A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Characterization and evaluation of wood strand composite load capacity with near infrared spectroscopy
Abstract This study looked at the ability to use near infrared reflectance spectroscopy to non-destructively assess the load capacity and deflection of oriented strand construction board in the presence of phenol formaldehyde (PF) resin variation. The influence of PF resin on both mechanical properties was significant. Principal components regression was used to determine and rank statistically important principal components. For prediction of load capacity, the following associated wavelengths were important and in the following order: urea > lignin > cellulose > PF. Likewise, for prediction of deflection within the elastic region, the following associated wavelengths were important: urea > cellulose > lignin > PF. Models for prediction of load capacity (R 2 = 0.69) were stronger than those for deflection (R 2 = 0.59). It was determined that the predictive capability of the multivariate models were strong enough to characterize population parameters and for interpretation purposes but may not be precise enough for the accurate screening of individual panels.
Characterization and evaluation of wood strand composite load capacity with near infrared spectroscopy
Abstract This study looked at the ability to use near infrared reflectance spectroscopy to non-destructively assess the load capacity and deflection of oriented strand construction board in the presence of phenol formaldehyde (PF) resin variation. The influence of PF resin on both mechanical properties was significant. Principal components regression was used to determine and rank statistically important principal components. For prediction of load capacity, the following associated wavelengths were important and in the following order: urea > lignin > cellulose > PF. Likewise, for prediction of deflection within the elastic region, the following associated wavelengths were important: urea > cellulose > lignin > PF. Models for prediction of load capacity (R 2 = 0.69) were stronger than those for deflection (R 2 = 0.59). It was determined that the predictive capability of the multivariate models were strong enough to characterize population parameters and for interpretation purposes but may not be precise enough for the accurate screening of individual panels.
Characterization and evaluation of wood strand composite load capacity with near infrared spectroscopy
Via, Brian (author)
Materials and Structures ; 46 ; 1801-1810
2013-02-05
10 pages
Article (Journal)
Electronic Resource
English
| British Library Online Contents | 2013