Characterization of Minerals, Metals and Materials: Characterization of Mechanical Properties
Sponsored by: TMS Extraction and Processing Division, TMS: Materials Characterization Committee
Program Organizers: Mingming Zhang, Baowu Ouyeel Co. Ltd; Zhiwei Peng, Central South University; Jian Li, CanmetMATERIALS; Bowen Li, Michigan Technological University; Sergio Monteiro, Instituto Militar de Engenharia; Rajiv Soman, Eurofins EAG Materials Science LLC; Jiann-Yang Hwang, Michigan Technological University; Yunus Kalay, Middle East Technical University; Juan Escobedo-Diaz, University of New South Wales; John Carpenter, Los Alamos National Laboratory; Andrew Brown, Devcom Arl Army Research Office; Shadia Ikhmayies, The University of Jordan
Tuesday 2:30 PM
March 21, 2023
Room: Aqua 313
Location: Hilton
Session Chair: Andrew Brown, Army Research Laboratory; Juan Escobedo-Diaz, University of New South Wales
2:30 PM
Considering Creep in a Thermo-mechanical Finite Element Analysis of a Drum Furnace Lining: Guenter Unterreiter1; Dean Gregurek1; Hans Ulrich Marschall1; 1RHI Magnesita GmbH
In many cases of refractory engineering the global loads (stresses, strains) are caused by restrictions of the refractory’s thermal expansion by rigid external structures such as steel shells. In this case creep will lead to relaxation resulting in a decrease of these stresses. In this study we show the impact of a Norton-Bailey based creep model on stresses during a finite element analysis using a simplified furnace lining model. The model considers a three-dimensional cross section of the lining including the steel shell. A finite element analysis including transient heat transfer and thermo-mechanical stresses and strains was conducted. The impact of considering creep on the stress distribution is shown.
2:50 PM
Multiscale Deformation Behavior of Metallic Materials Studied using Ultra-high-speed Imaging and Acoustic Emission Techniques: Michal Knapek1; Tomas Tayari1; Adam Gres1; 1Charles University
Elementary deformation events (e.g. dislocation avalanches and twin nucleation/growth) are typically concealed in the deformation curves as they provide only average information due to the limited sensitivity and time resolution of deformation devices. On the other hand, supplementary techniques such as ultra-fast imaging and acoustic emission, if implemented correctly, allow for detailed characterization of the activity of deformation mechanisms. Here, we apply these techniques to characterize metallic materials ranging from microsamples to complex advanced bulk materials, focusing on the correlated (yet intermittent) behavior of plastic events. Using these techniques, spatial and temporal patterns in the seemingly random plastic events can be recognized by employing various statistical analyzes. The obtained data contribute to the fundamental understanding of deformation dynamics and can be utilized in designing future metallic materials.
3:10 PM
Dynamic and Quasi-static Mechanical Response and Associated Microstructural Evolution of Damascus Steels: Alec Wackwitz1; Ali Ameri1; Jianshen Wang1; Paul Hazell1; Hongxu Wang1; Juan Escobedo-Diaz1; 1University of New South Wales
This study examines the mechanical response and microstructure evolution in multiple samples of modern manufactured high carbon Pattern Welded Damascus Steel. The characterisation efforts of the Damascus samples include quasi-static and dynamic compression testing, optical microscopy, ultrasonic sound speed measurements, and Vickers hardness. Initial ultrasonic and density testing confirm that the Damascus samples are similar to their parent materials: 1095 and 15N20 plain high carbon steels. The results from the quasi-static compression testing show that the yield strength of the materials is comparable to that of carbon steel (400-500MPa) and display similar strain hardening properties. The compression results also display a slightly higher Young’s Modulus for samples with layer orientation perpendicular to the uniaxial load than those with layer orientation of approximately 45 degrees to the uniaxial load. Dynamic testing using a Split Hopkinson Bar and post-mortem characterisation is ongoing, and the most important findings will be presented.
3:30 PM Cancelled
High Strain-rate Testing of Brittle Materials using Miniature All-beryllium Split-hopkinson Pressure Bars: Bryan Zuanetti1; Kyle Ramos1; Carl Cady1; Chris Meredith2; Dan Casem2; Adam Golder3; Cynthia Bolme1; 1Los Alamos National Laboratory; 2DEVCOM Army Reserach Laboratory; 3Intuitive Surgical Instruments
Conventional Split Hopkinson Pressure Bars (SHPB) or “Kolsky” bars are often used for determining the high-rate compressive failure strength of high-strength brittle materials. However, experiments generating very high strain-rates (> 10^3 /s) demand miniaturization of the setup for appropriately measuring decreasingly short loading events. Miniature aluminum and steel bars are often sufficient for this. However, for high enough strain-rates, miniaturization of these bars may require prohibitively small test specimens that can be inappropriate for inferring representative properties of materials with large grain size relative to the specimen size. The use of an all-Beryllium Kolsky bar setup enables high rates to be accessible with larger diameter bars/specimen combinations. For these reasons, we have developed a series of Steel, Al, and Be Kolsky bar setups each optimized for testing materials of different strength, stiffness and strain-rates. In this presentation, we provide a description of the setups experiments conducted on representative brittle material.
