Infrastructure Engineering - Research Publications
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ItemEnergy Efficient Time Synchronization in WSN for Critical Infrastructure Monitoring(SPRINGER-VERLAG BERLIN, 2011-01-01)Wireless Sensor Networks (WSN) based Structural Health Monitoring (SHM) is becoming popular in analyzing the life of critical infrastructure such as bridges on a continuous basis. For most of the applications, data aggregation requires high sampling rate. A need for accurate time synchronization in the order of 0.6 − 9 μs every few minutes is necessary for data collection and analysis. Two-stage energy-efficient time synchronization is proposed in this paper. Firstly, the network is divided into clusters and a head node is elected using Low-Energy Adaptive Clustering Hierarchy based algorithm. Later, multiple packets of different lengths are used to estimate the delay between the elected head and the entire network hierarchically at different levels. Algorithmic scheme limits error to 3-hop worst case synchronization error. Unlike earlier energy-efficient time synchronization schemes, the achieved results increase the lifetime of the network.
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ItemA novel approach for 3D neighbourhood analysis(Copernicus GmbH, 2017-09-12)Abstract. Population growth and lack of land in urban areas have caused massive developments such as high rises and underground infrastructures. Land authorities in the international context recognizes 3D cadastres as a solution to efficiently manage these developments in complex cities. Although a 2D cadastre does not efficiently register these developments, it is currently being used in many jurisdictions for registering land and property information. Limitations in analysis and presentation are considered as examples of such limitations. 3D neighbourhood analysis by automatically finding 3D spaces has become an issue of major interest in recent years. Whereas the neighbourhood analysis has been in the focus of research, the idea of 3D neighbourhood analysis has rarely been addressed in 3 dimensional information systems (3D GIS) analysis. In this paper, a novel approach for 3D neighbourhood analysis has been proposed by recording spatial and descriptive information of the apartment units and easements. This approach uses the coordinates of the subject apartment unit to find the neighbour spaces. By considering a buffer around the edges of the unit, neighbour spaces are accurately detected. This method was implemented in ESRI ArcScene and three case studies were defined to test the efficiency of this approach. The results show that spaces are accurately detected in various complex scenarios. This approach can also be applied for other applications such as property management and disaster management in order to find the affected apartments around a defined space.
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ItemApplications of phase change materials in concrete for sustainable built environment: a review(ICSECM 2011, 2011)The fast economic development around the globe and high standards of living imposes an ever increasing demand for energy. As a prime consumer of world‟s material and energy resources building and construction industry has a great potential in developing new efficient and environmentally friendly materials to reduce energy consumptions in buildings. Thermal energy storage systems (TES) with Phase change materials (PCM) offer attractive means of improving the thermal mass and the thermal comfort within a building. PCMs are latent heat thermal storage (LHTS) materials with high energy storage density compared to conventional sensible heat storage materials. Concrete incorporating PCM improves the thermal mass of the building which reduces the space conditioning energy consumption and extreme temperature fluctuations within the building. The heat capacity and high density of concrete coupled with latent heat storage of PCM provides a novel energy saving concepts for sustainable built environment. Microencapsulation is a latest and advanced technology for incorporation of PCM in to concrete which creates finely dispersed PCMs with high surface area for greater amount of heat transfer. This paper reviews available literature on Phase change materials in concrete, its application and numerical modelling of composite concrete. However most of the existing TES systems have been explored with wallboards and plaster materials and comparatively a few researches have been done on TES systems using cementitious materials. Thus, there is a need for comprehensive experimental and analytical investigations on PCM applications with cementitious materials as the most widely used construction materials in buildings.
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ItemApplication of nanomaterials in the sustainable built environment(University of Moratuwa, 2010)Nanotechnology is widely regarded as one of the twenty-first century’s key technologies, and its economic importance is sharply on the rise. In the construction industry, nanomaterials has potentials that are already usable today, especially the functional characteristics such as increased tensile strength, self-cleaning capacity, fire resistance, and additives based on nano materials make common materials lighter, more permeable, and more resistant to wear. Nanomaterial are also considered extremely useful for roofs and facades in the built environment. They also expand design possibilities for interior and exterior rooms and spaces. Nano–insulating materials open up new possibilities for ecologically oriented sustainable infrastructure development. It has been demonstrated that nanotechnology has invented products with many unique characteristics which could significantly provide solutions current construction issues and may change the requirement and organization of construction process. This paper examines and documents applicable nanotechnology based products that can improve the sustainable development and overall competitiveness of the construction industry.
