The assessment of global bending stiffness of three old timber beams is predicted by use of random sampling and Bayesian Network approaches. The information for the prediction models derive from the visual grading and localized mechanical testing of 20 beams retrieved from the same building, which have been scope of analysis in previous studies. Although the results indicate moderate correlations between predicted and experimental results, significant percentage errors are also found. To minimize the percentage error between experimental and predicted values, coefficients corresponding to the scale effect relation between existing chestnut timber elements with round cross section and sawn beams of smaller dimensions with rectangular cross s...
Regression trees, random forests, and generalized additive models (GAM) are statistical techniques o...
The assessment of existing timber structures requires the determination of the mechanical properties...
One of the main motivations for hierarchical modelling is to understand how properties, composition ...
The assessment of the mechanical properties of existing timber elements could benefit from the use o...
The assessment of the mechanical properties of existing timber elements could benefit from the use o...
The assessment of the mechanical properties of existing timber elements could benefit from the use o...
In this work, the variation of bending stiffness parameters of existing timber elements is assessed ...
In this work, the variation of bending stiffness parameters of existing timber elements is assessed ...
The results of visual inspection according to UNI 11119:2004 and bending tests made on 20 old chestn...
The results of visual inspection according to UNI 11119:2004 and bending tests made on 20 old chestn...
In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchi...
The assessment of existing timber structures requires the determination of the mechanical properties...
The assessment of the structural performance of existing timber structures is dependent, among othe...
The assessment of existing timber structures is often limited to information obtained from non or se...
Regression trees, random forests, and generalized additive models (GAM) are statistical techniques o...
Regression trees, random forests, and generalized additive models (GAM) are statistical techniques o...
The assessment of existing timber structures requires the determination of the mechanical properties...
One of the main motivations for hierarchical modelling is to understand how properties, composition ...
The assessment of the mechanical properties of existing timber elements could benefit from the use o...
The assessment of the mechanical properties of existing timber elements could benefit from the use o...
The assessment of the mechanical properties of existing timber elements could benefit from the use o...
In this work, the variation of bending stiffness parameters of existing timber elements is assessed ...
In this work, the variation of bending stiffness parameters of existing timber elements is assessed ...
The results of visual inspection according to UNI 11119:2004 and bending tests made on 20 old chestn...
The results of visual inspection according to UNI 11119:2004 and bending tests made on 20 old chestn...
In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchi...
The assessment of existing timber structures requires the determination of the mechanical properties...
The assessment of the structural performance of existing timber structures is dependent, among othe...
The assessment of existing timber structures is often limited to information obtained from non or se...
Regression trees, random forests, and generalized additive models (GAM) are statistical techniques o...
Regression trees, random forests, and generalized additive models (GAM) are statistical techniques o...
The assessment of existing timber structures requires the determination of the mechanical properties...
One of the main motivations for hierarchical modelling is to understand how properties, composition ...