Infrastructure Engineering - Theses
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ItemLow-fidelity Hydrodynamic Model-based Method for Efficient Flood Inundation Modelling( 2021)Flood is one of the most devastating natural hazards, as it often causes fatalities and damages to infrastructure. To develop strategies for flood risk mitigation, flood inundation models are often used to provide useful information for assessments of potential impacts of floods. Two-dimensional (2D) hydrodynamic models are commonly used for flood inundation simulations. However, they can be computationally intensive when used to simulate many flood events, for example for uncertainty analysis, or to simulate very large floodplains. To improve computational efficiency, data-driven models based on machine learning techniques and conceptual models based on simplified water-filling concepts have been developed. Data-driven models appear as black-box models and are yet to be used by many practitioners with confidence. Simplified conceptual models are generally not designed to simulate the temporal propagation of floods and are often only applied to estimate maximum/final flood extent and floodwater levels. In Australia, 2D hydrodynamic models have been established for many important catchments. There is potential to build on these existing models and develop methods to speed up flood inundation simulations. In this MPhil thesis, a new modelling method, LoHy+, is proposed based on existing 2D hydrodynamic models, to produce an efficient simulation of flood extent and depth with time. The method first develops a low-fidelity 2D hydrodynamic model (LFM) with coarse mesh based on an existing high-fidelity 2D hydrodynamic model (HFM). The aim of the LFM is to produce reasonably accurate simulation of water levels within the main river channels while tolerating poorer simulation elsewhere in the floodplain. Next, the method develops a Mapping Module by using training data to establish relationships between water levels in both river channels and across the floodplain generated using the HFM and water levels in the river channels generated using this LFM. In subsequent applications, the LFM is run first, and the Mapping Module is applied to estimate flood inundation within the entire model domain. The implementation of the LoHy+ is demonstrated using a real-world catchment located in the southern Murray Darling Basin, Australia. A fully calibrated HF MIKE21 FM hydrodynamic model is available for the catchment. The performance of the LoHy+ method is evaluated against simulation from the high-fidelity hydrodynamic model. There is a good agreement between results from the LoHy+ method and the original high-fidelity 2D hydrodynamic model. The new method is much more efficient and can simulate the spatiotemporal evolution of flood inundation with reasonable accuracy. It is potentially a useful tool for applications that require many model runs or long simulation durations.
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ItemDefect detection of concrete using ultrasonic pulse velocity and impact echo( 2019)It has been known that concrete is one of the most important construction materials used in building industry. However, the internal defects, such as cracks and voids, can significantly affect the durability of concrete, ultimately the service-life of the structures. Therefore, the development of advanced non-destructive testing technologies becomes increasingly important. By performing experiments in conjunction with the development of theoretical models, the purpose of this study is to conduct concrete defect detection using Ultrasonic Pulse Velocity (UPV) and Impact Echo (IE) technologies. First, a series experimental studies were carried out by using concrete blocks with different defect characteristics (e.g. size and location). Then, both UPV and IE techniques were used for defect detection and the results were compared. Finally, FEM model was developed to further understand the fundamental mechanism of UPV in defect detection. It shows that the numerical simulation results can accurately capture the defect characteristics of concrete specimens. Through the comparison of the measurement results from UPV and IE, it demonstrates that UPV method could provide a more effective and reliable way for concrete internal defect detection through measuring the time taken by a pulse of ultrasonic wave passing through the samples. However, the frequency of the compression waves has to be carefully chosen in order to identify the defects in an efficient and accurate manner.
