Data & Probabilistic Analysis Tool


Tutorial video on the "Data and Probabilistic Analysis Tool"

The "Data and Probabilistic Analysis Tool" is a collection of Matlab routines written for the analysis of wind load data obtained in wind tunnel experiments. Since wind loading is generally understood as a time-varying process main focus is on the analysis of time series of the acquired wind load but can easily as well be applied on measurements of stochastic processes in general. Following scrips are provided and are described in the documentation manual.

THA6.m - Time History Analysis
This script was developed to perform a first analysis on measured data from a wind tunnel test. A first check of the measurement quality is done by visual inspection, meaning that we just take a look at the raw data of the measurements. Furthermore, the probability density function of all data points is shown and compared to a Normal distribution density to indicate possible skewness of the ensemble of all data points. Additional functions like the calculation of the power spectral density, digital filtering and detrending, and application of sub-series allow for basic signal processing.

TSCorr.m - Time Series Correlation
In case we would like to compare two processes, XA(t) and XB(t), occurring at the same time we often are interested in how parallel the fluctuations in the two processes are to each other. A common graphical method is to create a correlation plot where for each single time instant, ti, the values XA(ti) and XB(ti) are the coordinates in a Cartesian system. The resulting graph gives an image of the correlation between both time processes.

JPDF.m - Joint Probability Density Function
Once the distribution density of a stochastic process is known we can use it to calculate probabilities for occurrence, exceedance or non-exceedance of a particular value. In this case we reduce the underlying stochastic time process to a stochastic variable characterised by it probability density. For events consisting of at least two variables we can calculate a joint probability density function (JPDF). This scripts illustrates the JPDF  of two variables and allows calculating the probability of a specific case consisting of certain combinations of the two variables.



Wind Load Data Base

Data sets used for teaching in Wind Engineering. The data formats are described in the documentation of the "Data and Probabilistic Analysis Tool".

BendTs.txt - Data file containing the time series of the base bending moment [N] of a high-rise building under wind. Two column structure: first column = time axis, second column = value of base moment.

18Signals.dat - File with 18 time series of pressure coefficients measured in a wind tunnel test on a model low-rise building (based on cpcent.00). At the top of the data set of 18 individual signals (pressure coefficients along the centre bay of a low-rise building) the mean velocity at building’s eaves height (model scale) is given in [kPa]. The data set has no time axis! To plot the signal correctly and to calculate the spectral density the sample frequency (1600Hz) has to be defined separately.

cpcent.00 and cpcent.01 -For the calculation of the dynamic non-linear response of the steel frame supporting structure the data have been organized alternatively in 12 blocks each lead by the mean velocity pressure applicable on the subsequent data set. This fragmented format of the measured wind load process is contained in file “cpcent.00” (family of 100 data sets cpcent.00 to cpcent.99). This data format has been chosen within the “BEATRICE Joint Project: Wind Action on low-rise buildings” and is included in the THA6.m scrip.