scholarly journals Continuum Approach to Computational Multi-Scale Modeling of Fracture

2014 ◽  
Vol 627 ◽  
pp. 349-352 ◽  
Author(s):  
Javier Oliver ◽  
M. Caicedo ◽  
E. Roubin ◽  
A.E. Huespe
Keyword(s):  
Mesh Size ◽  
Cementitious Materials ◽  
Strong Discontinuity ◽  
Structural Failure ◽  
Multi Scale ◽  
Scale Modeling ◽  
Macro Scale ◽  
Numerical Tools ◽  
Continuum Strong Discontinuity Approach ◽  
The Continuum

This paper presents a FE2 multi-scale framework for numerical modeling of the structural failure of heterogeneous quasi-brittle materials. The model is assessed by application to cementitious materials. Using the Continuum Strong Discontinuity Approach (CSD), innovative numerical tools, such as strain injection and crack path field techniques, provide a robust, and mesh-size, mesh-bias and RVE-size objective, procedure to model crack onset and propagation at the macro-scale.

Multi-Scale Modeling of Cementitious Materials (Briefing Chart)

2014 ◽  
Author(s):  
M. M. Shahzamanian ◽  
T. Tadepalli ◽  
A. M. Rajendran ◽  
W. D. Hodo ◽  
R. Mohan ◽  
...  
Keyword(s):  
Cementitious Materials ◽  
Multi Scale ◽  
Scale Modeling ◽  
Multi Scale Modeling

scholarly journals Energy Dissipation During Prey Capture Process in Spider Orb Webs

2020 ◽  
Vol 87 (9) ◽  
Author(s):  
Yanhui Jiang ◽  
Hamid Nayeb-Hashemi
Keyword(s):  
Energy Dissipation ◽  
Significant Role ◽  
Prey Capture ◽  
Aerodynamic Drag ◽  
Material Damping ◽  
Capture Process ◽  
Spider Dragline Silk ◽  
Multi Scale ◽  
Scale Modeling ◽  
Macro Scale

Abstract Capture of a prey by spider orb webs is a dynamic process with energy dissipation. The dynamic response of spider orb webs under prey impact requires a multi-scale modeling by considering the material microstructures and the assembly of spider silks in the macro-scale. To better understand the prey capture process, this paper addresses a multi-scale approach to uncover the underlying energy dissipation mechanisms. Simulation results show that the microstructures of spider dragline silk play a significant role on energy absorption during prey capture. The alteration of the microstructures, material internal friction, and plastic deformation lead to energy dissipation, which is called material damping. In addition to the material damping in the micro-scale modeling, the energy dissipation due to drag force on the prey is also taken into consideration in the macro-scale modeling. The results indicate that aerodynamic drag, i.e., aero-damping, plays a significant role when the prey size is larger than a critical size.

New Approach of Multi Scale Modeling Based on the Hygro-Cosserat Theory for Self Desiccation Deformation of Cement Mortars at Early Age

2010 ◽  
Vol 123-125 ◽  
pp. 563-566 ◽  
Author(s):  
J. Jeong ◽  
P. Mounanga ◽  
Hamidreza Ramezani ◽  
Marwen Bouasker ◽  
D. Bassir
Keyword(s):  
Autogenous Shrinkage ◽  
Early Age ◽  
Cosserat Theory ◽  
Sem Images ◽  
Element Analysis ◽  
New Approach ◽  
Multi Scale ◽  
Scale Modeling ◽  
Cement Mortars ◽  
Macro Scale

In the present paper, we concentrate on the heterogeneous cement mortars and we treat them as Cosserat-based media. The autogenous shrinkage phenomenon at early age (from 1 up to 3 days after mixing) has been analyzed by means of Cosserat theory. The characteristic length scale parameter Lc in this theory helps us to change the size specimen from macro-scale to micro-scale using the theoretical size effect aspects. This methodology is also capable of treating cracks initiation and their appearance in the cementitious matrix surrounding the sand-inclusions, which should occurred inside of the Representative Volume Elementary (RVE) of mortar subjected to self-desiccation shrinkage during hydration at early age. By taking advantage of the Nonlinear Finite Element Analysis (NFEA), the numerical experiments have been performed. The numerical outcomes are well agreed with the experimental observations coming from Scanning Electronic Microscopy (SEM) images. It concludes that the inclusions create not only a hygro stress concentration around the grains but also the number of inclusions should influence the network in cementitous matrix.

