94 research outputs found
Reduction of Volatile Organic Compounds Emitted during Kiln Drying of Southern Yellow Pine Lumber
The objective of the research is to reduce the volatile organic compounds (VOCs) emitted during kiln drying of southern yellow pine (SYP) lumber. Three treatment methods were explored to determine their effect on VOC emissions. The three methods were configured at the air exhaust of a pilot-scale dry kiln. 1) A steel reactor containing copper tubing heated to 100°, 200°, and 240° Celsius was evaluated. Temperature did not statistically affect VOC emissions (p-value = 0.1674). The average reduction of VOCs at 240° C was seven percent. 2) The use of hydrogen peroxide and ultra-violet (UV) light did not reduce VOCs emitted during kiln drying. 3) The use of Fenton?s reagent, with hydrogen peroxide and ferrous sulfate, also did not reduce VOCs emitted during kiln drying. 4) It is recommended that future studies with copper heated to temperatures above 240° C be performed
Image analysis to assess wood variability in longleaf pine cross-sectional disks
Image analysis is an important method for rapidly measuring wood property variation, but it is infrequently applied to disks collected from forestry studies. The objective of this study was to compare image estimated wood and bark volumes and diameters to reference measurements, and to extract more information from the images including the shape (out of round index, eccentric pith) and the amount and location of severe compression wood. A total of 1,120 disks were cut from multiple height levels of 48 defect-free and 56 defect-containing longleaf pine (Pinus palustris) trees from 16 stands across Georgia (U.S.). Disks were machined on one transverse surface using a computer numeric controlled router to prepare a clean surface for imaging. Three images; one under white light, second under blue light, and third under blue light with a green longpass filter, were taken for each disk. Volumes and diameters estimated from images were in close agreement with reference methods. Linear models fitted as measured versus image volumes for wood and bark had coefficient of determination (R2) values of >0.99 and 0.96. Linear models fitted as measured versus image diameters had R2 values of >0.99. Out of round index and pith eccentricity values calculated from images showed a moderate positive correlation (R=0.43). Algorithms developed were able to correctly identify severe compression wood, but not mild to moderate compression wood. Severe compression wood was moderately correlated to out of round index (R=0.54) and pith eccentricity (R=0.48). More than 98% of the disks having severe compression wood came from defect-containing trees
Comparison of Nondestructive Testing Methods for Evaluating No. 2 Southern Pine Lumber: Part B, Modulus of Rupture
The identification of strength-reducing characteristics that impact modulus of rupture (MOR) is a key differentiation between lumber grades. Because global design values for MOR are at the fifth percentile level and in-grade lumber can be highly variable, it is important that nondestructive evaluation technology be used to better discern the potential wood strength. In that manner, higher-performance pieces could potentially be identified and their value captured accordingly. In this study, laboratory tests of three nondestructive testing (NDT) technologies and destructive four-point static bending were applied to 343 pieces of visually graded No. 2 southern pine lumber in the 38140 mm2 (n . 86), 38186 mm2 (n . 112), 38236 mm2 (n . 91), and 38 287 mm2 (n . 54) sizes collected across the southeast region of the United States. The NDT tests included continuous lumber test in continuous proof bending (MetriguardModel 7200 High Capacity Lumber Tester), transverse vibration (Metriguard E-Computer), and two longitudinal stress wave tools (Falcon A-Grader and Fiber-gen Director HM200). Following nondestructive tests, the specimens were destructively tested in four-point static bending. Single-predictor linear correlations were observed between static bending MOE and MOR value; and NDT outputs and bending MOR value. The regression results showed that the average NDT outputs (r2 . 0.23-0.28) had lower performance than static bending MOE (r2 . 0.39), for predicting the bending MOR of sawn lumber.
