Towards a new ground snow-load map for structural design in Germany

<p>The current European standard for snow loads on structures relies on characteristic values (i.e., snow loads with an annual probability of exceedance of 0.02 and referred to as the 50-year mean return levels) derived for Germany in 2005 using about 350 snow water-equivalent (SWE) time series from ground stations operated by the German National Weather Service (DWD) [<em>DIN EN 1991-1-3/NA:2019-04</em>, 2019]. Here we present a methodology for generating a new ground snow-loads map for Germany, which aims at improving the relative coarse spatial resolution and reducing uncertainties and inconsistencies at national borders of the actual standard. Our methodology is based on (1) high-quality and homogeneous snow-cover time series, including both daily snow-depth (from about 6000 stations in Germany and in neighbouring countries) and three-weekly water-equivalent observation (from about 10<sup>3</sup> German stations) over the period from 1950 to 2020, (2) an integrated model combining an empirical regression model for snow bulk density and the semi-empirical multi-level ΔSNOW model for generating accurate daily SWE values from 6000 snow-depth time series [<em>Castino et al.</em>, 2022], (3) the spatial interpolation of both daily snow-depth and modelled-SWE time series using a universal-kriging method to generate high spatial-resolution (~1km<sup>2</sup>) rasterised daily snow loads over the period from 1950 to 2020, and (4) the extreme value analysis of the rasterized daily snow loads for estimating the characteristic values at high spatial resolution for the entire German territory. The uncertainties of the obtained characteristic snow-load values will be estimated using a leave-one-out cross validation based on a selection of observed-SWE time series representative of the diversity of the regional snow climatology in Germany. Finally, the characteristic values of the snow-load map generated with this methodology will be compared with the current German standard.   </p> <p> </p> <p><strong>References</strong></p> <p>Castino, F., H. Schellander, B. Wichura, and M. Winkler (2022), SWE modelling: comparison between different approaches applied to Germany, abstract submitted to D-A-CH MeteorologieTagung - 21-25.03.2022, Leipzig.</p> <p>DIN EN 1991-1-3/NA:2019-04 (2019), Nationaler Anhang - National festgelegte Parameter - Eurocode 1: Einwirkungen auf Tragwerke - Teil 1-3: Allgemeine Einwirkungen - Schneelasten, edited, p. 22, Deutsches Institut für Normung e.V., Beuth-Verlag, Berlin.</p>

Experimental Study of Interference Effects of a High-Rise Building on the Snow Load on a Low-Rise Building with a Flat Roof

To explore the interference effects of a high-rise building on the snow load on a low-rise building with a flat roof, a series of wind tunnel tests were carried out with fine silica sand as a substitute for snow particles. The effects of the height of the interfering building and the distance between buildings on the snow distribution of the target building under three different wind directions were studied. The snow depth on the target building roof and the mass of particles blown off from the target building were measured during the wind tunnel tests, and the results showed that the snow distribution of the target building roof tends to be uniform when the interfering building is located upstream of the target building due to the shelter effect. When the interfering building is on the side of the target building, the snow distribution of the target building tends to be more uneven, because the interfering building increases the friction velocity on the target building roof near the interfering building. However, when the interfering building is located downstream of the target building, there will be an amplification effect of snow accumulation, and the snow distribution on the target building roof is nearly the same as that of the isolated condition. Under each wind direction, the interference effect of the snow load increases with the increase of the building height and the decrease of the building spacing. Therefore, the influence of the surrounding buildings on the snow distribution of the building roof cannot be ignored and should be considered in the structure design.

Investigation of snow load reduction in the industrial sheds roof design with photovoltaic systems by mathematical modelling, solar system evaluation, X-steel simulation and thermodynamic practices

Since snow load is one of the loads of designing the industrial shed roof, this research presents a new system to reduce the industrial sheds roof design. In this system, sensitive units of moisture and temperature, which can be adjusted with different areas, are installed on the shed’s roof. The mechanism of system is that the sensors in the units detect the presence of snow on the shed roof and send an order to connect electricity to the elements; therefore, the snow on the roof melts by the heat generated. In this system, solar panels are used to supply electricity. As with the help of this mechanism, snow does not remain on the roof, it is possible to eliminate the snow load in the calculations of the shed and apply at least the live load of the sixth regulation (Due to having a one-story shed, minimum live load applied and it used only for the foundation design of the structure.), this issue will create an economic plan in shed designing. According to the study conducted in this research, it is shown that the dimensions of the sheet beam used in the shed are reduced, which will significantly reduce the cost of construction and installation to some extent. In the following, two samples of sheds with a span of 20 meters in the presence of snow and the absence of snow in the software were modelled, and the results were compared with each other.

