Identification of the hygrothermal properties of a building envelope material by the covariance matrix adaptation evolution strategy

Rouchier, Simon; Woloszyn, Monika; Kedowide, Yannick; Béjat, Timea

doi:10.1080/19401493.2014.996608

Cited by 28 publications

(53 citation statements)

References 28 publications

(29 reference statements)

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“…The rain is present in the simulation between hours [ 40,65 ] h , reaching a maximum value of 2 · 10 −4 kg/(m 2 · s) at 52 h , as presented in Figure 11(a), which generates a sensible heat flux of 12 W/m 2 at this boundary as shown in Figure 11(b). The rain flux is included at the left boundary, which causes a rapid increase of moisture within the material.…”

Section: Applicationmentioning

confidence: 95%

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An adaptive simulation of nonlinear heat and moisture transfer as a boundary value problem

Gasparin

Berger

Dutykh

et al. 2018

International Journal of Thermal Sciences

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An adaptive simulation of nonlinear heat and moisture transfer as a boundary value problem arXiv.org / hal Abstract. This work presents an alternative view on the numerical simulation of diffusion processes applied to the heat and moisture transfer through porous building materials. Traditionally, by using the finite-difference approach, the discretization follows the Method Of Lines (MOL), when the problem is first discretized in space to obtain a large system of coupled Ordinary Differential Equations (ODEs). Thus, this paper proposes to change this viewpoint. First, we discretize in time to obtain a small system of coupled ODEs, which means instead of having a Cauchy (Initial Value) Problem (IVP), we have a Boundary Value Problem (BVP). Fortunately, BVPs can be solved efficiently today using adaptive collocation methods of high order. To demonstrate the benefits of this new approach, three case studies are presented, in which one of them is compared with experimental data. The first one considers nonlinear heat and moisture transfer through one material layer while the second one considers two material layers. Results show how the nonlinearities and the interface between materials are easily treated, by reasonably using a fourth-order adaptive method. Finally, the last case study compares numerical results with experimental measurements, showing a good agreement.Key words and phrases: coupled heat and moisture diffusive transfer; boundary value problems; semi-discretization in time; semi-discretization in space; bvp4c MSC: [2010] 35R30 (primary), 35K05, 80A20, 65M32 (secondary)

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Section: Applicationmentioning

confidence: 95%

“…Thus, both boundaries are expressed as Dirichlet conditions for the model confirmation. For more details about the experiment one may refer to [38] and [40]. In this wok, the temporal derivative of ρ w in Equation (2.1b) was also taken into account, differently from [40].…”

Section: Comparison Of the Numerical Predictions With Experimental Datamentioning

confidence: 99%

An adaptive simulation of nonlinear heat and moisture transfer as a boundary value problem

Gasparin

Berger

Dutykh

et al. 2018

International Journal of Thermal Sciences

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“…These sensors provide observation data which will be used for comparison with model outputs. More details on the experimental design are available in [33]. The conditions on each side of the instrumented layer are recorded by sensors placed at the material surface: the boundary conditions of the simulation are prescribed temperature and vapour pressure.…”

Section: Methodsmentioning

confidence: 99%

“…[33] use the Covariance Matrix Adaptation evolutionary algorithm to solve the optimization problem of fitting a HAM model on dynamic temperature and RH observations. [28] apply another gradient-free optimization algorithm (Simplex) to minimize the residuals between RH measurements and predictions, and estimate the moisture diffusivity of spruce wood and fiber board without reaching mass equilibrium.…”

Section: Ham Characterizationmentioning

confidence: 99%

“…[5] address coupled heat and mass transfer and identify non-dimensional transport and storage properties of several materials through a Levenberg-Marquardt optimization scheme. [33] add regularisation to a Covariance Matrix Adaptation algorithm to identify the parameters of a coupled HAM model. [13] show how the Moisture Buffer Value test can be improved by using its dynamic measurements as observations in a Bayesian inference scheme.…”

Section: Introductionmentioning

confidence: 99%

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Hygric characterization of wood fiber insulation under uncertainty with dynamic measurements and Markov Chain Monte-Carlo algorithm

Rouchier

Busser

Pailha

et al. 2017

Building and Environment

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The present work is the hygric characterization of wood fibre insulation boards, using dynamic measurements of relative humidity and sample weight, analyzed in the frame of Bayesian inference for parameter identification under uncertainty. It is an attempt at identifying detailed profiles of moisture-dependent properties, and thus a relatively high number of parameters. Because of this ambition, some caution should be exercised once the outcome of the inversion algorithm is available: in addition to confidence intervals of parameters provided by the Bayesian framework, a simplified form of identifiability analysis is performed by analysing a posteriori parameter correlations and likelihood-based confidence intervals.The characterization methodology does not require for the model structure to have a differentiable analytical formulation, or for material samples to reach mass equilibrium between each RH step of the experimental process. Two separate experimental designs were used for material characterization and for validation, respectively. Results show a clear relation between available information (experimental data) and inference (confidence intervals of parameters). A single relative humidity step is not informative enough for a precise inference of moisture-dependent properties such as vapour permeability and moisture capacity. A two-step experiment however holds enough information to significantly reduce parameter uncertainty.

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A spectral method for solving heat and moisture transfer through consolidated porous media

Gasparin

Dutykh

Mendes

2018

Numerical Meth Engineering

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This work presents an efficient numerical method based on spectral expansions for simulation of heat and moisture diffusive transfers through multilayered porous materials. Traditionally, by using the finite-difference approach, the problem is discretized in time and space domains (method of lines) to obtain a large system of coupled ordinary differential equations (ODEs), which is computationally expensive. To avoid such a cost, this paper proposes a reduced-order method that is faster and accurate, using a much smaller system of ODEs. To demonstrate the benefits of this approach, three case studies are presented.The first one considers nonlinear heat and moisture transfer through one material layer. The second case, ie, highly nonlinear, imposes a high moisture content gradient, simulating a rain-like condition, over a two-layered domain, whereas the last one compares the numerical prediction against experimental data for validation purposes. Results show how the nonlinearities and the interface between materials are easily and naturally treated with the spectral reduced-order method. Concerning the reliability part, predictions show a good agreement with experimental results, which confirm robustness, calculation efficiency, and high accuracy of the proposed approach for predicting the coupled heat and moisture transfer through porous materials. KEYWORDSChebyshev polynomials, heat and moisture transfer, numerical simulation, reduced-order modeling, spectral methods, Tau-Galerkin method Int

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Identification of the hygrothermal properties of a building envelope material by the covariance matrix adaptation evolution strategy

Cited by 28 publications

References 28 publications

An adaptive simulation of nonlinear heat and moisture transfer as a boundary value problem

An adaptive simulation of nonlinear heat and moisture transfer as a boundary value problem

Hygric characterization of wood fiber insulation under uncertainty with dynamic measurements and Markov Chain Monte-Carlo algorithm

A spectral method for solving heat and moisture transfer through consolidated porous media

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