Rudolf Plagge

Stochastic study of hygrothermal performance of a wall assembly—The influence of material properties and boundary coefficients

An accurate description of material properties and boundary conditions is the prerequisite to achieve reliable results of a hygrothermal performance simulation. However, the uncertainties widely exist in those input variables, e.g., due to the inhomogeneous nature of materials and discrepancies in material manufacturing and measurement processes, the material properties are subjected to considerable variation. Therefore, the simulation result may not be only a single value, but in a range of possibilities. In this article, a stochastic approach is developed and implemented by using uncertainty analysis which assesses the uncertainties of a models input variables on that of the output variables, and sensitivity analysis, which identifies the most influential input variables. The hygrothermal performance of one typical wall assembly in North America is studied by applying this approach, considering the uncertainties of material properties of each individual layer and the uncertainties of the interior and exterior boundary coefficients. The influence of wall orientation is also presented. The results show that the effect of a single input variable on an output variable is not constant but varies with time. The key variables that affect the results are also different over time.

On the Hysteresis in Moisture Storage and Conductivity Measured by the Instantaneous Profile Method

The relative humidity (or the capillary pressure) and volumetric water content can be determined at specific locations inside a porous medium by means of the proposed instantaneous profile method (IPM). The measurements are carried out with temperature and relative humidity (RH) sensors as well as with time domain reflectometry probes during the whole duration of the experiment. Thus, the IPM allows a transient measurement of the moisture retention characteristic. In addition, from the spatial and temporal distributions of moisture content and RH one may calculate the moisture conductivity as a function of moisture content and RH as well. The adsorption and successive desorption experiments presented in this article have been performed on calcium silicate (a capillary active material). The results show a hysteretic behavior that appears to depend on the nature of the process. The moisture conductivity as function of RH shows a significant hystereses; however, the moisture conductivity in relation to the moisture content appears to be non-hysteretic.

Evaluation of Functional Approaches to Describe the Moisture Diffusivity of Building Materials

With a set of material parameters and a material model called engineering model of hygrothermal material characteristics, both proposed in (Scheffler, 2004), the material functions used for input to hygrothermal building component simulation programs can be adjusted. Using inverse identification of functional parameters by simulation of laboratory experiments, the model is calibrated to reproduce measured water uptake and drying curves. The developed material functions contain an approach to describe the liquid water conductivity of building materials. In addition, moisture storage data approximated by a GAUSSian functional approach, showing sufficient flexibility in the whole moisture range, is available. There with the derivative of the moisture retention curve is known at high precision and the liquid water diffusivity can be derived, too. There exists a wide interest in applicable material functions based on literature data. But literature reviews of hygrothermal material parameters often yield incomplete datasets and experimentally determined curves are lacking or are available at lower accuracy only. Different authors introduced several diffusivity approaches requiring less input parameters for description of liquid water transport in building materials. These models are evaluated by means of diffusivity data derived from the calibrated liquid water conductivity function of the engineering model. A selection of four accurately measured materials is used for this investigation. The investigation is based on controlled laboratory data of high resolution. With the knowledge gained from this study, the uncertainties in interpretation of incomplete datasets frequently encountered in literature reviews shall be reduced.

Application of clustering technique for definition of generic objects in a material database

In this article, generic objects are introduced into material databases of building simulation tools. A generic object has the common characteristics of one type of specific object and can represent specific ones in the simulation. The application of generic objects only requires some general design information; thus, it is convenient for the simulation users who do not have a detailed knowledge of building specification in the early design stage. First, the method to uncover the underlying cluster structure in the dataset is illustrated. Clustering of the objects depends on the adopted clustering variables and clustering procedure. Therefore, different clustering techniques are applied to agglomerate specific materials into different clusters, and the clustering solutions are compared for validation. Generic synthesis is then conducted to derive the generic material from each identified cluster. The approach on how to apply generic materials to fill in missing values of the incomplete material data is also described.

Ein autoregressives Verfahren zur Bestimmung der gesättigten und ungesättigten hydraulischen Leitfähigkeit

Mit Hilfe der Augenblicksprofilmethode wurde die Wasserleitfahigkeit fur den wasserungesattigten Bereich (k) bestimmt. Dabei wurden Wassergehalte und Wasserspannungen als Funktion der Zeit und Tiefe an Stechzylinderproben gemessen. Die Messungen der Wassergehalte und Wasserspannungen erfolgten mit TDR-Sonden bzw. Druckaufnehmertensiometern. Das Untersuchungsmaterial umfaste 40 Bodenhorizonte mit einem weiten Spektrum in Textur und Lagerungsdichte. Neben den k-Werten wurden auch die gesattigte Wasserleitfahigkeit kf und die pF-Kurve bestimmt. Anhand dieser Daten wurde ein „autoregressives Verfahren“ zur Berechnung der k-Werte fur die Wasserspannungen 30, 60, 100, 300 und 600 hPa fur lehmige Sande, sandige, tonige und schluffige Boden entwickelt. Dabei wurde zunachst der k-Wert berechnet, der sich mit der grosten Genauigkeit anhand von Kennwerten der pF-Kurve ermitteln last. Bei der k-Wertberechnung der benachbarten Wasserspannungsbereiche geht neben den Kennwerten der pF-Kurve der bereits berechnete k-Wert mit ein. Auf diese Weise wird eine hohere Genauigkeit bei der Ermittlung der k-ψ-Beziehung zwischen Wasserleitfahigkeit und Wasserspannung erreicht, wie der Vergleich mit anderen Verfahren zeigt. An autoregressive procedure to predict the hydraulic conductivity — Comparison of measured and predicted results An instantaneous profile method was used to measure the unsaturated hydraulic conductivity. Relatively new techniques involving undisturbed soil samples instrumented with minitensio-meters and Time-Domain-Reflectometry (TDR) mini-probes were used for the experiments. The laboratory method allows a high spatial and temporal resolution. Laboratory measurements were carried out for 40 soil horizons with a wide spectrum of texture and bulk density. In addition, retention curves were measured using the standard pressure plate apparatus. Using this homogeneous set of data, an autoregressive model was developed which allows a stepwise calculation of the hydraulic conductivity for a water potential range of —30 up to —600 hPa. This model was developed for loamy sands, sandy, silty and clayey soils in conjunction with data from the retention curves. The calculation procedure starts with the determination of an initial unsaturated conductivity (k) close to field capacity, i.e., for water potential from —60 hPa up to —100 hPa. This first value is then used to predict other conductivity values using appropriate changes in soil water content corresponding to a defined range of the soil water potential. Subsequently, the hydraulic conductivities for higher and lower potentials were estimated considering the k value of the previous step in combination with the data of the retention curve of the next water potential range. The advantage of this empirical model is the indirect consideration of soil structure, in contrast to the closed-form van Genuchten-Mualem (vGM) model. To demonstrate these effects on different fitting procedures, the vGM model was also used to describe soil hydraulic functions. The accuracy of both, the vGM model and the autoregressive one, were compared for various fitting procedures and soils.