Bowtie Beams: Novel Engineered Structural Beams from Southern Pine Lumber
The intersection of decreasing resources and increasing population and its associated demands creates a need to develop alternative products to solid sawn lumber. This research used a modified form of sawn southern pine (SP) lumber in which cants were sawn into symmetrical double-trapezoidal shapes and glued together to form a bowtie beam. The result was a cross-sectional shape that was widest at the beam flanges and narrowest at the neutral axis. Cants were cut from logs and sawn into trapezoids, nondestructively tested, glued into the bowtie beams, and nondestructively and destructively tested to determine mechanical values as per ASTM D4761. The objectives of this study were to manufacture composite bowtie beams and to conduct nondestructive and destructive testing on the beams. Overall, the bowtie beams compared favorably with strength properties of No. 2 SP lumber of roughly equivalent size to the bowtie beams. The bowtie beam shows promise as an engineered product because a minimal amount of capital and technology is needed to process small-diameter trees into this value-added product
FIBER QUALITY PREDICTION USING NIR SPECTRAL DATA: TREE-BASED ENSEMBLE LEARNING VS DEEP NEURAL NETWORKS
The growing applications of near infrared (NIR) spectroscopy in wood quality control and monitoring necessitates focusing on data-driven methods to develop predictive models. Despite the advancements in analyzing NIR spectral data, literature on wood science and engineering has mainly uti- lizedthe classic model development methods, such as principal component analysis (PCA) regression or partial least squares (PLS) regression, with relatively limited studies conducted on evaluating machine learning (ML) models, and specifically, artificial neural networks (ANNs). This couldpotentially limit the performance of predictive models, specifically for some wood properties, such as tracheid width that are both time-consuming tomeasure and challenging to predict using spectral data. This study aims to enhance the prediction accuracy for tracheid width using deep neural networks and tree-based ensemble learning algorithms on a dataset consisting of 2018 samples and 692 features (NIR spectra wavelengths). Accord- ingly, NIR spectra were fed into multilayer perceptron (MLP), 1 dimensional-convolutional neural net- works (1D-CNNs), random forest, TreeNet gradient-boosting, extreme gradient-boosting (XGBoost), and light gradient-boosting machine (LGBM). It was of interest to study the performance of the models with and without applying PCA to assess how effective they would perform when analyzing NIR spectra with- out employing dimensionality reduction on data. It was shown that gradient-boosting machines outper- formed the ANNs regardless of the number of features (data dimension). Allthe models performed better without PCA. It is concluded that tree-based gradient-boosting machines could be effectively used for wood characterization utilizing a medium-sized NIR spectral dataset
The NEO Surveyor Near Earth Asteroid Known Object Model
The known near-Earth object (NEO) population consists of over 32,000 objects,
with a yearly discovery rate of over 3000 NEOs per year. An essential component
of the next generation of NEO surveys is an understanding of the population of
known objects, including an accounting of the discovery rate per year as a
function of size. Using a near-Earth asteroid (NEA) reference model developed
for NASA's NEO Surveyor (NEOS) mission and a model of the major current and
historical ground-based surveys, an estimate of the current NEA survey
completeness as a function of size and absolute magnitude has been determined
(termed the Known Object Model; KOM). This allows for understanding of the
intersection of the known catalog of NEAs and the objects expected to be
observed by NEOS. The current NEA population is found to be complete
for objects larger than 140m, consistent with estimates by Harris & Chodas
(2021). NEOS is expected to catalog more than two thirds of the NEAs larger
than 140m, resulting in of NEAs cataloged at the end of its 5 year
nominal survey (Mainzer et al, 2023}, making significant progress towards the
US Congressional mandate. The KOM estimates that of the currently
cataloged objects will be detected by NEOS, with those not detected
contributing to the final completeness at the end its 5 year mission.