Towards a reproducible snow load map – an example for Austria

The European Committee for Standardization defines zonings and calculation criteria for different European regions to assign snow loads for structural design. In the Alpine region these defaults are quite coarse; countries therefore use their own products, and inconsistencies at national borders are a common problem. A new methodology to derive a snow load map for Austria is presented, which is reproducible and could be used across borders. It is based on (i) modeling snow loads with the specially developed Δsnow model at 897 sophistically quality controlled snow depth series in Austria and neighboring countries and (ii) a generalized additive model where covariates and their combinations are represented by penalized regression splines, fitted to series of yearly snow load maxima derived in the first step. This results in spatially modeled snow load extremes. The new approach outperforms a standard smooth model and is much more accurate than the currently used Austrian snow load map when compared to the RMSE of the 50-year snow load return values through a cross-validation procedure. No zoning is necessary, and the new map's RMSE of station-wise estimated 50-year generalized extreme value (GEV) return levels gradually rises to 2.2 kN m−2 at an elevation of 2000 m. The bias is 0.18 kN m−2 and positive across all elevations. When restricting the range of validity of the new map to 2000 m elevation, negative bias values that significantly underestimate 50-year snow loads at a very small number of stations are the only objective problem that has to be solved before the new map can be proposed as a successor of the current Austrian snow load map.

STATISTICAL SUBSTANTIATION OF SNOW LOAD STANDARDS ON BUILDING STRUCTURES

Ensuring the reliability and safety of buildings and structures largely depends on a proper understanding of nature and quantitative description and rationing of loads on building structures, including snow loads. These loads on structures have a very complex physical nature and changeable nature, requiring knowledge of thermodynamic processes in the atmosphere and soil, physical properties of snow, methods of meteorological observations and climatological description of the terrain, variability of loads, the nature of snow deposition on buildings and structures. Such features are to some extent reflected in the sections of design standards of building structures that contain standards for snow load. Most parameters of snow load norms are probabilistic in nature and require the use of statistical methods to justify them. These methods are constantly changing and evolving along with the regular review of building design codes. Analysis of the evolution of domestic snow load codes together with their statistical substantiation is an urgent task. Materials on snow load have been published in various scientific and technical journals, collections of articles, conference proceedings. Access to these publications is difficult, and published reviews of the development of snow load rationing are incomplete and do not include the results of research over the past 15 – 20 years. The article contains a systematic review of publications in leading scientific and technical journals on the problem of snow load over the 80-year period from the 40s of the twentieth century to the present. The main attention is paid to the analysis of tendencies of development of designing codes concerning changes of territorial zoning and design coefficients, appointment of normative and design values of snow load and involvement in it of experimental statistical data. There is a high scientific level of domestic code DBN B.1.2-2006 "Loads and loadings", which have a modern probabilistic basis and are associated with the codes of Eurocode. Scientific results that can be included in subsequent editions of snow load standards are highlighted.

Mapping the probability of forest snow disturbances in Finland

The changing forest disturbance regimes emphasize the need for improved damage risk information. Here, our aim was to (1) improve the current understanding of snow damage risks by assessing the importance of abiotic factors, particularly the modelled snow load on trees, versus forest properties in predicting the probability of snow damage, (2) produce a snow damage probability map for Finland. We also compared the results for winters with typical snow load conditions and a winter with exceptionally heavy snow loads. To do this, we used damage observations from the Finnish national forest inventory (NFI) to create a statistical snow damage occurrence model, spatial data layers from different sources to use the model to predict the damage probability for the whole country in 16 x 16 m resolution. Snow damage reports from forest owners were used for testing the final map. Our results showed that best results were obtained when both abiotic and forest variables were included in the model. However, in the case of the high snow load winter, the model with only abiotic predictors performed nearly as well as the full model and the ability of the models to identify the snow damaged stands was higher than in other years. The results showed patterns of forest adaptation to high snow loads, as spruce stands in the north were less susceptible to damage than in southern areas and long-term snow load reduced the damage probability. The model and the derived wall-to-wall map were able to discriminate damage from no-damage cases on a good level (AUC > 0.7). The damage probability mapping approach identifies the drivers of snow disturbances across forest landscapes and can be used to spatially estimate the current and future disturbance probabilities in forests, informing practical forestry and decision-making and supporting the adaptation to the changing disturbance regimes.

Effect of Circular, Square and Rectangular Column in Building

While designing any structural building, the only distress of the designer is the stability of the building and its performance under internal and external forces & Loads. These forces & loads mostly comprise of dead load of the structure, superimposed load, snow load, or some other loads due earthquake, wind etc. Increase in height more force will be generated in taller building. So, for repelling developed forces, high strength members of the structure are required. Column, being the vertical member, is the most important member in a structure as it transfers the whole loads & forces from all the other structural members to the foundations. Its shape, cross-section and the area of reinforcement will change with the total load acting on the structure. Shape & Size of column can change for any structure according to its purpose. In the present study various models were analyzed considering individual and combinations of various geometric and from results various conclusions were draft.