A Concurrent Multiscale Method for Coupling Atomistic and Continuum Models at Finite Temperatures

2009 ◽  
Vol 1229 ◽  
Author(s):  
Catalin Picu ◽  
Nithin Mathew
Keyword(s):  
Degrees Of Freedom ◽  
Interface Region ◽  
Continuum Models ◽  
Generalized Langevin Equation ◽  
Mechanical Coupling ◽  
Multi Scale ◽  
Scale Modeling ◽  
Temperature Boundary ◽  
Atomistic Region ◽  
The Continuum

AbstractA concurrent multi-scale modeling method for finite temperature simulation of solids is introduced. The objective is to represent far from equilibrium phenomena using an atomistic model and near equilibrium phenomena using a continuum model, the domain being partitioned in discrete and continuum regions, respectively. An interface sub-domain is defined between the two regions to provide proper coupling between the discrete and continuum models. While in the discrete region the thermal and mechanical processes are intrinsically coupled, in the continuum region they are treated separately. The interface region partitions the energy transferred from the discrete to the continuum into mechanical and thermal components by splitting the phonon spectrum into “low” and “high” frequency ranges. This is achieved by using the generalized Langevin equation as the equation of motion for atoms in the interface region. The threshold frequency is selected such to minimize energy transfer between the mechanical and thermal components. Mechanical coupling is performed by requiring the continuum degrees of freedom (nodes) to follow the averaged motion of the atoms. Thermal coupling is ensured by imposing a flux input to the atomistic region and using a temperature boundary condition for continuum. This makes possible a thermodynamically consistent, bi-directional coupling of the two models.

Degradation Modeling Research of Biodegradable Tissue Engineering Scaffold

2013 ◽  
Vol 873 ◽  
pp. 642-651
Author(s):  
Tao Hong Zhang ◽  
Shou Gang Xu ◽  
De Zheng Zhang ◽  
Aziguli Wulamu
Keyword(s):  
Tissue Engineering ◽  
Initial Step ◽  
Tissue Engineering Scaffold ◽  
Multi Scale ◽  
Modeling Methods ◽  
Degradation Modeling ◽  
Scale Modeling ◽  
Single Scale ◽  
Macro Scale ◽  
Scale Models

Although the degradation modeling of tissue engineering scaffold is in its initial step, it can direct the design, optimization of scaffold and help the application in medical case of illness. This paper analyzes the modeling methods and gives the speciality of every model which is put forward by researchers in China and abroad about the degradation of tissue engineering scaffold. These models are divided into micro scale, macro scale and two scale models based on the modeling scales. The recent research is belonging to single scale modeling. Some researchers abroad probed to two scale modeling. The future model is prospected in multi scale coupling macro, micro, and meta-macro model.

Integrating an Analytical Uncertainty Quantification Approach to Multi-Scale Modeling of Nanocomposites

2019 ◽  
pp. 1-22
Author(s):  
Pinar Acar
Keyword(s):  
Uncertainty Quantification ◽  
Uncertainty Propagation ◽  
Epoxy Nanocomposites ◽  
Linear Solution ◽  
Analytical Uncertainty ◽  
Multi Scale ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Scale Properties

Abstract The present study addresses the integration of an analytical uncertainty quantification approach to multi-scale modeling of single-walled carbon nanotube (SWNT)-epoxy nanocomposites. The main highlight is the investigation of the stochasticity of nanotube orientations, and its effects on the homogenized properties. Even though the properties of SWNT-epoxy nanocomposites are well-studied in the literature, the natural stochasticity that arises from the nanotube orientations has not been observed. To understand the effects of the variability in SWNT orientations to material properties of interest, an analytical uncertainty quantification algorithm is utilized. The analytical scheme computes the propagation of the orientational uncertainty to the volume-averaged properties with a linear solution and uses the transformation of random variables principle to obtain the variations in non-linear properties. The results indicate that the uncertainty propagation affects the macro-scale properties, including stiffness, thermal expansion, thermal conductivity, and natural frequencies.

scholarly journals Bayesian stochastic multi-scale analysis via energy considerations

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Muhammad S. Sarfaraz ◽  
Bojana V. Rosić ◽  
Hermann G. Matthies ◽  
Adnan Ibrahimbegović
Keyword(s):  
Nonlinear Approximation ◽  
Computational Cost ◽  
Cementitious Materials ◽  
Model Errors ◽  
Stored Energy ◽  
Standard Material ◽  
Multi Scale ◽  
Macro Scale ◽  
Optimal Material ◽  
Meso Scale

AbstractMulti-scale processes governed on each scale by separate principles for evolution or equilibrium are coupled by matching the stored energy and dissipation in line with the Hill-Mandel principle. We are interested in cementitious materials, and consider here the macro- and meso-scale behaviour of such a material. The accurate representations of stored energy and dissipation are essential for the depiction of irreversible material behaviour, and here a Bayesian approach is used to match these quantities on different scales. This is a probabilistic upscaling and as such allows to capture, among other things, the loss of resolution due to scale coarsening, possible model errors, localisation effects, and the geometric and material randomness of the meso-scale constituents in the upscaling. On the coarser (macro) scale, optimal material parameters are estimated probabilistically for certain possible behaviours from the class of generalised standard material models by employing a nonlinear approximation of Bayes’s rule. To reduce the overall computational cost, a model reduction of the meso-scale simulation is achieved by combining unsupervised learning techniques based on a Bayesian copula variational inference with functional approximation forms.

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