Ray S. Fertig

Temperature-Induced Switchable Adhesion using Nickel–Titanium–Polydimethylsiloxane Hybrid Surfaces

A switchable dry adhesive based on a nickel–titanium (NiTi) shape-memory alloy with an adhesive silicone rubber surface has been developed. Although several studies investigate micropatterned, bioinspired adhesive surfaces, very few focus on reversible adhesion. The system here is based on the indentation-induced two-way shape-memory effect in NiTi alloys. NiTi is trained by mechanical deformation through indentation and grinding to elicit a temperature-induced switchable topography with protrusions at high temperature and a flat surface at low temperature. The trained surfaces are coated with either a smooth or a patterned adhesive polydimethylsiloxane (PDMS) layer, resulting in a temperature-induced switchable surface, used for dry adhesion. Adhesion tests show that the temperature-induced topographical change of the NiTi influences the adhesive performance of the hybrid system. For samples with a smooth PDMS layer the transition from flat to structured state reduces adhesion by 56%, and for samples with a micropatterned PDMS layer adhesion is switchable by nearly 100%. Both hybrid systems reveal strong reversibility related to the NiTi martensitic phase transformation, allowing repeated switching between an adhesive and a nonadhesive state. These effects have been discussed in terms of reversible changes in contact area and varying tilt angles of the pillars with respect to the substrate surface.

Predicting Composite Fatigue Life Using Constituent-Level Physics

Use of composite materials is widespread in large aerospace structures. Many of these applications require the composite structure to perform under cyclic loading. Thus, fatigue life prediction in composite structures is an important part of composite design. In this paper, we present a comprehensive physics-based methodology for accurately predicting fatigue life in composite structures, which has been incorporated into the commercial software, Helius:Fatigue™. This methodology uses minimal coupon-level data for characterization (standard static tests plus two S-N fatigue curves). The basic framework for our approach is to use multicontinuum theory (MCT) to extract relevant constituent stresses from a composite stress or strain field and apply the kinetic theory of fracture (KTF) to predict fatigue life of the matrix constituent. Using KTF in conjunction with a damage variable allows the fatigue life of a composite to be accurately predicted. To demonstrate this approach, we evaluate the fatigue life of a composite plate with a hole in uniaxial tension fatigue.

Effect of Fiber Volume Fraction Variation Across Multiple Length Scales on Composite Stress Variation: The Possibility of Stochastic Multiscale Analysis

Prediction of composite failure is of critical importance to the design of composite structures. However, because failure of composite structures is typically sudden and catastrophic, understanding the stochastic behavior of failure is critical to accurate prediction of structural reliability. The research reported here focuses on quantifying the length scales of microstructural variability, specifically variation of fiber volume fraction, and their relationship to stress fluctuations in the bulk material. From this study, a stochastic multiscale progressive failure simulation of a compressive test is developed to demonstrate the feasibility of incorporating realistic stochastic information in a multiscale model. Unlike other stochastic studies that randomize strengths or stiffnesses, this approach randomizes an entire microstructure on the basis of volume fraction distributions computed directly from SEM images. Furthermore, the distributions are specific to mesh size. The predicted failure modes are correct and the scatter in the compressive strength predicted by the simulation is similar to scatter in strengths measured experimentally.

Characterization, synthetic generation, and statistical equivalence of composite microstructures

Mechanical behavior and reliability of composites are driven significantly by microstructural variability. Such variability can be present in the form of both morphological and constituent property variability. To understand the effect of this variability on macroscopic mechanical behavior, many statistically equivalent microstructures must be evaluated. This requires the ability to generate such microstructures. In this work, morphological variability was quantified by image analysis of actual microstructures. To reproduce this variability, a methodology was developed in which random microstructures are generated and subsequently adjusted to simultaneously match both short- and long-range statistics of actual microstructures. Synthetic microstructures were generated at a length scale of 70 µm, corresponding to the length scale at which fiber volume fractions of adjacent microstructures are uncorrelated. The utility of this methodology was also demonstrated for larger microstructures containing defects such as alignment fibers, voids and resin seams.

Physics-Based Multiscale Creep Strain and Creep Rupture Modeling for Composite Materials

In this study, a novel multiscale combined creep strain and creep rupture model is proposed. By comparing to experimental data, it was shown that the model provides accurate creep rupture predictions for unidirectional off-axis specimens. The creep strain model provides accurate predictions within the confines of the restrictions used in its development. This coupled model was incorporated into a progressive failure finite-element simulation so that the effects of load redistribution could be considered, which tended to increase the life of the part when strain gradients were present. The finite-element implementation also allowed for the consideration of realistic geometries resulting in complex stress states. By considering a perfectly flat specimen and one containing worst-case thickness variation, experimental open-hole creep rupture data was accurately bounded. This suggests that, by quantifying material defects, realistic lifetime predictions can be made, and an estimate of scatter can be acquired.

