Publications

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The classic models for ductile fracture of metals were based on experimental observations dating back to the 1950’s. Using advanced microscopy techniques and modeling algorithms that have been developed over the past several decades, it is possible now to examine the micro- and nano-scale mechanisms of ductile rupture in more detail. This new information enables a revised understanding of the ductile rupture process under quasi-static room temperature conditions in ductile pure metals and alloys containing hard particles. While ductile rupture has traditionally been viewed through the lens of nucleation-growth-and-coalescence, a new taxonomy is proposed involving the competition or cooperation of up to seven distinct rupture mechanisms. Generally, void nucleation via vacancy condensation is not rate limiting, but is extensive within localized shear bands of intense deformation. Instead, the controlling process appears to be the development of intense local dislocation activity which enables void growth via dislocation absorption.

An initial foray into the design of specimens that can be used to provide data about the quasistatic ductile failure of metals when subjected to shear-dominated (low triaxiality) states of stress was undertaken. Four specimen geometries made from two materials with different ductility (Al 7075, lower ductility and steel A286, higher ductility) were considered as candidates. Based on results from analysis and experimentation, it seems that two show promise for further consideration. Whereas preliminary results indicate that the Johnson-Cook model fit the failure data for Al 7075 well, it did not fit the data for steel A286. Further work is needed to consolidate the results and evaluate other failure models that may fit the steel data better, as well as to extend the results of this work to the dynamic loading regime.

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The third Sandia Fracture Challenge (SFC3) was a benchmark problem for comparing experimental and simulated ductile deformation and failure in an additively manufactured (AM) 316L stainless steel structure. One surprising observation from the SFC3 was the Challenge-geometry specimens had low variability in global load versus displacement behavior, attributed to the large stress-concentrating geometric features dominating the global behavior, rather than the AM voids that tend to significantly influence geometries with uniform cross-sections. This current study reinvestigates the damage and failure evolution of the Challenge-geometry specimens, utilizing interrupted tensile testing with micro-computed tomography (micro-CT) scans to monitor AM void and crack growth from a virgin state through complete failure. This study did not find a correlation between global load versus displacement behavior and AM void attributes, such as void volume, location, quantity, and relative size, which incidentally corroborates the observation from the SFC3. However, this study does show that the voids affect the local behavior of damage and failure. Surface defects (i.e. large voids located on the surface, far exceeding the nominal surface roughness) that were near the primary stress concentration affected the location of crack initiation in some cases, but they did not noticeably affect the global response. The fracture surfaces were a combination of classic ductile dimples and crack deviation from a more direct path favoring intersection with AM voids. Even though the AM voids promoted crack deviation, pre-test micro-CT scan statistics of the voids did not allow for conclusive predictions of preferred crack paths. This study is a first step towards investigating the importance of voids on the ductile failure of AM structures with stress concentrations.

The mounting reliance on computational simulations to predict all aspects of the lifecycle of a mechanical system, from fabrication to failure, has prompted the mechanics community to selfassess its abilities to perform those predictions. Benchmark problems in mechanics that compare simulations that use different computational approaches with experiments have sprung up lately, including the NIST AM-Bench looking at additively manufactured (AM) materials (https://www.nist.gov/ambench),the Contact-Mechanics Challenge (Miiser, 2017) considering adhesion between two nominally flat surfaces, Numisheet providing semiannual benchmarking activities in sheet metal forming (http://numisheet2018.org),and the Sandia Fracture Challenge (SFC) (Boyce, 2014 and Boyce, 2016) investigating ductile failure. The previous SFCs have shown that progress has been made in computations of ductile failure, but improvements still can be made, hence the third Sandia Fracture Challenge (SFC3), the subject of this Special Volume. The most recent installment of SFC is building on previous successes and tackling the difficult problem of fracture in an AM 316L stainless steel structure.

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The Sandia Fracture Challenges provide the mechanics community a forum for assessing its ability to predict ductile fracture through a blind, round-robin format where computationalists are asked to predict the deformation and failure of an arbitrary geometry given experimental calibration data. This presentation will cover the three Sandia Fracture Challenges, with emphasis on the third. The third Challenge, issued in 2017, consisted of an additively manufactured 316L stainless steel tensile bar with through holes and internal cavities that could not have been conventionally machined. The volunteer prediction teams were provided extensive materials data from tensile tests of specimens printed on the same build tray to electron backscatter diffraction microstructural maps and micro-computed tomography scans of the Challenge geometry. The teams were asked a variety of questions, including predictions of variability in the resulting fracture response, as the basis for assessment of their predictive capabilities. This presentation will describe the Challenges and compare the experimental results to the predictions, identifying gaps in capabilities, both experimentally and computationally, to inform future investments. The Sandia Fracture Challenge has evolved into the Structural Reliability Partnership, where researchers will create several blind challenges covering a wider variety of topics in structural reliability. This presentation will also describe this new venture.

