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.

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

2018 ◽  
Author(s):  
Pınar Acar
Keyword(s):  
Uncertainty Quantification ◽  
Single Walled Carbon Nanotube ◽  
Analytical Uncertainty ◽  
Multi Scale ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Scale Properties ◽  
Dynamics Simulations ◽  
Growth Approach

This work addresses the integration of an analytical uncertainty quantification approach to multi-scale modeling of single-walled carbon nanotube (SWNT)-epoxy nanocomposites consisting of pristine systems. The computational modeling starts with the dendrimer growth approach, which is used to build an epoxy-SWNT network. Next, the molecular dynamics simulations are performed to obtain thermal and mechanical properties. The SWNT orientations are assumed to have natural stochasticity which is modeled by an analytical uncertainty algorithm. Next, the propagation of the uncertainties to the volume-averaged properties of the SWNT and nanocomposite is obtained. The uncertainties are shown to affect the macro-scale properties such as stiffness, thermal expansion, thermal conductivity and natural frequencies.

scholarly journals A Multi-Scale Modeling Approach for Simulating Crack Sensing in Polymer Fibrous Composites Using Electrically Conductive Carbon Nanotube Networks. Part II: Meso- and Macro-Scale Analyses

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 106 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora
Keyword(s):  
Carbon Nanotube ◽  
Fibrous Composites ◽  
Electrically Conductive ◽  
Micro Scale ◽  
Multi Scale ◽  
Modeling Approach ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Meso Scale

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. Numerical models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS APDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.

scholarly journals A Multi-Scale Modeling Approach for Simulating Crack Sensing in Polymer Fibrous Composites Using Electrically Conductive Carbon Nanotube Networks. Part II: Meso- and Macro-Scale Analyses

2018 ◽  
Author(s):  
Konstantinos Tserpes ◽  
Christos Kora
Keyword(s):  
Carbon Nanotube ◽  
Fibrous Composites ◽  
Electrically Conductive ◽  
Micro Scale ◽  
Multi Scale ◽  
Modeling Approach ◽  
Scale Modeling ◽  
Macro Scale ◽  
Multi Scale Modeling ◽  
Meso Scale

This is the second of a two-paper series describing a multi-scale modeling approach developed to simulate crack sensing in polymer fibrous composites by exploiting interruption of electrically conductive carbon nanotube (CNT) networks. The approach is based on the finite element (FE) method. FE models at three different scales, namely the micro-scale, the meso-scale and the macro-scale, have been developed using the ANSYS PDL environment. In the present paper, the meso- and macro-scale analyses are described. In the meso-scale, a two-dimensional model of the CNT/polymer matrix reinforced by carbon fibers is used to develop a crack sensing methodology from a parametric study which relates the crack position and length with the reduction of current flow. In the meso-model, the effective electrical conductivity of the CNT/polymer computed from the micro-scale is used as input. In the macro-scale, the final implementation of the crack sensing methodology is performed on a CNT/polymer/carbon fiber composite volume using as input the electrical response of the cracked CNT/polymer derived at the micro-scale and the crack sensing methodology. Analyses have been performed for cracks of two different lengths. In both cases, the numerical model predicts with good accuracy both the length and position of the crack. These results highlight the prospect of conductive CNT networks to be used as a localized structural health monitoring technique.

Multi-Scale Modeling of Heterogeneous Materials and the Validation Challenge

2011 ◽  
Vol 70 ◽  
pp. 345-350
Author(s):  
Chris Pearce ◽  
Lukasz Kaczmarczyk
Keyword(s):  
Multiple Scales ◽  
Heterogeneous Materials ◽  
Heterogeneous Material ◽  
Material Behavior ◽  
Scale Separation ◽  
Multi Scale ◽  
Scale Modeling ◽  
Modeling Techniques ◽  
Multi Scale Modeling ◽  
Scale Properties

This paper considers multi-scale modeling strategies for heterogeneous materials while also highlighting the problems of determining experimentally the micro-scale properties and validating such techniques. Multi-scale modeling techniques enable us to capture the influence of (evolving) heterogeneous material microstructures on the overall macroscopic behavior. This paper discusses computational multi-scale modeling techniques for problems both with and without poor scale separation. In developing these powerful multi-scale modeling techniques, the obvious challenge of validating both the material behavior at multiple scales and the associated scale transition methodologies, using advances in material characterization and experimental mechanics, comes into sharp focus and this will be briefly explored here.

Multi-scale modeling of cross-linked epoxy nanocomposites

Polymer ◽  
2009 ◽  
Vol 50 (3) ◽  
pp. 945-952 ◽  
Author(s):  
Suyoung Yu ◽  
Seunghwa Yang ◽  
Maenghyo Cho
Keyword(s):  
Epoxy Nanocomposites ◽  
Multi Scale ◽  
Scale Modeling ◽  
Multi Scale Modeling
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