Progress 09/01/03 to 08/31/06
Outputs
OUTPUTS: This project consisted of three research objectives for enhancing performance of wood in composite processes and products. In the first objective, it was revealed that wood species affect mechanical and thermal properties of wood plastic composites. Yellow poplar (Liriodendron tulipifera), osage orange (Maclura pomifera), black cherry(Prunus serotina), sweet gum(Liquidamba styraciflua), eastern red cedar (Juniperus virgiana), black walnut (Juglans nigra), pine (Pinus spp.), maple (Acer spp.), and oak (Quercus spp.) wood flour was obtained and used in the research. The wood species demonstrated very little effect on the mobility of the amorphous polymer fraction. Nevertheless, the crystallization behavior was drastically different between wood species. These differences were attributed to surface morphology and energy. This led to differences in mechanical properties where pine was the highest to cedar and osage orange being the lowest. Moisture sorption tests proved to have the opposite behavior leading one to believe that the higher extractive content wood to perform better in durability testing. In the second objective, the effects of differences among earlywood, latewood, and tree ring within the stem cross-section on the water vapor sorption were also investigated. Wood sorption behavior influenced by processes such as refining steam pressure, resin and wax loading. The water mobility concept was used to study composite-water relationships and mold susceptibility of engineered wood products for the first time. Water vapor sorption isotherm modeling of commercial oriented strand panel based on species and resin type was conducted. Research was further conducted to understand the effect of species and process on wood surface energy. In the third objective, the project investigated predictive modeling of the physical properties of wood composites using advanced computational algorithms. A heuristic algorithmic method using genetic algorithms with real-time distributed data fusion was developed to predict the internal bond of medium density fiberboard and the parallel elasticity index for oriented strand board. The system incorporated real-time lags and statistical estimates of 285 critical process parameters with data quality verification algorithms. The real-time relational data fusion system was completely automated and represented the infrastructure of the genetic algorithm prediction system. Validation of the system was at one medium density fiberboard plant and one oriented strand board plant in the southeastern U.S. Results of the genetic algorithm modeling system indicate predictions within 10 percent of the median physical properties. Time-ordered residuals accurately detected trends and were normally distributed. PARTICIPANTS: Dr. Michael P. Wolcott from Washington State University colloborated on this research. Tim Stortz, T. Neimsuwan, W. Chen, Dr. J.W. Kim, Dr. Adam Taylor, Dr. Frank M. Guess, Dr. Nicolas Andre, Dr. R.V. Leon, from The University of Tennessee collaborated. Chris W. Huber from Georgia Pacific Chemicals, LLC was an industry collaborator with this research. TARGET AUDIENCES: Wood science community, wood composite manufacturers and adhesive formulators PROJECT MODIFICATIONS: Not relevant to this project.
Impacts
Durability of wood-plastic composites (WPC) is a large liability to manufacturers and of growing concern to the public. Our research demonstrates that some low valued tree species may add value to WPCs by increasing their durability. Chemical imaging has been conducted on several of the extruded composite that contains a copolymer-coupling agent, MAPP. This technique is able to track the location of specific chemical functionality. This research for the first time proves that MAPP copolymer added to the melt migrates to wood surfaces preferentially. Thus, producers may avoid many costly modification steps, such as pre-coating wood flour, in order to improve composite performance. This research has the potential for far-reaching impact on the wood products industry especially on wood and composite durability. The intrinsic moisture properties relate to mold susceptibility. A basic understanding of the water properties, its behavior, and its mobility relating to mold growth is required for continued improvement of wood and wood-based composites quality. This understanding through this research provides tool for examining mold growth under various condition and extends to application in process control. This information is also useful to understand the water uptake behavior of wood-based composites and its relationship to mold susceptibility during service and to engineer better products. Engineered wood manufacturing have a large number of differing, but interdependent process variables that have complex functional forms which influence properties. Wood passes through many processing stages that may influence the final properties. Key process parameters may include mat-forming consistency, line speed, press temperature, press closing rates, wood chip dimensions, fiber dimension, fiber-resin formation, etc. At the time of production, the quality of engineered wood is unknown, i.e., samples are analyzed at a later time in the lab using destructive testing. The time span between destructive tests may vary from two to six hours. Hours of unacceptable engineered wood production may go undetected between these tests. Many engineered wood manufacturers run higher than needed density targets to make up for this gap in product quality knowledge. The medium density fiberboard and oriented strand board plants used for validation are able to reduce resin usage from use of the genetic algorithm system. Cost savings from reduced resin use during the six-month validation study are as large as $700,000 at one test mill. The modeling system may lead to a lower wood waste, faster throughput, lower chemical usage, lower energy use and improve wood yield.
