Jacob D. Hochhalter

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.

A geometric approach to modeling microstructurally small fatigue crack formation: III. Development of a semi-empirical model for nucleation

It has been observed during fatigue cracking of AA 7075-T651 that a small percentage of Al7Cu2Fe particles crack during manufacturing or very early in their life. Some of the cracked particles eventually nucleate cracks into the surrounding microstructure, and among these the number of cycles required for nucleation varies widely. It is important to comprehend the mechanics underpinning the observed variation so that the subsequent propagation stage can be accurately modeled. To this end, finite element models of replicated grain and particle geometry are used to compute mechanical fields near monitored cracked particles using an elastic–viscoplastic crystal plasticity model that captures the effect of the orientation of the grains near each monitored particle. Nonlocal, slip-based metrics are used to study the localization and cyclic accumulation of slip near the cracked particles providing mechanics-based insight into the actuation of the nucleation event. A high slip localization and cyclic accumulation rate are found to be a necessary, but not sufficient, condition for nucleation from cracked particles. A sufficient local driving stress must also be present, which is strongly dependent on the local microstructure and accumulated slip. Furthermore, the simulation results elucidate a quantitative relationship between the slip accumulated during fatigue loading and a consequential reduction of the critical local driving stress for nucleation, providing a physical basis for the fatigue damage concept. The observed nucleation direction is orthogonal to the computed local maximum tangential stress direction, as expected for this alloy. The main result is a semi-empirical model for the number of cycles required for nucleation, which is dependent on the maximum tangential stress and cyclic slip-accumulation rate near a cracked particle.

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.

On the Effects of Modeling As-Manufactured Geometry: Toward Digital Twin

A simple, nonstandardized material test specimen, which fails along one of two different likely crack paths, is considered herein. The result of deviations in geometry on the order of tenths of a millimeter, this ambiguity in crack path motivates the consideration of as-manufactured component geometry in the design, assessment, and certification of structural systems. Herein, finite element models of as-manufactured specimens are generated and subsequently analyzed to resolve the crack-path ambiguity. The consequence and benefit of such a “personalized” methodology is the prediction of a crack path for each specimen based on its as-manufactured geometry, rather than a distribution of possible specimen geometries or nominal geometry. The consideration of as-manufactured characteristics is central to the Digital Twin concept. Therefore, this work is also intended to motivate its development.

MicroStamping for Improved Speckle Patterns to Enable Digital Image Correlation

Surface strain measurements using image correlation require a pattern to be applied to the surface of the object being measured. Lithography, the most widely used method for repeatable patterning is expensive, requiring dedicated technical staff and significant infrastructure. Lithography is time consuming, often requiring several days for each patterning application, which limits throughput. An innovative method has been developed and tested whereby repeatable patterns for image correlation are applied without dedicated technical staff or special infrastructure and can be completed in a few minutes rather than days. This new method is more amenable to application of patterns to complex surface geometries and larger surface areas. The new micro stamping method allows for higher contrast patterning materials, which improves the accuracy of strain measurements using image correlation.

Computationally Efficient Analysis of SMA Sensory Particles Embedded in Complex Aerostructures Using a Substructure Approach

The Digital Twin concept represents an innovative method to monitor and predict the performance of an aircraft’s various subsystems. By creating ultra-realistic multi-physical computational models associated with each unique aircraft and combining them with known flight histories, operators could benefit from a real-time understanding of the vehicle’s current capabilities. One important facet of the Digital Twin program is the detection and monitoring of structural damage. Recently, a method to detect fatigue cracks using the transformation response of shape memory alloy (SMA) particles embedded in the aircraft structure has been proposed. By detecting changes in the mechanical and/or electromagnetic responses of embedded particles, operators could detect the onset of fatigue cracks in the vicinity of these particles. In this work, the development of a finite element model of an aircraft wing containing embedded SMA particles in key regions will be discussed. In particular, this model will feature a technique known as substructure analysis, which retains degrees of freedom at specified points key to scale transitions, greatly reducing computational cost. By using this technique to model an aircraft wing subjected to loading experienced during flight, we can simulate the response of these localized particles while also reducing computation time. This new model serves to demonstrate key aspects of this detection technique. Future work, including the determination of the material properties associated with these particles as well as exploring the positioning of these particles for optimal crack detection, is also discussed.Copyright

Development and Characterization of Embedded Sensory Particles Using Multi-Scale 3D Digital Image Correlation

A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

Selectively Electron-Transparent Microstamping Toward Concurrent Digital Image Correlation and High-Angular Resolution Electron Backscatter Diffraction (EBSD) Analysis

Digital image correlation (DIC) in a scanning electron microscope and high-angular resolution electron backscatter diffraction (HREBSD) provide valuable and complementary data concerning local deformation at the microscale. However, standard surface preparation techniques are mutually exclusive, which makes combining these techniques in situ impossible. This paper introduces a new method of applying surface patterning for DIC, namely a urethane microstamp, that provides a pattern with enough contrast for DIC at low accelerating voltages, but is virtually transparent at the higher voltages necessary for HREBSD and conventional EBSD analysis. Furthermore, microstamping is inexpensive and repeatable, and is more suitable to the analysis of patterns from complex surface geometries and larger surface areas than other patterning techniques.

Investigation of fatigue crack incubation and growth in cast MAR-M247 subjected to low cycle fatigue at room temperature

MC carbide particles (with Hafnium and/or Tantalum as constituent metallic element, M) were observed to crack extensively in a cast polycrystalline nickel-base superalloy, MAR-M247, when subjected to low-cycle fatigue loading at room temperature. High resolution secondary electron images taken on the surface of a double edge notch test specimen revealed that approximately half the carbide particles cracked in the highly-strained notch section of the specimen. These images further illustrated that the average surface area of cracked particles was approximately three times that of the uncracked particles. Additional analysis illustrated that the cracks within a large number of particles aligned nearly perpendicular to the loading direction. However, high aspect ratio particles (with aspect ratio