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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Surface integrity and fatigue behaviour of electric discharged machined and milled austenitic stainless steel

Machining of austenitic stainless steels can result in different surface integrities and different machining process parameters will have a great impact on the component fatigue life. Understanding how machining processes affect the cyclic behaviour and microstructure are of outmost importance in order to improve existing and new life estimation models. Milling and electrical discharge machining (EDM) have been used to manufacture rectangular four-point bend fatigue test samples; subjected to high cycle fatigue. Before fatigue testing, surface integrity characterisation of the two surface conditions was conducted using scanning electron microscopy, surface roughness, residual stress profiles, and hardness profiles. Differences in cyclic behaviour were observed between the two surface conditions by the fatigue testing. The milled samples exhibited a fatigue limit. EDM samples did not show the same behaviour due to ratcheting. Recrystallized nano sized grains were identified at the severely plastically deformed surface of the milled samples. Large amounts of bent mechanical twins were observed ~ 5 μm below the surface. Grain shearing and subsequent grain rotation from milling bent the mechanical twins. EDM samples showed much less plastic deformation at the surface. Surface tensile residual stresses of ~ 500 MPa and ~ 200 MPa for the milled and EDM samples respectively were measured. - Highlights: •Milled samples exhibit fatigue behaviour, but not EDM samples. •Four-point bending is not suitable for materials exhibiting pronounced ratcheting. •LAGB density can be used to quantitatively measure plastic deformation. •Grain shearing and rotation result in bent mechanical twins. •Nano sized grains evolve due to the heat of the operation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An integrated modeling framework with open architecture for phase field simulation of multi-component alloys

An integrated modeling framework (PanPhaseField) has been developed, which enables a direct and fast coupling between CALPHAD calculations and large-scale phase field simulations for multi-component alloys. Further, it adopts an open architecture allowing for integration of user-defined phase field models in a plug-and-play manner by taking full advantage of the user-friendly graphical interface of Pandat software. The developed modeling platform becomes an enabling tool that can be used to simulate the evolution of spatially varying microstructures of industrial complex alloys for various engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Coupling a Cellular Automaton Model with a Finite Element Model for Simulating Deformation and Recrystallization of a Low-Carbon Micro-alloyed Steel During Hot Compression

This study simulated the dynamic recrystallization (DRX) of a 2.25Cr-1Mo-0.25V steel by coupling a cellular automaton (CA) method with a finite element (FE) model. A secondary development program (SDP) on DEFORM-2D was carried out and the stress strain response, dislocation density evolution and DRX were considered. In this way, an interaction between the microstructural evolution and the deformation behavior can be taken into account. The values of temperature, strain and strain rate from the FE analysis were passed to the CA model. In turn, the recrystallized grain size and volume fraction of DRX predicted by the CA model were passed back to the FE model, which influenced the flow stress. To validate the SDP, the predicted loads and flow stress were compared with the experimental values, which show a good agreement. Then, the SDP program was used to simulate the microstructural evolution. Morphological characteristic, recrystallized grain size and volume fraction of DRX were predicted and compared with experimental data. The results show that the comparison is in a good agreement, which indicates the SDP is reliable.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Crystal viscoplasticity model for the creep-fatigue interactions in single-crystal Ni-base superalloy CMSX-8

A crystal viscoplasticity (CVP) model for the creep-fatigue interactions of nickel-base superalloy CMSX-8 is proposed. At the microstructure scale of relevance, the superalloys are a composite material comprised of a γ phase and a γ' strengthening phase with unique deformation mechanisms that are highly dependent on temperature. Considering the differences in the deformation of the individual material phases is paramount to predicting the deformation behavior of superalloys at a wide range of temperatures. In this work, we account for the relevant deformation mechanisms that take place in both material phases by utilizing two additive strain rates to model the deformation on each material phase. The model is capable of representing the creep-fatigue interactions in single-crystal superalloys for realistic 3-dimensional components in an Abaqus User Material Subroutine (UMAT). Using a set of material parameters calibrated to superalloy CMSX-8, the model predicts creep-fatigue, fatigue and thermomechanical fatigue behavior of this single-crystal superalloy. In conclusion, a sensitivity study of the material parameters is done to explore the effect on the deformation due to changes in the material parameters relevant to the microstructure.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Deformation mechanisms in negative Poisson's ratio materials - Structural aspects

Poisson's ratio in materials is governed by the following aspects of the microstructure: the presence of rotational degrees of freedom, non-affine deformation kinematics, or anisotropic structure. Several structural models are examined. The non-affine kinematics are seen to be essential for the production of negative Poisson's ratios for isotropic materials containing central force linkages of positive stiffness. Non-central forces combined with pre-load can also give rise to a negative Poisson's ratio in isotropic materials. A chiral microstructure with non-central force interaction or non-affine deformation can also exhibit a negative Poisson's ratio. Toughness and damage resistance in these materials may be affected by the Poisson's ratio itself, as well as by generalized continuum aspects associated with the microstructure.

