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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Using machine-learning to understand complex microstructural effects on the mechanical behavior of Ti-6Al-4V alloys

Structural materials properties are highly dependent on their microstructure. Their microstructure is in turn affected by multiple fabrication and thermo-mechanical treatment parameters, all of which conform a highly-dimensional parametric space with often hidden correlations that are difficult to extract by experimentation alone. This is particularly true for alloys of the dual-phase Ti-6Al-4V family, with their greatly complex and rich microstructures, which combine several intrinsic length scales associated with multiple grain and subgrain structures, grains with different crystal lattices (α and β phases), and complex chemistry. In this paper we use a comprehensive set of machine learning techniques to develop predictive tools relating the yield strength and hardening rate of these alloys to a set of input parameters covering extensive ranges. The data generator is a finite-element crystal plasticity model for polycrystal deformation that takes into account slip anisotropy and employs standard dislocation evolution models for the α and β phases of Ti-based alloys. Our dataset includes over two thousand independent simulations and is used to train the machine learning models, which are then used to establish correlations between microstructural parameters and the alloys’ mechanical response. Our results point to the most influential parameters affecting yield strength and hardening rate, information that can then be used to guide experimental synthesis and characterization efforts to save time and resources.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗
DOE OSTI2025

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗
DOE OSTI2025

Subvoxel Control of Fiber Orientation via Multidirectional Shearing in 3D Printing

Anisotropy, the characteristic of materials exhibiting different properties based on their direction, is widespread in nature. Conventional manufacturing techniques often fall short in recreating such complex anisotropy. While 3D printing allows for precise fiber deposition in anisotropic composites, previous studies have only achieved bulk reorientation of fibers at the voxel level in two dimensions. This limits the replication of localized 3D anisotropies found in natural materials. To address this, a novel 3D printing technique is presented that enables subvoxel control of fiber orientation in all three directions using multidirectional shearing via nozzle rotation and inclination. The fiber orientation control in these experimental tests is driven by a numerical model, enabling a fully digital approach to program microstructures within a strand. This programmability is demonstrated through mechanical and thermal tests, illustrating a localized and controllable response to external stimuli. Achieving such complex anisotropy holds potential across several fields, including wearables and biomedical implants, lightweight composite structures, and energy storage technologies such as batteries and supercapacitors.

3D printing↗
DOE OSTI2021

Utilizing a Dynamic Segmentation Convolutional Neural Network for Microstructure Analysis of Additively Manufactured Superalloy 718

Additive manufacturing (AM) is revolutionizing almost all industries through the production of intricate geometries previously prohibited by cost or machinability. Ni-based superalloys form a primary alloy class for high temperature applications in the petrochemical, aerospace, and nuclear industries because of their intrinsic resistance to creep and the ability to heat treat the superalloy for high strength. Despite these attractive properties, the extreme work hardening of Ni-based superalloys makes traditional manufacturing of complex shapes difficult and thus, these alloys are an attractive target for AM. Superalloy 718 was chosen as an example superalloy because of the wide variety of precipitates that can form within its composition space from the repetitive heating and cooling cycles of the AM process. The precipitates and other microstructure features, such as grain boundaries and dislocations, will dictate the mechanical properties and thus, there is an extensive challenge to characterize the size, number density, composition, and volume fraction of each microstructural feature from AM fabrication using analytical electron microscopy. This work focused on the application of a pixel-wise classification machine learning (ML) model called a dynamic segmentation convolutional neural network (DSCNN) to identify the microstructural features of an as-fabricated additively manufactured superalloy 718.

Taller, Stephen↗
DOE OSTI2020

Grain boundary facilitated dissolution of nanocrystalline NpO 2 (s) from legacy waste processing