Publications
- Neimsuwan, T. and S. Wang. 2006. Prediction of furnish and OSB properties by NIR spectroscopy. Abstract IN: Biographies and Abstracts. Forest Products Society 60th International Convention, Newport Beach, California, June 25-28. pp. 48.
- Neimsuwan, T. 2007. The Influence of Selected Wood Characteristics and Composites Production Parameters on the Sorption Behavior of Wood Materials. Ph.D. Dissertation, University of Tennessee, p. 1-168.
- Neimsuwan, T. and Wang, S. 2007. Effect of resin and wax on sorption behavior of wood strands. Abstract IN: Biographies and Abstracts. Forest Products Society 61st International Convention, Knoxville, Tennessee, June 10-13. pp14.
- Neimsuwan, T. and Wang, S. 2007. Sorption behavior by refining fiber of varying pressure. Abstract IN: Biographies and Abstracts. Forest Products Society 61st International Convention, Knoxville, Tennessee, June 10-13. pp30.
- Taylor, Kim J-W. A. and D. Harper. 2007 The effect of wood species on the properties of wood plastic composites. Forest Products Society 61th Annual Meeting. Knoxville, TN.
- Wang, S., P.M. Winistorfer and T.M. Young. 2004. Fundamentals of vertical density profile formation in wood composites Part 3. MDF density formation during hot-pressing. Wood and Fiber Science. 36(1):17-25.
- Wang, S. and T. Neimsuwan. 2006. The relationship of surface characteristics and water uptake of wood and composition. Abstract IN: Biographies and Abstracts. Forest Products Society 60th International Convention, Newport Beach, California, June 25-28. pp. 21.
- Ye, X.P., S. Wang, R. Ruan, J. Qi, A.R. Womac and C.J. Doona. 2006. Water mobility and mold susceptibility of engineered wood products. Transactions of the ASABE 49(4):1159-1165.
- Young, T.M., N. Andre and C.W. Huber. 2004. Predictive modeling of the internal bond of MDF using genetic algorithms with distributed data fusion. Proc. 8th European Panel Products Symposium. Llandudno, United Kingdom. p. 45-59.
- Young, T.M. and C.W. Huber. 2004. Predictive modeling of the physical properties of wood composites using genetic algorithms with considerations for distributed data fusion. Proc. of the 38th International Particleboard/Composite Materials Symposium. Washington State University. Pullman, WA. p. 71-86.
- Zhang, Y. and S. Wang. 2007. Study on surface energy characteristics of poplar and yellow pine strands. Chinese Forestry Science and Technology 5(2):7-10.
- Chen, W., R.V. Leon, T.M. Young and F.M. Guess. 2005. Applying a forced censoring technique with accelerated modeling for improving estimation of extremely small percentiles of strengths. International Journal of Reliability and Application. 7(1):27-39.
- Guess, F.M., R.V. Leon, W. Chen and T.M. Young. 2004. Forcing a closer fit in the lower tails of a distribution for better estimating extremely small percentiles of strengths. International Journal of Reliability and Application. 5(4):129-145.
- Guess, F.M., X. Zhang, T.M. Young and R.V. Leon. 2005. Using mean residual life functions for unique insights into strengths of materials data. International Journal of Reliability and Application. . 6(2):79-85.
- Guess, F.M., J.C. Steele, T.M. Young and R.V. Leon. 2006. Applying novel mean residual life confidence intervals. International Journal of Reliability and Application. 7(2):177-186.
- Harper, D. P. and M. P. Wolcott. 2005. Chemical imaging of wood-polypropylene composites. Proceedings of the Eighth International Conference on Woodfiber-Plastic Composites. Madison, WI. pp. 153-160.
- Hartley I.D., S. Wang, and Y. Zhang. 2007. Water vapor sorption isotherm modeling of commercial oriented strand panel based on species and resin type. Building and Environment 42(10): 3655-3659
- Andre, N., T.M. Young and T.G. Rials. 2006. On-line monitoring of the buffer capacity of particleboard furnish by near-infrared spectroscopy. Applied Spectroscopy. 60(10):1204-1209.
