WOOD RESEARCH Volume 61, Number 2, 2016
Jaroslav Sandanus, Kristián Sógel, and Miloš Slivanský

Results of rheological test on timber trusses

In the paper the results of exceptional experimentation are presented, which focuses on the long-term loading of metal plate connected wood trusses. The uniqueness of research project is given by real dimensions of long-span samples and by the term of loading over one year. The aims of long-term experimentation were detection of two main parameters. The magnitude of additional deflections and time of load action needed for their development. In the paper the deflection curves are presented, namely time dependence of deflections. In the paper the recommendations for producers of metal plate connected wood trusses and for structural engineers are mentioned. The purpose of that research project is to increase the safety and reliability of timber load-bearing structures.

WOOD RESEARCH Volume 62, Number 3, 2017
Pierre Kisitotalla, Prisca Kuida Atchounga, and Blaise Mtopi

Kalman filtering of gauges noise on the creep behavior of Entandrophragma cylindricum (Sapelli) under a constant stress

In this work, we drew the experimental or the true creep-recovery curves of Entandrophragma cylindricum known as sapelli from the values obtained during many four points flexural tests carried out on several samples of this hardwood. Thereafter, the experimental values have been perturbed by the white Gaussian noise of the gauges and this allowed us to draw the noisy curves of deformations. The creep test lasted ten hours and the recovery forty hours. Our main target in this work was to implement the recursive discrete Kalman filter, in order to predict or to estimate the deformation of this species undergoing a constant stress. From the simulation, since our estimate and our state have the same expected value, then our estimate is not biased. The true deformation and the estimated deformation curves are almost too close to distinguish from one another. Once the Kalman filter applied to our system satisfied these two preceding criteria, we are able to mention that our estimator has a good response therefore, it is an optimal filter.