Infrastructure Engineering - Research Publications

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    Emergency
    McNiven, B ; Aye, L ; Holzer, D (Australian Institute of Refrigeration, Air Conditioning and Heating (AIRAH), 2022-10-31)
    As part of the i-Hub project, masters-level architectural and engineering students from the University of Melbourne, industry consultants, university academics, and Ambulance Victoria staff embraced the challenge of designing net zero emergency response stations. The university’s Brendon McNiven; Lu Aye, F.AIRAH; and Dominik Holzer discuss.
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    Sustainability and circular economy as part of strategic goals of businesses in Australia: Preliminary findings
    Pilipenets, O ; Hui, K ; Gunawardena, D ; Mendis, P ; Aye, L (Department of Infrastructure Engineering, 2022-09-27)
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    Exploring policy mixes for low-carbon and just energy transitions systems: An Australian case
    Rojas Arevalo, A ; de Haan, F ; Candy, S ; Foliente, G ; Aye, L (DUMU, 2022-11-09)
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    Virtual element retrieval in mixed reality
    Radanovic, M ; Khoshelham, K ; Fraser, C (Copernicus GmbH, 2022-05-17)
    Abstract. The application of mixed reality visualisation in construction engineering requires accurate placement and retrieval of virtual models within the real world, which depends on the localisation accuracy. However, it is hard to understand what this means practically from localisation accuracy alone. For example, when we superimpose a Building Information Model (BIM) over the real building, it is unclear how well does a BIM element fit the real one and how small a BIM element are we able to retrieve. In this paper, we evaluate virtual element retrieval by designing an experiment where we attempt to retrieve a set of cubes of different sizes placed in both the real and the virtual world. Furthermore, inspired by existing camera localisation methods for indoor MR being almost exclusively image-based, we use a localisation approach based solely on 3D-3D model registration. The approach is based on the automated registration of a low-density mesh model of the surroundings created by the MR device to the existing point cloud of an indoor environment. We develop a prototype and perform experiments on real-world data which show high localisation accuracy, with average translation and rotation errors of 1.4 cm and 0.24°, respectively. Finally, we show that the success rate of virtual element retrieval is closely related to the localisation accuracy.
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    Projected wave climate of Bass Strait and south-east Australia by the end of the twenty-first century
    Liu, J ; Meucci, A ; Young, IR (SPRINGER, 2022-05-24)
    Abstract A high-resolution third-generation wave model based on unstructured grids, WAVEWATCH III (WW3), was used to study the projected future wave climate of Bass Strait and south-east Australia under two different greenhouse gas emission scenarios (SSP1-2.6 and SSP5-8.5). The wave model, forced with winds from the Australian ACCESS-CM2 Global Climate Model, shows good agreement with coastal long-term buoy observations and an independent WW3 hindcast dataset over the historical period 1985–2014. The projected mean significant wave height ($$H_{s}$$ H s ) for SSP5-8.5 by the end of the twenty-first century (2071–2100) shows a robust increase for the majority of the domain, but a decrease in nearshore regions, mainly due to projected decreases in local wind speed. The increase in $$H_{s}$$ H s for SSP1-2.6 is relatively small. Seasonal variations show that $$H_{s}$$ H s (SSP5-8.5) is primarily influenced by Southern Ocean swell in spring and winter and local winds prevail in summer and autumn. Hs percentiles show a stronger increase in extreme wave climate for SSP5-8.5 than for SSP1-2.6. Extreme value $$H_{s}$$ H s for SSP1-2.6 shows a projected decrease in western regions of the domain and an increase in the east. Extreme value $$H_{s}$$ H s for SSP5-8.5 shows a decrease in the nearshore areas of Victoria. This study shows that projected wave climate changes in south-east Australia may have potential implications for Tasmanian and Victorian coastline stability.