Monotonic and cyclic loading behavior of porous scaffolds made from poly(para-phenylene) for orthopedic applications

Porous poly(para-phenylene) (PPP) scaffolds have tremendous potential as an orthopedic biomaterial; however, the underlying mechanisms controlling the monotonic and cyclic behavior are poorly understood. The purpose of this study was to develop a method to integrate micro-computed tomography (μCT), finite-element analysis (FEA), and experimental results to uncover the relationships between the porous structure and mechanical behavior. The μCT images were taken from porous PPP scaffolds with a porosity of 75vol% and pore size distribution between 420 and 500µm. Representative sections of the image were segmented and converted into finite-element meshes. It was shown through FEA that localized stresses within the microstructure were approximately 100 times higher than the applied global stress during the linear loading regime. Experimental analysis revealed the S-N fatigue curves for fully dense and porous PPP samples were parallel on log-log plots, with the endurance limit for porous samples in tension being approximately 100 times lower than their solid PPP counterparts (0.3-35MPa) due to the extreme stress concentrations caused by the porous microarchitecture. The endurance limit for porous samples in compression was much higher than in tension (1.60MPa). Through optical, laser-scanning, and scanning-electron microscopy it was found that porous tensile samples failed under Mode I fracture in both monotonic and cyclic loading. By comparison, porous compressive samples failed via strut buckling/pore collapse monotonically and by shearing fracture during cyclic loading. Monotonic loading showed that deformation behavior was strongly correlated with pore volume fraction, matching foam theory well; however, fatigue behavior was much more sensitive to local stresses believed to cause crack nucleation.

Composite Interaction Energy and Constituent Average Stresses for Predicting Composite Failure

Complex interactions in fiber-reinforced composites between multiple failure mechanisms have made accurate failure prediction a daunting challenge. One approach to better identify failure mechanisms has been the use of volume average constituent stresses in the composite to predict the onset and outcome of failure in individual constituents. However, this approach was shown here to not conserve strain energy in the composite, which could potentially affect the accuracy of failure prediction under certain loading conditions. The focus of this work was to develop an expression for the discrepancy in strain energy, termed the interaction energy, and to numerically evaluate the influence of constituent properties, fiber volume fraction, and load combinations on the magnitude of this energy. The simulation results showed that interaction energy accounts for nearly 30% of the total strain energy in the composite for certain loading conditions in typical aerospace-grade carbon-epoxy composites, suggesting that e...

Random Fiber Micromechanics of Fatigue Damage

A finite element (FE) micromechanics modeling capability has been developed for simulating the mechanical behavior of random distributions of fibers in a periodic unit cell to predict fatigue damage in the matrix. The model has automated features that facilitate parametric studies. This includes the ability to simulate any three-dimensional macroscopically uniform state of stress and to easily generate new fiber distributions that can have variable numbers of fibers. An interphase material was introduced to explore the effect of a weak fiber/matrix interface. A damage evolution variable driven by the kinetic theory of fracture was implemented within the FE computations to predict the time evolution of damage at each material point. The spatial and time evolution of damage in the micromechanics model has been predicted for several states of composite stress. The effects of a weak fiber/matrix interphase, fiber distribution, and fiber volume fraction were explored.

Development of a High-Fidelity Time-Dependent Aero-Structural Capability for Analysis and Design

The development of a tightly coupled aeroelastic simulation capability for analysis and design is described in this paper. The method makes use of a well established unstructured mesh computational fluid dynamics solver, combined with a recently developed structural dynamics code. These two disciplinary codes are coupled through a fluid-structure interface and a mesh deformation capability. The discrete adjoint for all disciplinary software components has also been implemented with the goal of enabling time-dependent aeroelastic optimization. The individual disciplinary components are validated both in analysis and adjoint mode. Subsequently, the coupled aeroelastic analysis capability is demonstrated for both static and dynamic problems. Based on the validation and performance of these components, the future development of a time dependent coupled aeroelastic adjoint optimization capability is described.

Generation of Synthetic FRP Microstructures Based on Experimentally Observed Microstructures

One of the key defects in composite materials is the large variability in mechanical properties. To capture the variability of strength in FRPs, random microstructures have to be analyzed. Developing a realistic model for generation of random microstructures required first imaging a carbon reinforced epoxy and then quantifying prominent microstructural features. Microstructures were synthetically generated including experimentally observed microstructural features such as elliptical fibers, alignment fibers, voids, and resin seams. Material periodicity of microstructures was considered to facilitate the application of displacement periodic boundary condition for later finite element analysis.