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ItemNovel approaches to investigate the complex interactions of bioturbation and clogging in the hyporheic zone( 2018)Bioturbation activity by macroinvertebrates in freshwaters may influence the hyporheic exchange processes in river systems. In this study, I focus on understanding the complex interaction of bioturbation by upward conveyor macroinvertebrates Lumbriculus variegatus and clogging processes in the hyporheic zone through novel methodological approaches. Upward conveyors are bottom feeders which align themselves vertically (heads buried in the sediment with their posterior ends at the surface water interface) and ingest and egest in a way that sediments move vertically upwards. The study aims at investigating (i) the effects of bioturbation on hyporheic flowpath patterns in clogged and unclogged sandy bedforms and (ii) the vertical spatial distribution of bioturbators in clogged sandy bedforms using an experimental setup. There is a paucity of agreed methodology to study the effects of bioturbation on hyporheic exchange processes in flowing waters. Therefore, this study is focused on developing the methods to understand these interactions in the laboratory flume. The above-mentioned objectives were addressed by running a series of dye tracing experiments in a recirculating perspex flume of dimensions 2.5m (L) X 0.2m (W) X 0.3m (H) filled with triple washed sand of 0.2mm mean particle size. The sand bed was later clogged with clay particles of 0.002mm to compare the flowpaths in clogged and unclogged bed conditions. Using image analysis of the injected dye flowpaths and X-ray technology for understanding the galleried structures created by the bioturbators we are able to better understand the role of these organisms in clogged river beds and their importance in the hyporheic exchange processes. Galleries were imaged using the micro-CT scans by taking core samples along the flume and scanning the top 5 cm of the core. This study can help us understand the need and importance to protect the bioturbator communities for maintaining ecosystem services and healthy functioning of the hyporheic zone.
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ItemInvestigating the benefits of considering the payload spectra of freight vehicles on pavement costs based on weigh-in-motion data( 2017)Truck traffic is a crucial factor that contributes to pavement damage. The urbanization and globalization promote the higher level of daily consumption for goods, thus increasing the derived demand for freight transport. In some countries, such as Australia, there is a trend towards using larger vehicles, which raised the road authorities’ concern about their effect on pavement because of the lack of pavement maintenance and rehabilitation funding. Therefore, it is important to have a comprehensive understanding of Australian road freight market and optimize the allocation of freight for different types of trucks to reduce the total pavement damage. Weigh-in-motion (WIM) system, which measures and records detailed vehicle information operating on road, was the data source for this study. The data was provided by the State Road Authority of Victoria (VicRoads). This thesis gave out a prototype filtering strategy for WIM database to improve the accuracy. Also, it investigated the efficiency of freight transport by comparing the effect of six-axle semi-trailers and nine-axle B-doubles with regards to pavement performance when carrying various payloads. Mathematical models were developed to help decision makers consider how to distribute the road freight task more efficiently to minimize the pavement damage induced by freight vehicles. A simplified pavement performance prediction model was utilized as a basis to determine the future pavement maintenance & rehabilitation schedules and thus, help compare the long-term pavement treatment costs for different traffic loading scenarios. The outcomes of the research showed that it would have considerable advantages in reducing the overall pavement damage by decreasing the percentage of empty trucks, changing the proportion of freight carried by B-doubles as well as optimizing the payload distributions. In addition, there would be significant benefits in the pavement maintenance & rehabilitation costs over the pavement service life by improving the allocation of freight for trucks.
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ItemAnswering queries for near places( 2017)Communication between people conveniently uses qualitative spatial terms, as shown by the high frequency of vague spatial prepositions such as ‘near’ in natural language corpora. The automatic interpretation of these terms, however, suffers from the challenges of capturing the conversational context in order to interpret such prepositions. This research presents an experimental approach to solicit impressions of near to identify distance measures that best approximate it (nuanced by the type of referent, and contrast sets). The presented model computes topological distances to sets of possible answers allowing a ranking of what is near in a context-aware manner. Context is introduced through contrast sets. The research compares the performance of topological distance, network distance, Euclidean distance, Manhattan distance, number of intersections, number of turns, and cumulative direction change. The aim of this comparison is to test whether a metric distance or topological distance is closer to human cognition, challenging the well-known paradigm of ’topology first, metric second’. The comparison results from our experiments show that topological distance appears to be closer to human perception of nearness than other distance measures only at larger scales, while a metric distance (Euclidean distance or Manhattan distance) is closer to how people perceive nearness in smaller scales. People with different sense-of-direction show no obvious differences in their inclination of the seven distance measures with regard to nearness. This research caters for the interpretation of ‘near’ with granular and local context, and provides a cognitively inspired method to answer near-queries automatically. The findings apply to urban environments and may need further verification in less structured environments.
