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Kappagantula, Keerti S.

Publications and source records attributed to Kappagantula, Keerti S..

36 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing

Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these techniques lags behind their development in the lab. This means that material and process development proceeds largely via trial and error. This is sub-optimal since experiments are cost-, time-, and labor-intensive. In this work we propose a machine learning framework, differential property classification (DPC), which enables an experimenter to leverage machine learning's unparalleled pattern matching capability to pursue data-driven experimental design. DPC takes two possible experiment parameter sets and outputs a prediction of which will produce a material with a more desirable property specified by the operator. We demonstrate the success of DPC on AA7075 tube manufacturing process and mechanical property data using shear assisted processing and extrusion (ShAPE), an emerging solid phase processing technology. We show that by focusing on the experimenter's need to choose between multiple candidate experimental parameters, we can reframe the challenging regression task of predicting material properties from processing parameters, into a classification task on which machine learning models can achieve good performance.

advanced manufacturing, machine learning, ShAPE↗
DOE OSTI2023

Assemblies, riveted assemblies, methods for affixing substrates, and methods for mixing materials to form a metallurgical bond

Riveted assemblies are provided that can include a substrate extending between two ends to define opposing substrate surfaces having a first opening extending between the opposing substrate surfaces; a metal-comprising substrate extending between two ends to define opposing metal-comprising substrate surfaces having a second opening extending between the opposing metal-comprising substrate surfaces. The riveted assemblies can further provide that the first and second openings complement one another when the substrate and metal-comprising substrate are engaged; and a rivet shaft extends through the openings and engages the substrate with the rivet head and the metal-comprising substrate with the rivet stop head, at least a portion of the stop head being mixed with, and forming a metallurgical bond with the metal-comprising substrate. Assemblies are provided that can include a rivet stop head mixed with, and metallurgically bonded with a metal-comprising substrate.Methods for affixing substrates to one another are also provided. The methods can include providing a substrate defining an opening configured to receive a rivet shaft; providing a metal-comprising substrate defining a complimentary opening; operatively engaging the substrates with the rivet shaft; and forming a stop head from the rivet shaft to affix the substrates. The method further includes that the stop head mixes with, and forms a metallurgical bond with the metal-comprising substrate. Methods for mixing materials to form a metallurgical bond are also provided. The methods can include forming a metallurgical bond between a stop head of a rivet and a metal-comprising substrate.

Whalen, Scott A.↗
DOE OSTI2022

TopTemp: Parsing Precipitate Structure from Temper Topology

Technological advances are in part enabled by the development of novel manufacturing processes that give rise to new materials or material property improvements. Development and evaluation of new manufacturing methodologies is labor-, time-, and resource-intensive expensive due to complex, poorly defined relationships between advanced manufacturing process parameters and the resulting microstructures. In this work, we present a topological representation of temper (heat-treatment) dependent material micro-structure, as captured by scanning electron microscopy, called TopTemp. We show that this topological representation is able to support temper classification of microstructures in a data limited setting, generalizes well to previously unseen samples, is robust to image perturbations, and captures domain interpretable features. The presented work outperforms conventional deep learning baselines and is a first step towards improving understanding of process parameters and resulting material properties.

Kassab, Lara↗
DOE OSTI2022

Solid Phase Processing of Lead-Free Brass with Carbon Additives

Currently, “lead-free” brass alloys (like C27450/C27451/C6930), used extensively in drinking water fixtures and automotive, electrical, and electronic applications contain maximum 0.25% lead to maintain mechanical performance and machinability. Adding graphite to brass as an alternative to lead, using casting, powder metallurgy, and extrusion methods, has been explored previously. However, all these methods have proven to be energy-, time-, and resource-intensive, while not enabling performance equivalent to that of C36000 brass. In this project, we developed a one-step approach using friction extrusion and ShAPE to make lead-free brass/graphite components such as wires, rods and tubes with mechanical performance equivalent to commercial lead-free brass alloys. Manufacturing temperatures were maintained ~550-730 °C with feed rates ranging between 4 – 25 mm/min. Results show larger grains at the center of the rods and wires with smaller grains developing at the edges. Graphite particles were sheared in the direction of extrusion with higher strains observed towards the edges. Hardness of the brass/graphite samples was over 25% higher than that of the corresponding brass-only samples (rods and wires), also friction extruded. Our results show that the sub-micron graphite plays an important role in limiting process temperature and restraining grain growth during friction extrusion, thus reducing grain size in composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Friction-based riveting technique for AZ31 magnesium alloy

