An application for line elements embedded in a 2D or 3D finite element mesh

Konrad, A.; Graovac, M.

doi:10.1109/20.497321

Cited by 11 publications

(6 citation statements)

References 4 publications

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“…In the model discussed herein, the nanotubes are approximated as line elements. This approximation is accurate and computationally efficient, as shown by Konrad & Graovac [61].…”

Section: (I) Representative Volume Element Generationmentioning

confidence: 85%

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Spanos

Elsbernd

Ward

et al. 2013

Phil. Trans. R. Soc. A.

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This paper reviews and enhances numerical models for determining thermal, elastic and electrical properties of carbon nanotube-reinforced polymer composites. For the determination of the effective stress–strain curve and thermal conductivity of the composite material, finite-element analysis (FEA), in conjunction with the embedded fibre method (EFM), is used. Variable nanotube geometry, alignment and waviness are taken into account. First, a random morphology of a user-defined volume fraction of nanotubes is generated, and their properties are incorporated into the polymer matrix using the EFM. Next, incremental and iterative FEA approaches are used for the determination of the nonlinear properties of the nanocomposite. For the determination of the electrical properties, a spanning network identification algorithm is used. First, a realistic nanotube morphology is generated from input parameters defined by the user. The spanning network algorithm then determines the connectivity between nanotubes in a representative volume element. Then, interconnected nanotube networks are converted to equivalent resistor circuits. Finally, Kirchhoff's current law is used in conjunction with FEA to solve for the voltages and currents in the system and thus calculate the effective electrical conductivity of the nanocomposite. The model accounts for electrical transport mechanisms such as electron hopping and simultaneously calculates percolation probability, identifies the backbone and determines the effective conductivity. Monte Carlo analysis of 500 random microstructures is performed to capture the stochastic nature of the fibre generation and to derive statistically reliable results. The models are validated by comparison with various experimental datasets reported in the recent literature.

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“…In the model discussed herein, the nanotubes are approximated as line elements. This approximation is accurate and computationally efficient, as shown by Konrad & Graovac [61].…”

Section: (I) Representative Volume Element Generationmentioning

confidence: 85%

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Spanos

Elsbernd

Ward

et al. 2013

Phil. Trans. R. Soc. A.

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“…To determine the piezoelectric parameters of the carbon nanotubes, each nanotube is approximated as a line element which results in efficient computation and sufficient accuracy [ 37 ]. Natural coordinates of the CNTs are used to determine the corresponding shape functions.…”

Section: Numerical Modelingmentioning

confidence: 99%

Development of Nanocomposite-Based Strain Sensor with Piezoelectric and Piezoresistive Properties

Sanati

Sandwell

Mostaghimi

et al. 2018

Sensors

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Sensors provide an interface between mechanical systems and the physical world. With the move towards Industry 4.0 and cyber-physical systems, demands for cost-effective sensors are rapidly increasing. Conventional sensors used for monitoring manufacturing processes are often bulky and need complex processes. In this study, a novel high-sensitive nanocomposite-based sensor is developed for measuring strain. The developed sensor is comprised of polyvinylidene fluoride (PVDF) as a piezoelectric polymer matrix, and embedded carbon nanotube (CNT) nanoparticles creating a conductive network. Exhibiting both piezoelectric and piezoresistive properties, the developed sensors are capable of strain measurement over a wide frequency band, including static and dynamic measurements. The piezoresistive and piezoelectric properties are fused to improve the overall sensitivity and frequency bandwidth of the sensor. To simulate the sensor, a 3D random walk model and a 2D finite element (FE) model are used to predict the electrical resistivity and the piezoelectric characteristics of the sensor, respectively. The developed models are verified with the experimental results. The developed nanocomposite sensors were employed for strain measurement of a cantilever beam under static load, impulse excitation, free and forced vibrations, collecting both piezoelectric and piezoresistive properties measurements. The obtained signals were fused and compared with those of a reference sensor. The results show that the sensor is capable of strain measurement in the range of 0–10 kHz, indicating its effectiveness at measuring both static and high frequency signals which is an important feature of the sensor.

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“…In the current model, the nanotubes are approximated as line elements. This approximation is accurate and economical as shown by Konrad and Graovac [43]. With this approximation, the stiffness matrix of a one-dimensional fiber, expanded using zeros to two dimensions, is given as…”

Section: The Embedded Fiber Methodsmentioning

confidence: 99%

“…Esteva [42] reported a finite element model in which nanotube-composite structures are modeled using finite elements and the Embedded Fiber Method, originally developed to model steel bar reinforcements in concrete [43][44][45]. This useful approach allows a simple square mesh of the entire RVE to be generated, circumventing a complicated meshing process while still producing accurate results.…”

Section: Current Cnt Composite Modelsmentioning

confidence: 99%

Coarse Molecular-Dynamics Analysis of Structural Transitions in Solid Materials

2010

Multiscale Modeling

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An application for line elements embedded in a 2D or 3D finite element mesh

Cited by 11 publications

References 4 publications

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Estimation of the physical properties of nanocomposites by finite-element discretization and Monte Carlo simulation

Development of Nanocomposite-Based Strain Sensor with Piezoelectric and Piezoresistive Properties

Coarse Molecular-Dynamics Analysis of Structural Transitions in Solid Materials

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