2019
DOI: 10.1016/j.applthermaleng.2019.02.065
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Dynamic integrated method applied to assessing the in-situ thermal performance of walls and whole buildings. Robustness analysis supported by a benchmark set-up

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Cited by 7 publications
(19 citation statements)
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“…This paper repots a further systematic analysis focusing on the following aspects: the effect of the solar radiation on the heat flux through the opaque walls versus the performance of the models including this effect. Although previous work [31] analyzed this issue applying another method and concluded that neglecting this effect is convenient, a deeper analysis is here reported. This work also studied the optimum number of nodes required to represent the thermal systems, the assignment of inputs and outputs and the length of the test period.…”
Section: Introductionmentioning
confidence: 77%
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“…This paper repots a further systematic analysis focusing on the following aspects: the effect of the solar radiation on the heat flux through the opaque walls versus the performance of the models including this effect. Although previous work [31] analyzed this issue applying another method and concluded that neglecting this effect is convenient, a deeper analysis is here reported. This work also studied the optimum number of nodes required to represent the thermal systems, the assignment of inputs and outputs and the length of the test period.…”
Section: Introductionmentioning
confidence: 77%
“…The detailed information of the construction of the building which is available, including accurate geometrical parameters and thermal properties of its construction materials, strengthens and complements the criteria for validation. This issue together with the simplicity of the building, the oversizing of its test set up and length, and the richness of the weather conditions throughout the test campaign, are relevant features to make this case study suitable to corroborate, complement, and extend some findings from previous works [31]. These analyses and comparisons give background to support the criteria for selecting the best model among the considered candidates and the minimum set of variables required to guarantee an adequate accuracy of the analysis.…”
Section: Introductionmentioning
confidence: 77%
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“…It was detected that some variables that in principle were considered relevant to model some of the terms relevant to the energy balance terms were not available, particularly: Several assumptions and approximations were considered to model the terms that required available and non-available variables. The assumptions regarding the contributions to the energy balance, their corresponding approximations and criteria to construct candidate models were applicable to other modelling approaches that could be applied to obtain the same performance parameters (see, for example, [11,19] reporting the application of a dynamic integrated approach). The assumptions and approximations applied in this work are discussed hereafter.…”
mentioning
confidence: 99%