Dissolution of actinide dioxides, including neptunium dioxide (NpO 2 (s)), is paramount for the prediction of the environmental fate of nuclear materials. Quantifying dissolution rates, as well as understanding qualitative dissolution mechanisms, informs performance assessment for geologic disposal of spent nuclear fuel and management of legacy radioactive waste. The aim of this research was to measure the dissolution rate of nanocrystalline NpO 2 (s), produced through legacy nuclear waste processing, under oxidizing conditions, as well as to characterize surface alteration to the material. The solid phase was characterized using electron microscopy techniques (SEM/STEM) and X-ray photoelectron spectroscopy (XPS), indicating preferential dissolution of Np-hydroxide contained in the grain boundaries of NpO 2 (s) and fragmentation of grains from the matrix. The oxidative dissolution was monitored over 40 weeks, yielding a two-step kinetic dissolution model involving hydration of NpO 2 (s) and subsequent oxidation and dissolution of the hydroxide phase. Here, the proposed dissolution models for nanocrystalline NpO 2 (s) suggest that microstructural features such as grain boundaries are key factors affecting dissolution, including release of colloidal particles, and ultimately, environmental fate and transport of nuclear materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Review on the growth, properties and applications of self-assembled oxide–metal vertically aligned nanocomposite thin films—current and future perspectives

Self-assembled oxide–metal nanocomposite thin films have aroused great research interest owing to their wide range of functionalities, including metamaterials with plasmonic and hyperbolic optical properties, and ferromagnetic, ferroelectric and multiferroic behaviors. Oxide–metal nanocomposites typically self-assemble as metal particles in an oxide matrix or as a vertically aligned nanocomposite (VAN) with metal nanopillars embedded in an oxide matrix. Among them, the VAN architecture is particularly interesting due to the vertical strain control and highly anisotropic structure, enabling the epitaxial growth of materials with large lattice mismatch. In this review, the driving forces behind the formation of self-assembled oxide–metal VAN structures are discussed. Specifically, an updated in-plane strain compensation model based on the areal strain compensation concept has been proposed in this review, inspired by the prior linear strain compensation model. It provides a guideline for material selection for designing VAN systems, especially those involving complex orientation matching relationships. Based on the model, several case studies are discussed, comparing the microstructure and morphology of different oxide–metal nanocomposites by varying the oxide phase. Specific examples highlighting the coupling between the electrical, magnetic and optical properties are also discussed in the context of oxide–metal nanocomposites. Finally, future research directions and needs are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In-service Oxidation and IASCC in High Fluence Baffle-Former Bolts Retrieved from a Westinghouse PWR

Baffle-former bolts (BFBs) are subjected to significant mechanical stress and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and reduced load-carrying capacity of the bolts, and life extension of existing pressurized water reactors (PWRs) would only cause more damage to the bolt material. To this end, the Light Water Reactor Sustainability (LWRS) Program Materials Research Pathway (MRP) successfully harvested two high fluence BFBs from a Westinghouse two-loop downflow type PWR in 2016. In the same year, the two BFBs were received at the Westinghouse Churchill facility for inspection and specimen fabrication. The fabrication was completed in 2017 with specimens shipped to Oak Ridge National Laboratory (ORNL) for further testing. The objective of this project is to provide information that is integral to evaluating end of life microstructure and properties as a benchmark of international models developed for predicting radiation-induced swelling, segregation, precipitation, mechanical property degradation, and with the latest findings, susceptibility to irradiation-assisted stress corrosion cracking (IASCC).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Novel additive manufacturing for plasma facing materials ‐ creating a research pathway for minority students

This project addresses two critical and intertwined challenges in fusion energy, namely the shortage of a broadly trained scientific workforce and the lack of scalable manufacturing solutions for plasma-facing components (PFCs). Through a collaboration among Florida International University (FIU), Miami Dade College (MDC), and Purdue University, the project established structured, reproducible educational and research pathways that recruit and advance students from institutions historically outside the fusion energy enterprise, building the human capital that this field urgently needs. The project integrates the complementary research strengths of FIU and Purdue to investigate flash sintering as a transformative processing route for tungsten-based PFCs. Unlike conventional sintering approaches, flash sintering offers rapid densification at significantly reduced thermal budgets, making it a compelling candidate for fabricating complex tungsten geometries that must withstand extreme plasma-facing environments. Systematic experimental and modeling efforts will elucidate the fundamental mechanisms governing microstructure evolution, grain boundary chemistry, and thermomechanical response during flash sintering — knowledge that is presently lacking but essential for translating this technology into reliable manufacturing practice. The convergence of workforce development and cutting-edge manufacturing research positions this project to deliver measurable, durable impact: a pipeline of fusion-ready researchers cultivated through expanded institutional partnerships, and a validated materials processing framework that accelerates domestic readiness for next-generation fusion reactor construction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1974

