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The high accuracy of log positioning and the stability of saw blades in breakdown machinery in modern sawmills have reduced the need to add margins for sawing variations. Oversize green sawing dimensions are still needed, but mainly to allow for drying shrinkage. This has put a new focus on better adapting green sawing dimensions to the shrinkage behavior of wood. In this study, a method for optimization of green sawing dimensions using stochastic simulation is presented. Normal distributions were generated for planed dry dimensions, kerf width, and target moisture content. The minimum share of boards exceeding the specified dry dimensions was decided, and deformations in boards from all positions in the cross section in a number of logs were simulated. The simulated shrinkage allowance from stochastic simulations was compared to experimental results from an industry test and to finite element results based on material data for Norway spruce. The results showed that the green width of the sawn boards should increase when the number of boards in the center yield increases. The green thickness of boards should be thinner for center boards and outer boards than for inner boards.

Industrial measurements of green and dry cross-section dimensions were performed for 189 Norway spruce (Picea abies) centre-yield boards with dry dimensions 51x49 mm. Two, three or four boards were sawn from each log, depending on log size. Different approaches were used for simulations of cross-section shrinkage during drying. An analytical model, an elastic, an elastic mechanosorptive and an elastic plastic finite element simulation model were tested. Thickness and width shrinkage and deformation were simulated. Shrinkage results were compared with each other and with the experimental results. All simulation models gave roughly the same degree of agreement with experimental results except for the centre board from the three-board sawing pattern. For the other boards, the analytical model was not generally better or worse than the results from the finite element models. Shrinkage deformations in finite element models that included mechanosorption or plasticity were nearly the same as for the elastic finite element model except for the centre board of the three-board sawing pattern. The mechanosorptive model was the best model for the shrinkage of the centre board of this sawing pattern except for mid-thickness shrinkage. Comparison between the different finite element simulation models of stresses in the centre board revealed large differences.

A microwave imaging sensor that measures the signal transmitted through a board was investigated with respect to the ability to predict the distribution of moisture and density in sawn lumber. Furthermore, the response from the sensor was related to strength properties of the boards. Multivariate statistics was used to relate the measured variables to various properties. A finite element model based on X-ray computed tomography images was developed to describe the interactions between microwaves and wood. The model made it possible to simulate the response from the sensor under varying conditions.

The results show that microwaves can be used for prediction of density and moisture content. They can also be used for prediction of strength properties, mainly from the correlation to density, but also from the influence on microwaves of structural variations in the wood. The finite element model is useful in the evaluation of microwave sensors for wood, drying equipment or other applications where electromagnetic waves interact with wood.

In this study, 90 boards of Norway spruce (Picea abies (L.) Karst.) sized 48 x 148 mm in cross-section, have been examined using different scanning and measurement techniques. All of the boards originated from a sawmill located in southern Finland. Planar X-ray scanning, microwave scanning, and grain-angle measurement have been performed. In addition, strength and elastic properties were assessed for each piece by four point bending. The purpose of the study was to relate the potential of microwave scanning compared to other, industrially available techniques and to explain the physiological background of the microwave responses. The results show that the microwave signal, after transmission through wood, contains information about the bending strength and the modulus of elasticity. The correlation to density is a key factor. Annual ring width was also found to be correlated both to microwave measurements and strength properties.

Dipole polarization of water molecules is an important factor when microwaves interact with moist wood. Hence there will be a considerable change in dielectric properties when the wood changes from frozen to nonfrozen condition. The aim of this study was to develop a model that simulates measurements with a microwave scanner based on a sensor working at 9.4 GHz. Two-dimensional finite element modelling (FEM) was implemented to analyze interactions between microwaves and green wood during thawing of frozen wood at room temperature. A medical computed tomography scanner was used to measure the internal structure of density in a piece of wood in green and dry condition. From these density images the distribution of dry weight moisture content was calculated for a cross section of the piece and used in the model. Images describing the distribution of the electric field and phase shift at different temperatures where obtained from the FEM simulation. The results show that simulated values correspond well to measured values. This confirms that the model presented in this study is a useful tool to describe the interaction between microwaves and wood during microwave scanning at varying conditions.

The aim of this study was to use finite element modeling (FEM) as a tool to analyze microwave scattering in wood and to verify the model by measurements with a microwave scanner. A medical computed tomography scanner was used to measure distribution of density and moisture content in a piece of Scots pine (Pinus sylvestris). Dielectric properties were calculated from measured values for cross sections from the piece and used in the model. Images describing the distribution of the electric field and phase shift were obtained from the FEM simulation. The model was verified by measurements with a scanner based on a microwave sensor. The results show that simulated values correspond well to measured values. Furthermore, discontinuities in the material caused scattering in both the measured and the simulated values. The greater the discontinuity in the material, the greater was the need for computational power in the simulation.

The purpose of this study was to use images from a microwave sensor on a pixel level for simultaneous prediction of moisture content and density of wood. The microwave sensor functions as a line-scan camera with a pixel size of 8mm. Boards of Scots pine (Pinus sylvestris), 25 and 50mm thick, were scanned at three different moisture contents. Dry density and moisture content for each pixel were calculated from measurements with a computed tomography scanner. It was possible to create models for prediction of density on a pixel level. Models for prediction of moisture content had to be based on average values over homogeneous regions. Accuracy will be improved if it is possible to make a classification of knots, heartwood, sapwood, etc., and calibrate different models for different types of wood. The limitations of the sensor used are high noise in amplitude measurements and the restriction to one period for phase measurements.

It is possible to determine properties of wood using microwave scanning techniques. The purpose of this study was to verify the measured values from a microwave imaging sensor. Attenuation and phase shift of an electromagnetic wave transmitted through birch wood were measured and compared with theoretical calculated values. A test piece with varying thickness was measured with a scanner based on a microwave sensor (Satimo 9.375 GHz) at different temperatures and moisture contents. The density distribution of the test piece was determined by computer tomography scanning. The result showed good correspondence between measured and theoretical values. The proportion of noise was higher at low moisture content due to lower attenuation. There is more noise in attenuation measurement than in measurement of phase shift. A reason for this could be that wood is an inhomogeneous material in which reflections and scattering affect attenuation more than phase shift. The microwave scanner has to be calibrated to a known dielectric to quantify the error in the measurement. (C) 2005 Elsevier Ltd. All rights reserved.