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At least 253 records · Page 14

Higher-Order Theory for Functionally Graded Materials

Functionally graded materials (FGM's) are a new generation of engineered materials wherein the microstructural details are spatially varied through nonuniform distribution of the reinforcement phase(s). Engineers accomplish this by using reinforcements with different properties, sizes, and shapes, as well as by interchanging the roles of the reinforcement and matrix phases in a continuous manner (ref. 1). The result is a microstructure that produces continuously or discretely changing thermal and mechanical properties at the macroscopic or continuum scale. This new concept of engineering the material's microstructure marks the beginning of a revolution both in the materials science and mechanics of materials areas since it allows one, for the first time, to fully integrate the material and structural considerations into the final design of structural components. Functionally graded materials are ideal candidates for applications involving severe thermal gradients, ranging from thermal structures in advanced aircraft and aerospace engines to computer circuit boards. Owing to the many variables that control the design of functionally graded microstructures, full exploitation of the FGM's potential requires the development of appropriate modeling strategies for their response to combined thermomechanical loads. Previously, most computational strategies for the response of FGM's did not explicitly couple the material's heterogeneous microstructure with the structural global analysis. Rather, local effective or macroscopic properties at a given point within the FGM were first obtained through homogenization based on a chosen micromechanics scheme and then subsequently used in a global thermomechanical analysis.

Aboudi, J.↗

Development of a high-temperature Inconel 625 heat exchanger by model design and binder jetting additive manufacturing

A nickel-based Inconel 625 superalloy heat exchanger for high-temperature applications was developed via binder jetting additive manufacturing. The material properties were characterized first on printed and sintered parts. Two sintering temperatures were used to investigate the effects of the temperature on densification and microstructure. For channel geometry design, the heat transfer capabilities of the heat exchanger were optimized for the cross-section geometry of fluid flow channels in a counterflow configuration, and a stress analysis was conducted to investigate the effects of channel geometry. After headers were incorporated into the heat exchanger as a one-piece component, a prototype was printed. A complete depowdering was achieved via compressed air blowing, and sintering was performed with the developed profile. Ultimately, a one-piece heat exchanger with a nearly full density was obtained. Heat transfer tests were performed on this unit, and the results were compared with those from the simulations. In this study, systematic processes were developed for an additively manufactured Inconel-based heat exchanger for high-pressure, high-temperature heat transfer applications.

36 MATERIALS SCIENCE↗

An AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems

Materials design aims to identify the material features that provide optimal properties for various engineering applications, such as aerospace, automotive, and naval. One of the important but challenging problems for materials design is to discover multiple polycrystalline microstructures with optimal properties. This paper proposes an end-to-end artificial intelligence (AI)-driven microstructure optimization framework for elastic properties of materials. In this work, the microstructure is represented by the Orientation Distribution Function (ODF) that determines the volume densities of crystallographic orientations. The framework was evaluated on two crystal systems, cubic and hexagonal, for Titanium (Ti) in Joint Automated Repository for Various Integrated Simulations (JARVIS) database and is expected to be widely applicable for materials with multiple crystal systems. The proposed framework can discover multiple polycrystalline microstructures without compromising the optimal property values and saving significant computational time.

36 MATERIALS SCIENCE↗

Multilayer, Multimaterial Thermal Barrier Coating Systems: Design, Synthesis, and Performance Assessment

Thermal barrier coatings ( TBC s) are increasingly playing a vital role in enhancing efficiency and performance of gas turbine engines. As engine operating temperatures rise, yttria‐stabilized zirconia ( YSZ ), the currently principal TBC material, reaches its operational limits. Gadolinium Zirconate ( GDZ )‐based pyrochlore oxides are now emerging contenders, not only due to their lower thermal conductivity, but also their ability to resist attack by silicate deposits. However, GDZ cannot be directly substituted for YSZ due to its incompatibility with the thermally grown alumina layer, therefore requiring to be a component of multilayer system. Although industry has already adopted these materials in various applications, a number of fundamental issues arise with respect to layered‐coating design, their properties and processing dependence. In this study several multilayer architectures, based on the YSZ – GDZ system, have been developed and tested for durability under furnace thermal cycling conditions. Coating designs considered optimization of microstructure and properties of individual layers based on their location within the top‐coat thickness to address competing interests of thermal conductivity, compliance, and resistance to silicates. A large variance in durability was observed in coatings made with different multilayer designs. The results and the associated failure mechanisms are rationalized through preliminary evaluation of elastic energies at the failure locations and corresponding energy release rates. The results point to new strategies in the design and manufacturing of optimal multilayer coatings.

