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1
Content available remote Szary styropian w systemach ETICS
PL
W artykule omówiono zalety szarego styropianu w rozwiązaniach ETICS. Podano zalecenia odnoszące się do reżimu aplikacyjnego tych materiałów. Zwrócono uwagę na dokładne przestrzeganie zaleceń producentów. Wskazano perspektywy szarego styropianu na rynku polskim i europejskim.
EN
The article presents the advantages of grey EPS in ETICS solutions. Recommendations are given regarding application regimes for these materials. Attention is drawn to exact compliance with manufacturers’ recommendations. The perspectives of grey EPS on the Polish and European market are identified.
2
Content available remote Zbiornik intercepcyjny brzozy brodawkowej (Betula pendula Roth)
EN
The aim of the paper is the description of the tree interception reservoir which, in this case, is the reservoir of European white birch (Betula pendula Roth). The target is to determine the interception capacity of an arbitrary species tree. A method is sought for determining the interception capacity of the reservoir of a tree which retains on its surface, in its structure, certain amounts of rain water passing from the atmosphere to the ground surface here the plant lives. To give the sought reservoir the physical sense, the reservoir base was accepted as the tree surface (two-side leaf area plus bark area), while the reservoir height was defined as the average depth of water layer that can be retained on the surface. The measured leaf area and bark area exhibit strong correlation with the breast height diameter and tree shoot diameter. It is therefore possible to determine the tree leaf and bark area based on the measured breast height diameter and tree height.Experimentally determined average depth of water layer on tree green and bark surfaces enables the tree interception reservoir height to be determined. Due to this, after making inventory of trees on the representative plot of the forest area, and taking into account its age and compactness, there will be the possibility to calculate its interception capacity. In this paper a method of calculating of the interception reservoir capacity of European white birch occurring frequently as single species or as an addition to other forest communities. As regards to its structure, the birch represents a specific tree type. Up today, in the Hydrology Section of the Institute of Water Engineering and Water Management of Cracow University of Technology, there were developed descriptions of interception reservoirs of other trees, both coniferous and deciduous, as spruce (Picea abies), oak (Quercus robur), hornbeam (Carpinus betulus), and pine (Pinus silvestris).We hope that the descriptions of reservoirs of various tree species will be integrated into a common description in future.
3
EN
The paper concerns the method of determining reservoir capacity of pine trees (Pinus silvestris) commonly occurring in Poland and Europe. Based on cumbersome and many-year measurements, experimental and field studies on plots in the Trzebuńka stream experimental catchment of the Hydrology Section of the Institute of Water Engineering and Water Management of Cracow University of Technology, a physical model is presented of the interception reservoir of an individual tree. The tree green (needle) surface and surface of stem and branches is the basis of the reservoir. Its height is determined by the depth of water layer that can be retained on the surface. However, if it can be accepted that the whole green surface retains rain water of the same average depth, then the depth of this layer on the bark surface depends on the stem or branch diameter. The older the stem or branch are the greater is the possibility of intercepting water because ofincreased roughness and fracturing of the intercepting surface. The magnitude of the green and bark surface of an arbitrary tree, as well as the depth of water intercepted by these surfaces, can be made using the relation with physical characteristics of the tree that are relatively easy to be measured: tree height, breast height diameter or both. If the green and total pine surface areas are to be calculated, the pine crown height may be added. It can be then calculated the green surface area of a tree taking into account the total surface area, not only the surface of the leaf projection onto the plane surface, FL1, (so FL2), stem surface, FB, and the bark total surface, FkC, as well as the depth of water stored on the bark surface Rk, versus the stem and branch diameter d. Water storage on the green surface was divided into wetting storage which will leave the surface by evaporation, and free water storage that gravity can force to flow down.All calculation formulas have high indices of correlation significance and enable the interception calculation to be carried out of a pine canopy consisting of trees of any age and density.
EN
Intensive increase of computational power available to process data, being collected and produced, caused that a large numberr of inwestigation method was constructed, and a large amount of different cycle of the climatic system variations was found. Some of them have strong physical support or natural explanation but major kinds of this periodicity have no confirmation, neither physical nor environmental. Astronomic cycles cause periodicity in various physical processes within the atmosphere-ocean-cryosphere system. If the interactions within the components of the climatic system combine properly and balance each other, they can give roughly cyclic variations. But therre is other possible way that can give rise to periodicity. For short time series, cyclicity may often be the result of sampling fluctuation. In that case it is called pseudo or sampling cyclicity. Determining that these pseudo-cycles are not statistically significant poses the main problem for analysis. The objective of this text is to present four methods considered as classical and relevant tools to solve problems of cyclic climatic variations. Various historical time series was put under analyze by applied described methods. It was shown how could the results for particular method differ from each other. No physical explanation for found varrious cycles is provided in the paper. The methods employed are: regression, autocorrelation function, periodogram and spectral density function. The data used are: monthly water level of the Baltic sea in Świnoujście (S) in the period 1986-1997, precipitation totals (P mm) in July at Warsaw over 1811-1960 and mean air temperature (7°C) in July at Warsaw over 1811-1960, annual flows of the River Odra at Słubice for the period 1951-1989 and annual mean Wolf numbers for the period 1749-1996. Figures 1-2 shows plotted time series for every phenomenon. Plot of the raw data set versus time makes possible recognition of the patterns how process evaluate can. It is the best starting point for further investigation. Another pictures present the way how particular method works.
EN
Ower the last decades, there has been a great increase of methods and techniques used for investigation of periodic structure of climatologic processes, caused by vital importance of determining climatic changes. The conventional methods and their modification as new computational techniques, differ between one another on the effectiveness and accuracy of results. In the paper there are presented methods applied for detection of periodicity in time series, and suitable statistical procedures for verification of periods detected. Regression and autocorrelation function methods were shown in their applications to various real data sets.
EN
Over the last decades there has been a great increase of methods and techniques used for investigation of periodic structure of climatologic processes, caused by vital importance to be able to determinate climatic changes. As the conventional methods and their modification as new computational techniques, differ between one another on the effectiveness and accuracy of results. In the paper there are presented two traditional methods applied in frequency domain for detection of periodicity in time series: periodogram and spectral density function together with suitable statistical procedures for verification of periods detected. The methods were shown in their applications to various real data sets.
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