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ItemApplication of nano insulation materials in the sustainable built environment(University of Moratuwa, 2010)Nanotechnology is widely being used in the built environment for its advantages in many improved engineering properties of the nano materials. Nano insulating materials open up new possibilities for ecologically oriented sustainable infrastructure development. The most widely used nano material in built environment is for the purpose of insulation to improve the energy efficiency namely in the buildings and dwellings. Nanotechnology has now provided an effective and affordable means to increase energy efficiency in pre-existing buildings as well as new construction by increasing thermal resistance. The major advantage of nano insulation materials is its benefit of translucent coatings which increase the thermal envelope of a building without reducing the square footage. The intrinsic property of nano insulating material is it can be applied to windows to reduce heat transfer from solar radiation due it its thermal resistant property and the translucent property allows diffusing of day light. The nano insulating material has significant advantage in reducing the operational energy aspects of buildings due to its valuable insulating properties. This paper examines applicable nanotechnology based products that can improve the sustainable development and overall competitiveness of the building industry. The areas of applying nano insulating material in building industry will be mainly focused on the building envelope. The paper also examines the potential advantages of using nanotechnology based insulating material in reducing the life cycle energy, reduction of material usage and enhancing the useable life span. The paper also investigates the operational energy by simulation methodology and compares the reduction of operational energy consumption.
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ItemThe value of water in storage: Implications for operational policies(Curran Associate Inc., 2018-01-01)With desalination plants becoming an increasingly common feature of water supply systems for major cities, the options for managing water security are now markedly different to past times when the short-term response to low water availability essentially revolved around reducing usage. The operation of desalination plants and other components of diversified water supply systems now enable operators to increase availability, essentially by producing water. The operation of such systems clearly impacts operational costs but, more subtly, also impacts future augmentation decisions. This can have major cost implications as there is a trade-off between the costs of operating a water supply system and the probability and timing of future augmentations that leads to important differences in the economics of reliably supplying water. This paper first summarises an economic analysis framework in which to explore the interaction of short (operational) and long (capital investment) term decisions towards maintaining water security. It then explores the implications of different operation approaches in Melbourne’s water supply system, assuming a planned augmentation pathway under conditions of low water availability. We assume augmentation decisions are prompted by critically low water availability events, rather than long-term reliability analysis. We show that the majority of the variation in cost of maintaining a reliable water supply is associated with impacts of operational rules on likely capital investment and that this results in a strong interaction between short and long-term decision making. The outcome of this work has implications for both operational decision making and augmentation planning for urban water supply systems. These implications are relevant to any water supply system where a climate independent water supply source, such as desalination, can be accessed.
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ItemA Machine Learning Approach for the Performance Prediction of GCHPs with Horizontal Ground Heat Exchangers(IOS PRESS, 2019-01-01)This study aims to provide a machine learning approach to predict the performance of Ground Coupled Heat Pumps (GCHPs) with horizontal Ground Heat Exchangers (GHEs). Specifically, an ANN model was developed for this purpose which can potentially be generally applied to similar sites at different locations and climate conditions, with even limited types of input data. In this example, a TRNSYS model regarding a typical horizontal trench within a rural farm in Australia, has been developed and verified, covering over 50 different yearly loading patterns under 3 different climate conditions. The simulated performance data is then used to train the artificial neural network. As results, the trained ANN is able to predict the performance of GSHPs systems with identical GHEs even under climatic conditions (and locations) that has not been specifically trained for. With only limited input data, the presented ANN shows no more than 5% error in most cases tested.