Rivet materials used in the aerospace and automotive industries are typically alloys of aluminum (Al) or steel. Magnesium (Mg) is an attractive alternative because it is 33% and 75% lighter than Al and steel, respectively. However, a primary barrier for using Mg as rivet material is its poor formability at room temperature, resulting in brittle fracture of the rivet head during cold riveting. Hot riveting is possible but suffers from high cycle time due to the need for pre-heating. A new friction-based riveting technique, Rotating Hammer Riveting (RHR), is reported to fully form AZ31 Mg rivet heads in a mere 0.23 seconds cycle time. Heat and pressure generated through severe plastic deformation during the process was sufficient to form the Mg rivet head without the need for a separate pre-heating operation. Due to dynamic recrystallization, AZ31 Mg grains in the rivet head were significantly refined from about 15 to 2.6 µm during RHR, which favors the formability of Mg rivet by triggering grain boundary sliding and reducing plastic anisotropy of Mg. In addition, RHR joints showed a metallurgical bond between the rivet head and top sheet, which eliminates a significant pathway for corrosion.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic stochasticity in the process) and many different inputs can yield the same output (that is, the map is not injective). For example, imagine a sentiment analysis task where, due to linguistic ambiguity, a single statement can have a range of different sentiment interpretations while at the same time many distinct statements can represent the same sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it is frequently useful to be able to model the distribution on $f(x)$ for specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for specific output $y$. Such an analysis helps the user (i) better understand the variance intrinsic to the process they are studying and (ii) understand the range of specific input $x$ that can be used to achieve output $y$. Following existing work which used a fiber bundle framework to better model many-to-one processes we describe how morphisms of fiber bundles provide a template for building models which naturally capture the structure of many-to-many processes.

Coda, Elizabeth D.↗
DOE OSTI2022

A Finite Difference Analysis of the Effect of Graphene Additions on the Electrical Conductivity of Polycrystalline Copper

A finite-difference method was used to explore the effect of graphene on the bulk electrical conductivity of copper-graphene composites. In this capacity, grain orientation information from pure copper and copper-graphene composites were used to generate synthetic 3D microstructures. The electrical conductivity of these microstructures were calculated using the finite difference method assuming different average grain sizes. From these calculations, we demonstrate that when high-conductivity grain boundaries are present within the microstructure arising from the presence of graphene, an increase in the bulk electrical conductivity is observed. On the other hand, the difference in textures between copper and copper-graphene composites may not account for a significant difference in bulk electrical conductivity. In comparison, the copper grain size has a considerably larger effect on electrical conductivity as previously anticipated. This is one of the first demonstrations of a physical basis for enhanced conductivity composites and presents pathways for further investigations on the effects of composite microstructural features, material interfaces and graphene content on electrical performance.

Frazier, William E.↗
DOE OSTI2021

Microstructure evolution, enhanced aging kinetics, and mechanical properties of AA7075 alloy after friction extrusion

