2021
DOI: 10.1016/j.foar.2021.02.007
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Conflicts in passive building performance: Retrofit and regulation of informal neighbourhoods

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Cited by 4 publications
(5 citation statements)
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“…The goals were to find (1) the cheapest and (2) fairest retrofit solution for all buildings that (3) minimized annual heating and cooling loads, i.e., Each building is represented as a variable with 4 options for its corresponding construction period: (1) no retrofit, (2) wall retrofit, (3) roof retrofit, and (4) wall and roof retrofit (Table 1). The defined objective functions for the optimization are intended to minimize annual loads (kWh/m 2 ), cost (€), and standard deviation (σ) to ensure some homogeneity of performance among all buildings (Araújo et al, 2021). This MOO experiment used two methods: (1) a simulation-based approach that fully simulates each building block in each MOO evaluation, and (2) using our surrogate model.…”
Section: Predictionmentioning
confidence: 99%
See 1 more Smart Citation
“…The goals were to find (1) the cheapest and (2) fairest retrofit solution for all buildings that (3) minimized annual heating and cooling loads, i.e., Each building is represented as a variable with 4 options for its corresponding construction period: (1) no retrofit, (2) wall retrofit, (3) roof retrofit, and (4) wall and roof retrofit (Table 1). The defined objective functions for the optimization are intended to minimize annual loads (kWh/m 2 ), cost (€), and standard deviation (σ) to ensure some homogeneity of performance among all buildings (Araújo et al, 2021). This MOO experiment used two methods: (1) a simulation-based approach that fully simulates each building block in each MOO evaluation, and (2) using our surrogate model.…”
Section: Predictionmentioning
confidence: 99%
“…Thus, we used different supervised learning models from the Sci-Kit learn package for Julia. From those, to find the most suitable model, we must (1) understand how the parameters affect energy consumption in a building (Araújo et al, 2021), and (2) test multiple models (Wolpert & Macready, 1997). Figure 4 shows interpolations of the energy needs (z-axis) according to our discrete (layers) and continuous (x-and y-axis) parameters step sizes.…”
Section: Digital Design and Fabrication Of A 3d Concrete Printed Funi...mentioning
confidence: 99%
“…In each of the five case studies, the existing buildings were evaluated in terms of their interior comfort and daylighting using ladybug and honeybee tools [10] that integrate both Energyplus [i] and Daysim [ii] in a single simulation workflow. This integrated simulation approach has yielded promising results in the past for similar analyses and assessments [11,12].…”
Section: The Case Study Of Ondjivamentioning
confidence: 99%
“…Most BPS is time-consuming and still requires a considerable amount of time to perform the calculations for multiple or large models. This constitutes a significant limitation, particularly for BPO that requires testing of multiple iterations of a project [8,9].…”
mentioning
confidence: 99%
“…The use of ADA constitutes a trade-off, since it allows practitioners to obtain higher portability between their projects' design, performance analysis, and optimization, at the cost of having to learn programming languages that have a high learning curve [23]. Moreover, ADA does not address the remaining limitations of BPS processes, which still require significant computation time, expertise, and testing to be successfully applied [9,13].…”
mentioning
confidence: 99%