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Moisture Effects on Conduction Loads N Energy and Buildings 35 (2003) 631–644 Moisture effects on conduction loads N. Mendesa,*, F.C. Winkelmannb, R. Lambertsc, P.C. Philippic aDepartment of Mechanical Engineering, Pontifical Catholic University of Parana´, Thermal Systems Laboratory, Curitiba, PR 80215-901, Brazil bLawrence Berkeley National Laboratory, Environmental Energy Technologies Division, Simulation Research Group, Berkeley, CA 94720, USA cFederal University of Santa Catarina, Floriano´polis, SC 88040-900, Brazil Received 15 February 2002; accepted 1 October 2002 Abstract The effects of moisture on sensible and latent conduction loads are shown by using a heat and mass transfer model with variable material properties, under varying boundary conditions. This model was then simplified to reduce calculation time and used to predict conduction peak load (CPL) and yearly integrated wall conduction heat flux (YHF) in three different cities: Singapore (hot/humid), Seattle (cold/humid) and Phoenix (hot/dry). The room air temperature and relative humidity were calculated with the building energy simulation program DOE-2.1E. The materials studied were aerated cellular concrete (ACC), brick (BRK), lime mortar (LMT) and wood. It is shown that the effects of moisture can be very significant and that simplified mathematical models can reduce the calculation time with varying effects on accuracy. # 2002 Elsevier Science B.V. All rights reserved. Keywords: Conduction; Hygroscopic; Moisture 1. Introduction In the work of International Energy Agency Annex 24 [7], five programs were presented in detail: 1D-HAM, WUFIZ, In building energy analysis the calculation of heat con- MATCH, HYGRAN24 and LATENITE. All of these pro- duction through walls usually neglects the storage and grams have a similar physical basis: heat and mass balance transport of moisture in the porous structure of the walls. equations, Philip and DeVries model, and the laws of Four- However, walls are normally subjected to both thermal and ier, Fick and Darcy. The main difference among the pro- moisture gradients so that an accurate heat transfer deter- grams are the simplifying assumptions that are made. Some mination requires a simultaneous calculation of both sen- models, such as that used in MOIST, have been validated for sible and latent effects. The transfer of moisture through some cases and shown to be reliable [8,9]. Therefore, it is common building materials, such as wood, concrete and believed that these models are generally reliable, especially brick, depends on the complex morphotopological charac- for weather conditions that are not too humid. teristics of the pores in these materials. Therefore, it is Our dynamic model allows the cooling loads due to important to consider hygroscopic phenomena in building combined heat and moisture transport through walls to be energy simulation; however, this usually implies much calculated for a wide range of materials, even under the longer run times. extreme conditions found in hot/humid climates. For the Several investigators have developed models for moisture walls we consider sensible and latent surface convection, transport in buildings [1–6]. Some models use the response absorbed solar radiation, heat and mass transfer through the factor method so that they are limited to constant transport wall, and vapor/liquid phase change. The walls are described coefficients. Others are limited to low moisture content. mathematically using the model of Philip and DeVries [10] Lacking a data base of moisture transport coefficients and in which vapor and liquid flow under moisture and thermal faced with long run times, we have developed a faster- gradients and the mathematical model used was the same running model that is dynamic but avoids restrictions, such proposed by Mendes et al. [11]. In this model, heat, vapor as low moisture content and constant transport coefficients. and liquid flow are taken to be simultaneous and coupled. Physical quantities, such as mass transport coefficients, * Corresponding author. Tel.: þ55-41-330-1322; fax: þ55-41-330-1349. thermal conductivity and specific heat, are variable and E-mail address: [email protected] (N. Mendes). depend on wall temperature and moisture content. 