2022
DOI: 10.1007/s12273-022-0899-7
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Design optimisation of mean room surface exitance and total corneal illuminance using Monte Carlo simulation

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Cited by 5 publications
(2 citation statements)
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“…A major obstacle in implementing MRSE is the TAIR assignment on each interior surface within the room. On the one hand, TAIR serves as a tool in the lighting design objectives (LiDOs) procedure to determine the Direct Flux Distribution (DFD), which is relevant in achieving the desired lighting design objectives [15] On the other hand, the MRSE approach can be applied to optimize the placement and scheduling of indoor lighting systems, such that a compromise between achieving the visual emphasis and for reducing the lighting energy consumption is always required [22] One advantage of TAIR is that lighting designers can selectively choose target surfaces to obtain the desired visual emphasis distribution. In this case, the designers can use the list of TAIR values to represent the illumination distribution on those target surfaces.…”
Section: Resultsmentioning
confidence: 99%
“…A major obstacle in implementing MRSE is the TAIR assignment on each interior surface within the room. On the one hand, TAIR serves as a tool in the lighting design objectives (LiDOs) procedure to determine the Direct Flux Distribution (DFD), which is relevant in achieving the desired lighting design objectives [15] On the other hand, the MRSE approach can be applied to optimize the placement and scheduling of indoor lighting systems, such that a compromise between achieving the visual emphasis and for reducing the lighting energy consumption is always required [22] One advantage of TAIR is that lighting designers can selectively choose target surfaces to obtain the desired visual emphasis distribution. In this case, the designers can use the list of TAIR values to represent the illumination distribution on those target surfaces.…”
Section: Resultsmentioning
confidence: 99%
“…To collect a large enough sample size, a Monte Carlo simulation is conducted, relying on repeated random sampling, , to obtain the statistical properties of a phenomenon, which is the source-specific contributions to indoor UFPs in this study. The Monte Carlo method has been applied in previous studies for various applications, such as building energy, optimization of total corneal illuminance, particle penetration, particle deposition on heat exchangers, quanta emission rates of SARS-CoV-2, as well as assessments of indoor air pollutant concentrations and human exposure. Given that the dynamic mechanism of UFPs differs from PM 2.5 , ozone, nitrogen dioxide, and semivolatile organic compounds, the development of a Monte Carlo Simulation specifically for residential UFP concentrations remains to be established. In this study, the probabilistic distribution of source contributions in Chinese residences was estimated, starting from a source-specific, time-dependent UFP concentration model via Monte Carlo simulation.…”
Section: Introductionmentioning
confidence: 99%