Joel Johnston

Effect of Material Variability on Multiscale Modeling of Rate-Dependent Composite Materials

AbstractThe effects of material variability on the mechanical response and failure of composites under high strain rate and impact loading are investigated in this paper. A previously developed strain rate–dependent, sectional micromechanics model is extended to account for the variability in microstructure and constituent material properties. The model presented in this paper also includes a three-dimensional damage law based on a work potential theory and a microscale failure criterion. Microstructural characterization of the composite is performed to obtain the statistical distributions needed for the stochastic methodologies. A Latin hypercube sampling technique is used to model the uncertainties in fiber volume fraction and viscoplastic material constants. A comparison of general Monte Carlo simulation and Latin hypercube–based Monte Carlo shows that the Latin hypercube technique converges using fewer simulations. The modulus and failure strain obtained using the developed methodology show good corre...

In-situ Strain and Damage Sensing in Glass Fiber Laminates Using Embedded CNT

Carbon nanotube (CNT) membranes manufactured by a novel slurry compression process have been used to introduce self-sensing capability in glass fiber reinforced polymer matrix (GFRP) laminates. The CNT membranes were embedded in the interlaminar region of the laminates and piezoresistive characterization studies were conducted under monotonic and cyclic loading. High sensitivity to strain was observed. A measurement model, developed using the resistance measurements obtained under fatigue loading, was used to quantify fatigue crack length in real time. The fatigue crack growth rates and the nature of crack propagation in baseline and self-sensing GFRP (SGFRP) specimens were compared. The results show that the average crack growth rate reduced by an order of magnitude by the introduction of CNT membrane. The SGFRP laminates developed in this study exhibited crack tip blunting during fatigue, while facilitating real time strain and damage sensing. doi: 10.12783/SHM2015/213

Effect of material variability on progressive damage and micromechanics of composite materials

The effects of material variability on the mechanical response, damage, and failure of polymer matrix composites are investigated in this paper. A previously developed strain rate dependent, sectional micromechanics model is extended to account for the variability in microstructure and constituent material properties. The model presented in this paper also includes a three-dimensional damage law based on a work potential theory and a microscale failure criterion. Microstructural characterization of the composite is performed to understand the spatial variability. Additionally, the Bayesian information criterion is used to obtain the best fit statistical distributions which are needed for the stochastic methodologies. A Latin hypercube sampling technique is used to link the microstructural, statistical distributions to the sectional micromechanics. The results obtained show that the novel stochastic sectional model is more accurate than the deterministic sectional model.

Stochastic multiscale modeling and damage progression for composite materials

Modeling and characterization of complex composite structures is challenging due to uncertainties inherent in these materials. Uncertainty is present at each length scale in composites and must be quantified in order to accurately model the mechanical response and damage progression of this material. The ability to pass information between length scales permits multiscale models to transport uncertainties from one scale to the next. Limitations in the physics and errors in numerical methods pose additional challenges for composite models. By replacing deterministic inputs with random inputs, stochastic methods can be implemented within these multiscale models making them more robust.This work focuses on understanding the sensitivity of multiscale models and damage progression variations to stochastic input parameters as well as quantifying these uncertainties within a modeling framework. A multiscale, sectional model is used due to its efficiency and capacity to incorporate stochastic methods with little difficulty. The sectional micromechanics in this model are similar to that of the Generalized Method of Cells with the difference being the discretization techniques of the unit cell and the continuity conditions. A Latin Hypercube sampling technique is used due to its reported computational savings over other methods such as a fully random Monte Carlo simulation. Specifically in the sectional model, the Latin Hypercube sampling method provides an approximate 35 % reduction in computations compared to the fully random Monte Carlo method. The Latin Hypercube sampling is a stratified technique which discretizes the distribution function and randomizes the input parameters within those discretized fields. Within this multiscale modeling framework, a progressive failure theory is implemented using these stochastic methods and a modified Hashin failure theory. With a combined stochastic method and progressive failure theory, this multiscale model is capable of modeling the uncertainty and material property variations for composite materials.© 2013 ASME

Mechanical properties and damage characterization of triaxial braided composites in environmental conditions

Under environmental conditions, triaxial braided composites exhibit complex behavior and damage mechanisms. This paper investigates the damage mechanisms of these complex composites under varying environmental conditions. Tensile, compressive, and shear specimens of triaxial braided composite material were tested at room, hot (100℃), and hot/wet conditions (60℃/90% relative humidity). The strain field was studied using a digital image correlation system and the effect that the specimens’ edges have on the strain field was quantified. For the tension specimens, the environmental conditions caused reductions in the elastic and failure properties, whereas the compression specimens exhibited degradation exclusively in the failure properties. An increase in temperature rather than humidity was found to be a driving factor for the degradation of the mechanical properties. A non-destructive, flash thermography technique was used to characterize surface/subsurface damage in the specimens. Scanning electron microscopy was conducted to determine the microstructural modes of failure.

Non-Destructive Evaluation of Composite Adhesive Kissing Bond

Adhesive bonded joints have been increasingly employed in aerospace, automotive, and other mechanical systems due to the advantages of uniform stress distribution, less stress concentration, light in weight, etc. However, the early damage stage of the adhesive bond joints, which are usually named as kissing bond, can significantly impact the structural integrity and safety. Kissing bond is difficult to detect and identify using current non-destructive evaluation (NDE) techniques since there is no clearly gap or interface between the bond area. Attempts using advanced ultrasonic methods have reached limited success, but more reliable methods need to be developed before adhesive joints can be more widely applied to the engineering field. This paper focuses on the development of detection method using digital image correlation (DIC) technique. Three types of adhesive kissing bond joint samples were fabricated using different contamination recipe to simulate the kissing bonds. The performance of the fabricated joint samples were tested using uniaxial hydraulic test frame and the detection capability of DIC system was investigated. The noncontact strain field measurement method using DIC can indicate the existence of kissing bonds with limited load. The results of DIC measurement is encouraging and can be further used for the NDE estimation of mechanical properties of the kissing bond.Copyright