2017
DOI: 10.1016/j.expthermflusci.2016.10.008
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On the optimal experiment design for heat and moisture parameter estimation

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Cited by 20 publications
(15 citation statements)
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“…If there is no prior information, the methodology of the OED can be done using an outer loop on the parameter P sampled using, for instance, Latin hypercube or Halton or Sobol quasi-random samplings. Interested readers may refer to [8] for further details on the computation of sensitivity coefficients. Equation (2.10) has been written for a relative humidity step at the boundary of the material.…”
Section: Optimal Experiments Designmentioning
confidence: 99%
See 1 more Smart Citation
“…If there is no prior information, the methodology of the OED can be done using an outer loop on the parameter P sampled using, for instance, Latin hypercube or Halton or Sobol quasi-random samplings. Interested readers may refer to [8] for further details on the computation of sensitivity coefficients. Equation (2.10) has been written for a relative humidity step at the boundary of the material.…”
Section: Optimal Experiments Designmentioning
confidence: 99%
“…The estimation of the unknown parameters, e.g., wall thermo-physical properties, based on observed data and identification methods, strongly depends on the experimental protocol and particularly on the imposed boundary conditions and on the location of the sensors. In [8], the concept of searching the Optimal Experiment Design (OED) was used to determine the best experimental conditions in terms of quantity and location of sensors, and flux imposed to the material. These conditions ensure to provide the best accuracy of the identification method and thus the estimated parameter.…”
Section: Introductionmentioning
confidence: 99%
“…A second practice is maximizing the so-called D-optimum criterion, the determinant of the sensitivity matrix and its transpose, which minimizes the confidence regions of the parameters. Several articles apply this criterion on mass transfer in a porous building material [5,6]. Studies of optimal experiment design of heat transfer have been performed in controlled laboratory conditions.…”
Section: Introductionmentioning
confidence: 99%
“…This paper is an interesting example of an incremential workflow implying OED and model selection, for a maximized utilization of data. [Berger et al, 2017] is an example of OED applied to a non-linear problem: the estimation of heat and moisture transfer properties of building materials; [Cai et al, 2016] proposed generating an optimal training data set for zone temperature setpoints to maximise the accuracy of parameter estimates in an RC building model.…”
Section: Optimisationmentioning
confidence: 99%