Investigation of the oxidation behavior of dispersion stabilized alloys when exposed to a dynamic high temperature environment

The oxidation behavior of TD-NiCr and TD-NiCrAlY alloys have been studied at 2000 and 2200 F in static and high speed flowing air environments. The TD-NiCrAlY alloys preoxidized to produce an Al2O3 scale on the surface showed good oxidation resistance in both types of environments. The TD-NiCr alloy which had a Cr2O3 oxide scale after preoxidation was found to oxidize more than an order of magnitude faster under the dynamic test conditions than at comparable static test conditions. Although Cr2O3 normally provides good oxidation protection, it was rapidly lost due to formation of volatile CrO3 when exposed to the high speed air stream. The preferred oxide arrangement for the dynamic test consisted of an external layer of NiO with a porous mushroom type morphology, an intermediate duplex layer of NiO and Cr2O3, and a continuous inner layer of Cr2O3 in contact with the alloy substrate. An oxidation model has been developed to explain the observed microstructure and overall oxidation behavior of all alloys.

Tenney, D. R.↗
NASA NTRS1983

The effect of microstructure on the fatigue behavior of Ni base superalloys

Nickel-base superalloys are used in jet engine components such as disks, turbine blades, and vanes. Improvements in the fatigue behavior will allow the life to be extended or the payloads to be increased. The first part of the present investigation deals primarily with the effects of microstructural variations on the fatigue crack propagation (FCP) behavior of nickel-base alloys, while the second part is concerned with low-cycle fatigue (LCF) behavior of Ni base systems. Waspaloy at low temperature is considered, taking into account material heat treatment and test procedures, a composite plot of Waspaloy FCP data, Paris law fatigue crack propagation constants, monotonic tensile data, and overload FCP test results for Waspaloy. It is found that the FCP and overload behavior of nickel-base alloys may be markedly improved by heat treating. Attention is given to effects of cyclic deformation on microstructure and substructure, environmental damage, and an environmental/deformation model of high temperature LCF.

Antolovich, S. D.↗
NASA NTRS1989

Stereological characterization of dry alpine snow for microwave remote sensing

A persistent problem in investigations of electromagnetic properties of snow, from reflectance at visible wavelengths to emission and backscattering in the microwave, has been the proper characterization of the snow's physical properties. It is suggested that the granular and laminar structure of snow can be measured in its aggregated state by stereology performed on sections prepared from snow specimens, and that these kinds of measurements can be incorporated into models of the electromagnetic properties. With careful sampling, anisotropy in the snow microstructure at various scales can be quantified. It is shown how stereological parameters can be averaged over orientation and optical depth for radiative transfer modeling.

Davis, Robert E.↗
NASA NTRS2003

Analysis of Plasma-Sprayed Thermal Barrier Coatings With Homogeneous and Heterogeneous Bond Coats Under Spatially Uniform Cyclic Thermal Loading

This report summarizes the results of a numerical investigation into the spallation mechanism in plasma-sprayed thermal barrier coatings observed under spatially-uniform cyclic thermal loading. The analysis focuses on the evolution of local stress and inelastic strain fields in the vicinity of the rough top/bond coat interface during thermal cycling, and how these fields are influenced by the presence of an oxide film and spatially uniform and graded distributions of alumina particles in the metallic bond coat aimed at reducing the top/bond coat thermal expansion mismatch. The impact of these factors on the potential growth of a local horizontal delamination at the rough interface's crest is included. The analysis is conducted using the Higher-Order Theory for Functionally Graded Materials with creep/relaxation constituent modeling capabilities. For two-phase bond coat microstructures, both the actual and homogenized properties are employed in the analysis. The results reveal the important contributions of both the normal and shear stress components to the delamination growth potential in the presence of an oxide film, and suggest mixed-mode crack propagation. The use of bond coats with uniform or graded microstructures is shown to increase the potential for delamination growth by increasing the magnitude of the crack-tip shear stress component.

