Stochastically Correlated Signals

Generation of spatially and temporally correlated signals from spectra. This is used in wind engineering to simulate the dynamic action of wind turbulence on structures.

Signal Analysis

Analysis of months of sampling of a high-rise building's acceleration and correlation with wind speed.

Frequency sensitivity

Sensitivity analysis of the highest response factors to quasi-random inputs.

We do research in signal processing and engineering applied to buildings' accelerations for retrofitting, vibration tests, and crowd modeling as well. We use Matlab, Python, C++ or C# according to your needs 👌.
ax.plot(acc_all.index, acc_all[['acc_x', 'acc_y']])
ax.set_ylabel('Displacements')
ax.legend(['acc_x', 'acc_y'],loc="upper right")

displacements

Stochastically correlated wind turbulence time-history

Wind turbulence speed at points in space can be described as a spatially- and temporally-correlated stochastic process.

A computationally optimized algorithm was developed to model this effect on slender buildings such as skyscrapers, bridges, and cable structures.

low freq 3d

Response of dynamic excitation

FE models and Matlab/python scripts are used to model the response of complex structures and materials to dynamic input such as wind, pedestrian movements, and machinery.