Analysis of Non-Destructive Indicating Properties for Predicting Compressive Strengths of Dendrocalamus sericeus Munro Bamboo Culms

Abstract

Bamboo is a natural material with the potential for being used in sustainable construction. However, uncertainty in the bearing capacity of the bamboo results in nonstandard values for structural engineering design. This research studied the simple and multiple linear regression analyses for indicating properties to predict the axial compressive load capacity and strength of bamboo culms, which will be useful information for quality control during building construction and further structural grading. First, twelve basic physical properties were measured from 111 samples of Dendrocalamus sericeus Munro bamboo culms, and axial compressive load tests of the bamboo culms were performed. Then, the correlation significance of the physical properties to axial load capacity and strength (load per area) were analyzed by the Pearson correlation method. The results show that five parameters, i.e., linear mass, culm wall thickness, external diameter, moisture content, and density, were statistically significant with the responses (compressive load capacity and compressive strength) and then defined as “candidates for indicating properties”. Next, simple linear and multiple linear regression were analyzed to formulate the relationship between the significant indicating properties and the responses. From the simple linear regression analysis, linear mass can be best used as an indicating property for predicting the maximum compressive load. The maximum compressive strength was well associated with density. The multiple linear regression analysis shows an improvement in the response predictions with respect to the simple linear regression analysis with the higher R2-values. Finally, structural grading of the bamboo is determined.

Structural Optimization Design of a Six-Degrees-of-Freedom Serial Robot with Integrated Topology and Dimensional Parameters

“…In this paper, Pearson correlation analysis [ 38 ] is used to explore the relationship between independent variables and dependent variables. Here, the critical variables were used as independent variables, and the stiffness values in the X, Y, and Z directions were studied as dependent variables to explore the relationship between each group of critical variables and stiffness.…”