https://ogma.newcastle.edu.au/vital/access/ /manager/Index en-au 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43716 Wed 28 Sep 2022 10:22:59 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:43696 Wed 28 Sep 2022 09:33:43 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34321 Wed 27 Feb 2019 12:32:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36612 Wed 22 Mar 2023 17:13:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:55326 Building performance prediction is a significant area of research, due to its potential to enhance the efficiency of building energy management systems. Its importance is particularly evident when such predictions are validated against field data. This paper presents an intelligent computational model combining Monte Carlo analysis, Energy Plus, and an artificial neural network (ANN) to refine energy consumption and thermal comfort predictions. This model addresses various combinations of architectural building design parameters and their distributions, effectively managing the complex non-linear relationships between the response variables and predictors. The model’s strength is demonstrated through its alignment with R2 values exceeding 0.97 for both thermal discomfort hours and energy consumption during the training and testing phases. Validation with field investigation data further confirms its accuracy, demonstrating average relative errors below 2.0% for total energy consumption and below 1.0% for average thermal discomfort hours. In particular, an average underestimation of −12.5% in performance discrepancies is observed when comparing the building energy simulation model with field data, while the intelligent computational model presented a smaller overestimation error (of +8.65%) when validated against the field data. This discrepancy highlights the model’s potential and reliability for the simulation of real-world building performance metrics, marking it as a valuable tool for practitioners and researchers in the field of building sustainability.]]> Wed 15 May 2024 15:40:29 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25749 Wed 11 Apr 2018 15:04:08 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:22714 Wed 11 Apr 2018 12:04:08 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49821 Wed 07 Feb 2024 17:04:59 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31873 Tue 27 Mar 2018 13:42:33 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:49598 Tue 23 May 2023 14:44:01 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:37104 Tue 18 Aug 2020 11:05:43 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52556 Tue 17 Oct 2023 15:34:22 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34055 Tue 05 Feb 2019 12:51:07 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23040 Thu 18 Aug 2016 14:52:55 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:7241 Sat 24 Mar 2018 10:44:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31534 Sat 24 Mar 2018 08:44:29 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:8797 Sat 24 Mar 2018 08:41:10 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:920 Sat 24 Mar 2018 08:29:41 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:12313 Sat 24 Mar 2018 08:11:36 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:9911 Sat 24 Mar 2018 08:10:42 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:10061 Sat 24 Mar 2018 08:07:22 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:16617 Sat 24 Mar 2018 08:03:01 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27528 Sat 24 Mar 2018 07:28:58 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:23260 Sat 24 Mar 2018 07:17:01 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44063 −1; at this speed, the car consumes the least amount of energy (around 137 MJ when travelling a distance of 100 km). All the speeds less than the optimum speed will consume more energy; the same is true when the speed is increased over the optimum. For the second application using water pumps, it was found that a 1.1 kW pump is the most efficient at pumping a specific amount of water, and using higher or lower rated pumps will consume higher energy levels but correspondingly will reduce the time required to perform the same application. This research emphasised the concept that time can save energy, which is not yet covered in the literature as time value of energy when time is not an essential aspect and can be delayed without affecting the main tasks.]]> Mon 29 Jan 2024 17:50:44 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:52714 90 % removal) for diuron even at extremely high initial pollutant concentrations (240 μg L−1), demonstrating its capacity to handle varying contaminant loads in stormwater. Energy consumption analysis revealed that flow rate as the primary factor influenced the specific energy consumption rate. Higher flow rate (e.g., 610 mL min−1) were preferable in flow reactor due to its well-balanced performance between removal and energy consumption. These findings confirm that the PECO flow system offers an efficient and promising approach for stormwater treatment applications.]]> Mon 23 Oct 2023 16:12:30 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:54182 Mon 12 Feb 2024 13:40:09 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:45414 Fri 28 Oct 2022 14:57:11 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:40352 Fri 08 Jul 2022 11:57:37 AEST ]]>