Viswanathan, Vaishak↗

Benefits of utilizing CellProfiler as a characterization tool for U–10Mo nuclear fuel

Automated image processing techniques have the potential to aid in the performance evaluation of nuclear fuels by eliminating judgment calls that may vary from person-to-person or sample-to-sample. Analysis of in-core fuel performance is required for design and safety evaluations related to almost every aspect of the nuclear fuel cycle. This study presents a methodology for assessing the quality of uranium–molybdenum fuel images and describes image analysis routines designed for the characterization of several important microstructural properties. The analyses are performed in CellProfiler, an open-source program designed to enable biologists without training in computer vision or programming to automatically extract cellular measurements from large image sets. The quality metric scores an image based on three parameters: the illumination gradient across the image, the overall focus of the image, and the fraction of the image that contains scratches. The metric presents the user with the ability to ‘pass’ or ‘fail’ an image based on a reproducible quality score. Passable images may then be characterized through a separate CellProfiler pipeline, which enlists a variety of common image analysis techniques. The results demonstrate the ability to reliably pass or fail images based on the illumination, focus, and scratch fraction of the image, followed by automatic extraction of morphological data with respect to fission gas voids, interaction layers, and grain boundaries. - Graphical abstract: Display Omitted - Highlights: • A technique is developed to score U–10Mo FIB-SEM image quality using CellProfiler. • The pass/fail metric is based on image illumination, focus, and area scratched. • Automated image analysis is performed in pipeline fashion to characterize images. • Fission gas void, interaction layer, and grain boundary coverage data is extracted. • Preliminary characterization results demonstrate consistency of the algorithm.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Designing the Structure of Carbon Fibers for Optimal Mechanical Properties

Carbon fiber manufacturing follows generic processing steps: formation of thermoplastic fibers, stabilization, and carbonization. The final structures and end properties of the carbon fiber can differ significantly depending on the precursor chemistry and the associated processing sciences. Polyacrylonitrile (PAN) and mesophase pitch are the predominant precursors used in the production of carbon fibers. PAN-based carbon fibers consist of nanocrystalline graphitic domains typically 1.5 5 nm in size surrounded by amorphous carbon; in contrast, pitch-based carbon fibers are 10 50 nm crystallites with the graphitic (002) planes mostly aligned parallel to the fiber axis. It has been seen that the skin core structure of PAN-based carbon fibers plays a significant role in their mechanical properties. Designing a more homogenous carbon fiber microstructure by controlling the starting polymer and process parameters results in a different set of tensile strengths and elastic moduli. In this study the microstructural defect distribution (0.1 200 nm), measured by small-angle X-ray scattering, was shown to be directly related to the tensile strength of the carbon fibers. Here the formation of carbon structures from various polymer precursors is reviewed. Such a comprehensive understanding offers the opportunity to design carbon fiber microstructures with improved properties and to ultimately create new types of carbon fibers from alternative precursors at reduced cost.

Ozcan, Soydan↗

Physics-Based Design Tools for Lightweight Ceramic Composite Turbine Components with Durable Microstructures

Under the Supersonics Project of the NASA Fundamental Aeronautics Program, modeling and experimental efforts are underway to develop generic physics-based tools to better implement lightweight ceramic matrix composites into supersonic engine components and to assure sufficient durability for these components in the engine environment. These activities, which have a crosscutting aspect for other areas of the Fundamental Aero program, are focusing primarily on improving the multi-directional design strength and rupture strength of high-performance SiC/SiC composites by advanced fiber architecture design. This presentation discusses progress in tool development with particular focus on the use of 2.5D-woven architectures and state-of-the-art constituents for a generic un-cooled SiC/SiC low-pressure turbine blade.

DiCarlo, James A.↗

Influence of fine-scale B2 precipitation on dynamic compression and wear properties in hypo-eutectic Al0.5CoCrFeNi high-entropy alloy

The near equiatomic high-entropy alloys based on Al, Co, Cr, Fe, Ni have provided a novel microstructural template for alloy design. The face-centered cubic (FCC) matrix strengthened by body-centered cubic (BCC) based ordered B2 precipitates can be used to develop a new generation of precipitation strengthened alloys. The present study focuses on an Al0.5CoCrFeNi hypo-eutectic alloy consisting of an as-solidified FCC+B2 microstructure. Guided by solution thermodynamic modeling, this alloy has been isothermally aged for solid-state precipitation of a high fraction of fine-scale intragranular B2 particles. The dynamic compressive strength, hardness, and sliding wear response of the alloy as a function of B2 phase fraction is examined. The flow stress at 0.02% true strain increased from ~ 670 MPa to ~1350 (102%) MPa, the ultimate compressive strength increased from ~1160 MPa to 1500 MPa (20%), and the wear resistance increased more than 5 times with progressively increasing phase fraction of B2 precipitates.

