Investigation of wood properties that influence the final moisture content of air-dried sugi (Cryptomeria japonica) using principal component regression analysis
Sugi (Cryptomeria japonica D. Don) lumber is known to have a large variability in final moisture content (MCf) and is difficult to dry. This study investigated the variability in MCf of sugi in relation to wood properties. The wood property variables included initial moisture content (MCi), basic density (BD), annual ring orientation (ARO), annual ring width (ARW), heartwood ratio (HR) and CIE L* color (L*). Sugi samples were cut from flat-sawn lumbers and air-dried; a principal component regression (PCR) model for predicting MCf was developed with the wood property variables. The wood properties that contributed to the prediction of MCf were evaluated by PCR analysis. Significant positive regression coefficients of the PCR model were observed in the MCi, BD, ARO and HR, whereas negative ones in the L*. There were no significant regression coefficients in the ARW. These results suggest that the MCi, BD, ARO and HR had a positive influence, the L* had a negative influence, and the ARW had little influence on the MCf of air-dried sugi wood. This finding is in line with the general view on the drying characteristics in relation to these wood properties.
Estimation of Drying Time for Air-drying of Logs and Evaluation of Log Properties Affecting Drying Characteristics of Logs Using a Hierarchical Bayesian Model
Air-drying is one of the most frequently used operations to dehydrate logging residues for produc-tion of wood fuel chips. This study developed a drying curve model for the air-drying of logs in order to estimate drying time to reach a given moisture level, and to evaluate the influence of log properties on drying characteristics of logs. Log piles of sugi （(cid:9479)(cid:9526)(cid:9533)(cid:9524)(cid:9528)(cid:9523)(cid:9521)(cid:9513)(cid:9526)(cid:9517)(cid:9509)(cid:9444)(cid:9518)(cid:9509)(cid:9524)(cid:9523)(cid:9522)(cid:9517)(cid:9511)(cid:9509)） were air-dried in Tsukuba city, Japan, from November 2014 to August 2015. A hierarchical Bayesian model was used to estimate the moisture content of individual logs as a function of initial moisture content, diameter, length, heartwood ratio, and drying time. The measured mean moisture content fit well to the estimated drying curve, indicating that the developed model is a potentially useful method to estimate the drying time for any moisture content within the limited range of climate conditions studied here. A comprehensive evaluation of log properties affecting the drying characteristics of logs showed that initial moisture content, diameter, and length have an influence on the drying rate of logs. time, hierarchical Bayesian model.
Drying of Loose and Particulate Materials
Particle properties moisture in particulate solids handling of feedstocks effects of drying moisture in gases heat transfer to particles kinetics of drying material and energy requirements in drying design and specification of a dryer process conditions in progressive dryers process conditions in non-progressive dryers hazards in drying control of dryers product collection and recovery.