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Highlights • Simple lumped surrogate models can emulate the behaviour of high-fidelity models. • States and simulation time is reduced by 3 and 6 orders of magnitude, respectively. • The surrogate models are robust to type of training data and sensitive to model scale. • The surrogate models can be fitted to both warning, RTC, and planning applications. • Uncertainty of surrogate models are within acceptable ranges. Abstract Distributed physically based models (DPMs) have become the standard tool for urban drainage modelling. However, high computational demands limit these in applications where fast or multiple simulations are needed. This paper presents simple fit-for-purpose cheaper-to-run surrogate models (SMs) for pipe network simulations which are validated against a DPM. The SMs are set up by lumping the DPM network into compartments in which the volume of water is governed by mass balances. Outgoing discharges to downstream compartment(s) and surcharging are computed from unambiguous volume-discharge curves. The SMs are applied on a 45 km2 catchment, Elster Creek in Melbourne, Australia. The number of simulated states and simulation times are reduced by approximately 3 and 6 orders of magnitude, respectively. Different SM complexities are examined. The simplest SM using steady state training data performed well with NSE of 0.98 for volume in the most upstream compartment. When emulating the aggregated surcharge from that compartment, the SM captured all surcharge events correctly. NSE improved from 0.35 to 0.84 when subdividing the compartment into 17 subcompartments. Uncertainty of SM parameters was examined using the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. Two different sampling methods were applied. Limits of acceptability for real-time control, warning and planning, resulted in many accepted models upstream and few to none in downstream backwater-prone areas. All applications showed SM uncertainty bands within expected uncertainty bands for DPM, supporting the use of a simpler conceptual model in fit-for-purpose modelling in urban water systems when computational demands of DPMs are prohibitive. [ABSTRACT FROM AUTHOR]

In this paper we present Ace Mod, an agent-based modelling framework for studying influenza epidemics in Australia. The simulator is designed to analyse the spatiotemporal spread of contagion and influenza spatial synchrony across the nation. The individual-based epidemiological model accounts for mobility (worker and student commuting) patterns and human interactions derived from the 2006 Australian census and other national data sources. The high-precision simulation comprises 19.8 million stochastically generated software agents and traces the dynamics of influenza viral infection and transmission at several scales. Using this approach, we are able to synthesise epidemics in Australia with varying outbreak locations and severity. For each scenario, we investigate the spatiotemporal profiles of these epidemics, both qualitatively and quantitatively, via incidence curves, prevalence choropleths, and epidemic synchrony. This analysis exemplifies the nature of influenza pandemics within Australia and facilitates future planning of effective intervention, mitigation and crisis management strategies. [ABSTRACT FROM AUTHOR]

This paper evaluates and compares the system performance of a solar desiccant-evaporative cooling (SDEC) system with a referenced conventional variable air volume (VAV) system for a typical office building in all 8 Australian capital cities. A simulation model of the building is developed using the whole building simulation software EnergyPlus. The performance indicators for the comparison are system coefficient of performance (COP), annual primary energy consumption, annual energy savings, and annual CO 2 emissions reduction. The simulation results show that Darwin has the most apparent advantages for SDEC system applications with an annual energy savings of 557 GJ and CO 2 emission reduction of 121 tonnes. The maximum system COP is 7. For other climate zones such as Canberra, Hobart and Melbourne, the SDEC system is not as energy efficient as the conventional VAV system. [ABSTRACT FROM AUTHOR]

Australia’s agriculture industry, particularly in the north, is characterised by supply chains of long travel distances, often in excess of 2500 km and costing up to 35% of farm gate price. Such travel distances increase the vulnerability of the industry to climatic variability and extreme events. Infrastructure investments in roads, bridges, processors and storage, along with changes in policy, have the potential to substantially reduce costs and increase resilience of the agriculture industries. In this paper, we outline the model, TRAnsport Network Strategic Investment Tool (TRANSIT) which is based on ArcGIS, and utilizes the Origin to Destination Cost Matrix solver within the Network Analyst toolkit. TRANSIT estimates the transport costs for all movements between enterprises, accommodating road conditions, vehicle types, vehicle access restrictions and regulatory requirements. TRANSIT was applied to the northern Australia livestock industry, consisting of 12 million cattle across 10,000 enterprises and 89,000 unique trips between these enterprises. Its ability to estimate the transport benefits from road upgrades, new processing facilities and biosecurity changes are shown using three priority case studies identified by industry and government. [ABSTRACT FROM AUTHOR]

In assessing the energy efficiency of a house design, particularly methods incorporating building performance simulation, assumptions are made about how the occupants operate the building. Often these assumptions are standardised to simplify the assessment process with the intention of enabling a straight forward comparison between designs. Assessment of performance using standardised operations may pose a disadvantage to house designs that are intended for households who are likely to operate the house outside of the assumed norm. This paper examines occupant behaviour in low energy houses in the context of the Australian regulatory house energy rating scheme and, using simulation, demonstrates the impact of alternative occupancy settings on the validity of the predicted house energy rating. The results clearly show that current occupant assumptions within the scheme fail to adequately reflect actual heating and cooling practices in low energy dwellings and, as such, overestimate energy consumption within these households. Based on these results it is suggested that, for equitable assessment of these households, settings within the simulation engine used for assessment must be modified to align with actual user behaviour. [ABSTRACT FROM AUTHOR]

City-scale simulation modelling of active modes of transportation (i.e., walking and cycling) is becoming increasingly popular in recent years. The heterogeneous and complex behaviour of these transportation modes, however, indicates the need for a shift from the traditional car and public transport centred modelling approaches towards incorporating the requirements for walking and cycling behaviour, while maintaining the run-time efficiency of the models. In this paper, we introduce and test our algorithm to create road network representations, designed and optimised to be used in city-scale active transportation modelling. The algorithm relies on open and universal data. In addition to the major roads and attributes typically used in transport modelling (e.g., speed limit, number of lanes, permitted travel modes), the algorithm also captures minor roads usually favoured by pedestrians and cyclists, along with road attributes such as bicycle-specific infrastructure, traffic signals, road gradient and road surface type. Furthermore, it simplifies the complex geometries of the network and merges parallel roads, if applicable, to make it suitable for large-scale simulations. To examine the utility and performance of the algorithm, we used it to create a network representation for Greater Melbourne, Australia, and compared the output with a network created using an existing simulation toolkit along with another network from an existing city-scale transport model from the Victorian government. Through simulation experiments with these networks, we illustrated that for routed trips on our network for walking and cycling, it is of comparable accuracy to the common network conversion tools in terms of travel distance of the shortest paths while being more than two times faster when used for simulating different sample sizes. Therefore, our algorithm offers a flexible and adjustable solution for users to create road networks for city-scale active transport modelling while balancing between their desired simulation accuracy and run-time. • We developed an algorithm to generate road networks for city-scale transport models. • Our algorithm captures road attributes important for walking and cycling simulation. • We compared our network to two common networks types in transport modelling. • Our approach provides a good balance between accuracy and simulation run-time. [ABSTRACT FROM AUTHOR]