Infrastructure Engineering - Research Publications

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    PARAMETER CONSIDERATIONS FOR THE RETRIEVAL OF SURFACE SOIL MOISTURE FROM SPACEBORNE GNSS-R
    Munoz-Martin, JF ; Onrubia, R ; Pascual, D ; Park, H ; Camps, A ; Rüdiger, C ; Walker, JP ; Monerris, A (IEEE, 2021-01-01)
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    3D CITYLUR: MODELLING 3D CITY LAND-USE REGULATIONS to SUPPORT ISSUING A PLANNING PERMIT
    Emamgholian, S ; Pouliot, J ; Shojaei, D (ISPRS, 2021-10-07)
    The applications and understanding of Land-use Regulations (LuR) are more communicable when they are linked to the digital representation of the physical world. In order to support issuing a planning permit and move towards the establishment of automated planning permit checks, this paper investigates how LuRs related to a planning permit process can be modelled in 3D called 3D CityLuR. 3D CityLuR serves as a 3D model for representing LuRs' legal extents on a city scale. It is formed based on multiple geometric modelling approaches representing LuRs, which can provide a better cognitive understanding of LuRs and subsequently facilitate LuR automatic checks. To this purpose, according to LuRs' descriptions and characteristics explained in related planning documents, key parameters representing LuRs' extent are identified (e.g. maximum distance in overlooking or maximum allowed height in building height regulations). Accordingly, to automatically model each LuR, a geometric modelling approach (e.g. Boundary Representation (B-Rep), CSG, and extrusion) that best fits with the identified key parameters is proposed. In addition, to combine 3D CityLuR with an integrated BIM-GIS environment, the level of information need in terms of geometries and semantics is specified. Finally, the paper results in a showcase for five LuRs including building height, energy efficiency protection, overshadowing open space, overlooking, and noise impacts regulations. The showcase is a proof of concept for determining how these LuRs can be modelled in 3D and combined with 3D city models based on the selected geometric modelling approaches, identified parameters, and level of information need.
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    A multi-layered energy resilience framework and metrics for energy master planning of communities: A university campus case study
    Charani Shandiz, S ; Rismanchi, B ; Foliente, G ; Aye, L (Society of Risk Analysis, 2021-12-05)
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    An innovative cost-effective floating solar still with integrated condensation coils
    Mohsenzadeh, M ; Aye, L ; Christopher, P (Australian PV Institute, 2021-12-16)
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    An update on Activity C1 Design Tools and Models, Task 65 Solar Cooling Sunbelt Regions
    Aye, L ; Daborer-Prado, N ; Neyer, D ; Jakob, U (Australian PV Institute, 2021-12-16)
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    Testing uncertainty in a model of stream bank erosion
    Jha, S ; Western, AW ; Rutherfurd, ID ; Grayson, RB ( 2020-01-01)
    Sediment and nutrient loads in Australian rivers are a significant management concern. The National Land and Water Audit (2002) identified bank erosion as a major source of sediment, particularly in southern Australian systems. This paper tests a method of incorporating uncertainty into and the up-scaling of a cross-section scale stream bank erosion model. The cross-section scale model is based on an understanding of fluvial erosion and mass failure processes in which fluvial erosion is estimated using an excess shear stress approach while mass failure is estimated using a limit equilibrium analysis at the cross-section scale. Figure 1 shows a schematic of the model. A Monte-Carlo framework is used to propagate input uncertainty to output uncertainty in the model and to scale up to the reach scale. Widely available databases are used to estimate variables for the two model components. A range of spatial information (GIS layers) is used to describe spatial variations in general properties such as soil type and catchment area. These are considered to be relatively well known (compared with cross-section geometry, geotechnical properties of the bank materials, riparian tree density, and hydrologic variables), although spatially coarse. A variety of empirical models and assumptions are used to transform the spatial information into model parameters, which are considered to be relatively poorly known. Two major challenges, which are related, involve incorporating the effects of natural variability along a river reach and estimating the uncertainty in the model inputs and the effect that this has on uncertainty in the model prediction. A Monte Carlo framework is used to achieve this. This involves developing a series of statistical models to predict the erosion model inputs and their (co)variability. A hierarchical approach is used to develop these input models. An attempt is first made to construct a statistical model that predicts each model parameter from available spatial information using multiple regressions. Uncertainty in these parameters is incorporated using the regression error statistics. Where cross-correlations were found to be important, these were incorporated in the generation models. Where it was not possible to develop empirical relationships with available spatial data sets, a suitable parametric distribution is fitted for those input variables for which some data is available. Where no data were available for fitting a distribution, a distribution was assumed with a shape and parameters based on heuristic consideration of the relevant processes. Once both the erosion model and the various input models were established, the Monte Carlo technique was applied. This involves generating sets of the input variables of the model from the respective stochastic input models and the running the erosion model. This allows the probability distribution for the model output to be estimated for a location in the stream network. The model is tested using historical records of plan form change from a 40km reach of the Goulburn River downstream of Eildon Dam in Victoria, Australia. The results obtained from the model are promising; with bank erosion rates being predicted within a factor of two without calibration. A series of sensitivity analyses (detail sensitivity analysis, scenario analysis, and advance sensitivity analysis) were conducted to identify key variables for predicting bank erosion rates using this particular bank erosion model. This suggested that bank angle, bank material physical characteristics, stream bed slope, and the high-flow flow regime (bankfull duration) control the behaviour of the model for loam bank materials.
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    3D Cadastre in Australian and New Zealand Jurisdictions: Similarities and Differences
    Atazadeh, B ; Olfat, H ; Rajabifard, A (International Federation of Surveyors (FIG), 2021)
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    Daily and seasonal thermal energy storage for enhanced flexible operation of low-temperature heating and cooling network
    Vecchi, A ; Rismanchi, B ; Mancarella, P ; Sciacovelli, A (Ecos 2021 ‎, 2021)
    Synergic operation of electricity, heating and cooling networks can bring savings and low carbon footprint through energy efficiency. In such context, the present work proposes a novel Smart Thermal Loop (STL) solution: a fully electrified thermal generation and distribution system where a low-temperature underground loop and reversible heat pumps are used to supply users’ heating and cooling demand. Additionally, STL includes short and long-term thermal energy storage (TES) by means of sensible storage tanks and geothermal boreholes. The proposed solution is described and investigated in the case of the new campus of the University of Melbourne (with aggregated peak load of about 2 and 3 MWth, respectively, for heating and cooling). A numerical model is proposed to simulate the yearly operation of STL with 1-hour resolution. Key features include (i) network model for the underground loop to track temperature evolution over space and time, (ii) variable heat pump performance, which depends on network temperatures, (iii) physical model for the heat transfer between system and soil, in the geothermal storage, (iv) modelling of the interaction between neighbouring boreholes. Results explore the dynamics of the integrated STL system, with a focus on the role that energy storage over different timescales plays in enabling efficient and flexible operation of system components. TES contribution to system operation goes beyond the use of low-price electricity and allows energy savings through efficient scheduling of heat pumps operation and reduction of pumping work. Benefits from the flexible operation of STL are quantified as a 10% reduction in energy expenditure and 28% in system running costs. The presented model can also instruct on the impact of different design choices on STL operation.
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    Target Word Masking for Location Metonymy Resolution
    Li, H ; Vasardani, M ; Tomko, M ; Baldwin, T (International Committee on Computational Linguistics, 2020)