In the present study we utilized Friction Extrusion (FE) a solid phase processing technique to produce fully consolidated dense 5 mm rods of AA7075 alloy. The combination of large shear stresses and temperatures at the tool-billet interface during the FE process resulted in the formation of dynamically recrystallized ~2.0 μm equiaxed grains and fine uniformly distributed stable η (MgZn 2 ) precipitates ~25–100 nm in size. Formation of such a microstructure resulted in lower solutionizing temperature and times (flash annealing) as compared to the conventionally extruded counterparts. Here we demonstrate for the first time that the solutionizing times for the T6 heat treatment of AA7075 can be reduced by three times using this FE process. In addition to being an energy efficient process, FE also serves to improve the performance of AA7075 alloys by retaining their strength while enhancing the ductility of the material. The tensile data for samples that were flash annealed and artificially aged after FE processing showed exceptional increase in ultimate tensile strength by over 19% and yield strength by over 59%, compared with an as-FE-processed sample.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Shear Assisted Processing and Extrusion (ShAPE) of Aluminum Alloy 7075, 2024, and Al-12.4TM

The most common aluminum alloys utilized in the aerospace industry are 7075 and 2024 due to their high strength-to-weight ratio compared to advanced high strength steels and other aluminum alloys. Despite excellent performance, these aluminum alloys have seen limited use outside of the aerospace industry due in part to high cost. If high-performance aluminum extrusions could be made more cost effectively by eliminating energy intensive process steps typical of conventional extrusion, then numerous opportunities exist for more widespread adoption. A key reason for the high cost of 7075 and 2024 extrusions (25-75% higher than 6061) is their slow extrusion speed. 7075 and 2024 are limited to 2 m/min and 3.5 m/min respectively, in contrast to 6061 which can be extruded at 20–80 m/min. In addition to slow speed, aluminum alloys require numerous thermal treatments throughout the extrusion process including homogenization and pre-heating prior to extrusion, and solution heat treating and artificial aging after extrusion. Each of these steps contribute to the total energy consumed during manufacturing of extruded components. This project investigates the use of ShAPE to improve extrusion speed and reduce, or even eliminate, the typical thermal treatments for high strength aluminum alloys, all while improving material performance. The overarching goal of this project was to demonstrate that Shear Assisted Processing and Extrusion (ShAPE) can manufacture high-performance aluminum alloy tubing with lower manufacturing energy and improved mechanical properties compared to conventional extrusion. Unlike conventional extrusion where the billet is rammed against a stationary die using a strictly linear motion, the ShAPE process superimposes a rotational shear force by spinning the die while the billet is plunged. Compared to conventional linear extrusion, the ShAPE process imparts significantly more strain into the feedstock material, which enables the formation of novel microstructures. These microstructures manifest an array of property and process improvements for extrusion of high-performance aluminum alloys. The following accomplishments were achieved for this project: Extrusion of 7075 at 12.2 meters/min compared to 2 meters/min for conventional extrusion; Elimination of 7075 billet homogenization (430 °C for 20 hours) which is required prior to conventional extrusion; Elimination of 7075 billet pre-heating (400 °C for 1 hour) in a separate furnace which is required prior to conventional extrusion; Achieved 7075-T6with yield strength = 595 MPa, ultimate tensile strength = 531MPa, and elongation = 17.4% for extrusions made from unhomogenized billets. Exceeds the ASTM and ASM standard, and typical industry values; Achieved 7075-T5 (i.e., no solution heat treatment) with yield strength = 588 MPa, ultimate tensile strength = 535 MPa, and elongation = 14.8% for extrusions made from homogenized billets; Extrusion of 2024 at 7.4 meters/min compared to 3.5 meters/min for conventional extrusion; Achieved 2024-T8510 yield strength = 522 MPa, ultimate strength = 510MPa, and elongation = 7.1% for extrusions made from wrought billets. Exceeds the ASTM and ASM standard, and typical industry values; Extrusion of Al-12.4TM high-performance aluminum powder directly into tubing, in a single step, which eliminates process steps typical of powder metallurgy extrusion.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Macro copper-graphene composites with enhanced electrical conductivity