Gwalani, Bharat↗

Deep Neural Network Algorithm for CMC Microstructure Characterization and Variability Quantification

Microstructure characterization and variability quantification are crucial for understanding ceramic matrix composites (CMCs) mechanical behavior and deformation mechanisms across length scales. Traditionally, analyses of the micrographs obtained from microscopy are labor-intensive. However, with the vast improvement in computer vision (CV) and deep learning (DL), an automated algorithm can be designed to extract essential microstructure variability from micrographs which can then be used to construct a statistically representative volume element (SRVE). The DL-based algorithm spans the taxonomy of microstructure analyses, including semantic segmentation of microstructure constituents, secondary phases, matrix/fiber interface, and defects, and quantifying the microstructure variability in terms of probability distributions. In this work, C/SiNC and SiC/SiNC CMCs microstructures are semantically segmented through a deep convolutional neural network, followed by variability quantification through the implementation of a fully connected regression layer, hence forming a deep regression network. The deep regression network operates in a feedforward regime, in which the neuron output signal traverses through the network in a unidirectional manner. The weight tensor associated with each layer is updated through a backpropagation stochastic gradient descent approach. The input gray-scale image obtained through in-house scanning electron microscope and confocal microscope micrographs is augmented through affine transformations to increase the training set size, which is then processed through four strided convolutional layers. This compresses the image resolution by half at each layer while increasing the image depth by applying different filters (image encoding). The class activation maps (CAMs) corresponding to the applied filters highlight the key architectural features and assist with the semantic segmentation of the microstructure.

Hamza, Mohamed H.↗

Relationships Between Solidification Parameters in A319 Aluminum Alloy

The design of high-performance materials depends on a comprehensive understanding of the alloy-specific relationships between solidification and properties. However, the inconsistent use of a particular solidification parameter for presenting materials characterization in the literature impedes inter-study comparability and the interpretation of findings. Therefore, there is a need for accurate expressions relating the solidification parameters for each alloy. In this study, A319 aluminum alloy castings were produced in a permanent mold with various preheating temperatures in order to control metal cooling. Analysis of the cooling curve for each casting enabled the identification of its liquidus, Al-Si eutectic, and solidus temperatures and times. These values led to the calculation of the primary solidification rate, total solidification rate, primary solidification time, and local solidification time for each casting, which were related to each other as well as to the average casting SDAS and material hardness. Expressions for each of their correlations have been presented with high coefficients of determination, which will aid in microstructural prediction and casting design.

36 MATERIALS SCIENCE↗

Predicting Geometric Influences in Metal Additive Manufacturing

Metal additive manufacturing (AM) has evolved from scientific curiosity to a potential paradigm shift in materials manufacturing owing to its ability to control microstructure and fabricate complex geometries. However, geometry, often ignored as a variable, can have a significant impact on microstructure evolution, thereby indirectly limiting the design flexibility offered by AM. Currently, the process of retaining microstructure with changing geometry relies on trial and error-based processing followed by microstructural evaluation that places significant demands on time and costs associated with experimentation and characterization. We demonstrate herein that lightweight thermal models can be effectively used to predict microstructural changes with geometry. These models can in turn be used as precursors to developing geometry independent scan strategies and achieve microstructure control in various alloy systems. Even if the thermal signatures predicted by the model are not accurate, scan strategies can be developed to mimic the thermal conditions during initial process development. We present a case study on one of the most studied AM alloys: Ti-6Al-4V.

36 MATERIALS SCIENCE↗

Effect of build geometry on the microstructural development of 316L parts produced by additive manufacturing

Highlights: • Stainless steel ribs were created via direct metal laser sintering to investigate microstructural effect of part design. • EBSD confirmed the presence of large elongated grains in the center of the part, with preferred orientation. • Small grains at the rib surface were found to grow towards the center of the rib with random orientation. • By changing rib thickness and build angle varying texture was observed in the final products. • Large intragranular misorientations were observed in all samples. - Abstract: Additive manufacturing (AM) technology has shown great potential in manufacturing complex products, such as lattice structures without extensive tooling. The focus of this study was to understand the effect of the part geometry on the resulting microstructure. Direct metal laser sintering was used for fabrication of ribs with thicknesses varying between 0.2 and 3.0 mm as well as inclined ribs the with build angles of 30° and 45°. The investigation showed that grains were growing in an epitaxial manner parallel to the building direction. The large elongated grains had a preferential orientation, resulting from the temperature gradient. Additionally, it was found that small grains had formed close to the part surface which were inclined towards the center of the rib. In contrast to the elongated grains, they had a random orientations. The results also indicated that at build angles below 45°, the formed microstructure consisted of the large grains elongated in the building direction. For the used process parameters, the critical part thickness to avoid large elongated grains was found to be about 0.4 mm. These findings allowed us to establish the basics for design rules when it comes to thin wall structures.

