Practical application of an uncertainty approach for hygrothermal building simulations—drying of an AAC flat roof

Holm, Andreas; Künzel, Hartwig M.

doi:10.1016/s0360-1323(02)00047-1

Cited by 35 publications

(20 citation statements)

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“…Macdonald and Strachan [2] applied a Monte Carlo uncertainty analysis for thermal properties of construction materials, weather, internal heat gains, and infiltration rate to evaluate the variation of energy consumption using assumed uncertainty distribution patterns. Holm and Kuenzel [3] evaluated the impacts of materials properties and surface coefficients on hygrothermal building simulation using a Monte Carlo analysis. De Wit and Augenbroe [4] addressed the effects of uncertainty in two important factors -wind-pressure coefficients and room airtemperature distribution-on simulation results for design evaluation.…”

Section: Introductionmentioning

confidence: 99%

Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building

Wang

Mathew

Pang

2012

Energy and Buildings

146

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Deviations between predicted and actual building energy consumption can be attributed to uncertainties introduced by four components of such projections: (1) the accuracy of the underlying models in simulation tools, (2) the accuracy of input parameters describing the design conditions of building envelope and HVAC systems, (3) actual weather, (4) variations in building operation practices. This study investigates uncertainties in energy consumption due to actual weather and building operational practices, using a simulation-based analysis of a medium-size office building. The combined effect of poor practice in building operations across multiple parameters results in an increase in energy use of 49-79% across four selected cities, while good practice reduces energy use by 15-29% across the cities. The impact of year-to-year weather fluctuation on energy use ranges from -4% to 6%. To determine the uncertainty distribution profile for annual energy use, a Monte Carlo method is applied to sample the possible combinations. This study finds that the uncertainty distribution in annual energy consumption approximately follows a log-normal distribution, and shows that the uncertainty range due to operational factors even at an 80% confidence level can dwarf the impact of design features.

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Section: Introductionmentioning

confidence: 99%

Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building

Wang

Mathew

Pang

2012

Energy and Buildings

146

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“…the amplitudes of the indoor air temperature and relative humidity in the room. 8 Analysis of the thermal and hygric effusivity, which represent the measure of the material's ability to exchange heat and moisture with its surroundings is done using Equations (7) and (8). ].…”

Section: Discussionmentioning

confidence: 99%

“…They have demonstrated that predictions of building energy demand and consumption can be strongly influenced by the choice of the convective surface heat transfer coefficient. Holm and Künzel [8] investigated the influence of the indoor and outdoor climatic conditions on the uncertainty of the simulated hygrothermal conditions in an autoclaved aerated concrete roof. Janssen et al [9] similarly indicated that the hygrothermal conditions in building components may be sensitive to the model applied for the external surface heat and moisture transfer coefficient.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Convective Surface Transfer Coefficients on the Heat, Air, and Moisture (HAM) Building Performance

Steskens

Janssen

Rode

2009

Indoor and Built Environment

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Current models to predict heat, air, and moisture (HAM) conditions in buildings assume constant boundary conditions for the temperature and relative humidity of the neighboring air and for the surface heat and moisture transfer coefficients. These assumptions may introduce errors in the predicted HAM conditions. The paper focuses on the influence of the interior surface heat and moisture transfer coefficients, and investigates its effect on the hygrothermal performance. The parameter study showed that the magnitude of the convective surface transfer coefficients has a relatively large influence on the predicted hygrothermal conditions at the surface of a building component and on the heat and vapor exchange with the indoor environment.

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“…These models are commonly used to assess the moisture management capabilities of portions of building envelopes. Many examples exist in the literature including but not limited to retrofit studies [12], drying studies [13,14], and performance assessments of envelope systems, some verified with experimental data [15,16,17,18,19]. Hygrothermal models also form the basis for other models providing input for damage models of corrosion, mould, and rot [20,21].…”

Section: Introductionmentioning

confidence: 99%

Adapting rain data for hygrothermal models

Cornick

Dalgliesh²

2009

Building and Environment

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/npsi/ctrl?lang=en http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/ctrl?lang=fr Access and use of this website and the material on it are subject to the Terms and Conditions set forth at http://nparc.cisti-icist.nrc-cnrc.gc.ca/npsi/jsp/nparc_cp.jsp?lang=en NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous.http://dx.doi.org/10.1016/j.buildenv.2008.07.002 Building and environment, 30, pp. 1-10, 2008-10-20 Adapting rain data for hygrothermal modeling Cornick, S. M.; Dalgliesh, A.http://irc.nrc-cnrc.gc.ca Adapting rain data for hygrothermal modeling NRCC-50832Cornick, S.M.; Dalgliesh, A. 2008-10-01A version of this document is published in / Une version de ce document se trouve dans: Building and environment, v. 30, 2008 The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit http://laws.justice.gc.ca/en/showtdm/cs/C-42Les renseignements dans ce document sont protégés par la Loi sur le droit d'auteur, par les lois, les politiques et les règlements du Canada et des accords internationaux. Ces dispositions permettent d'identifier la source de l'information et, dans certains cas, d'interdire la copie de documents sans permission écrite. Pour obtenir de plus amples renseignements : http://lois.justice.gc.ca/fr/showtdm/cs/C-42 AbstractDesign for moisture control has now become an established part of building envelope design. Hygrothermal modeling tools, capable of simulating moisture transfer in materials, are a key element of the design process. There are three principle methods of moisture transfer in envelopes. They are, in order of magnitude, capillary action, vapour convection, and vapour diffusion. Wind-driven rain has the potential to deposit large amounts of liquid water on the exterior surface, as well inside walls through rain penetration, providing a significant source for moisture transport.

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Practical application of an uncertainty approach for hygrothermal building simulations—drying of an AAC flat roof

Cited by 35 publications

References 1 publication

Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building

Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building

Influence of the Convective Surface Transfer Coefficients on the Heat, Air, and Moisture (HAM) Building Performance

Adapting rain data for hygrothermal models

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