Composites demonstrating simultaneously enhanced-electrical conductivity, current density and lowered-temperature coefficient of resistance (TCR) compared to copper have been highly sought after for their advantages in efficient energy transport behavior. While such conductors have been demonstrated in 1D (nanowires) and 2D (films) samples, achieving similar behavior in 3D has been challenging owing to the limitations of the synthesis techniques used. In this paper, novel macro-scale 3D copper conductors were demonstrated with simultaneously increased electrical conductivity and decreased temperature coefficient of resistance (TCR) through the addition of graphene. Hot-extrusion was used to manufacture over 1-m-long, 2-mm-diameter copper-graphene composites with varying graphene content and defect density. Results showed that the electrical conductivity and current density in composites with low defect density graphene increased monotonically as a function of graphene content. They also demonstrated a significant decrease of over 17% in TCR with the addition of only 15 ppm graphene along with over 52% improvement in current density. Comparatively composites with high defect density graphene demonstrated lower electrical conductivity and current density. This study provides first-of-its-kind evidence of 3D metal composites whose bulk electrical performance has been enhanced using graphene additive in minute quantities. Further developments in this area are essential to achieve high performance composite conductors that can improve energy transport efficiency and pave way for industrial adoption of such materials in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evaluating Effects of Shear Processing on 2D Crystalline Materials in 3D Metal Matrices: Atomistic Understanding of High Shear Deformation of Copper Graphene Composites

Composites made of copper and graphene demonstrate high strength, lubricity and enhanced electrical and thermal conductivity compared pure copper. However, manufacturing these composites at bulk volumes for industrial applications has been a big challenge. Shear deformation assisted processing is an effective method for manufacturing materials such as copper-graphene composites demonstrating ultra-fine grain structures and compositional homogeneity. Nevertheless, microstructural evolution of the composites and their property development under such conditions is not clearly understood currently. To rectify this gap in literature, high strain shear deformation of copper coated graphene foils was performed using a tribometer pin in this study. Changes in microstructure of the composite as well as the constituent components under shear deformation was correlated to process conditions. A sharp increase in the coefficient of friction attributed to rupture and smearing of graphene layer into copper substrate was observed during the shear processing. The coefficient of friction of the sheared copper/graphene composite was lower than that of pure copper, suggesting that partially worn graphene is effectively lubricious at the macroscale. A multimodal characterization of the processed region further revealed a shear deformation-induced ultrafine two-phase grain-structure consisting of copper and graphitic domains. Shear deformation reduced the copper grain size from around 50 – 100 µm to ~200 nm on an average and ~2 – 5 nm in some locations. The semicrystalline graphene films were observed to fracture into 10 – 50 µm size flakes. Oxygen enrichment was observed in the processed region. Finally, graphitic domain were identified for the first time in the copper matrix and not just at the grain boundaries providing evidence for a metastable composite microstructure as a result of solid phase processing at room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Manufacturing Dissolvable Alloy Components using ShAPE: A Study on Solid Phase Processing of Mg-W Composites and WJ11 Alloys

Dissolvable alloys and composites are an emerging class of materials that demonstrate tailored sorptivity in corrosive environments. This work explored the viability of solid phase processing (SPP) techniques, namely the shear assisted processing and extrusion (ShAPETM) method, to manufacture dissolvable magnesium composites and alloys components such as rods and tubes. The study also determined the effects of material composition and manufacturing process conditions on material microstructures developed during SPP and the resulting performance of the components. Explicit properties of interest included ultimate tensile strength, ultimate compressive strength, and yield strength. The application fields of interest for dissolvable alloys were identified as oil-and-gas operations and biomedical implants. Accordingly, PNNL collaborated with industrial and academia partners, Fortek Industries, Houston and University of Pittsburgh, during the course of this project for material and ShAPE process development. PNNL determined the viability of the using ShAPE to process the custom-designed materials provided by the project partners. This was done by identifying process parameters such as tool rotation rate, tool plunge rate, and process cooling optimal for manufacturing components with consolidated microstructures. Subsequently, PNNL also performed microstructural characterization on unprocessed and processed samples and mechanical property testing. One of the major findings from this work is that ShAPE was able to manufacture dissolvable magnesium composite and alloy rods and tubes with consolidated homogeneous microstructures and minimal macroscale defects on component surfaces. It was observed that samples processed via ShAPE demonstrated an average grain size < 2 - 5 µm, which was markedly lower than that of the precursors with 8 – 13 µm grains. Results showed that the ShAPE synthesized dissolvable magnesium composite and alloy strength was on par with or better than those components that were manufactured using traditional manufacturing processes such as forging and extrusion. It is noteworthy that the ShAPE samples were made with considerably lower number of process steps.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Copper carbon composite wire with a uniform carbon dispersion made by friction extrusion

