Infrastructure Engineering - Research Publications
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ItemArtificial neural networks for predicting the performance of heat pumps with horizontal ground heat exchangers(Frontiers Media SA, )A Ground Coupled Heat Pump (GCHP) is a highly energy efficient heating, ventilation, and air conditioning (HVAC) system that utilises the ground as the heat source when heating and as the heat sink when cooling. This paper investigates GCHP systems with horizontal Ground Heat Exchangers (GHEs) in the rural industry, exemplifying the technology for poultry (chicken) sheds in Australia. This investigation aims to provide an Artificial Neural Network (ANN) model that can be used for GCHP design at various locations with different climates. To this extent, a Transient System Simulation Tool (TRNSYS) model for a typical horizontal GHE applied in a rural farm was first verified. Using this model, over 700,000 hourly performance data items were obtained, covering over 80 different yearly loading patterns under three different climate conditions. The simulated performance data was then used to train the ANN. As a result, the trained ANN can predict the performance of GCHP systems with identical (multiple) GHEs even under climatic conditions (and locations) that have not been specifically trained for. Unlike other works, the newly introduced ANN model is accurate even with limited types of input data, with high accuracy (less than 5% error in most cases tested). This ANN model is 100 times computationally faster than TRNSYS simulations and 10,000 times faster than finite element models.
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ItemDevelopment and validation of a transient simulation model of a full-scale PCM embedded radiant chilled ceiling(TSINGHUA UNIV PRESS, 2023-06)Abstract The recent significant rise in space cooling energy demand due to the massive use of air-conditioning systems has adversely changed buildings’ energy use patterns globally. The updated energy technology perspectives highlight the need for innovative cooling systems to address this growing cooling demand. Phase change material embedded radiant chilled ceiling (PCM-RCC) has lately acquired popularity as they offer more efficient space cooling together with further demand-side flexibility. Recent advancements in PCM-RCC applications have increased the necessity for reliable simulation models to assist professionals in identifying improved designs and operating settings. In this study, a transient simulation model of PCM-RCC has been developed and validated using measured data in a full-scale test cabin equipped with newly developed PCM ceiling panels. This model, developed in the TRNSYS simulation studio, includes Type 399 that uses the Crank-Nicolson algorithm coupled with the enthalpy function to solve transient heat transfer in PCM ceiling panels. The developed model is validated in both free-running and active operation modes, and its quality is then evaluated using several validation metrics. The results obtained in multiple operating scenarios confirm that the model simulates the transient behaviour of the PCM-RCC system with an accuracy within ±10%. Aided by this validated model, which offers the user detailed flexibilities in the system design and its associated operating schemas, PCM-RCC’s potentials regarding peak load shifting, energy savings, and enhanced thermal comfort can be investigated more reliably.
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ItemAssessing the opportunity for producing hemp-based insulation in the Australian market(EJSE International, 2024-04-29)By-products (wastes or residues) of renewable materials have the potential to be manufactured into higher value fibre insulation products for the Australian market. Currently, such products have been imported for servicing the Australian market. This presents a potential opportunity to divert considerable quantities of waste from landfill and produce a high performance, locally made, low carbon, natural fibre insulation product for the Australian domestic and commercial building industry. This article assesses the hemp-based bulk insulations available in the Australian market.
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ItemMechanical properties and life cycle greenhouse gas analysis of textile waste fibre-based concrete(Elsevier BV, 2024-05-17)The application of textile waste as an aggregate in concrete enhances sustainability in construction and promotes circular economy. This work develops a novel fibre-based concrete incorporating textile waste fibres. The experiments showed that including textile waste fibres reduces flowability of concrete and improves its tensile and compressive strengths, alongside strain resistance. The fibres enhance concrete’s ductility and resilience against environmental damage. Textile waste fibre exhibits a lower greenhouse gas emissions compared to other non-polymer fibres. This work emphasises the benefits of textile waste in enhancing construction sustainability and highlights the need for expanded exploration.
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ItemSizing behind-the-meter solar PV for pumped water distribution systems: A comparison of methods(Elsevier BV, 2024-01-01)Water distribution systems (WDSs) are vital urban infrastructure systems. To meet increasing pumping energy demands and minimise environmental impacts, behind-the-meter (BTM) solar photovoltaic (PV) systems have been considered by water utilities. However, there currently is not a systematic approach to size BTM solar PV for WDSs, considering the life cycle performance of the integrated systems. This study evaluates three methods to size BTM solar PV in pumped WDSs: 1) the heuristic method developed from current industry practice; 2) the minimum total life cycle cost (TLCC) method based on the system minimum TLCC; and 3) the minimum payback method to minimise the time needed to pay off the solar capital investment. The performance of the integrated water-solar system has been assessed against economic, energy and emissions performance metrics using two case studies. The results indicate that the heuristic method leads to the largest solar PV size, potentially oversizing the system. The minimum payback method leads to the smallest solar PV system, potentially under-sizing the system. The minimum TLCC method leads to more balanced system performance, but the solar PV size determined using this method is sensitive to the discount rate used. The insights into the performance of the system sized using the three methods provide decision-makers guidance to select appropriate solar PV systems for WDSs.