3:50 PM Break
4:05 PM
Investigation of the Mechanical Properties of (Zr30Hf25Al20Ni10Co10Cu5)99.9Y0.1 Bulk Metallic Glass by Controlled Crystallization: Fatma Güven1; Yunus Kalay1; 1Middle East Technical University
High entropy metallic glasses have been under research recently due to the structural complexity of the high entropy alloy systems supporting the development of metallic glasses with the excellent glass-forming ability and unique properties. Although metallic glasses have high mechanical strength and hardness, they are brittle at room temperature in nature due to the lack of a crystal slip mechanism. In order to expand their potential uses in engineering, there is a great need to overcome the embrittlement problem. One of the potential solutions to increase the ductility of metallic glasses is to introduce nanocrystals into the glassy matrix through controlled devitrification. In this respect, we have investigated the mechanical properties of a newly developed high entropy metallic glass system ((Zr30Hf25Al20Ni10Co10Cu5)99.9Y0.1) in as-solidified and partially devitrified conditions. The mechanical properties based on the uniaxial compression test and nanoindentation tests will be investigated along with the transmission electron microscopy analysis.
4:25 PM
Evaluation of Feature Engineering Methods for the Prediction of Sheet Metal Properties by an Artificial Neural Network from Punching Force Curves: Marcel Goerz1; Adrian Schenek1; Mathias Liewald1; Kim Riedmüller1; 1Institute for Metal Forming Technology
The part quality that can be achieved in forming and stamping processes depends on the properties of the sheet metal material to be processed. Since these properties may fluctuate considerably, however, and thus lead to the production of scrap, it is therefore important to monitor such material fluctuations during part production. For this, the ongoing digitization of production processes provides new possibilities for part or quality monitoring. In this context, a novel AI-based method for the direct determination of material parameters from punching force curves measured in production was presented in a past study of the IFU. This paper deals with the investigation of three methods for extracting features from these measuring data. In addition to domain knowledge-based feature engineering, statistical feature extraction (PCA) as well as a gradient-based method are analyzed and compared regarding their influence on the prediction accuracy of sheet metal properties by the AI (ANN) used.
4:45 PM
Integrated Simulation, Machine Learning, and Experimental Approaches in Small-scale Mechanical Characterization of Materials: Xing Liu1; Christos Athanasiou1; Nitin Padture1; Brian Sheldon1; Huajian Gao2; 1Brown University; 2Nanyang Technological University
The past decades have witnessed an increasing demand for characterizing mechanical properties of materials at small scales due to the miniaturization of devices. While tremendous advances in experimental techniques have been achieved, researchers are still struggling with the knowledge gap between the experimental measurements and the target mechanical property that needs to be extracted. To bridge this gap, we propose a new paradigm for small-scale mechanical characterization of materials, in which delicate experiments, high-fidelity simulations, and advanced machine learning (ML) techniques are seamlessly integrated. Its feasibility and value are demonstrated in small-scale fracture toughness measurements: microcantilevers bending experiments and pillar indentation splitting experiments. These applications highlight the potential transformative impact as well as the open challenges of data-driven approaches in small-scale materials characterization.
5:05 PM
Investigation of the Failure Mechanism of a 35CrMo Polycrystalline Diamond Compact Drill Bit: Xingjie Li1; 1Sinopec Oilfield Equipment Corporation
Polycrystalline diamond compact (PDC) drill bits are widely used in oil and gas drilling. In this study, the failure mechanism of a 35CrMo drill bit is addressed by fracture analysis, dye penetrant inspection, hardness test and stress distribution simulation. The results show that the PDC bit is mainly composited of sorbite and ferrite. The presence of the bulk ferrite can significantly reduce the hardness and tensile strength of the drill bit. With the help of stress distribution simulation, it is found that there is a stress concentration at the intersection of the blade root and its adjacent water outlet. Cracks initiate at some stress concentration sites and then propagate along the bulk ferrite, causing the failure of the PDC drill.