Copper-carbon composites are a group of materials with excellent mechanical, electrical, thermal, and tribological properties. However, bulk size copper-carbon composites made by the traditional manufacturing processes, like rolling or extrusion, fall short of reaching some of these properties predicted by theory or demonstrated only by samples at centimeter scale or smaller. The two main challenges to the successful scaling-up are: 1) to uniformly disperse carbon in the metal matrix; 2) to avoid degradation due to oxidation or reaction from overheating. In this work, we first demonstrate friction extrusion as a new method to make bulk-size void-free copper-carbon composite wires with homogenized carbon dispersion. Three different carbon varieties, graphite powder, graphene nanopowder, and carbon nanotubes, were added to the copper matrix with the concentration ranging from 0.5 wt% to 15 wt%. Special tooling, processing parameters, and procedures were developed, especially for high carbon content samples. Ten-fold reductions of both copper grain size and carbon particle size were achieved and attributed to the high shear deformation. Energy dispersive X-ray spectrometry indicates the carbon powder was refined to a sub-micron level and uniformly dispersed in the copper matrix. Compared with that of pure copper, the thermal capacity of the composite wire increases by 30 % while density reduces by 29 %.

Friction extrusion, Metal matrix composite, Graphe↗
DOE OSTI2020

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Joining of Thermoset Carbon Fiber Reinforced Polymer and AZ31 Magnesium Alloy Sheet Via Friction Stir Interlocking

A new technique called friction stir interlocking (FSI) was applied for lap-joining of AZ31 magnesium sheet and thermoset carbon fiber reinforced polymer (TS-CFRP) sheet. Instead of directly joining AZ31 and TS-CFRP, a series of magnesium interlocks were used to friction stir weld with AZ31 sheet to enable joining with TS-CFRP. Microstructural characterization of joint cross sections showed that a tool rotation rate of 800 rpm produced incomplete mixing of magnesium interlocks and the top AZ31 sheet, while 1200 rpm achieved sufficient material mixing to avoid unwelded regions. Mechanical property characterization showed that AZ31/TS-CFRP dissimilar joints failed through the magnesium interlock shanks during lap shear tensile testing, with a maximum normalized joint strength reaching ~100 MPa.

Wang, Tianhao↗
DOE OSTI2020

Joining Dissimilar Materials via Rotational Hammer Riveting Technique

A mechanically robust joining method for Mg/Al and Mg/CFRP could enable multi-material assemblies that decrease vehicle weight while offering more flexibility for designers. However, certain challenges exist for joining Mg/Al and Mg/CFRP. Mechanical joining, such as conventional riveting, clinching and bolting do not form a metallurgical bond between the fastener and metal sheet being fastened. Large differences in physical and mechanical properties of metals and polymers make joining Al or Mg to CFRP challenging via various welding techniques. With solid-state and fusion based welding, rapid formation of brittle intermetallic compounds at the Mg/Al interface lead to interfacial fracture under mechanical loading. In this study, a Rotational Hammer Rivet (RHR) technique was developed to fabricate Mg/CFRP and Mg/Al joints. With RHR technique, direct joining between Mg/Al and Mg/CFRP were replaced by joining Mg rivet head and top Mg sheet. Through heat generated by plastic deformation of an Mg rivet, RHR creates a metallurgical bond between rivet head and Mg sheet which seals corrosive electrolyte from penetrating around the rivet head.

riveting, magnesium alloys, CFRP, Dissimilar Joini↗