Infrastructure Engineering - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 10 of 841
  • Item
    Thumbnail Image
    Energy Efficient Time Synchronization in WSN for Critical Infrastructure Monitoring
    Rao, AS ; Gubbi, J ; Tuan, N ; Nguyen, J ; Palaniswami, M ; Wyld, DC ; Wozniak, M ; Chaki, N ; Meghanathan, N ; Nagamalai, D (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.
  • Item
    Thumbnail Image
    A Novel Approach for 3D Modeling and Geovisualization of Easement Rights in Apartments
    Emamgholian, S ; Taleai, M ; Shojaei, D (CMV Verlag, 2018-12-01)
  • Item
    Thumbnail Image
    A novel approach for 3D neighbourhood analysis
    Emamgholian, S ; Taleai, M ; Shojaei, D (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.
  • Item
    Thumbnail Image
    Multi-scale analysis of bias correction of soil moisture
    Su, C-H ; Ryu, D ( 2014-07-29)
    Abstract. Remote sensing, in situ networks and models are now providing unprecedented information for environmental monitoring. To conjunctively use multi-source data nominally representing an identical variable, one must resolve biases existing between these disparate sources, and the characteristics of the biases can be non-trivial due to spatiotemporal variability of the target variable, inter-sensor differences with variable measurement supports. One such example is of soil moisture (SM) monitoring. Triple collocation (TC) based bias correction is a powerful statistical method that increasingly being used to address this issue but is only applicable to the linear regime, whereas nonlinear method of statistical moment matching is susceptible to unintended biases originating from measurement error. Since different physical processes that influence SM dynamics may be distinguishable by their characteristic spatiotemporal scales, we propose a multi-time-scale linear bias model in the framework of a wavelet-based multi-resolution analysis (MRA). The joint MRA-TC analysis was applied to demonstrate scale-dependent biases between in situ, remotely-sensed and modelled SM, the influence of various prospective bias correction schemes on these biases, and lastly to enable multi-scale bias correction and data adaptive, nonlinear de-noising via wavelet thresholding.
  • Item
    Thumbnail Image
    Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes
    Alvarez-Garreton, C ; Ryu, D ; Western, AW ; Su, C-H ; Crow, WT ; Robertson, DE ; Leahy, C ( 2014-09-23)
    Abstract. Assimilation of remotely sensed soil moisture data (SM–DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM–DA is a particularly attractive tool. Within this context, we assimilate active and passive satellite soil moisture (SSM) retrievals using an ensemble Kalman filter to improve operational flood prediction within a large semi-arid catchment in Australia (>40 000 km2). We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM–DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation and seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided more accurate streamflow prediction (Nash–Sutcliffe efficiency, NS = 0.77) than the lumped model (NS = 0.67) at the catchment outlet. However, this did not ensure good performance at the "ungauged" inner catchments. After SM–DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 27 and 31%, respectively; the NS of the ensemble mean increased by 7 and 38%, respectively; the false alarm ratio was reduced by 15 and 25%, respectively; and the ensemble prediction spread was reduced while its reliability was maintained. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed SSM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM–DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM–DA is effective at improving streamflow ensemble prediction, however, the updated prediction is still poor since SM–DA does not address systematic errors in the model.
  • Item
    Thumbnail Image
    Estimating Annual Water Storage Variations Using Microwave-based Soil Moisture Retrievals
    Crow, WT ; Han, E ; Ryu, D ; Hain, CR ; Anderson, MC ( 2016-11-21)
    Abstract. Due to their shallow vertical support, remotely-sensed surface soil moisture retrievals are commonly regarded as being of limited value for water budget applications requiring the characterization of temporal variations in total terrestrial water storage (S). However, advances in our ability to estimate evapotranspiration remotely now allow for the direct evaluation of approaches for quantifying annual variations in S via water budget closure considerations. By applying an annual water budget analysis within a series of medium-scale (2,000–10,000 km2) basins within the United States, we demonstrate that, despite their clear theoretical limitations, surface soil moisture retrievals derived from passive microwave remote sensing contain significant information concerning relative inter-annual variations in S. This suggests the possibility of using (relatively) higher-resolution microwave remote sensing to enhance the spatial resolution of S estimates acquired from gravity remote sensing. However, challenging calibration issues regarding the relationship between S and surface soil moisture must be resolved before the approach can be used for absolute water budget closure.
  • Item
    No Preview Available
    A predictive model for spatio-temporal variability in stream water quality
    Guo, D ; Lintern, A ; Webb, JA ; Ryu, D ; Bende-Michl, U ; Liu, S ; Western, AW ( 2019-07-23)
    Abstract. Degraded water quality in rivers and streams can have large economic, societal and ecological impacts. Stream water quality can be highly variable both over space and time. To develop effective management strategies for riverine water quality, it is critical to be able to predict these spatio-temporal variabilities. However, our current capacity to model stream water quality is limited, particularly at large spatial scales across multiple catchments. This is due to a lack of understanding of the key controls that drive spatio-temporal variabilities of stream water quality. To address this, we developed a Bayesian hierarchical statistical model to analyse the spatio-temporal variability in stream water quality across the state of Victoria, Australia. The model was developed based on monthly water quality monitoring data collected at 102 sites over 21 years. The modelling focused on six key water quality constituents: total suspended solids (TSS), total phosphorus (TP), filterable reactive phosphorus (FRP), total Kjeldahl nitrogen (TKN), nitrate-nitrite (NOx), and electrical conductivity (EC). Among the six constituents, the models explained varying proportions of variation in water quality. EC was the most predictable constituent (88.6 % variability explained) and FRP had the lowest predictive performance (19.9 % variability explained). The models were validated for multiple sets of calibration/validation sites and showed robust performance. Temporal validation revealed a systematic change in the TSS model performance across most catchments since an extended drought period in the study region, highlighting potential shifts in TSS dynamics over the drought. Further improvements in model performance need to focus on: (1) alternative statistical model structures to improve fitting for the low concentration data, especially records below the detection limit; and (2) better representation of non-conservative constituents by accounting for important biogeochemical processes. We also recommend future improvements in water quality monitoring programs which can potentially enhance the model capacity, via: (1) improving the monitoring and assimilation of high-frequency water quality data; and (2) improving the availability of data to capture land use and management changes over time.
  • Item
    Thumbnail Image
    Applications of phase change materials in concrete for sustainable built environment: a review
    JAYALATH, A ; Mendis, PA ; Gammampila, GR ; Aye, L (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.
  • Item
    Thumbnail Image
    Application of nanomaterials in the sustainable built environment
    Gammampila, GRG ; Mendis, PAM ; Ngo, TDN ; Aye, LA ; JAYALATH, A ; RUPASINGHE, RAM (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.
  • Item
    Thumbnail Image
    Application of nano insulation materials in the sustainable built environment
    Gammampila, GRG ; Mendis, PAM ; Ngo, TDN ; Aye, LA ; Herath, NCH (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.