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ItemMaking the connection: a case study analysis of the public transport network effect in practice( 2017)Public transit mode share in dispersed lower density cities common in North America and Australia is typically low. Except where users are captive, or where the density of activity is so high that congestion is a significant deterrent, transit generally fails to compete with the private car. However, a high proportion of private car use is associated with a range of economic, social and environmental challenges. A number of public transport operational approaches are available to policy makers. The ‘network effect’ is one operating approach specifically aimed at serving the complex travel patterns of dispersed lower density cities. The approach relies on effective transfers between transit modes. In compensation for the inconvenience of transfer, passengers are rewarded with a service providing access to a wide, rather than limited, geographic area. Whilst the theory is well established, analysis of its success in practice is less well researched. Network effect theory would benefit from further research into the relationship between urban density, service levels and rates of transfer between transit modes using real world case studies. Using the case study of the Dandenong railway line in Melbourne and the eastern branch of the Montreal Metro Green line, the thesis addressed three key questions. (i) Is there a level of feeder transit service above or below which we see substantial shifts in the number of people transferring?; (ii) which variables play the greatest role in influencing rates of transfer between transit modes?; and (iii) do subjective attributes of station urban design influence transfer numbers — everything else being broadly equal? Data was collected from transit operators, Australian Bureau of Statistics (ABS), Statistics Canada and by direct observations during field visits. An empirical quantitative approach was used to address question (i), a hierarchal linear multiple regression statistical approach used to address question (ii), whilst a quantitative approach was used for question (iii). It was found that where fewer than 100 feeder bus services operated per weekday day, limited transferring will occur, regardless of urban density. However, it was additionally found that frequent, connected services alone will not guarantee high rates of transfer. Evidence suggests direct bus routes, accessing stations at right angles to rail lines, are strongly correlated with higher rates of transfer, again regardless of density. The findings will be important for transit agencies looking to benefit from the theoretical advantages of the network effect. The results are particularly relevant to transport planners in Melbourne and Montreal where the Melbourne Metro and Reseau Electric Metropolitan (REM) projects will require substantial passenger access via feeder bus to achieve their patronage forecasts.
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ItemIdentifying drivers of streamflow salinity in data-limited catchments( 2016)Salinisation of water and land is a serious problem affecting global environment, economy and food security. The strategies to mitigate salinity problem require an improved understanding of the factors causing it. This requires exploring the variability of streamflow salinity, which is an indicator of catchment salinity and highly variable in space and time. Previous research has focused on estimating streamflow salinity through a variety of models that are usually data-intensive, site specific and do not have wider applicability. The arid and semi-arid regions of the world, which are worst affected by the salinity problem, have data-limitations and commonly cannot support calibration of complex models. Therefore, a simple approach in analysis is required. This research project developed a simple approach for assessing the variability of streamflow salinity in data-limited catchments. This aim was achieved by developing a data-based approach to identify drivers of spatial and temporal variability of streamflow salinity. The spatial variability of streamflow salinity was analysed with the help of two methods. The first method used the Budyko curve to classify study catchments between the less-saline catchments and the catchments at risk of salinity. The Budyko curve analysis identified the long-term annual catchment water balance and climate as the main drivers of the spatial variability of streamflow salinity. The second method applied a statistical analysis and identified five drivers of streamflow salinity. These drivers are climate, topography, land-use, streamflow characteristics and mean annual evapotranspiration. The statistical model used long-term climate data and catchment static metrics. The catchment static metrics were derived from data on topography, climate, land-use and