Thick-walled wound fibrous-composite structures

1976 ◽  
Vol 11 (1) ◽  
pp. 116-125
Author(s):  
Yu. M. Tarnopol'skii
Keyword(s):  
Composite Structures ◽  
Fibrous Composite

Failure Analysis of Composite Structures Using Multiscale Technique

2020 ◽  
Vol 995 ◽  
pp. 209-213
Author(s):  
Young W. Kwon
Keyword(s):  
Composite Structures ◽  
Failure Modes ◽  
Cell Model ◽  
Fibrous Composite ◽  
Failure Criteria ◽  
Multiscale Approach ◽  
Interface Failure ◽  
Fiber Failure ◽  
Strain Rate Effects ◽  
Constituent Material

Failure analyses of laminated fibrous composite structures were conducted using the failure criteria based on a multiscale approach. The failure criteria used the stresses and strains in the fiber and matrix materials, respectively, rather than those smeared values at the lamina level. The failure modes and their respective failure criteria consist of fiber failure, matrix failure and their interface failure explicitly. In order to determine the stresses and strains at the constituent material level (i.e. fiber and matrix materials), analytical expressions were derived using a unit-cell model. This model was used for the multiscale approach for both upscaling and downscaling processes. The failure criteria are applicable to both quasi-static loading as well as dynamic loading with strain rate effects.

Multiscale Analysis of Multifunctional Composite Structures

2013 ◽  
Author(s):  
Yehia Bahei-El-Din ◽  
Amany Micheal
Keyword(s):  
Finite Element ◽  
Electric Field ◽  
Composite Structures ◽  
Multiscale Analysis ◽  
Fibrous Composite ◽  
Computation Time ◽  
Local Fields ◽  
Composite Medium ◽  
Field Analysis ◽  
Laminated Structures

In a truly multiscale analysis of multilayered composites, the underlying phenomena are represented and their effect on the overall behavior is determined considering the interaction between the different phases and between the laminas. The analysis gets more involved when multiple phenomena are considered since in this case not only the direct effects play a role but also the coupled effects contribute to the distribution of the local fields and the overall response. In a fibrous composite laminate reinforced with piezoelectric filaments, for example, passing an electric field in the fibers generates stresses and strains which propagate through the composite medium due to constraints that exist both at the micromechanical, ply level, and the macromechanical, laminate level. Pyroelectricity is another coupling phenomenon in which a temperature change is caused by an electric field, and hence leads to changes in the stress and strain fields throughout the composite medium. The above phenomena have been considered by the authors in a unified, transformation field analysis (TFA) approach in which stresses and strains which cannot be removed by mechanical unloading are treated as transformation fields. Due to mutual constraints of the phases and the bonded plies, local transformations generate stresses at the micro and macro levels, which are computed by means of influence functions which depend on material geometry and properties. Treatment of damage follows the same scheme but the transformation fields are instead determined such that the local stresses in the affected phase are removed. In the present paper, implementation of the TFA approach in a general purpose finite element code is described. This expands the multiscale analysis outlined above to composite structures where complex geometries can be modeled and the effect of local phenomena can be considered. This naturally comes at a much larger cost of the computations compared to finite element analysis with homogenized models but the benefit of obtaining a more realistic response is clear. Moreover, the availability of high performance computing and parallel processing overcomes the computation time barrier. In the present paper however, simple examples of laminated structures are given as proof of concept in which the results are compared to those of standalone routines. Since the TFA approach centers on treating the composite medium as elastic with induced local transformations, implementation in the finite element framework does not require generation of an overall instantaneous stiffness matrix, which saves tremendously on the computation time. Instead, overall transformation strains, or stresses, are computed through a multiscale model, which is implemented as a user routine, and treated in the general finite element solution as nonmechanical strains in the same way thermal strains are treated.

scholarly journals Stereological Estimation of Orientation Distribution of Generalized Cylinders from a Unique 2D Slice

2013 ◽  
Vol 19 (6) ◽  
pp. 1678-1687 ◽  
Author(s):  
Jean-Pierre Da Costa ◽  
Stefan Oprean ◽  
Pierre Baylou ◽  
Christian Germain
Keyword(s):  
Cross Sections ◽  
Composite Structures ◽  
Large Scale ◽  
Fibrous Composite ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Inequality Constraints ◽  
Orientation Distribution ◽  
Industrial Applications ◽  
Cost Constraints

AbstractThough three-dimensional (3D) imaging gives deep insight into the inner structure of complex materials, the stereological analysis of 2D snapshots of material sections is still necessary for large-scale industrial applications for reasons related to time and cost constraints. In this paper, we propose an original framework to estimate the orientation distribution of generalized cylindrical structures from a single 2D section. Contrary to existing approaches, knowledge of the cylinder cross-section shape is not necessary. The only requirement is to know the area distribution of the cross-sections. The approach relies on minimization of a least squares criterion under linear equality and inequality constraints that can be solved with standard optimization solvers. It is evaluated on synthetic data, including simulated images, and is applied to experimental microscopy images of fibrous composite structures. The results show the relevance and capabilities of the approach though some limitations have been identified regarding sensitivity to deviations from the assumed model.

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