Infrastructure Engineering - Research Publications
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ItemA review of augmented reality visualization methods for subsurface utilities(Elsevier BV, 2022-01-01)Subsurface utilities are important assets that need to be perceived during any construction activities. Positioning and visualizing the subsurface utilities before the construction work starts has significant benefits for the effective management of construction projects. Augmented Reality (AR) is a promising technology for the visualization of subsurface utilities. The aim of this paper is to provide a comprehensive review of the state-of-the-art in AR visualization of subsurface utilities, including existing AR visualization methods, categorization of the methods and their drawbacks, comprehensive discussion on the challenges, research gaps and potential solutions. The paper begins with an introduction of current practice of locating subsurface utilities and an overview of different reality technologies including AR. We propose a taxonomy of AR visualization methods including X-Ray view, transparent view, shadow view, topo view, image rendering and cross-section view. We provide a comparison of existing methods in terms of quality of depth perception, occlusion of real world, complexity of visualization and parallax effect followed by a discussion of the drawbacks in these methods. Poor depth perception, parallax effect caused by the user movement, poor positional accuracy in Global Navigation Satellite System (GNSS) deprived or indoor areas and unavailability of accurate location information for generating virtual models are identified as main challenges and topics of future research in effective AR visualization of subsurface utilities.
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ItemCorrigendum to “A review of augmented reality visualization methods for subsurface utilities” [Adv. Eng. Inf. 51 (2022) 101498] (Advanced Engineering Informatics (2022) 51, (S1474034621002470), (10.1016/j.aei.2021.101498))(Elsevier BV, 2022-01-01)The authors regret, Our article that was published in the previous issue of the journal contains incorrect citations to research work in a few places. The correct reference should be 140. Hansen, L.H.; Fleck, P.; Stranner, M.; Schmalstieg, D.; Arth, C. Augmented Reality for Subsurface Utility Engineering, Revisited. IEEE Transactions on Visualization and Computer Graphics 2021, 27, 4119–4128. Instead of 140. Piroozfar, P.; Judd, A.; Boseley, S.; Essa, A.; Farr, E.R. Augmented reality for urban utility infrastructure: a UK perspective. In Collaboration and Integration in Construction, Engineering, Management and Technology; Springer: 2021; pp. 535–541. Additionally, Figure 20 should be referenced as 37. Eren, M.T.; Balcisoy, S. Evaluation of X-ray visualization techniques for vertical depth judgments in underground exploration. The visual Computer 2017, 34, 405–416, https://doi.org/10.1007/s00371-016-1346-5. Instead of 62. Doolani, S.; Wessels, C.; Kanal, V.; Sevastopoulos, C.; Jaiswal, A.; Nambiappan, H.; Makedon, F. A Review of Extended Reality (XR) Technologies for Manufacturing Training. Technologies 2020, 8, https://doi.org/10.3390/technologies8040077. And Figure 21 should be referenced as 144. Baek, J.-M.; Hong, I.-S. The Design of an Automatically Generated System for Cross Sections of Underground Utilities using Augmented Reality. International Journal of Smart Home 2013, 7, 255–264, https://doi.org/10.14257/ijsh.2013.7.6.25. Instead of 64. Chuah, S.H.-W. Why and who will adopt extended reality technology? Literature review, synthesis, and future research agenda. Literature Review, Synthesis, and Future Research Agenda (December 13, 2018) 2018. The authors would like to apologise for any inconvenience caused.
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ItemRequirements of a data storage infrastructure for effective land administration systems: case study of Victoria, Australia(TAYLOR & FRANCIS LTD, 2022-01-27)Land administration systems are being modernised to streamline the cadastral data lodgement. However, in many jurisdictions, cadastral data are still stored as a flat file. This method of data storage has significant limitations in terms of effective access, management, query, and analysis of cadastral data. Therefore, this study elicited the requirements and proposed an approach to automate the cadastral data storage. The proposed approach was successfully implemented within the land registry organisation in Victoria, Australia and the database management system was rigorously tested. The outcomes can potentially contribute to the implementation of a similar data storage infrastructure in other jurisdictions.
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ItemExperimental and Analytical Investigation of a RC Wall with a Gabion Cushion Subjected to Boulder Impact(PERGAMON-ELSEVIER SCIENCE LTD, 2021-05-31)An experimental investigation involving the use of a full-scale pendulum device to deliver solid object impact on a reinforced concrete (RC) barrier specimen that was fitted with a layer of gabion cushion is reported in this paper. The deflection behaviour of the stem wall of the RC barrier including the tensile strains developed in the longitudinal reinforcement was of interests. Results recorded from the tests are compared with results from control experiments which were without the protection of any cushion materials. The introduction of a layer of cushion is shown to be able to have the contact force reduced by more than 95% and deflection demand reduced by about 70%. An analytical procedure employing the Hunt and Crossley contact model, Swiss code model and two-degrees-of-freedom (2DOF) system modelling technique is presented for calculating the flexural response behaviour of the cushioned barrier and validated by comparison with experimental measurements. An important outcome from the study is a simple hand calculation procedure featuring the use of a closed form expression along with a design chart which is illustrated by a worked example, to facilitate uptake in design practices.
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ItemA multi-model approach to assessing the impacts of catchment characteristics on spatial water quality in the Great Barrier Reef catchments(ELSEVIER SCI LTD, 2021-05-14)Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water quality; and b) to predict spatial variability in water quality more reliably and robustly. Tropical catchments in the Great Barrier Reef (GBR) area, Australia, were used as a case study. We developed statistical models using 58 catchment characteristics to predict the spatial variability in water quality in 32 GBR catchments. An exhaustive search method coupled with multi-model inference approaches were used to identify important catchment characteristics and predict the spatial variation in water quality across catchments. Bootstrapping and cross-validation approaches were used to assess the uncertainty in identified important factors and robustness of multi-model structure, respectively. The results indicate that water quality variables were generally most influenced by the natural characteristics of catchments (e.g., soil type and annual rainfall), while anthropogenic characteristics (i.e., land use) also showed significant influence on dissolved nutrient species (e.g., NOX, NH4 and FRP). The multi-model structures developed in this work were able to predict average event-mean concentration well, with Nash-Sutcliffe coefficient ranging from 0.68 to 0.96. This work provides data-driven evidence for catchment managers, which can help them develop effective water quality management strategies.
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ItemNo Preview AvailableAdaptive conservative time integration for transport in fractured porous media(Elsevier BV, 2022-07-01)
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