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ItemStochastic modelling of annual rainfall data(Conference Design, 2006-01-01)Rainfall data are generally required in computer simulations of rainfall-runoff processes, crop growth and water supply systems. The length of historical climate data is usually not long enough to describe the complete range of variability that might be experienced during the life of a water resources or agricultural project. Using the statistical characteristics of historical data, it is possible to generate many sequences of data that better represent the climatic variability. In developing the stochastic models, the data are generally assumed stationary in the broad sense and any long-term fluctuations in the data are ignored. Typically, only in monthly, daily and sub-daily models, is the seasonal variation within a year considered explicitly in stochastic models. However, there is a growing interest and concern about the role of interdecadal variability in climate and its influence on rainfall. One approach is to identify any long-term fluctuations in the observed rainfall and model them explicitly. Empirical Mode Decomposition (EMD) was used to identify any low frequency fluctuations in annual rainfall data from 44 sites in Australia. The results did not allow easy identification of low frequency fluctuations in the data. As a means of aiding interpretation of the EMD results, the following ploy was adopted. The AR1 model, the most widely used model for the generation of annual rainfall data, was used to generate stochastic data based on the statistics of the observed sequences and the EMD analysis was performed on the stochastic data sets. The results of the analysis comparing both the historical and generated data showed that, in general, both the data sets have similar low frequency characteristics except for Perth.
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ItemDetection of a soil moisture and groundwater signal in ground-based gravity observations(Conference Organising Committee for the 40th Australian Conference of Economists, 2006)Gravity observations have the potential to provide an exciting new source of remotely sensed data to constrain the water balance in land surface models. This would result in more accurate soil moisture and flux predictions and correspondingly improved numerical weather prediction and global climate forecasts. However before existing or future (GRACE or GOCE) dedicated gravity satellites can be utilised in an operational setting it must be shown that a soil moisture signal is detectable in gravity observations. This is extremely difficult to show directly for the satellite observations due to the massive spatial scale involved (1000 km2or larger depending on accuracy requirements), so a ground-based field study of soil moisture, groundwater and gravity changes is essential in verifying the magnitude of the hydrological signal in gravity observations. This paper presents results from two field sites in the Kyeamba Creek catchment in NSW where soil moisture, groundwater and gravity have been monitored for one year. One is a hillslope site with no groundwater whereas the other is a valley site with a shallow water table. After correcting for earth tides and gravity meter drift, a gravity network adjustment is performed for two time periods chosen to capture the full range of subsurface water storage (autumn and spring). The adjustment improves the precision of the gravity estimates at each site relative to a hydrologically stable bedrock reference site. A t-test is performed on the gravity changes at the two sites and the valley site is found to have a significant change in gravity that corresponds extremely well to the predicted hydrologically induced gravity change. There are many complicating factors in a ground-based study, but nevertheless a hydrological signal (predominantly soil moisture) has been detected in the gravity observations of a valley site with a shallow groundwater table.
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ItemRecharge mechanisms in an Arid Zone River: Effects of channelisation(Conference Organising Committee, 2006)Arid zone, ephemeral rivers typically experience very high transmission losses. Most international studies have identified infiltration into stream sediments and subsequent percolation to the unconfined alluvial aquifer as the major cause of transmission losses. There is relatively little data regarding mechanisms and stores controlling transmission loss processes in Australian arid zone streams, particularly in regards recharge to the unconfined aquifer. This study reports on a field study of recharge mechanisms occurring in the Neales River of the Lake Eyre Basin (northern South Australia). Piezometric monitoring, numerical and analytical modelling were used to identify and quantify recharge to the unconfined aquifer during streamflow events in 2004-2005. Significant recharge only occurred in channelised reaches and rates of recharge did not show a clear relationship with stage but tended to be higher for flow events occurring after longer periods of no flow. Reaches lacking a single, well-defined channel are common in the anastomosing rivers of the Lake Eyre Basin. Piezometers monitoring the alluvial sediments at two locations lacking well-defined channels did not measure any development of a saturated zone in the alluvial aquifer following flow events. The data suggests that most percolation and recharge occurs through the bank, rather than the floodplain and this needs to be taken into account when estimating transmission losses for these river systems.