Although it is common to model modulus of elasticity (MOE) and modulus of rupture (MOR) of graded lumber as normal, lognormal, or Weibull distributions, recent theories and empirical practices have cast doubt on these models. Mathematical proofs have been used to shown how the MOR distributions of graded lumber can be derived from the MOR distributions of mill-run populations. The MOR distribution of a graded lumber subpopulation is "pseudo- truncated" and does not exhibit the same theoretical form as the mill-run population from which it was drawn. Therefore, it is essential to explore the properties of mill-run lumber populations and properly characterize their MOE and MOR distributions. To investigate this topic, this dissertation has three objectives: 1) to determine if the within-mill means and standard deviations of MOE and MOR in mill-run southern pine (Pinus spp.) lumber differ over time, 2) to determine the correlations among hand-held grain angle meter readings, MOE, and MOR in mill- run southern pine lumber, and 3) to model statistical distributions of MOE and MOR in mill-run red pine (Pinus resinosa) and spruce (Picea spp.) lumber. This research features four main sections: 1) an introduction summarizing the conclusions of each chapter, 2) a chapter investigating if there are statistically significant differences between the means and variances of MOE and MOR in mill-run southern pine lumber populations at the same mill over time, 3) a chapter evaluating the bivariate correlations among handheld grain angle meter readings, MOR, and three measures of MOE in mill-run southern pine lumber, and 4) a chapter modeling the distributions of MOE and MOR in mill-run red pine and spruce lumber populations and comparing those to previous work on mill-run southern pine lumber populations.
| Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6076 |
| Date | 30 April 2021 |
| Creators | Anderson, Guangmei Cao |
| Publisher | Scholars Junction |
| Source Sets | Mississippi State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations |
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