Publications

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To support higher fidelity modeling of residual stresses in glass-to-metal (GTM) seals and to demonstrate the accuracy of finite element analysis predictions, characterization and validation data have been collected for Sandia’s commonly used compression seal materials. The temperature dependence of the storage moduli, the shear relaxation modulus master curve and structural relaxation of the Schott 8061 glass were measured and stress-strain curves were generated for SS304L VAR in small strain regimes typical of GTM seal applications spanning temperatures from 20 to 500 C. Material models were calibrated and finite element predictions are being compared to measured data to assess the accuracy of predictions.

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Fracture or tearing of ductile metals is a pervasive engineering concern, yet accurate prediction of the critical conditions of fracture remains elusive. Sandia National Laboratories has been developing and implementing several new modeling methodologies to address problems in fracture, including both new physical models and new numerical schemes. The present study provides a double-blind quantitative assessment of several computational capabilities including tearing parameters embedded in a conventional finite element code, localization elements, extended finite elements (XFEM), and peridynamics. For this assessment, each of four teams reported blind predictions for three challenge problems spanning crack initiation and crack propagation. After predictions had been reported, the predictions were compared to experimentally observed behavior. The metal alloys for these three problems were aluminum alloy 2024-T3 and precipitation hardened stainless steel PH13-8Mo H950. The predictive accuracies of the various methods are demonstrated, and the potential sources of error are discussed.

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Recent work at Sandia National Laboratories has focused on preparing strong predictive models for the simulation of ductile failure in metals. The focus of this talk is on the development of engineering-ready models that use a phenomenological approach to represent the ductile fracture processes. As such, an empirical tearing parameter that accounts for mean stress effects along the crack front is presented. A critical value of the tearing parameter is used in finite element calculations as the criterion for crack growth. Regularization is achieved with three different methods and the results are compared. In the first method, upon reaching the critical tearing, the stress within a solid element is decayed by uniformly shrinking the yield surface over a user specified amount of strain. This yields mesh-size dependent results. As a second method for regularization, cohesive surface elements are inserted using an automatic remeshing technique. In the third method, strain-localization elements are inserted with the automated remeshing.

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Glass-to-metal seals are widely used in engineering applications, but are often plagued by cracking and loss of hermeticity despite design efforts to avoid these problems. Standard computational approaches typically rely on under-refined meshes and rule-of-thumb approaches that are not always effective. This paper investigates improvements to current practice in glass-to-metal seal design. First, material models with more extensive temperature dependence are used to enhance the accuracy of residual stress prediction. Second, a Weibull-statistics approach is adopted for the prediction of the likelihood of failure. These approaches are then applied to a simplified seal geometry. The paper demonstrates that the application of these methods, especially the Weibull-statistics approach, have difficulties that need to be addressed before this proposed set of approaches can be effectively used for seal design. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. Copyright © 2010 by ASME.

Most engineering materials are inherently inhomogeneous in their processing, internal structure, properties, and performance. Their properties are therefore statistical rather than deterministic. These inhomogeneities manifest across multiple length and time scales, leading to variabilities, i.e. statistical distributions, that are necessary to accurately describe each stage in the process-structure-properties hierarchy, and are ultimately the primary source of uncertainty in performance of the material and component. When localized events are responsible for component failure, or when component dimensions are on the order of microstructural features, this uncertainty is particularly important. For ultra-high reliability applications, the uncertainty is compounded by a lack of data describing the extremely rare events. Hands-on testing alone cannot supply sufficient data for this purpose. To date, there is no robust or coherent method to quantify this uncertainty so that it can be used in a predictive manner at the component length scale. The research presented in this report begins to address this lack of capability through a systematic study of the effects of microstructure on the strain concentration at a hole. To achieve the strain concentration, small circular holes (approximately 100 {micro}m in diameter) were machined into brass tensile specimens using a femto-second laser. The brass was annealed at 450 C, 600 C, and 800 C to produce three hole-to-grain size ratios of approximately 7, 1, and 1/7. Electron backscatter diffraction experiments were used to guide the construction of digital microstructures for finite element simulations of uniaxial tension. Digital image correlation experiments were used to qualitatively validate the numerical simulations. The simulations were performed iteratively to generate statistics describing the distribution of plastic strain at the hole in varying microstructural environments. In both the experiments and simulations, the deformation behavior was found to depend strongly on the character of the nearby microstructure.

Fatigue cracking in metals has been and is an area of great importance to the science and technology of structural materials for quite some time. The earliest stages of fatigue crack nucleation and growth are dominated by the microstructure and yet few models are able to predict the fatigue behavior during these stages because of a lack of microstructural physics in the models. This program has developed several new simulation tools to increase the microstructural physics available for fatigue prediction. In addition, this program has extended and developed microscale experimental methods to allow the validation of new microstructural models for deformation in metals. We have applied these developments to fatigue experiments in metals where the microstructure has been intentionally varied.