A stochastic plasticity approach to strength modeling of strand-based wood composites

Clouston, Peggi L.; Lam, Frank

doi:10.1016/s0266-3538(02)00086-6

Cited by 36 publications

(21 citation statements)

References 9 publications

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“…The computational model builds upon previous efforts by one of the writers ͑Clouston and Lam 2001Lam , 2002Clouston 2006͒ to develop finite-element models of SCL mesostructures that capture the variation in properties between strands and incorporate a reasonable model for the failure surface of the strands. Although stochastic models have been proposed for the mechanics of the PSL cross section ͑Bejo and Lang 2004͒, this is the first attempt to model the lengthwise features of the mesostructure.…”

Section: Introductionmentioning

confidence: 99%

Variability of the Compressive Strength of Parallel Strand Lumber

2010

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Measurement of the compressive strength of parallel strand lumber ͑PSL͒ is conducted on specimens of varying size with nominally identical mesostructure. The mean of the compressive strength is found to vary inversely with the specimen size, and the coefficient of variation of the strength is found to decrease with increasing specimen size, and to be smaller than the coefficient of variation of strength for solid lumber. The correlation length of the compressive strength is approximately 0.5 m, and this correlation length leads to significant specimen-to-specimen variation in mean strength. A computational model is developed that includes the following properties of the PSL mesostructure: the strand length, the grain angle, the elastic constants, and the parameters of the Tsai-Hill failure surface. The computational model predicts the mean strength and coefficient of variation reasonably well, and predicts the correct form of correlation decay, but overpredicts the correlation length for compressive strength, likely because of sensitivity to the distribution of strand length used in the model. The estimates of the statistics of the PSL compressive strength are useful for reliability analysis of PSL structures, and the computational model, although still in need of further development, can be used in evaluating the effect of mesostructural parameters on PSL compressive strength.

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Section: Introductionmentioning

confidence: 99%

Variability of the Compressive Strength of Parallel Strand Lumber

2010

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“…An average stress-strain curve was generated for each group using the stress-strain data from each test specimen in the group by calculating the mean stress along lines of constant strain [8][9][10]. Fig.…”

Section: Resultsmentioning

confidence: 99%

“…The literature review suggested that strength and stiffness properties of wood-based composites tend to follow either the normal or lognormal probability distribution models [8][9][10][11]. A preliminary analysis using Minitab 15.0 statistical software confirmed this finding.…”

Section: Advanced Computational Engineering and Experimentingmentioning

confidence: 89%

“…Excellent agreement was observed between the predicted and experimental probability distributions of ultimate strength and MOE in tension, compression and bending. Further studies by Clouston and Lam [9,10] developed the model into a 3-D non-linear stochastic finite element model for predicting the probabilistic distribution of strength, stiffness and failure load of angle-ply laminates subjected to tension, compression and bending. Clouston [11] and Arwade et al [12] further developed this model to enable it to predict the strength and MOE of large section parallel strand lumber (PSL) members loaded in tension, compression and bending.…”

Section: Wang and Lammentioning

confidence: 99%

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A Probabilistic Approach to the Simulation of Non-Linear Stress-Strain Relationships for Oriented Strandboard Subject to In-Plane Tension

McTigue

Harte

2011

KEM

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Abstract. This paper presents the results from an experimental test program conducted on commercially available oriented strandboard (OSB) panels and statistical analyses of the results. Standardised testing was used to determine the short-term behaviour of OSB/3 panels subjected to tension loading. A variety of thicknesses sourced from three different producers were used.Analysis of the results indicate that a quadratic expression in the form of σ = aε 2 + bε provides the best description of the relationship between stress (σ) and strain (ε) up to the point of failure. It has also been shown that the coefficients a and b of the quadratic regression equations are negatively correlated to each other. Anderson-Darling goodness-of-fit tests were conducted on the results for tension strength and modulus of elasticity (MOE). The results indicate that the tension strength and MOE come from populations that follow either normal or lognormal probability distributions.

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“…Consequently, the spatial variability is frequently neglected in the probabilistic simulations of timber structures [7][8][9]. The knowledge of the random spatial variability in elastic parameters can lead to predicting more accurate stress fields within the material.…”

Section: Introductionmentioning

confidence: 99%