2002
DOI: 10.3183/npprj-2002-17-02-p105-110
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Simulation of network shrinkage

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Cited by 6 publications
(3 citation statements)
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“…The assembled experimental material is shared as open data and can be served as a verification or calibration material for the micromechanical models Bosco et al (2015), Motamedian and Kulachenko (2019), Salminen et al (2002), Sellén and Isaksson (2014) as well as for training the machine learning algorithms to identify the fibers in micro-CT datasets, which are among the emerging techniques for the analysis of paper products.…”
Section: Hygroexpansion Coefficient As a Function Of Drying Constraintsmentioning
confidence: 99%
“…The assembled experimental material is shared as open data and can be served as a verification or calibration material for the micromechanical models Bosco et al (2015), Motamedian and Kulachenko (2019), Salminen et al (2002), Sellén and Isaksson (2014) as well as for training the machine learning algorithms to identify the fibers in micro-CT datasets, which are among the emerging techniques for the analysis of paper products.…”
Section: Hygroexpansion Coefficient As a Function Of Drying Constraintsmentioning
confidence: 99%
“…The factor that dominates the elastic modulus of paper is the effect of drying stresses, which has a much larger effect than bonding degree [119]. The same can also be demonstrated by computer simulations [120]. It has been shown experimentally that the mechanical properties of a fibre depend on the axial stress applied on the fibre during drying [121].…”
Section: Elasticity Of Papermentioning
confidence: 99%
“…For other micrometric or nanometric brous systems where proper 3D images of the brous architectures are not available, analytical or numerical structure generators were developed to estimate the previously mentioned suitable descriptors. 27,[47][48][49][50][51] For NFCbased materials, Kulachenko et al 27 recently used a numerical generation procedure to evaluate the mechanical behavior of NFC nanopapers. However, the authors did not provide compact analytical descriptors to describe the brous nanostructures.…”
Section: Introductionmentioning
confidence: 99%