0378-7788/02/$ – see front matter # 2002 Elsevier Science B.V. All rights reserved. PII: S 0378-7788(02)00171-8 632 N. Mendes et al. / Energy and Buildings 35 (2003) 631–644 Nomenclature We also present results showing the importance of the terms in the heat and mass transfer model and the influence of weather on the conduction loads. In most cases, we shall Bim mass Biot number c specific heat (J/kg K) see that simplified heat and moisture transfer models lead to acceptable results, while at the same time reducing the run DTv vapor phase transport coefficient associated with a temperature gradient (m2/s K) time and number of inputs. Dyv vapor phase transport coefficient associated with a moisture content gradient (m2/s) 2. Mathematical model DT mass transport coefficient associated with a temperature gradient (m2/s K) The governing partial differential equations to model heat Dy mass transport coefficient associated with a moisture content gradient (m2/s) and mass transfer through porous walls are given by Eqs. (1) h heat convection transfer coefficient (W/m2 K) and (2). They were derived from conservation of mass and energy flow in a one dimensional elemental volume of hm mass convection transfer coefficient (m/s) j total (vapor plus liquid) flow (kg/m2 s) porous material, since the temperature and moisture content 2 gradients are predominantly in the x-direction. Therefore, jv vapor flow (kg/m s) L heat of vaporization (J/kg), wall thickness (m) the energy conservation equation is written as q short-wave solar radiation (W/m2) r @T @ @T @ t time (s) r0cmðT; yÞ ¼ lðT; yÞ À LðTÞ ðjVÞ: (1) T temperature (8C) @t @x @x @x x distance into wall (m) and the mass conservation equation is Greek letters @y @ j : a solar thermal radiation absorptance ¼À (2) @t @x rl l thermal conductivity (W/m K) y total moisture volumetric content (m3 of Note that Eq. (1) differs from Fourier’s equation for transient water/m3 of porous material) heat flow by an added convective transport term (due to r mass density (kg/m3) moisture diffusion associated with evaporation and conden- sation of water in the pores of the medium) and by a Subscripts dependence on the moisture content (so that it is coupled app apparent to Eq. (2)). The driving forces for convective transport are l liquid temperature and moisture gradients. The vapor flow (Jv) and m mean total flow (J, vapor plus liquid) are expressed in terms of o solid matrix transport coefficients, D, associated with the thermal and v vapor moisture gradients [10] as: jv @T @y ¼ÀDTvðT; yÞ À DyvðT; yÞ ; (3) We have created submodels from this model by making rl @x @x various simplifications, such as assuming constant coeffi- j @T @y cients, neglecting latent effects within the wall, working ¼ÀDT ðT; yÞ À DyðT; yÞ : (4) with both ‘‘pure’’ and ‘‘apparent’’ thermal conductivity and rl @x @x approaching, in the most simplified form, Fourier’s equation Internally, the wall is exposed to convection and phase for transient heat flow. From these submodels we can change and externally (x ¼ 0) it is exposed to solar radiation determine how the simplifications effect accuracy and run (aqr), convection hextðText À Tð0ÞÞ and phase change time. (hm;extðrv;ext À rv;x¼0Þ), so that the energy equation becomes Submodel analysis is done for four different types of wall material: aerated cellular concrete (ACC), brick (BRK), @T À lðT; yÞ ÀðLðTÞjvÞx¼0 ¼ hextðText À Tx¼0Þ lime mortar (LMT) and wood. For the simulations we used @x x¼0 typical meteorological year (TMY) weather files for three þ aqr þ LðTÞhm;extðr À r Þ: (5) different climates: Singapore (hot/humid), Seattle (cold/ v;ext v;x¼0 humid) and Phoenix (hot/dry). Hourly room air temperature where hðT1 À Tx¼0Þ represents the heat exchanged with the and relative humidity were calculated with the DOE-2.1E outside air (described by the surface conductance h), aqr is building energy simulation program [12,13]. The submodels the absorbed short-wave radiation, and hmðrv;1 À rv;x¼0Þ is are compared to the results of the original, unsimplified the phase-change energy term. The solar absorptivity is a model to determine the effect on cooling loads and simula- and the mass convection coefficient is hm, which is related to tion run time. h by the Lewis relation. N. Mendes et al. / Energy and Buildings 35 (2003) 631–644 633 The mass balance at the outside surface (x ¼ 0) is In Submodel 4, the coefficients Dy,DT and l and the specific heat are held constant. Therefore, for Submodel 4, the @ @y @T hm energy and mass conservation equations can be written as: À DyðT; yÞ þ DT ðT; yÞ ¼ ðrv;1 À rx¼0Þ: @x @x @x x¼0 rl (6) @T @2T r c ¼ l ; (13) 0 m @t @x2 The above equations also apply to the inside surface (x ¼ L), with the omission of short-wave related terms. @y @2T @2y ¼ D ðT; yÞ þ D ðT; yÞ : (14) @t T @x2 y @x2 2.1. Submodels In fact, all of the submodels have the same basic mathema- tical structure except for Submodel 5 which neglects all In order to reduce CPU time or when there is a lack of moisture effects. In Submodel 5, the governing equation is material data, we derived six submodels as follows: the Fourier’s equation for transient heat flow with constant @T @ @T @ thermophysical properties, as described in Eq. (13).How- r c ðT; yÞ ¼ lðT; yÞ þ LðTÞr 0 m @t @x @x l @x ever, the boundary conditions are written as @T @ @y @T  DTvðT; yÞ þ LðTÞr DyvðT; yÞ : (7) @x l @x @x À l ¼ hextðÞþText À Tx¼0 aqr: (15) @x x¼0 To simplify writing this equation, we will use VT and Vq to Table 1 summarizes the submodels derived from the original designate the second and third right-hand terms of Eq.
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