Evaluation of a prototype NIR system for Douglas-fir wood density estimation

Forest products companies in the U.S. face vigorous competition from other wood producers around the world and other industries (steel, aluminum, plastics, composites). To be competitive, forest companies need to control costs, sort and allocate logs to the most appropriate markets, and recover more value at time of harvest. Interest in log sorting based on internal wood properties is increasing. Wood properties, such as stiffness and density, are now being considered by log buyers. Assessing these properties in-forest and in real-time will be a challenge for log supply managers. The utility of near infrared (NIR) technology for measuring wood density is showing promise in laboratory conditions. The rationale behind this study was to evaluate NIR under conditions that are similar to field harvesting operations to estimate log density. Douglas-fir wood samples (110 disks) were collected from the McDonald-Dunn forest and processed in the OSU Oak Creek laboratories. Processing conditions were organized to simulate a harvester processor environment by using a chainsaw, and then channeling the chips with a chute to concentrate chips to move past an NIR sensor. This apparatus was intended to mimic a sensor system fitted to a harvester head.. A rugged Prospectra D² NIR sensor was used to collect spectral data. The generated spectra were analyzed in two forms, as raw data (without any transformations) and a transformed data (2nd derivative). Then, four types of calibration models were applied to predict log density: (1) models that used tree parameters only as a predictor (the simple model), (2) models that used NIR absorbance data and Partial Least Squares (PLS) analysis procedures , (3) models that used NIR absorbance data and Multiple Linear Regression (MLR) analysis procedures, and (4) models that used a mix of NIR absorbance data and tree parameter data and MLR analysis procedures. The goal of the models was to use the NIR data to predict the density of the log that has been cut. Model results were also obtained for validation (full cross validation) and calibration sets. Data analysis suggests that correlations for calibration sets (R) were high, but when validation was applied there were large drops in R values. The best fit model was the simple model, the model that did not include NIR data as predictors. Our interpretation of why the simple model was the best fit is that there is great variability of wood characteristics across the stem section, that there was morphological problems associated with how we presented the samples, and that we used a narrower spectral range of NIR compared to the range used in earlier studies

Forest Harvest Residue Moisture Management in the Pacific Northwest, USA

Moisture content management is a key requirement to improve forest harvest residue economics for bioenergy production. This dissertation aims to contribute towards better management through these three general objectives (1) Determine average moisture content of fresh forest harvest residues and its changes over the different seasons of the year, focusing on the three main commercial forest species growing in the Pacific Northwest, (2) Determine in-forest stored drying rates of this material for two harvest systems and the same species specified in objective (1) and (3) Determine the cost effectiveness of in-forest drying for two harvest systems and the advantages of drier material when its energy content is considered at a cogeneration facility. A repeated measures experimental design was conducted to determine average branch moisture content in live trees during each season of the year in four different locations in Oregon. At the same time, an innovative sampling protocol was employed to determine moisture content for in-forest stored of piled and scattered harvest residues for one year in four different Oregon sites. These data were used to calibrate finite element analysis (FEA) models to predict residue drying rates based on weather information such as temperature, relative humidity, precipitation and wind velocity. Finally, one of the FEA models was used to determine drying rates on real Douglas-fir units harvested with different harvest systems (a case study). These harvest units were employed to set a mixed integer linear program to optimally deliver harvest residues to a hypothetical cogeneration plant over 24 periods (months) and determine processing and transport costs. Major findings indicate that from all sites, the highest moisture recorded was 50% (wet basis) in ponderosa pine during the winter; the lowest was 43% in the summer for both the same ponderosa pine and Willamette Valley Douglas-fir. When compared by season, ponderosa pine had significantly higher moisture content in the winter than in other seasons (1.6 to 9.8% higher). Summer moisture content was also significantly lower than fall moisture content for ponderosa pine (5.4 to 2.5% lower). Willamette Valley Douglas-fir had significantly lower moisture content during summer than during other seasons (0.8 to 3.9% lower). FEA models were successfully developed to determine drying rates for four different climate regions in Oregon. These models were compared with data obtained in the field and statistical tests show model agreement with correlations between 0.56 and 0.92 (Kendall’s tau) on all sites. The harvest residue generated from the case study was sufficient to optimally deliver the necessary volume to supply 63% of a hypothetical 6 MW-hr cogeneration plant. Approximately 98% of the harvest residue generated with cable logging system was delivered to the plant compared with only 56% of the residue generated with a ground-based system. By considering the energy content of drier residues, the amount of ODMT needed to supply the plant can be reduced by 13.3% without affecting the energy output over a 6-period planning horizon. A lower ODMT demand and shifting to drier material results in 16.5% lower cost, which represents a more accurate estimate of the production cost. We conclude that forest harvest residues that are mainly composed of branches should not have moisture content levels greater than 50%. Seasonality should not affect the average moisture content of this material unless it is composed of ponderosa pine. After harvesting, piling residues in a berm (windrow) shape will promote drying in the summer and re-wetting in the winter. It is best to reduce pile size to facilitate drying in summer, and increase pile size if material will be left in the field over the winter. Drying times can be reduced up to 1/3 if the material is cut and left to dry during the dry, warm summer months versus starting in the winter. I this case study, residues coming from cable harvest units present a cost advantage compared to ground-based harvest units. Collection cost from the drier ground-based units was too large to offset the higher moisture content of piled residue in the cable harvest units. Recognizing the energy value of drier material has potential to improve the supply and cost estimates of the utilization of forest harvest residues for power generation

Economic implications of moisture content and logging system in forest harvest residue delivery for energy production: a case study

The need for improving the cost effectiveness of forest harvest residue utilization for bioenergy production has been widely recognized. A number of studies show that reducing residue moisture content presents advantages for transportation and energy content. However, previous research has not focused on the relative advantages of in-forest drying depending on the residue characteristics from different logging systems, comminution, and equipment mobilization. Residue drying curves were developed using Finite Element Analysis for two primary Pacific Northwest logging systems. These curves were applied to a case study in Oregon where mixed integer mathematical programming was used to optimize residue delivery to a hypothetical cogeneration plant with a generating capacity of 6 MW-hr. Assuming rear-steered trailers can access cable logging units, approximately 98% of the harvest residue generated with cable system was delivered to the plant, compared with only 56% of residue generated with a ground-based system. Mainly because collection costs incurred with ground-based system residues exceed cost benefits of drier material. By considering the energy content of drier residues, the amount of Oven Dried Metric Tonnes (ODMT) needed to supply the plant can be reduced by 16% without affecting the energy output on the 24-period planning horizon. Lower ODMT demand and shifting to drier material decreases the overall production cost by 20.4%.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author