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Forest Products Laboratory
One Gifford Pinchot Drive
Madison, WI 53726-2398
Phone: (608) 231-9200
Fax: (608) 231-9592


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Economics, Statistics and Life Cycle Analysis Research

Project Title :  Improved statistical modeling of wood, fiber and composite properties, processing, and performance
Project Number : FPL-4851-2A
Start Date : 07-23-2007
End Date : 07-23-2012

View the 5 publications associated with this project.

Principal Investigator:
Kenneth E. Skog

Non Technical Summary
PhotoResearch efforts in this problem area will focus on developing the improved statistical modeling methodology needed by FPL's research programs including evaluating effectiveness of different methods to estimate wood failure under weight loads, improved methods to refine estimates of the variation in properties of a certain category of wood material, improved methods sort wood into property classes, and improved modeling of the performance of wood assemblies that are engineered to have specific performance.

Objectives Summary
The objective of this problem area is to develop new statistical tools and evaluate existing tools. A better understanding of existing tools and development of new tools are critical to the innovative research by FPL scientists and to the FPL mission. For example, development of new methods of engineering design which will conserve wood will require development and application of refined statistical methods. Wood design has progressed from deterministic design methods to reliability-based design methods that are more dependent on statistical methods. Also, to help provide higher economic value from mixed species to offset the cost of removing wood fuel to reduce fire hazard in western states requires improved characterization of the wood properties of these species. Such characterization no longer starts with an assumption that the strength properties of lumber specimens under load are normally distributed and independent from each other. Instead wood properties are now regularly assumed to follow two and three parameter Weibull distributions or are characterized through nonparametric estimates. To obtain the best use of fiber from the national forests, we need to be able to characterize wood properties as coming from several different distributions. Modeling multidimensional dependencies among wood properties requires the development of the bivariate Weibull distribution for use in wood property estimation. As our options for characterizing wood properties increase, we need to know how to choose which distributional form best represents the data or whether to use methods that do not assume a distributional form. We need to be able to model the relationships between properties in a way that allows us to use these models to predict performance in situations where the material is under a combination of stresses. We also need to be able to predict how processing affects performance through the development of models that help us understand the statistical uncertainty of our predictions.

Approach Summary
Innovative research efforts of FPL scientists to address critical issues often violate standard statistical assumptions and thus are hampered by the lack of appropriate statistical methodology. Research efforts in this problem area will focus on developing the improved statistical modeling methodology needed by FPL's research programs. Sometimes the research effort will focus on the evaluation of existing statistical methods. In other situations, it will be necessary to develop new methods or extend the capability of existing methods. The breadth of this research is as broad as FPL's research program. Research under this problem area has a strong expectation of producing results that will be published in both statistical journals and journals appropriate to the areas of FPL's research program. Anticipated activities within the next 5 years are as follows: Improved material characterization under combined loading, 1. Evaluation of the effectiveness of different methods of estimating the correlation between lumber strength properties when the properties must be estimated through a destructive test. Improved estimation of material properties, 1. Evaluation of estimation methods and development of goodness-of-fit measures for complete and censored Weibull distributions. Wood classification systems, 1. Evaluation of potential measures of sorting effectiveness, assuming both equal and unequal cost for any misclassification. Improved modeling of the performance of engineered assemblies, 1. Improved understanding of the statistical issues involved in RBD with wood. 2. Evaluate proposed statistical paradigms of service life prediction in complicated environments for applicability to wood products. 3. Evaluate relationships between service life distributions and reliability based designs to improve structural and product safety at the design stage. Development and evaluation of statistical methodology for specific problems related to FPL research, 1. Review the exact approach to COV and development of a technology transfer procedure to aid ASTM committees in writing standards associated with COV measurements. 2. Evaluate the effect of normalizing transformations for the Shapiro-Wilk test. 3. Develop tables that augment Tables 2 and 3 of ASTM D2915 when predictor sort sampling is used. 4. Comparison of five approaches in estimating mean, standard deviation and percentiles currently available for evaluating fastener strengths. Development of Web-Based Tools for Predicting Air-Drying Times of Small-Diameter Logs

Publications associated with this Project

Publication YearTitleDate Posted
2012Asymptotically efficient estimation of a bivariate Gaussian–Weibull distribution and an introduction to the associated pseudotruncated Weibull08/03/12
2008Material variability and repetitive member allowable property adjustments in forest products engineering10/15/10
2012Small Sample Properties of Asymptotically Efficient Estimators of the Parameters of a Bivariate Gaussian–Weibull Distribution08/06/12
2009Statistical Framework for Comparing Lumber Sorting Procedures08/19/09
2008The distribution of McKay's approximation for the coefficient of variation11/20/09

Project Summaries last modified: 06-21-2011