36 MATERIALS SCIENCE↗

Supramolecular bending and twisting in the hierarchical self-assembly of monodisperse mesogenic oligomers

Understanding how different forms of supramolecular curvature arise during assembly is crucial to designing and tuning the microstructure of hierarchically self-assembled materials. Here, we show that in crystalline phases of mesogenic oligomers, the oligomer length is a critical parameter that determines the type of curvature (Gaussian or cylindrical) exhibited by the self-assembled structures. We use iterative exponential growth to synthesize monodisperse mesogenic oligomers ranging from dimer to octamer. By analyzing their phase behavior and microstructure, we elucidate how length-dependent thermodynamic and kinetic effects tune their hierarchical degree of ordering. The oligomers’ length-dependent crystalline order drives the formation of scrolled sheets in shorter oligomers and twisted ribbons in longer oligomers. These studies highlight how oligomer length interplays with mesogen geometry and crystalline packing to drive self-assembly, introducing oligomer length as a powerful design parameter toward tailored applications of mesogenic systems.

36 MATERIALS SCIENCE↗

Handbook for Additively Manufactured Materials: Microstructure, Properties, and Fractography

As the additive manufacturing (AM) industry has grown and the processes have matured more alloys have been adapted to the various AM processes. Understanding the microstructure and properties of these AM alloys is important in designing parts that perform appropriately in application. For decades materials handbooks have been informative references for designers and engineers alike to know what properties and microstructures to expect in alloys produced by other forms of manufacturing. AM alloy references for properties and microstructures have been largely limited to literature that may not be subject to the same industry standard heat treatments or in standard process parameters. NASA has worked with partners to characterize various commercially available AM alloys with a high degree of traceability. This work aims utilize industry-relevant, traceable datasets to develop a new handbook for AM alloys to better inform designers and engineers of the microstructures, fractures, and first order properties from over 30 AM alloys produced across the industry.

Additive Manufacturing↗

High-temperature ordered intermetallic alloys III; Proceedings of the Third Symposium, Boston, MA, Nov. 29-Dec. 1, 1988

The present conference on high-temperature ordered intermetallic alloys discusses alloy theory and phase stability, defects and microstructures, mechanical behavior, alloy design and material processing, multiphase and composite materials, nickel aluminides, titanium aluminides, and other ordered intermetallics. Attention is given to compositional effects on processing and properties of nickel aluminides, dynamic compaction and hot-isostatic-pressing of nickel aluminides, improvement of elevated-temperature material properties in Ni3Al, the effect of microalloying B on the high-temperature mechanical properties of Ti3Al, the effects of structure on creep of Ti-53.4 mol pct Al intermetallics, the deformation microstructure in Ni3Si polycrystals strained over the range of temperature of flow stress anomaly, and the microstructure and mechanical properties of dual phase alloys consisting of the intermetallic phases.

Liu, C. T.↗

Evolution of B2 and laves phases in a ferritic steel under Fe 2+ ion irradiation at 475 °C

Microstructural evolution in a novel ferritic steel (Fe–12Cr–3W–3Ni–3Al–1Nb, in wt.%) computationally designed to contain B2 and Laves phases after 4 MeV Fe 2+ ion irradiation up to 220 dpa at 475 °C was characterized using transmission electron microscopy in conjunction with x-ray energy dispersive spectroscopy. The ferritic matrix phase exhibited dislocation loops and tangled dislocations, but our focus was on stability of two types of intermetallic precipitates. The B2–NiAl precipitates ~13 nm in size remained crystalline and appeared to have slightly lower Al concentration after irradiation. The Laves phase, (Fe,Cr) 2 (Nb,W), were present in two size ranges: coarse micron-scale precipitates which were amorphized with a slight composition change at irradiation doses above~30 dpa, while the finer precipitate particles~100 nm in size were partially disintegrated with a noticeable composition change at doses above~70 dpa. Meanwhile, many Nb/Cr-enriched particles ~8 nm in size formed within a few hundreds of nanometers from the disintegrated particles. The understanding of the phase stability would help design advanced steels and engineer microstructures that are stable against high irradiation doses, while retaining good high temperature strength.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