Publications

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Ductile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios, such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Rather than evaluate the predictions of a single simulation approach, the Sandia Fracture Challenge relies on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive models to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5–68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti–6Al–4V sheet under both quasi-static and modest-rate dynamic loading (failure in (Formula presented.) 0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile- and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. Additional shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the ‘state-of-the-art’ in computational failure prediction of ductile tearing scenarios, but also provides a detailed dataset for non-blind assessment of alternative methods.

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Evermore sophisticated ductile plasticity and failure models demand experimental material characterization of shear behavior; yet, the mechanics community lacks a widely accepted, standard test method for shear-dominated deformation and failure of ductile metals. We investigated the use of the V-notched rail test, borrowed from the ASTM D7078 standard for shear testing of composites, for shear testing of Ti-6Al-4V titanium alloy sheet material, considering sheet rolling direction and quasi-static and transient load rates. In this paper, we discuss practical aspects of testing, modifications to the specimen geometry, and the experimental shear behavior of Ti-6Al-4V. Specimen installation, machine compliance, specimen-grip slip during testing, and specimen V-notched geometry all influenced the measured specimen behavior such that repeatable shear-dominated behavior was initially difficult to obtain. We will discuss the careful experimental procedure and set of measurements necessary to extract meaningful shear information for Ti-6Al-4V. We also evaluate the merits and deficiencies, including practicality of testing for engineering applications and quality of results, of the V-notched rail test for characterization of ductile shear behavior.

Evermore sophisticated ductile plasticity and failure models demand experimental material characterization of shear behavior; yet, the mechanics community lacks a widely accepted, standard test method for shear-dominated deformation and failure of ductile metals. We investigated the use of the V-notched rail test, borrowed from the ASTM D7078 standard for shear testing of composites, for shear testing of Ti-6Al-4V titanium alloy sheet material, considering sheet rolling direction and quasi-static and transient load rates. In this paper, we discuss practical aspects of testing, modifications to the specimen geometry, and the experimental shear behavior of Ti-6Al-4V. Specimen installation, machine compliance, specimen-grip slip during testing, and specimen V-notched geometry all influenced the measured specimen behavior such that repeatable shear-dominated behavior was initially difficult to obtain. We will discuss the careful experimental procedure and set of measurements necessary to extract meaningful shear information for Ti-6Al-4V. We also evaluate the merits and deficiencies, including practicality of testing for engineering applications and quality of results, of the V-notched rail test for characterization of ductile shear behavior.

In this study, ductile failure of structural metals is a pervasive issue for applications such as automotive manufacturing, transportation infrastructures, munitions and armor, and energy generation. Experimental investigation of all relevant failure scenarios is intractable, requiring reliance on computation models. Our confidence in model predictions rests on unbiased assessments of the entire predictive capability, including the mathematical formulation, numerical implementation, calibration, and execution.

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The 2014 WSEAT X-Prize is modeled as a double blind study to challenge the computational and material mechanics communities methodologies to develop better capabilities in modeling and experimentation to predict the failure in ductile metals. The challenge is presented as a distinct, yet relatively, simple geometry with all reported modeling predictions blind to each of the modeling teams. The experimental testing is validated by two independent test labs to confirm the experimentally observed behavior and results are unbiased and repeatable. The WSEAT X-Prize was issued to both external participants and internal participants as the Sandia Fracture Challenge 2 (SFC2) on May 30, 2014. A Challenge Supplemental Information Packet was sent to participants on August 13, 2014 to Prior years SFCs focused on the ability to predict failures under a quasi-static loading condition that focused on either a shear or tensile-dominated failure mode. This year’s challenge focuses on a geometry with a shear and/or tensile-dominated failure mode influenced by a moderate strain-rate ductile fracture in a metallic alloy.

The Virtual Fields Method (VFM) is an inverse method for constitutive model parameter identication that relies on full-eld experimental measurements of displacements. VFM is an alternative to standard approaches that require several experiments of simple geometries to calibrate a constitutive model. VFM is one of several techniques that use full-eld exper- imental data, including Finite Element Method Updating (FEMU) techniques, but VFM is computationally fast, not requiring iterative FEM analyses. This report describes the im- plementation and evaluation of VFM primarily for nite-deformation plasticity constitutive models. VFM was successfully implemented in MATLAB and evaluated using simulated FEM data that included representative experimental noise found in the Digital Image Cor- relation (DIC) optical technique that provides full-eld displacement measurements. VFM was able to identify constitutive model parameters for the BCJ plasticity model even in the presence of simulated DIC noise, demonstrating VFM as a viable alternative inverse method. Further research is required before VFM can be adopted as a standard method for constitu- tive model parameter identication, but this study is a foundation for ongoing research at Sandia for improving constitutive model calibration.

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