land-cover, geology, streamflow and salinity for the characterisation of study catchments. The 78 study catchments were projected into a physiographic space using the principal component analysis. This analysis was based on the catchment static metrics significantly associated with streamflow salinity. The statistical models involved ordinary least squares regression and inverse distance weighting interpolation method as the tools for prediction in the study region. The temporal variability in streamflow salinity was analysed at an annual and monthly time steps using a catchment water balance. It was demonstrated that catchment water balance is the driver of temporal variability in streamflow salinity based on the observed data. The Budyko curve and the Zhang et al. (2001) model were used to assess the inter-annual variability in the average streamflow salinity. A simple Thornthwaite-type monthly catchment water balance was used to explore the seasonal variations in streamflow salinity on time-series plots. However, no significant relationship between monthly water balance and streamflow salinity was detected on an ‘x-y’ scatter plot for all the study catchments, This is mainly due to uncertainty in data inputs, model error, the time-lag effect and bias in the observed streamflow salinity data. A simple data-driven approach was developed to analyse drivers of the spatial and temporal variability in streamflow salinity. This approach is suitable for data-limited catchments. The Budyko curve has the potential to explain both the spatial (geographical) as well as temporal (inter-annual) variability in the average annual streamflow salinity. The variability in streamflow salinity is derived by climate, catchment water balance and physical attributes of catchments. Most of these drivers are natural processes except for changes in land use. Therefore, the management of catchment water balance through vegetation management (e.g. reafforestation) is a practical measure to mitigate the salinity problem.
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ItemExploring susceptibility to use demand responsive transport (DRT)( 2016)Shared transportation providing point-to-point services on demand, although not an unknown element in urban mobility, has started gaining more presence with growth of information technology in the transport sector. These forms of transport modes will supplement or compete with existing public and private transport. Their mixed reception in the past is a matter of concern especially before making investment decisions. To find feasible opportunities of implementation, an estimation of the demand patterns in the target city is desirable. This research provides and evaluates a methodology for this estimation that avoids ambivalent and expensive user surveys. Demand patterns are caused by the spatial variation of socio-economic and demographic characteristics, family structures, and travel behavior over the city. Thus, the new methodology takes into account the use of socio-economic and demographic data and current trip data from travel surveys of a sample of the population, along with usage patterns of existing similar services elsewhere in the world. Demographic factors such as gender, age, occupation, income, household structure, motor vehicle ownership, and driving licence availability together with trip characteristics such as current trip purpose, walking time, and waiting time can be analyzed to come up with demand patterns, and their variation in the city. Usage patterns from existing similar services worldwide are then used to explore the overall spatial pattern of susceptibility of DRT in a target city. The outcomes identify more favorable areas for implementation of DRT. The methodology can be validated by applying it on existing transport modes in the target city which will also help in understanding the nature of competition among the proposed and existing transport modes. As the review of operating services is generic, it can be used in conjunction with respective travel surveys in different places. Similarly, review can be done for any proposed transport mode, and provided methodology can be applied for exploring demand patterns. The methodology is tested for Greater Melbourne in this study. Further, synthetic population is created at household and person levels for Greater Melbourne. PopSynWin, which is based on Iterative Proportional Fitting (IPF) algorithm, and PopGen, which is based on Iterative Proportional Update (IPU) algorithm, are used as tools for this purpose, generating two different synthetic populations. Both the generated populations are compared statistically, and the better one is used to assign travel diaries from sample travel surveys for a study region. The methodology to explore the susceptibility to use DRT, provided in this research, is applied on individual travel diaries to further explore demand patterns at a finer granularity.