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Modeling material and component behavior using finite element analysis (FEA) is critical for modern engineering. One key to a credible model is having an accurate material model, with calibrated model parameters, which describes the constitutive relationship between the deformation and the resulting stress in the material. As such, identifying material model parameters is critical to accurate and predictive FEA. Traditional calibration approaches use only global data (e.g. extensometers and resultant force) and simplified geometries to find the parameters. However, the utilization of rapidly maturing full-field characterization techniques (e.g. Digital Image Correlation (DIC)) with inverse techniques (e.g. the Virtual Feilds Method (VFM)) provide a new, novel and improved method for parameter identification. This LDRD tested that idea: in particular, whether more parameters could be identified per test when using full-field data. The research described in this report successfully proves this hypothesis by comparing the VFM results with traditional calibration methods. Important products of the research include: verified VFM codes for identifying model parameters, a new look at parameter covariance in material model parameter estimation, new validation techniques to better utilize full-field measurements, and an exploration of optimized specimen design for improved data richness.

This project targeted a full-field understanding of the conversion of plastic work into heat using advanced diagnostics (digital image correlation, DIC, combined with infrared, IR, imaging). This understanding will act as a catalyst for reformulating the prevalent simplistic model, which will ultimately transform Sandia's ability to design for and predict thermomechanical behavior, impacting national security applications including nuclear weapon assessments of accident scenarios. Tensile 304L stainless steel dogbones are pulled in tension at quasi-static rates until failure and full-field deformation and temperature data are captured, while accounting for thermal losses. The IR temperature fields are mapped onto the DIC coordinate system (Lagrangian formulation). The resultant fields are used to calculate the Taylor-Quinney coefficient, β, at two strain rates rates (0.002 s^-1 and 0.08 s^-1) and two temperatures (room temperature, RT, and 250°C).

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Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Lastly, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.

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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.

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This memo addresses the calibration of anisotropic yield functions based on data obtained from a series of uniaxial tension specimens extracted from a tubular Al 7079 circular cylindrical extrusion. Achieving the calibrations completed an important step in the Experimentally Enhanced Computations (ExEC) project. The focus of the project is on novel calibration approaches that will be based on advanced diagnostics and numerical simulations with the intention of reducing the overall calibration effort. The test data used here resulted from traditional tensile tests on specimens cut at 12 orientations within the extrusion. Two anisotropic yield surfaces — Hill’s (1948) and Barlat’s (2005) — were calibrated based on the test data. The methods used to conduct the calibrations are described, and the results show that the material exhibited significant yield anisotropy. The larger number of parameters in Barlat’s yield function allowed it to fit the test data more accurately than Hill’s. Although work remains to assess the sensitivity of the calibrated model parameters to various factors, the methods implemented and the results obtained here provide bases for further work and useful benchmarks for future calibrations to be conducted using the novel approach.

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A “good” speckle pattern enables DIC to make its full-field measurements, but oftentimes this artistic part of the DIC setup takes a considerable amount of time to develop and evaluate for a given optical configuration. A catalog of well-quantified speckle patterns for various fields of view would greatly decrease the time it would take to start making DIC measurements. The purpose of this speckle patterning study is to evaluate various speckling techniques we had readily available in our laboratories for fields of view from around 100 mm down to 5 mm that are common for laboratory-scale experiments. The list of speckling techniques is not exhaustive: spray painting, UV-printing of computer-designed speckle patterns, airbrushing, and particle dispersion. First, we quantified the resolution of our optical configurations for each of the fields of view to determine the smallest speckle we could resolve. Second, we imaged several speckle patterns at each field of view. Third, we quantified the average and standard deviation of the speckle size, speckle contrast, and density to characterize the quality of the speckle pattern. Finally, we performed computer-aided sub-pixel translation of the speckle patterns and ran correlations to examine how well DIC tracked the pattern translations. We discuss our metrics for a “good” speckle pattern and outline how others may perform similar studies for their desired optical configurations.

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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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