Browsing by Subject "Multiscales"

Now showing 1 - 3 of 3

Open Access
Computational thermal homogenization of concrete
(2013) Wu, T.; Temizer, I.; Wriggers, P.
Computational thermal homogenization is applied to the microscale and mesoscale of concrete sequentially. Microscale homogenization is based on a 3D micro-CT scan of hardened cement paste (HCP). Mesoscale homogenization is carried out through the analysis of aggregates which are randomly distributed in a homogenized matrix. The thermal conductivity of this matrix is delivered by the homogenization of HCP, thereby establishing the link between micro-mesoscale of concrete. This link is critical to capture the dependence of the overall conductivity of concrete on the internal relative humidity. Therefore, special emphasis is given to the effect of relative humidity changes in micropores on the thermal conductivity of HCP and concrete. Each step of homogenization is compared with available experimental data. © 2012 Elsevier Ltd. All rights reserved.
Open Access
A method of two-scale chemo-thermal-mechanical coupling for concrete
(CIMNE, 2011) Wu, T.; Temizer, İlker; Wriggers, P.
The Alkali Silica Reaction(ASR) is one of the most important reasons to cause damage in cementitious constructions, which can be attributed to the expansion of hydrophilic gel produced in the reaction. In this contribution, the chemical extent is described depending on the temperature and it has influences on damage parameters. Expansions of the gel are assumed to only happen in the micropores of Hardened Cement Paste. Afterwards, the homogenization of damage in the microscale is initialized and the effective damage can be applied in the mesoscale directly. Moreover, parameter identification is implemented to extract the effective inelastic consititutive equation. In all, 3D multiscale chemo-thermo-mechanical coupled model is set up to describe the damage in the concrete due to ASR.
Open Access
Multiscale motion saliency for keyframe extraction from motion capture sequences
(John Wiley & Sons Ltd., 2011) Halit, C.; Capin, T.
Motion capture is an increasingly popular animation technique; however data acquired by motion capture can become substantial. This makes it difficult to use motion capture data in a number of applications, such as motion editing, motion understanding, automatic motion summarization, motion thumbnail generation, or motion database search and retrieval. To overcome this limitation, we propose an automatic approach to extract keyframes from a motion capture sequence. We treat the input sequence as motion curves, and obtain the most salient parts of these curves using a new proposed metric, called 'motion saliency'. We select the curves to be analysed by a dimension reduction technique, Principal Component Analysis (PCA). We then apply frame reduction techniques to extract the most important frames as keyframes of the motion. With this approach, around 8% of the frames are selected to be keyframes for motion capture sequences. © 2011 John Wiley & Sons, Ltd.