This model allows for placing the NEO Surveyor mission in the context of
current surveys to more completely assess the progress toward the goal of
cataloging the population of hazardous asteroids.Comment: 27 pages, 18 figures, 3 tables. Accepted for publication in Planetary
Science Journal (PSJ
RELATIONSHIP BETWEEN LOBLOLLY PINE SMALL CLEAR SPECIMENS AND DIMENSION LUMBER TESTED IN STATIC BENDING
Prior to the 1980s the allowable stresses for lumber in North America were derived from testing of small clear specimens but the procedures changed because these models were found to be inaccurate. Nevertheless, small clear testing continues to be used around the world for allowable stress determinations and in studies that examine forest management impacts on wood quality. Using small clears and nondestructive technologies is advantageous because of the ease of obtaining and testing small clear specimens compared to lumber. The objective of this study was to compare the mechanical properties in bending of small clear specimens with lumber specimens for loblolly pine. Eight hundred and forty-one pieces of lumber in the No. 1 to No. 3 grades and 2×4 to 2×10 sizes were collected from a forest-thru-mill study and tested in static bending. A small clear specimen (25 x 25 x 410 mm) was prepared from each piece of lumber and tested in static bending. The effect of growth ring orientation was explored and overall samples tested on the radial or rift face did a better job of explaining the variation in lumber than samples tested on the tangential face; however, the relationships were generally poor for the modulus of elasticity (MOE) (R2 = 0.22) and modulus of rupture (MOR) (R2 = 0.11) pooled data. A lumber-based multiple regression model explained 44% and 37% of the variability for MOE and MOR, respectively; whereas a stand-based multiple regression model explained 41% and 29% of the variability for MOE and MOR, respectively
Validation of the Survey Simulator tool for the NEO Surveyor mission using NEOWISE data
The Near Earth Object Surveyor mission has a requirement to find two-thirds
of the potentially hazardous asteroids larger than 140 meters in size. In order
to determine the mission's expected progress toward this goal during design and
testing, as well as the actual progress during the survey, a simulation tool
has been developed to act as a consistent and quantifiable yardstick. We test
that the survey simulation software is correctly predicting on-sky positions
and thermal infrared fluxes by using it to reproduce the published measurements
of asteroids from the NEOWISE mission. We then extended this work to find
previously unreported detections of known near Earth asteroids in the NEOWISE
data archive, a search that resulted in 21,661 recovery detections, including
1,166 objects that had no previously reported NEOWISE observations. These
efforts demonstrate the reliability of the NEOS Survey Simulator tool, and the
perennial value of searchable image and source catalog archives for extending
our knowledge of the small bodies of the Solar System.Comment: 19 pages, 6 figures, accepted for publication in PS
Size and Albedo Constraints for (152830) Dinkinesh Using WISE Data
Probing small main-belt asteroids provides insight into their formation and
evolution through multiple dynamical and collisional processes. These asteroids
also overlap in size with the potentially hazardous near-earth object
population and supply the majority of these objects. The Lucy mission will
provide an opportunity for study of a small main-belt asteroid, (152830)
Dinkinesh. The spacecraft will perform a flyby of this object on November 1,
2023, in preparation for its mission to the Jupiter Trojan asteroids. We
employed aperture photometry on stacked frames of Dinkinesh obtained by the
Wide-field-Infrared Survey Explorer and performed thermal modeling on a
detection at 12 m to compute diameter and albedo values. Through this
method, we determined Dinkinesh has an effective spherical diameter of
km and a visual geometric albedo of
at the 16th and 84th percentiles. This albedo is
consistent with typical stony (S-type) asteroids.Comment: Submitted to Astrophysical Journal Letter
Compensatory guaiacyl lignin biosynthesis at the expense of syringyl lignin in 4CL1-knockout poplar
The lignin biosynthetic pathway is highly conserved in angiosperms, yet pathway manipulations give rise to a variety of taxon-specific outcomes. Knockout of lignin-associated 4-coumarate:CoA ligases (4CLs) in herbaceous species mainly reduces guaiacyl (G) lignin and enhances cell wall saccharification. Here we show that CRISPR-knockout of 4CL1 in poplar (Populus tremula x alba) preferentially reduced syringyl (S) lignin, with negligible effects on biomass recalcitrance. Concordant with reduced S-lignin was downregulation of ferulate 5-hydroxylases (F5Hs). Lignification was largely sustained by 4CL5, a low-affinity paralog of 4CL1 typically with only minor xylem expression or activity. Levels of caffeate, the preferred substrate of 4CL5, increased in line with significant upregulation of caffeoyl shikimate esterase1. Upregulation of caffeoyl-CoA O-methyltransferase1 and downregulation of F5Hs are consistent with preferential funneling of 4CL5 products toward G-lignin biosynthesis at the expense of S-lignin. Thus, transcriptional and metabolic adaptations to 4CL1-knockout appear to have enabled 4CL5 catalysis at a level sufficient to sustain lignification. Finally, genes involved in sulfur assimilation, the glutathione-ascorbate cycle, and various antioxidant systems were upregulated in the mutants, suggesting cascading responses to perturbed thioesterification in lignin biosynthesis
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