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ItemHigh water use plants influence green roof substrate temperatures and their insulative benefits(Elsevier BV, 2023-12-01)Green roofs are amongst the solutions employed to deliver sustainable buildings in cities. Their vegetation and substrate layers can reduce the heat transfer through the roof, thus potentially reducing energy used for building cooling and heating. However, little research has investigated the insulative properties of drought-tolerant plants which also have high water use. These plants have been found to improve runoff retention by removing larger volumes of water from the substrate through higher transpiration rates than succulents. This planting strategy may also enhance green roof cooling performance due to their greater evapotranspiration rates. In this study, the thermal performance of three drought-tolerant species with high water use — Lomandra longifolia, Dianella admixta, and Stypandra glauca — was evaluated and compared with a commonly used succulent species (Sedum pachyphyllum) and a bare unplanted module. L. longifolia had the best insulative performance during the entire investigated period, reducing green roof substrate surface temperature up to 1.86 °C compared to succulent S. pachyphyllum. In summer, the mixture reduced heat gain to a greater extent than monoculture plantings of all species except L. longifolia. Summer measurements also suggest that plants with high leaf area index (LAI) and higher albedo should be selected to reduce surface temperatures. High evapotranspiration rates of high water use L. longifolia led to greatest reduction of bottom surface temperatures during a heatwave when decreasing its water content from 18.5% to 2.9%. Results obtained using an analytical hierarchical partitioning technique indicated air temperature had the most significant impact on temperatures at both the surface of the planting substrate and the bottom of each green roof unit, accounting for 48% to 58% of the variation.
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ItemThe carbon footprint of treating patients with septic shock in the intensive care unit(College of Intensive Care Medicine of Australia and New Zealand, 2018-12-01)OBJECTIVE: To use life cycle assessment to determine the environmental footprint of the care of patients with septic shock in the intensive care unit (ICU). DESIGN, SETTING AND PARTICIPANTS: Prospective, observational life cycle assessment examining the use of energy for heating, ventilation and air conditioning; lighting; machines; and all consumables and waste associated with treating ten patients with septic shock in the ICU at BarnesJewish Hospital, St. Louis, MO, United States (US-ICU) and ten patients at Footscray Hospital, Melbourne, Vic, Australia (Aus-ICU). MAIN OUTCOME MEASURES: Environmental footprint, particularly greenhouse gas emissions. RESULTS: Energy use per patient averaged 272 kWh/day for the US-ICU and 143 kWh/day for the Aus-ICU. The average daily amount of single-use materials per patient was 3.4 kg (range, 1.0-6.3 kg) for the US-ICU and 3.4 kg (range, 1.2-8.7 kg) for the Aus-ICU. The average daily particularly greenhouse gas emissions arising from treating patients in the US-ICU was 178 kg carbon dioxide equivalent (CO2-e) emissions (range, 165-228 kg CO2-e), while for the Aus-ICU the carbon footprint was 88 kg CO2-e (range, 77-107 kg CO2-e). Energy accounted for 155 kg CO2-e in the US-ICU (87%) and 67 kg CO2-e in the Aus-ICU (76%). The daily treatment of one patient with septic shock in the US-ICU was equivalent to the total daily carbon footprint of 3.5 Americans' CO2-e emissions, and for the Aus-ICU, it was equivalent to the emissions of 1.5 Australians. CONCLUSION: The carbon footprints of the ICUs were dominated by the energy use for heating, ventilation and air conditioning; consumables were relatively less important, with limited effect of intensity of patient care. There is large opportunity for reducing the ICUs' carbon footprint by improving the energy efficiency of buildings and increasing the use of renewable energy sources.
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ItemComparison of waste photovoltaic panel processing alternatives in Australia(Elsevier BV, 2023-09-15)This work aims to compare end-of-life (EoL) alternative processing scenarios of waste photovoltaic panel in Australia. Landfill, generic waste electrical and electronic equipment recycling (European business-as-usual (EU BAU)), full-recovery EoL photovoltaic (FRELP), and Modified FRELP are the alternative processing scenarios considered for the next five years. Environmental analysis by a simplified life cycle assessment is performed using Material, Energy, Chemical, and Other (MECO) matrix. This semi-quantitative comparison eliminates reliance on LCA software and environmental expertise for preliminary screening. Financial analysis is also performed by using a life cycle costing (LCC) approach. Overall, comparative findings are consistent with full-quantitative LCA and LCC despite magnitude differences. Simplified analysis merely reflects process complexity and resource consumption. A full financial insight can only be acquired when non-resource-derived costs are incorporated. Considering the increasing trend of waste levies and landfill ban extending into the future, landfill is no longer the cheapest option in Australia. Consequently, mass-based waste recovery for landfill diversion facilitates cost savings. Recovering 8% more waste with FRELP compared to modified FRELP has the potential to save $19 more per tonne of processed PV waste. EU BAU is the most eco-efficient interim solution, while waste volume is still low. Modified FRELP saves 321 kg CO2-e emission by avoiding traditional incineration. The focus on reclaiming solar-grade silicon rather than silver has the potential to attract $154 more revenue per tonne compared to FRELP.
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ItemEfficient HVAC system identification using Koopman operator and machine learning for thermal comfort optimisation(Elsevier BV, 2023-08-15)The aim of this article is to improve the efficiency of heating, ventilation, and air conditioning (HVAC) systems by using a linear control approach. Conventional HVAC systems use a wall thermostat and a simplified ON/OFF controller to condition the thermal environment, but this approach is not always efficient in meeting indoor heat loads. To address this issue, we propose using the Koopman operator combined with Machine Learning, a linear embedding method, to model the nonlinear behaviour of thermal comfort indices. Specifically, we use the Predictive Mean Vote (PMV) index, which has been a superior indicator of occupants’ thermal sensation. We apply Computational Fluid Dynamics to create high-dimensional training, testing, and validation datasets, and a deep autoencoder network framework to map the original nonlinear coordinates of the PMV index into a latent space where the system is behaving linearly. Our results show that the Koopman autoencoder can reproduce and predict data from the latent space, enabling offline system identification for the zone thermal conditions and this has the potential to improve HVAC feedback control systems.