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ItemRetrieving forest height from TanDEM-X for an Indonesian peat swamp and Australian temperate forests( 2015)Forests are among the most important GHG and carbon sequester. Therefore, quantifying and mapping the carbon or biomass stored in forests is very important for climate change mitigation. However, there is a high uncertainty of carbon estimation using current methods. Accuracy of carbon or biomass estimates can be improved by integrating forest height into the estimation methods. Forest height can in turn be estimated using the elevation of the forest canopy surface created from TanDEM-X radar data, after removing the terrain elevation. In this study, a series of DSMs (digital surface models) from TanDEM-X have been created for three different sites. The first site is a tropical peat swamp forest located in Indonesia, while the remaining two forest sites are temperate forests located in south-eastern Australia. By subtracting the digital terrain models (DTMs) (from LiDAR) from the TanDEM-X DSMs, the canopy height or tree heights within these forests have been estimated. The estimated tree heights have been validated against two reference heights: ground based measurement and LiDAR. For all sites validation results show that tree heights produced from TanDEM-X are underestimates of the reference height. In addition, the magnitude of biases of estimated tree height depends on the forest density with denser forests having less bias than sparser forests. Nonetheless, despite such biases, the estimated tree heights from TanDEM-X are strongly correlated with the reference heights, regardless of the forest density. Therefore, by using linear regression, tree heights from TanDEM-X can be utilised to predict the reference heights. Furthermore, integration of backscattering and coherence into the regression model improved tree height estimation. The tree heights were predicted from TanDEM-X with an accuracy (RMSE) of 1.99 m (6.7%), 1.27 m (6.5%), and 2.33 m (9.6%) for Kapuas, Boona and Gillenbah respectively.
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ItemAnalyses of passive and low energy cooling systems for retrofitting office buildings in Melbourne( 2016)In recent years, concern about the future increase in energy consumption for cooling office buildings due to climate change has motivated the use of alternative cooling technologies. Development of passive and low energy cooling (PALENC) technologies is an example of the efforts being taken to alleviate this concern. Previous researchers have investigated the contribution of PALENC technologies to savings in energy consumption for cooling buildings. Few studies, however, have investigated the cost-effectiveness of applying PALENC technologies in office building retrofits. This study investigates the energy performance and cost-effectiveness of various PALENC technologies for retrofitting a typical office building in Melbourne. The first part of this study examines the energy performance and financial evaluation of PALENC technologies using literature based analysis. The following PALENC technologies were initially explored: a) passive design features; b) night ventilation; c) ground cooling; d) direct and indirect evaporative cooling; e) night sky radiative cooling; f) chilled beam (radiant ceiling cooling) and g) slab cooling. Two most cost-effective PALENC technologies suitable for retrofitting a typical office building in Melbourne, namely passive design features and indirect evaporative cooling were identified. The second part of this research investigates the potential energy saving of selected passive designs features including shading instalment and window replacement. The investigated shading strategies were horizontal overhangs for north-, east- and west-facing windows and vertical fins for west- and east-facing windows. Four types of window glazing were investigated as window replacement strategies: single clear, single reflective, lowE double glazing and lowE plus reflective double glazing. TRNSYS simulations showed that installing external shading devices on a typical commercial office building in Melbourne can save cooling energy consumption by 0.6%–11%, depending on the type and orientation of the shading device applied. The energy performance of the different window types showed that the cooling energy reduction yielded by the reflective single glazing window is about 25%. The results of financial analysis showed that all of the selected passive design strategies have higher costs of conserved energy (CCEs), compared to the current cost of supplied electricity in Melbourne. The third part of this study, investigates the energy and financial performance of indirect evaporative cooling (IEC) combined with selected passive design features for retrofitting a typical office building in Melbourne. TRNSYS simulations showed 60% saving in electricity consumption as compared to the conventional cooling system. The financial analysis using levelised cost of cooling (LCOC) indicated that replacing the current conventional cooling system with an IEC is cost-effective only if the current cooling system is in poor condition and needed to be replaced by a new one. It was also found that LCOC for applying IEC in combination with selected passive design strategies is higher than the LCOC for applying the conventional vapour compression cooling system for a typical office building retrofit in Melbourne.