Development of a Methodology to Guaranteed Energy Performance

Ligier, Simon; Schalbart, Patrick; Peuportier, Bruno

doi:10.1201/9781003095071-19

Cited by 2 publications

(3 citation statements)

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“…In both case, the approach consists in generating a diversity of realistic scenarios (climates or occupancy), and randomly sampling from the generated scenarios for each simulation. A sample of meteorological years is generated by applying the model of Ligier et al [80,81]. The temperature and radiation of a typical meteorological year are characterised into a mean trend and a residual series, using a Fourier decomposition and a seasonal auto-regressive moving average model.…”

Section: Dbesmentioning

confidence: 99%

Dealing with uncertainties in comparative building life cycle assessment

Pannier

Schalbart

Peuportier

2023

Building and Environment

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Section: Dbesmentioning

confidence: 99%

Dealing with uncertainties in comparative building life cycle assessment

Pannier

Schalbart

Peuportier

2023

Building and Environment

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“…Since climate and user behaviour have a strong influence on the energy performance [29], two additional models linked to COMFIE are used to generate a set of realistic meteorological years [30] and occupancy scenarios [31].…”

Section: Dbes and Lca Frameworkmentioning

confidence: 99%

“…The three other categorical factors may have many-level. For the variability of climate, a set of 2,000 realistic climate files was generated with the model of Ligier et al [30]. Similarly, a set 2,000 realistic occupancy scenarios were generated with the model of Vorger et al [31].…”

Section: List Of Uncertain Factorsmentioning

confidence: 99%

Computationally efficient sensitivity analysis for building ecodesign with many-level categorical input factors

Pannier,

Schalbart,

Peuportier

2023

Int. J. Metrol. Qual. Eng.

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Dynamic building energy simulation and life cycle assessment (LCA) are useful ecodesign tools to mitigate the energy and environmental impacts of buildings. Various uncertain factors can affect the building energy and environmental modelling, including continuous and categorical factors (i.e., discrete factors without logical ranking). Sensitivity analysis (SA) is applied to identify the most influential factors on which additional research efforts are needed to increase the robustness of results. The Sobol method (Sobol) is the reference SA method, but it requires a significant amount of computation. Less time-consuming methods, such as an adaptation of the Morris screening (Morris), have shown a good ability to quantify the influence of factors, but their performance has not been investigated for categorical factors having many (more than two) levels. Two strategies (2LA-Morris and MA-Morris) based on the adaptation of Morris are proposed to handle many-level factors. Their performance is compared to that of Sobol based on four criteria: computation time, factor's relative influence, factor's ranking, and ability to detect interactions. For the LCA of a house including 24 uncertain factors, MA-Morris was able to quantify the influence of factors in the same way as Sobol, while reducing the computation time by a factor of 12.

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Development of a Methodology to Guaranteed Energy Performance

Cited by 2 publications

References 1 publication

Dealing with uncertainties in comparative building life cycle assessment

Dealing with uncertainties in comparative building life cycle assessment

Computationally efficient sensitivity analysis for building ecodesign with many-level categorical input factors

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