Sharlotte Kramer

The sandia fracture challenge: Blind round robin predictions of ductile tearing

Existing and emerging methods in computational mechanics are rarely validated against problems with an unknown outcome. For this reason, Sandia National Laboratories, in partnership with US National Science Foundation and Naval Surface Warfare Center Carderock Division, launched a computational challenge in mid-summer, 2012. Researchers and engineers were invited to predict crack initiation and propagation in a simple but novel geometry fabricated from a common off-the-shelf commercial engineering alloy. The goal of this international Sandia Fracture Challenge was to benchmark the capabilities for the prediction of deformation and damage evolution associated with ductile tearing in structural metals, including physics models, computational methods, and numerical implementations currently available in the computational fracture community. Thirteen teams participated, reporting blind predictions for the outcome of the Challenge. The simulations and experiments were performed independently and kept confidential. The methods for fracture prediction taken by the thirteen teams ranged from very simple engineering calculations to complicated multiscale simulations. The wide variation in modeling results showed a striking lack of consistency across research groups in addressing problems of ductile fracture. While some methods were more successful than others, it is clear that the problem of ductile fracture prediction continues to be challenging. Specific areas of deficiency have been identified through this effort. Also, the effort has underscored the need for additional blind prediction-based assessments.

The Sandia Fracture Challenge: How Ductile Failure Predictions Fare

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.

Experimentally Enhanced Computations: Calibration Methodology for an Anisotropic Metal, Part I: Traditional Approach

The Experimentally Enhanced Computations project was motivated by the combined availability of advanced diagnostics such as digital image correlation (DIC) and non-quadratic, anisotropic yield functions for metals that have been implemented in computational mechanics codes. Here we propose to investigate the use of DIC combined with inverse methods as an alternative to traditional model calibration methods. The objective of this novel approach is to reduce the number of tests required for calibration, thus expediting the calibration process.

Experimentally Enhanced Computations: Calibration Methodology for an Anisotropic Metal, Part II – Novel Approach/Validation

Here, we present our current progress towards Part~II of the Experimentally Enhanced Computations project: a~novel calibration approach. While the first part discussed the traditional calibration approach, the availability of advanced diagnostics combined with the development of a new finite element updating inverse method that utilizes full field displacement data and the virtual fields method enables a novel calibration approach.

The Third Sandia Fracture Challenge

The Third Sandia Fracture Challenge (SFC3) is a collaborative effort for assessment of the state-of-the-art predictive capability in ductile failure. The Challenge is designed such that computational modelers are asked to predict ductile failure in an unfamiliar geometry using provided standard materials data. The SFC3, issued in December 2016, is centered on an additively manufactured 316L stainless steel geometry with through holes and internal cavities that could not be produced by conventional machining. The provided information to enable the predictions includes: base material tensile behavior for different material configurations and loading rates; notched base material tensile behavior; fabrication drawings of the base material specimens and the Challenge (unfamiliar) geometry; electron backscatter diffraction of the Challenge geometry mid-plane; micro-computed tomography data of all Challenge geometry specimens; scanning electron microscope images of the fracture surface of tensile and notched tensile base material specimens; macroscopic images of fractured base material specimens; descriptions of the boundary conditions for the base-material and Challenge-geometry tests; questions to be answered for the prediction (quantities of interest); and an overview presentation of the Challenge.

Damage Evolution in 304L Stainless Steel Partial Penetration Laser Welds

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.

Combining Full-Field Measurements and Inverse Techniques for Smart Material Testing

Traditionally, material properties (such as Young’s modulus, yield stress, etc.) are determined from a series of simple tensile and shear tests performed under various temperatures, strain rates, etc. This process is time-consuming and expensive. Additionally, material properties determined from simplified stress states may not adequately describe material behaviour under more complex loading conditions. In the past decade, full-field deformation measurements such as Digital Image Correlation (DIC) and inverse techniques such as the Virtual Fields Method (VFM) have reached a maturity level that takes them from the realm of development to the realm of application. This paper will present a concerted effort beginning at Sandia National Laboratory to explore a new experimental protocol for high-throughput, high-quality material identification by combining DIC, full-field temperature measurements, and VFM. Our current thrust is focused on identifying visco-plastic material parameters of 304L stainless steel. In particular, we will discuss the question of uniqueness of the material model and how parameter covariance affects material identification.

A Speckle Patterning Study for Laboratory-Scale DIC Experiments

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.

V-Notched Rail Test for Shear-Dominated Deformation of Ti-6Al-4V

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.

Preface to the special volume on the second Sandia Fracture Challenge

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.