Arnold, Steven M.↗
NASA NTRS1999

Monte Carlo Simulation of Alloy Design Techniques: Fracture and Welding Studied Using the BFS Method for Alloys

Large-scale simulations of dynamic processes at the atomic level have developed into one of the main areas of work in computational materials science. Until recently, severe computational restrictions, as well as the lack of accurate methods for calculating the energetics, resulted in slower growth in the area than that required by current alloy design programs. The Computational Materials Group at the NASA Lewis Research Center is devoted to the development of powerful, accurate, economical tools to aid in alloy design. These include the BFS (Bozzolo, Ferrante, and Smith) method for alloys (ref. 1) and the development of dedicated software for large-scale simulations based on Monte Carlo- Metropolis numerical techniques, as well as state-of-the-art visualization methods. Our previous effort linking theoretical and computational modeling resulted in the successful prediction of the microstructure of a five-element intermetallic alloy, in excellent agreement with experimental results (refs. 2 and 3). This effort also produced a complete description of the role of alloying additions in intermetallic binary, ternary, and higher order alloys (ref. 4).

Bozzolo, Guillermo H.↗
NASA NTRS1990

Thermal Conductivity and Temperature Limits of Electron-Beam Physical-Vapor-Deposited ZrO2-7wt%Y2O3 Thermal Barrier Coating

The electron-beam physical-vapor-deposited (EB-PVD) ZrO2-7wt%Y2O3 thermal barrier coating has been widely used to protect engine hot section components in modem aircraft engines. Thermal conductivity and the conductivity increases due to sintering and phase changes are important coating design parameters. There is a need to characterize the coating thermal conductivity behavior and temperature limits, in order to potentially take full advantage of the coating capability. In addition, since the ZrO2-7wt%Y2O3 coating is often used as a baseline coating for the development of advanced lower thermal conductivity and higher temperature capability coatings, a thorough evaluation of the coating conductivity behavior at future higher engine operating temperatures will be useful for more accurately assessing the benefit gained from the new coating systems. In this study, thermal conductivity behavior of EB-PVD ZrO2-7wt%Y2O3 coating has been systematically investigated as a function of temperature (up to 2600 F) and time under steady-state and cyclic test conditions using a laser heat-flux technique. Thermal conductivity change kinetics were determined under realistic engine high temperature thermal gradient conditions, and correlated to the coating microstructural and phase changes. The thermal conductivity prediction models have been established in terms of heat flux, time, and testing temperatures.

Zhu, Dongming↗
NASA NTRSDate not supplied

Advancement of Extreme Environment Additively Manufactured Alloys for Next Generation Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into propulsion development and flight applications. NASA matured commonly used aerospace alloys from various alloy families (Nickel, Copper, Stainless and Steel, Aluminum, and Titanium-based) through detailed AM process and heat treatment characterization, in addition to mechanical and thermophysical testing. While these alloys are actively used in many propulsion applications, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are liquid rocket engines; advanced propulsion systems; and in-space propulsion with high heat fluxes, high pressure, and/or that use propellants that can degrade alloys (e.g., hydrogen). This paper highlights the characterization and physical properties of the more common AM alloys using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes. Additionally, this paper discusses some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop42, GRCop-84, NASA HR-1, GRX-810, and C-103. The results from these processes demonstrated that AM could enable rapid development and ongoing efforts for optimized alloys using ICME, yielding higher performances. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. A background and overview of these novel AM-enabled alloys and AM processing developments including metallurgical and mechanical property studies is presented here. The latest advancement in the parallel component development and hot-fire testing and future developments for these alloys is also discussed.

Additive Manufacturing↗
NASA NTRSDate not supplied

Advancement of Extreme Environment Additively Manufactured Alloys for Next Generation Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into propulsion development and flight applications. NASA matured commonly used aerospace alloys from various alloy families (Nickel, Copper, Stainless and Steel, Aluminum, and Titanium-based) through detailed AM process and heat treatment characterization, in addition to mechanical and thermophysical testing. While these alloys are actively used in many propulsion applications, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are liquid rocket engines; advanced propulsion systems; and in-space propulsion with high heat fluxes, high pressure, and/or that use propellants that can degrade alloys (e.g., hydrogen). This paper highlights the characterization and physical properties of the more common AM alloys using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes. Additionally, this paper discusses some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, GRX-810, and C-103. The results from these processes demonstrated that AM could enable rapid development and ongoing efforts for optimized alloys using ICME, yielding higher performances. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. A background and overview of these novel AM-enabled alloys and AM processing developments including metallurgical and mechanical property studies is presented here. The latest advancement in the parallel component development and hot-fire testing and future developments for these alloys is also discussed.

Additive Manufacturing↗