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    Wave breaking probabilities under wind forcing in open sea and laboratory
    Knobler, S ; Winiarska, E ; Babanin, A ; Liberzon, D (AIP Publishing, 2022-03-01)
    Water wave breaking represents one of the most arduous problems in fluid mechanics. Understanding the process of wave breaking and developing an ability to quantify the associated energy losses and redistribution are critical across a wide range of coastal oceanic applications, maritime navigation, and climate and hydrodynamic research. Naturally, waves become steeper toward the inception of breaking; however, there is still a lack of unanimity regarding the relationship between breaking probability statistics and wave steepness. Here, we present a detailed investigation of breaking vs non-breaking statistics estimated using a recently developed method for accurate detection of breaking waves, based on the phase-time approach to identify breaking-associated patterns in the instantaneous frequency variations of surface elevation fluctuations. The findings are based on data collected both in the open sea and in a laboratory wind wave flume. An in-depth examination of celerities and steepnesses of breaking and non-breaking waves is presented. The analysis, which involved wave-by-wave examination, produced skewed Gaussian-like steepness histograms, revealing that non-breaking waves and breaking waves can reach steeper profiles, above the Stokes limit. All extreme steepness values were investigated and are presented here.
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    Forest expansion dominates China's land carbon sink since 1980
    Yu, Z ; Ciais, P ; Piao, S ; Houghton, RA ; Lu, C ; Tian, H ; Agathokleous, E ; Kattel, GR ; Sitch, S ; Goll, D ; Yue, X ; Walker, A ; Friedlingstein, P ; Jain, AK ; Liu, S ; Zhou, G (NATURE PORTFOLIO, 2022-09-13)
    Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China's reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting.
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    Real-time road safety optimization through network-level data management
    Muthugama, L ; Xie, H ; Tanin, E ; Karunasekera, S (Springer Science and Business Media LLC, 2022-01-01)
    Abstract With the increasing connectedness of vehicles, real-time spatio-temporal data can be collected from citywide road networks. Innovative data management solutions can process the collected data for the purpose of reducing travel time. However, a majority of the existing solutions have missed the opportunity to better manage the collected data for improving road safety at the network level. We propose an efficient data management framework that uses network-level data to improve road safety for citywide applications. Our framework uses a graph-based data structure to maintain real-time network-level traffic data. Based on the graph, the framework uses a novel technique to generate driving instructions for individual vehicles. By following the instructions, inter-vehicular spacing can be increased, leading to an improvement of road safety. Experimental results show that our framework improves road safety, measured based on the time to collision between vehicles, from the state-of-the-art traffic data management solutions by a large margin while achieving lower travel times compared with the solutions. The framework is also readily deployable for large-scale real-time applications due to its low computation costs.
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    Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
    Trotter, L ; Knoben, WJM ; Fowler, KJA ; Saft, M ; Peel, MC (COPERNICUS GESELLSCHAFT MBH, 2022-08-26)
    Abstract. The Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) is a flexible modelling framework reproducing the behaviour of 47 established hydrological models. This toolbox can be used to calibrate and run models in a user-friendly and consistent way and is designed to facilitate the sharing of model code for reproducibility and to support intercomparison between hydrological models. Additionally, it allows users to create or modify models using components of existing ones. We present a new MARRMoT release (v2.1) designed for improved speed and ease of use. While improved computational efficiency was the main driver for this redevelopment, MARRMoT v2.1 also succeeds in drastically reducing the verbosity and repetitiveness of the code, which improves readability and facilitates debugging. The process to create new models or modify existing ones within the toolbox is also simplified in this version, making MARRMoT v2.1 accessible for researchers and practitioners at all levels of expertise. These improvements were achieved by implementing an object-oriented structure and aggregating all common model operations into a single class definition from which all models inherit. The new modelling framework maintains and improves on several good practices built into the original MARRMoT and includes a number of new features such as the possibility of retrieving more output in different formats that simplifies troubleshooting, and a new functionality that simplifies the calibration process. We compare outputs of 36 of the models in the framework to an earlier published analysis and demonstrate that MARRMoT v2.1 is highly consistent with the previous version of MARRMoT (v1.4), while achieving a 3.6-fold improvement in runtime on average. The new version of the toolbox and user manual, including several workflow examples for common application, are available from GitHub (https://github.com/wknoben/MARRMoT, last access: 12 May 2022; https://doi.org/10.5281/zenodo.6484372, Trotter and Knoben, 2022b).