Infrastructure Engineering - Research Publications
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ItemMore sustainable agriculture: Energy perspective( 2023-11-27)Invited Lecture, 4th International Conference on Natural Resources Management and Sustainability, Udayana University (UNUD), Bali, Indonesia, 26-30 November 2023
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ItemTransdisciplinary education for multidisciplinary students( 2023-11-14)Distinguished Speaker, Presented at 45th IEOM Global Engineering Education, 2nd Australian Conference on Industrial Engineering and Operations Management, 14-16 November 2023
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ItemNo Preview AvailableDataset - EMA protocol in action: Unlocking Mexico's clean energy potential( 2023-10-26)This dataset presents the outcomes of implementing the exploratory modelling and analysis (EMA) protocol for identifying robust policy mixes for clean energy transitions. The protocol, detailed in Protocol Exchange (https://protocolexchange.researchsquare.com/), is designed to explore the consequences of diverse policy alternatives and multiple uncertainties within energy transitions through computational experiments. EMA, a computational experimentation technique, plays a key role in systematically exploring the potential impacts of various policy alternatives and uncertainties within complex systems, particularly in the energy domain. This publication outlines the application of the EMA protocol in the specific case of Mexico, offering a detailed approach for researchers, policymakers, and energy analysts to explore the complex interactions between policy alternatives and uncertainties in the clean energy transition. The dataset provides insights into how different policy alternatives perform under various conditions, shedding light on their robustness and potential trade-offs. The dataset encompasses the outcomes of an open exploration and directed search processes, along with analytical sub-processes integrated to provide a comprehensive analysis. The results from implementing the EMA protocol offer a valuable resource for decision-makers and researchers seeking to navigate the complex interactions between policy alternatives and uncertainties in energy transitions.
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ItemDesign Tools and Models, IEA Solar Heating and Cooling Task 65, Subtask C(IEA, 2023-08-22)This is the final report on activity C1, “Design tools and models” of the IEA SHC Task 65 “Solar Cooling for the Sunbelt regions”. The work involved reviewing and adapting tools and models for technical and financial assessment and design for solar cooling and the project phases from pre-feasibility to simulation to monitoring. The main focus is the documentation of the tools and their specific application to provide measured data for validating the tools and the adaptation of selected ones for Sunbelt countries. Three approaches are used to evaluate tools used worldwide and this IEA SHC Task. First, a (i) generic literature research in Web of Science (WoS), (ii) interviews and questionnaires among the IEA SHC Task Expert, and (iii) interactive questionnaires during Task expert meetings. A total of 1,216 documents were identified as a result of the search in WoS. The query search string used is ALL=(“solar cooling” OR “solar refrigeration”), and the index dates covered are 1990/01/01-2021/06/30. A network visualization diagram was generated in VOSviewer. A query search string (“solar cooling”) (“design”) AND (“software”) in the topic field produced 38 documents. The initial data gathered provide a general idea of which components are being used and which software is being implemented. Based on the information provided by the task participants, the following software are currently being implemented in their applications/research: MATLAB, Meteonorm + Excel tool, TRNSYS, EES, and Phyton. This is also reflected in the third evaluation of tools. Conclusion: Modelling and assessing the technical and economic behavior of solar cooling plants is essential in all design phases up to implementation and optimization. Different tools are used, from sophisticated dynamic simulation models to simple spreadsheet calculations. Companies and their experts often develop their own for their specific components and systems. Generic publicly available models can be found for almost all applications, especially simulation tools. The configuration and data sheets for the entire tool depend on the approach and are often difficult to find.
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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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ItemWhole-life baseline carbon assessment of residential building stock – A Victorian case study(Australian Life Cycle Assessment Society (ALCAS), 2023-07-19)Assessing residential building decarbonisation opportunities requires a whole-life approach, given the increasing share of embodied carbon as housing becomes more energy efficient. Since most of the projected housing stock would consist of existing buildings, emissions from renovation should also be included in determining both embodied and operational carbon in the residential building sector. A bottom-up typology framework was developed to estimate carbon emissions for existing and new housing up to 2050, scalable from local government area (LGA) to state-level jurisdiction which allows for granularity in testing scenarios for the future. Housing typologies were developed for existing, new, and renovation housing stock based on census data. Operating carbon was obtained using building energy simulation while embodied carbon data was accounted from localised life cycle construction datasets. The state of Victoria along with its corresponding LGAs was used as a case study for said framework. Heating load comprised most of the operating energy demand for most typologies while external walls and floors contributed significant embodied carbon for new residential buildings, particularly for detached houses. For Victoria, detached houses built prior to 1991 contributed most of the operational carbon, however with high construction rates set for most LGAs, new housing may contribute more GHG emissions in 2050. Brick veneer housing yielded more embodied carbon from the external wall compared to timber homes while concrete slabs used in floors also incurred a large amount of embodied carbon for the residential building stock. Renovating existing housing has the potential to reduce operating energy demand while emitting less embodied carbon, thus policies on this should be considered in developing decarbonisation pathways. Using the bottom-up typology whole-life carbon framework offers granularity in analysing individual-level carbon impact which can be expanded to LGA and state level.
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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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ItemA simplified sustainable circular economy evaluation for end-of-life photovoltaic(Australian Life Cycle Assessment Society (ALCAS), 2023-07-19)Sustainability and circular economy in the photovoltaic (PV) industry has been gaining increasing traction. Yet, it is still in its infancy. Sustainability is not synonymous to circularity. The correlations between the two paradigms vary case-by-case. PV panel waste has become one of the fastest growing electronic waste. The potential economic and environmental benefits through recycling and other recircularity initatives have been confirmed. However, there is still an urgency to delineate End-of-Life (EoL) PV management practice that is both sustainable and circular. Private PV stakeholders play a prominent role in achieving best practice. However, the exhaustive nature of life cycle impact studies and their data gathering may deter PV producers and recyclers to consider sustainability and circularity performance in their decision-making. This work aims to propose a framework to evaluate sustainability and circular economy performance of discarded PV processing in an integrated manner for private sector users. Sustainability will be assessed through life cycle assessment for environmental impacts, life cycle cost for economic impacts, and industry stakeholder survey to compensate for the lack of social impacts data. Circularity will be evaluated using selected sets of existing product-level circularity indicators. The two paradigms will be reconciled through a joint analysis via multi-criteria decision making.
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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.