fuzzy neural network may be very useful in situations where the important information is contained in a small fraction of the available data.

Corrosion impact on drinking water distribution systems : a review and future research direction

At present water treatment and distribution is of high priority to ensure that communities have access to safe and affordable drinking water. Current information states that in the United States a total annual cost of $36 billion (US) is spent replacing aging infrastructure, lost water from unaccounted-for leaks, corrosion inhibitors, internal mortar linings, external coatings, and cathodic protection as a result of corrosion. In order to reduce the cost incurred as a result of corrosion in the water distribution industry, it is essential that better corrosion management and preventative strategies are implemented. However through investigation of research previously undertaken by others, it was found that there was a lack of study of corrosion within distribution systems in the tropics taking into account the related seasonal temperature variations. To assist in the development of management strategies to improve the outcomes of drinking water distribution systems, the authors propose to implement a pilot study involving the installation of a corrosion reactor based on standard corrosion assessment technologies in a water distribution system located in the tropics.

Performance of suspended and attached growth MBR systems in treating high strength synthetic wastewater

The performance of laboratory-scale attached growth (AG) and suspended growth (SG) membrane bioreactors (MBRs) was evaluated in treating synthetic wastewater simulating high strength domestic wastewater. This study investigated the influence of sponge suspended carriers in AG-MBR system, occupying 15% reactor volume, on the removal of chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP), and compared it to that of SG-MBR. Results showed that the removal efficiencies of COD, TN and TP in AG-MBR were 98%, 89% and 58%, respectively as compared to 98%, 74% and 38%, respectively in SG-MBR. Improved TN removal in AG-MBR systems was primarily based on simultaneous nitrification and denitrification (SND) process. These results infer that the presence of small bio-particles having higher microbial activity and the growth of complex biomass captured within the suspended sponge carriers resulted in improved TN and TP removal in AG-MBR.

Prediction interval-based control of nonlinear systems using neural networks

Prediction interval (PI) is a promising tool for quantifying uncertainties associated with point predictions. Despite its informativeness, the design and deployment of PI-based controller for complex systems is very rare. As a pioneering work, this paper proposes a framework for design and implementation of PI-based controller (PIC) for nonlinear systems. Neural network (NN)-based inverse model within internal model control structure is used to develop the PIC. Firstly, a PI-based model is developed to construct PIs for the system output. This model is then used as an online estimator for PIs. The PIs from this model are fed to the NN inverse model along with other traditional inputs to generate the control signal. The performance of the proposed PIC is examined for two case studies. This includes a nonlinear batch polymerization reactor and a numerical nonlinear plant. Simulation results demonstrated that the proposed PIC tracking performance is better than the traditional NN-based controller.