Publications

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Partial penetration laser welds join metal surfaces without additional filler material, providing hermetic seals for a variety of components. The crack-like geometry of a partial penetration weld is a local stress riser that may lead to failure of the component in the weld. Computational modeling of laser welds has shown that the model should include damage evolution to predict the large deformation and failure. We have performed interrupted tensile experiments both to characterize the damage evolution and failure in laser welds and to aid computational modeling of these welds. Several EDM-notched and laser-welded 304L stainless steel tensile coupons were pulled in tension, each one to a different load level, and then sectioned and imaged to show the evolution of damage in the laser weld and in the EDM-notched parent 304L material (having a similar geometry to the partial penetration laser-welded material). SEM imaging of these specimens revealed considerable cracking at the root of the laser welds and some visible micro-cracking in the root of the EDM notch even before peak load was achieved in these specimens. The images also showed deformation-induced damage in the root of the notch and laser weld prior to the appearance of the main crack, though the laser-welded specimens tended to have more extensive damage than the notched material. These experiments show that the local geometry alone is not the cause of the damage, but also microstructure of the laser weld, which requires additional investigation.

Sealing glasses are ubiquitous in high pressure and temperature engineering applications, such as hermetic feed-through electrical connectors. A common connector technology are glass-to-metal seals where a metal shell compresses a sealing glass to create a hermetic seal. Though finite-element analysis has been used to understand and design glass-to-metal seals for many years, there has been little validation of these models. An indentation technique was employed to measure the residual stress on the surface of a simple glass-to-metal seal. Recently developed rate- dependent material models of both Schott 8061 and 304L VAR stainless steel have been applied to a finite-element model of the simple glass-to-metal seal. Model predictions of residual stress based on the evolution of material models are shown. These model predictions are compared to measured data. Validity of the finite- element predictions is discussed. It will be shown that the finite-element model of the glass-to-metal seal accurately predicts the mean residual stress in the glass near the glass-to-metal interface and is valid for this quantity of interest.

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Microstructural variabilities are among the predominant sources of uncertainty in structural performance and reliability. We seek to develop efficient algorithms for multiscale calcu- lations for polycrystalline alloys such as aluminum alloy 6061-T6 in environments where ductile fracture is the dominant failure mode. Our approach employs concurrent multiscale methods, but does not focus on their development. They are a necessary but not sufficient ingredient to multiscale reliability predictions. We have focused on how to efficiently use concurrent models for forward propagation because practical applications cannot include fine-scale details throughout the problem domain due to exorbitant computational demand. Our approach begins with a low-fidelity prediction at the engineering scale that is sub- sequently refined with multiscale simulation. The results presented in this report focus on plasticity and damage at the meso-scale, efforts to expedite Monte Carlo simulation with mi- crostructural considerations, modeling aspects regarding geometric representation of grains and second-phase particles, and contrasting algorithms for scale coupling.

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Traditional singularity-based fracture mechanics theories rely on their ability to infer the crack tip driving force (local field) by surveying macroscopic physical magnitudes far from the crack tip (far field). This key capability allows engineers to employ nominal forces or displacements to estimate the potential for stable or unstable crack growth. In the case of heterogeneous or anisotropic materials, traditional fracture approaches are not fully theoretically sound and applications rely on extrapolating methodologies with ad-hoc corrections. This Express Laboratory Directed Research and Development (ELDRD) program employed mesoscale-sensitive finite element simulations to assess the impact of grain size and texture on the crack tip behavior. A dislocation-based crystal plasticity model conveys grain size effects by computing the constraint on dislocation cell structures. We assessed the effects of microstructural variability on multiple displacement-based measurements of the fracture driving forces for crack opening (Mode I) and sliding (Mode II). We also consider multiple microstructural realizations of single phase metals undergoing ductile failure. The results show that grain size and texture affect the applied fracture driving force and can induce a significant Mode II deformation under force and displacement control, which is completely neglected in homogeneous models. A large variability in driving forces upon identical far field applied conditions is attributed to a buffering effects of the microstructure. Furthermore, crack mouth opening displacement is almost insensitive to microstructure, which suggests that experimental measurements using such a magnitude (e.g., plastic hinge model) may underestimate local crack tip driving force variability.

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A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). The Bayesian method is also employed to characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.

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Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cell represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Ultimately, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.

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