- Chen, W. 2005. A reliability case study on estimating extremely small percentiles of strength data for the continuous improvement of medium density fiberboard product quality. M.S. Thesis. The University of Tennessee. Knoxville.
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Progress 01/01/05 to 12/31/05
Outputs
The study has resulted in a real-time genetic algorithm and neural network (GANN) predictive modeling system of the physical properties of wood composites. The system was validated at a U.S. medium density fiberboard manufacturing facility. The GANN model was written in C++ and has a Visual Net human machine interface. The GANN model was based on the fusion of real-time univariate process data with event-based destructive test data. The relational database was completely automated using Transact SQL code. A Microsoft SQL database is used as the fusion database. The mean and median residuals for all products were 1.19 and -0.13 p.s.i., respectively. The GANN predictions of IB tended to follow actual IB trends and residuals were approximately normal. In drying related research, the literature was surveyed and revealed very good data in the middle of the temperature range we are interested in, but none at the extremes. A series of microwave preheating experiments were
conducted on both red oak and white oak, revealing that white oak is very susceptible to checking in this process although the behavior is very dependent upon the grain direction and the application of the microwaves. Fabrication of a new testing fixture was completed to allow across grain tension tests, and to measure both load and actual specimen elongation. Test samples were designed and machined, and preliminary experiments confirm that we are getting a true cross grain tension test and that we can derive the elongation values. Also, during this reporting period we have conducted chemo-mechanical studies of wood cell walls by means of infrared spectroscopy and nanoindentation providing new insight on fundamental structure-property relationships. This approach was also successfully extended to characterize the interphase of natural fiber-reinforced polymer composites. Research also developed a chemical imaging technique to study the phase behavior of cellulose derivatives in
solvent/non-solvent systems. The goal is to better control the regeneration process of cellulose fiber for enhanced properties.
Impacts
The time span between production and destructive quality control tests varies from two to six hours, leading to the manufacture of product with potentially unacceptable properties. A GANN-based monitoring system was developed to provide information on performance properties in real time. As a direct result of the system, cost savings from reduced resin use during a six-month mill validation study were as large as $700,000. The relationships between cell wall structure and properties have not been experimentally accessible. Nanoindentation techniques were developed and applied for the first time to southern pine wood material isolated from different growth rings. The influence of molecular organization on mechanical properties was clarified. This creates the opportunity to study fundamental questions of interaction with synthetic polymers, and improve performance of adhesive-bonded wood joints.
Publications
- Lee, S.H., S. Wang and G.M. Pharr. 2005. Characterization of interfacial properties between cellulose fiber and thermoplastic by AFM and nanoindentation. Abstract IN: 230th ACS National Meeting, Washington, DC.
- Young, T.M., N. Andre and C.W. Huber. 2004. Predictive modeling of the internal bond of MDF using genetic algorithms with distributed data fusion - a preliminary investigation. Proc. 8th European Panel Products Symposium. Llandudno, United Kingdom. p 45-59
- Young, T.M. and C.W. Huber. 2004. Predictive modeling of the physical properties of wood composites using genetic algorithms with considerations for distributed data fusion. Proc. of the 38th International Particleboard/Composite Materials Symposium. Washington State University, Pullman, WA. p.145-153.
- Groom, L.H., C.-L. So, T. Elder, T. Pesacreta, and T.G. Rials. 2005. Effects of Refiner Pressure on the Properties of Individual Wood Fibers. In: Stokke, D. and L. Groom (eds.), Characterization of the Cellulosic Cell Wall, Blackwell Publishing, Ames, IA. Chapter 17.
