A comparison of hygrothermal simulation results derived from four simulation tools

Defo, Maurice; Lacasse, Michael A.; Laouadi, Abdelaziz

doi:10.1177/1744259120988760

Cited by 26 publications

(13 citation statements)

References 15 publications

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“…Perhaps the most obvious cause of error is the inaccuracies in the material properties, which was studied by Yamamoto and Takada (2022). Also, because numerical simulation consists of vast number of details related to for example, numerical methods, discretization and treatment of tabulated nonlinear material properties, the choice of simulation program has also certain effect on the results (Defo et al, 2022). However, lesser attention is often paid to the fact that the simulation of combined heat and moisture transfer in building physical examinations rely typically on local equilibrium assumption, which allows using only one variable to determine the local state of water in the material.…”

Section: Introductionmentioning

confidence: 99%

Dynamic water vapor sorption in wood-based fibrous materials and material parameter estimation

Huttunen

Vinha

2023

Journal of Building Physics

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Building physical simulation software rely on assumptions regarding the local equilibria in materials’ pore systems, which may be unjustified for certain materials. While local hygrothermal non-equilibrium has still been in focus in some previous studies, it has been unclear how significant factor it may be when modeling real structures. In case of wood, the non-equilibrium is related to the slowness of intrusion of water molecules into the hygroscopic cell walls. Including local non-equilibrium in macroscopic model requires separate variables for pore air vapor and adsorbed moisture, and modeling the local mass transfer between pore air and adsorbed moisture requires effective material parameters, whose experimental determination is not straightforward. Commercially available sorption balances can be used to record data, which can be used in the parameter estimation. In this type of problem of parameter estimation from time-dependent data the mathematical challenge is to find global optimum from different solutions, which yield similar values for objective function. This difficulty can be overcome by using statistical inversion approach, which we applied in studying low-density woodfibre material (LDF). Dynamic sorption parameters were finally applied in numerical analysis of a laboratory test assembly. Based on the results, our conclusion is that the slowness of sorption is obvious in small LDF sample, which is exposed to changing humidity, but with the studied material the sorption seem to happen fast enough so that local non-equilibrium may have only slight effects in modeling of real structures.

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Section: Introductionmentioning

confidence: 99%

Dynamic water vapor sorption in wood-based fibrous materials and material parameter estimation

Huttunen

Vinha

2023

Journal of Building Physics

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“…Main focus lies on the vapour permeability ratio between in- and exterior sheathing to assess the risk on mould growth and/or interstitial condensation (Geving and Holme, 2013; Kalamees and Vinha, 2003; Karagiozis, 2002). Most of these studies are limited to 1D-simulations (Defo et al, 2022; Fu et al, 2020; Gatland et al, 2007; Kabatova et al, 2019; Kalamees and Vinha, 2003; Pihelo and Kalamees, 2016; Straube and Finch, 2009), despite the inherent 2D or 3D character of timber frame walls. And the few two-dimensional simulations that can be found in literature mainly investigate the effect of the ventilated cavity (Langmans et al, 2013; Laukkarinen et al, 2021; Straube and Finch, 2009; Vanpachtenbeke et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The impact of wooden studs on the moisture risk of timber frame constructions

Roels

Tijskens

2022

Journal of Building Physics

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Since timber frame constructions can help to reduce CO2-emissions and lower the embodied energy of buildings, the market share of timber-based buildings is growing across Europe. Unfortunately, timber frame constructions are found to be susceptible to moisture damage, such as interstitial condensation, mould growth and wood rot. To avoid moisture damage, a correct design of the wall composition is crucial, with special emphasis on the ratio between vapour resistance of wind and vapour barrier. Given that experimental investigations are time-consuming and expensive, numerical tools are common to assess the hygrothermal behaviour of building components. And although timber frame constructions are inherently two- or even three-dimensional due to the embedded wooden elements, most often, 1D-simulations focussing on the basic configuration with insulation between wind and vapour barrier are conducted. This paper investigates to what extent neglecting the embedded wooden elements influences the risk assessment of the wall. Three different wall configurations have been considered and their hygrothermal response, as predicted by 1D- and 2D-numerical simulations, are compared. Variability of the exterior climate is included by using four distinct different climate regions. Contrary to common assumptions, buffering of moisture in wooden elements does not always lower the risk on moisture damage, but might even increase it. While the predicted risk on mould growth was found to be similar between 1D and 2D-simulations, the opposite was found for the risk on interstitial condensation. Mainly for cold climates and wall configurations with hardly any other hygric buffering capacity, levels of interstitial condensation were found to be significantly higher when taking the wooden elements into account in the numerical simulations. Hence, care should be taken when assessing the reliability of timber frame walls based on 1D-simulations only.

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“…With the gradual maturity of the theoretical model of hygrothermal prediction, based on those theoretical models, hygrothermal prediction simulation software WUFI has been developed and widely used [18]. It has been proven that WUFI can be used in a wide range of building materials, such as lightweight timber-frame [19], cross-laminated timber [20], and bamboo-wood composite materials [21].…”

Section: Introductionmentioning

confidence: 99%

Using Machine Learning Method to Discover Hygrothermal Transfer Patterns from the Outside of the Wall to Interior Bamboo and Wood Composite Sheathing

Wang

Zhu

et al. 2022

Buildings

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To identify hygrothermal transfer patterns of exterior walls is a crucial issue in the design, assessment, and construction of buildings. Temperature and relative humidity, as sensor monitoring data, were collected from the outside of the wall to interior bamboo and wood composite sheathing over the year in Huangshan Mountain District, Anhui Province, China. Combining the machine learning method of reservoir computing (RC) with agglomerative hierarchical clustering (AHC), a novel clustering framework was built for better extraction of the characteristics of hygrothermal transfer on the time series data. The experimental results confirmed the hypothesis that the change in the temperature and relative humidity of the outside of the wall (RHT12) dominated the change of the interior sheathing (RHT11). The delay time between two adjacent peaks in temperature was 1 to 2 h, while that in relative humidity was 1 to 4 h from the outside of the wall to interior bamboo and wood composite sheathing. There was no significant difference in temperature peak delay time between April and July. Temperature peak delay time was 50 to 120 min. However, relative humidity peak delay time was 100 to 240 min in April, whereas it was 20 to 120 min in July. The impact formed a relatively linear relationship between outdoor temperature and relative humidity peak delay time. The hygrothermal transfer patterns were characterized effectively by the peak delays. The discovery of the hygrothermal transfer patterns for the bamboo and wood composite walls using the machine learning method will facilitate the development of energy-efficient and durable bamboo and wood composite wall materials and structures.

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A comparison of hygrothermal simulation results derived from four simulation tools

Cited by 26 publications

References 15 publications

Dynamic water vapor sorption in wood-based fibrous materials and material parameter estimation

Dynamic water vapor sorption in wood-based fibrous materials and material parameter estimation

The impact of wooden studs on the moisture risk of timber frame constructions

Using Machine Learning Method to Discover Hygrothermal Transfer Patterns from the Outside of the Wall to Interior Bamboo and Wood Composite Sheathing

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