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Analysis of Red Oak Timber Defects and Associated Internal Defect Area for the Generation of Simulated Logs

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dc.contributor.authorWinn, Matthew F.en
dc.contributor.committeechairWynne, Randolph H.en
dc.contributor.committeememberOderwald, Richard G.en
dc.contributor.committeememberAraman, Philip A.en
dc.contributor.committeememberBaumgras, John E.en
dc.contributor.departmentForestryen
dc.date.accessioned2014-03-14T20:50:01Zen
dc.date.adate2002-12-30en
dc.date.available2014-03-14T20:50:01Zen
dc.date.issued2002-12-05en
dc.date.rdate2003-12-30en
dc.date.sdate2002-12-16en
dc.description.abstractLog sawing simulation computer programs can be a valuable tool for training sawyers as well as for testing different sawing patterns. Most available simulation programs rely on databases from which to draw logs and can be very costly and time-consuming to develop. In this study, a computer program was developed that can accurately generate random, artificial logs and serve as an alternative to using a log database. One major advantage of using such a program is that every log generated is unique, whereas a database is finite. Real log and external defect data was obtained from the Forest Service Northeastern Research Station in Princeton, West Virginia for red oak (Quercus rubra, L.) logs. These data were analyzed to determine distributions for log and external defect attributes, and the information was used in the program to assure realistic log generation. An attempt was made to relate the external defect attributes to internal defect characteristics such as volume, depth, and angle. CT scanning was used to obtain internal information for the five most common defect types according to the Princeton log data. Results indicate that external indicators have the potential to be good predictors for internal defect volume. Tests performed to determine whether a significant amount of variation in volume was explained by the predictor variables proved significant for all defect types. Corresponding R2 values ranged from 0.39 to 0.93. External indicators contributed little to the explanation of variation in the other dependent variables. Additional predictor variables should be tested to determine if further variation could be explained.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-12162002-104624en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12162002-104624/en
dc.identifier.urihttp://hdl.handle.net/10919/36181en
dc.publisherVirginia Techen
dc.relation.haspartthesis.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectlog simulationen
dc.subjectdata generationen
dc.subjectlog defectsen
dc.titleAnalysis of Red Oak Timber Defects and Associated Internal Defect Area for the Generation of Simulated Logsen
dc.typeThesisen
thesis.degree.disciplineForestryen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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