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Progress 01/01/04 to 12/31/04
Outputs
A heuristic algorithmic method using genetic algorithms with real-time distributed data fusion was developed to predict the internal bond of medium density fiberboard. The system incorporated real-time lags and statistical estimates of 285 critical process parameters with data quality verification algorithms. The real-time relational data fusion system was completely automated and represented the infrastructure of the genetic algorithm prediction system. The real-time data fusion system was written in Microsoft Transact SQL and was an important outcome of the research. Validation results of the genetic algorithm prediction system had mean and median residuals for all product types of 1.19 and -0.13 pounds per square inch, respectively with less than 5% error of the average or target internal bond. In wood drying, we have investigated several ways of preparing and sealing samples for this project, determining that a commercial vacuum sealer with a thin Mylar bag will
do an adequate job. We have demonstrated heating these samples after sealing in a water bath to bring them to the proper temperature. We have been able to follow the temperature change of these samples by sealing a small thermocouple wire in with the sample. We have encountered some sealing problems with the entry point of the thermocouple. We think we can overcome these problems by using a silicone sealant on the wire entry point. We have identified a testing machine to be used for this project. The testing machine order is working its way through the University bid process at this time. We will begin fabricating the sample holders for this machine when it arrives. Nanoindentation has been successfully developed to characterize mechanical behavior of wood cell walls. The hardness and modulus values that are independent of penetration depth were examined. To illustrate our nanoindentation results, juvenile wood and mature wood cell walls were studied. The results clearly showed that
the cell wall of the juvenile wood is not as stiff, but is as hard as mature wood. For further investigations, the cell-wall longitudinal stiffness was adjusted for the specific gravity (SG) of the respective annual rings, so that the elastic moduli of the porous wood can be estimated. The resulting data closely correlate to the moduli of elasticity determined from conventional mechanical tests.
Impacts
The medium density fiberboard plant used for the validation study was able to reduce resin usage as a result of the genetic algorithm system. Cost savings from reduced resin use during the six-month validation study were approximately $700,000 at the test mill. The proposed system may also lead to a lower rate of rejected panels, faster throughput, identify key sources of variability, lower wood usage, lower energy use and improve wood yield. Mechanical properties largely determine the utilization scenario for wood fibers. The new ability to analyze stiffness of individual cell walls is an important advance that will lead to more effective synthesis and formulation of adhesive resins.
Publications
- Young, T.M., N. Andre and C.W. Huber. 2004. Predictive modeling of the internal bond of MDF using genetic algorithms with distributed data fusion. Proc. 8th European Panel Products Symposium. Llandudno, United Kingdom. p. 45-59.
- Young, T.M. and C.W. Huber. 2004. Predictive modeling of the physical properties of wood composites using genetic algorithms with considerations for distributed data fusion. Proc. of the 38th International Particleboard/Composite Materials Symposium. Washington State University. Pullman, WA. p. 71-86.
- Guess, F.M., D.J. Edwards, T.M. Pickrell and T.M. Young. 2003. Exploring graphically and statistically the reliability of medium density fiberboard. International Journal of Reliability and Application. 4(4):157-170.
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Progress 01/01/03 to 12/31/03
Outputs
The program is structured into four stand-alone projects. The first research problem builds on recent reprogramming of our Center's research to include a focus on renewable composites. The project seeks to develop low-modulus, carbon fibers from cellulose fibers regenerated from NMMO solution. New catalyst systems have emerged that promise to overcome the low yield of carbon fiber from a cellulose starting material. This capability would improve the economics of the process, potentially creating affordable carbon fiber for a much wider array of applications. The second research problem addresses the challenges of minimizing lumber degrade during the drying process, and builds on several active research projects. This work will utilize dynamic mechanical experiments, among other tools, to better describe the nature of the critical points associated with the drying of red oak lumber, a very high-value species. Composite materials continue to offer tremendous
opportunities for improvements in utilization efficiency of wood. The third research problem will apply an innovative new method, nanoindentation, to study fundamental questions of interphase structure and properties to composite performance. Using this tool, new information on the material properties of the wood cell wall will be generated. The effect of resin type and cure on wood cell wall properties will also be studied, providing new insight into the complex structure of the wood-resin interphase. The final research problem builds on the earlier success of the Tennessee Quality Lumber Initiative, established through this funding program. Statistical process control offers an important opportunity to reduce manufacturing losses, as has been established for hardwood lumber. Even greater impacts from process monitoring can be expected for composite systems like medium-density fiberboard. This work will explore the potential of predictive modeling using new, genetic algorithms to
create the capability of feed-forward control in composite manufacturing. At the same time, the analysis of new signature data from near infrared sensors will also be explored and developed. The results of this collective work will create information and processes for the improved utilization of forest resources in the southern Appalachian region. Initiated in September 2003, there is no substantial progress to report on this project. The effort to date has focused on identifying personnel and acquiring materials needed for the experiments. Wang and Rials were awarded a ShaRe grant at Oak Ridge National Laboratory providing access to nanoindentation instrumentation and expertise.
Impacts
The research will enhance competitiveness of the forest products industry with enhanced information on raw material properties and process behavior and control. New, high-value materials to accommodate low-quality raw material will be available.
Publications
- No publications reported this period
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