Infrastructure Engineering - Research Publications
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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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ItemOpening the door on refrigerator energy consumption: quantifying the key drivers in the home(SPRINGER, 2018-08)There is little concrete understanding of the energy consumption of refrigerating appliances during normal use or the main influences on their energy consumption. To date, no widely accepted method to disaggregate measured energy consumption measured in the home into its key components has been demonstrated. This paper examines the main external factors that impact on the energy consumption of existing refrigerating appliances in the home and how they respond to changing conditions, namely: room air temperature, defrosting behaviour and user interactions. Analysis of field data from 235 homes in Australia demonstrates that room air temperature is by far the largest factor accounting for typically around 75% of total energy consumption. Where present, energy used for defrosting is relatively small at around 10%, but this does vary by household and the type of defrost controller. User interactions typically account for 15% of total energy consumed by main household refrigerating appliances, but this varies from a few percent to as much as 45% in large households. The method set out in this paper provides a basis for more in depth analysis and a better understanding of energy consumption of household refrigerators in different regions.
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ItemA Machine Learning Approach for the Performance Prediction of GCHPs with Horizontal Ground Heat Exchangers(IOS PRESS, 2019-01-01)This study aims to provide a machine learning approach to predict the performance of Ground Coupled Heat Pumps (GCHPs) with horizontal Ground Heat Exchangers (GHEs). Specifically, an ANN model was developed for this purpose which can potentially be generally applied to similar sites at different locations and climate conditions, with even limited types of input data. In this example, a TRNSYS model regarding a typical horizontal trench within a rural farm in Australia, has been developed and verified, covering over 50 different yearly loading patterns under 3 different climate conditions. The simulated performance data is then used to train the artificial neural network. As results, the trained ANN is able to predict the performance of GSHPs systems with identical GHEs even under climatic conditions (and locations) that has not been specifically trained for. With only limited input data, the presented ANN shows no more than 5% error in most cases tested.
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ItemChapter 37: Heat Pumps(CRC Press, 2020-07-29)In this second volume, Managing Air Quality and Energy Systems, the reader is introduced to the general concepts and processes of the atmosphere, with its related systems. Heat pumps capture heat energy from low-grade heat sources such as ambient air, ground, and waste heat streams and upgrade to a higher temperature level for useful applications. This entry includes a brief history, fundamentals, classifications, applications and performance parameters of heat pumps. Working principles of the thermoelectric heat pump, the absorption heat pump, the gas compression heat pump and the vapor compression heat pump are explained. Performance parameters of the heat pump systems (coefficient of performance, energy efficiency ratio, primary energy ratio, and ambient energy fraction) are presented. The short-term and long-term greenhouse gas saving potential for the use of heat pumps are discussed.
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ItemBiophilic design features in vernacular architecture and settlements of the Naxi(Vilnius Gediminas Technical University, 2020-12-16)As a newly formed concept, “Biophilic design” is attracting a growing attention among both practitioners and academics. However, the link between biophilic design and vernacular architecture has yet to be thoroughly explored, especially in the context of China, which is the gap this article aims to fill. Investigating the vernacular architecture of the Naxi, this research found that biophilic design attributes and features existed in vernacular buildings and settlements. A matrix framework was developed to facilitate the in-depth investigation of the interrelated elements of the Naxi such as local climate, topography, culture, their belief system, conventions, arts and literature. Among other results, we found that the local culture was influenced by animism and distinct cosmic models. Also, the buildings were constructed using the traditional ways of material preparation and conventions of occupancy. This research serves as an important springboard to bridge between studies in biophilic design and studies in vernacular architecture and settlements.
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ItemConnection to Nature( 2020-12-10)Melbourne School of Engineering, Health and Wellbeing Session, 10 December 2020
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ItemEffects of substrate depth and native plants on green roof thermal performance in South-East Australia(IOP Publishing, 2020-11-20)Three experimental green roofs in Melbourne with depth of 100, 150 and 300 mm have been assessed to quantify their thermal performance. To evaluate the benefit of substrate depth, temperature was recorded every 50 mm along a vertical profile. Green roofs consisted of scoria substrate and a mix of three species of plants: Lomandra longifolia, Dianella dmixta and Stypandra glauca. Statistical analyses applying the hierarchical partitioning technique showed that solar radiation is the main driver affecting the green roof surface temperature, air temperature has strong correlations with the variations of the temperatures recorded below the surface, while moisture content has the least influence. Temperature profiles of the green roof show that the first 50 mm do reduce the heat flowing through the green roof substrate regardless the total green roof substrate depth. Differences in thermal performance arise at deeper points, where thicker green roofs are able to delay the change of substrate temperatures. Similar effects were found for the heat fluxes measured at the interface between the green roof and building roof. These results confirmed that green roofs may be used as a sustainable passive technology to reduce building energy consumptions for South-East Australia climate.
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ItemNo Preview AvailableDataset on baseline performance and sensitivity analysis of a prefabricated house in six climate zones in Australia( 2020-11-26)This dataset includes the results of baseline performance evaluation and sensitivity analysis of a prefabricated house in six climate zones in Australia. The performance parameters investigated are monthly heating loads, monthly cooling loads, monthly thermal discomfort hours (TDHs) and monthly daylight unsatisfied hours (DUHs) of the living room, study room, and rumpus room in the prefabricated house.
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ItemNo Preview AvailableDataset on validation of TRNSYS building model for a prefabricated house built in Australia( 2020-11-26)This dataset includes data from the validation of TRNSYS building model for a prefabricated house built in Australia. The simulated indoor temperatures were compared with the measured ones in Melbourne. The comparison was carried out for the period between 19:00:00 on 31 March 2018 and 00:00:00 on 2 April 2018. Coefficient of determination (R²), Root Mean Square Error (RMSE), Mean Bias Error (MBE), Mean Absolute Error (MAE), and Correlation Coefficient (CC) were applied for quantification of the agreement between simulated and measured temperatures.
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ItemBiophilic Design Features in Vernacular Architecture and Settlements of the Naxi( 2020-07-04)2020 University of Nottingham Ningbo China (UNCC) Symposium Disruption vs Integration: Pathways to urban trans-formation, July 4