Lakes, R.↗
NASA NTRS1990

Corrosion fatigue crack propagation in metals

This review assesses fracture mechanics data and mechanistic models for corrosion fatigue crack propagation in structural alloys exposed to ambient temperature gases and electrolytes. Extensive stress intensity-crack growth rate data exist for ferrous, aluminum and nickel based alloys in a variety of environments. Interactive variables (viz., stress intensity range, mean stress, alloy composition and microstructure, loading frequency, temperature, gas pressure and electrode potential) strongly affect crack growth kinetics and complicate fatigue control. Mechanistic models to predict crack growth rates were formulated by coupling crack tip mechanics with occluded crack chemistry, and from both the hydrogen embrittlement and anodic dissolution/film rupture perspectives. Research is required to better define: (1) environmental effects near threshold and on crack closure; (2) damage tolerant life prediction codes and the validity of similitude; (3) the behavior of microcrack; (4) probes and improved models of crack tip damage; and (5) the cracking performance of advanced alloys and composites.

Gangloff, Richard P.↗
DOE OSTI2017

Microstructure selection in thin-sample directional solidification of an Al-Cu alloy: In situ X-ray imaging and phase-field simulations

We study microstructure selection during directional solidification of a thin metallic sample. We combine in situ X-ray radiography of a dilute Al-Cu alloy solidification experiments with three-dimensional phase-field simulations. We explore a range of temperature gradient G and growth velocity V and build a microstructure selection map for this alloy. We investigate the selection of the primary dendritic spacing Lambda and tip radius rho. While rho shows a good agreement between experimental measurements and dendrite growth theory, with rho similar to V-1/2, Lambda is observed to increase with V (partial derivative Lambda/partial derivative V > 0), in apparent disagreement with classical scaling laws for primary dendritic spacing, which predict that partial derivative Lambda/partial derivative V <0. We show through simulations that this trend inversion for Lambda(V) is due to liquid convection in our experiments, despite the thin sample configuration. We use a classical diffusion boundary-layer approximation to semi-quantitatively incorporate the effect of liquid convection into phase-field simulations. This approximation is implemented by assuming complete solute mixing outside a purely diffusive zone of constant thickness that surrounds the solid-liquid interface. This simple method enables us to quantitatively match experimental measurements of the planar morphological instability threshold and primary spacings over an order of magnitude in V. We explain the observed inversion of partial derivative Lambda/partial derivative V by a combination of slow transient dynamics of microstructural homogenization and the influence of the sample thickness.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reification of latent microstructures: On supervised unsupervised and semi-supervised deep learning applications for microstructures in materials informatics

Machine learning (ML), including deep learning (DL), has become increasingly popular in the last few years due to its continually outstanding performance. In this context, we apply machine learning techniques to "learn" the microstructure using both supervised and unsupervised DL techniques. In particular, we focus (1) on the localization problem bridging (micro)structure (localized) property using supervised DL and (2) on the microstructure reconstruction problem in latent space using unsupervised DL. The goal of supervised and semi-supervised DL is to replace crystal plasticity finite element model (CPFEM) that maps from (micro)structure (localized) property, and implicitly the (micro)structure (homogenized) property relationships, while the goal of unsupervised DL is (1) to represent high-dimensional microstructure images in a non-linear low-dimensional manifold, and (2) to discover a way to interpolate microstructures via latent space associating with latent microstructure variables. At the heart of this report is the applications of several common DL architectures, including convolutional neural networks (CNN), autoencoder (AE), and generative adversarial network (GAN), to multiple microstructure datasets, and the quest of neural architecture search for optimal DL architectures.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

A Combined Computational, Experimental, and Technology Development Approach to In-Space Laser Manufacturing Maturation at NASA Marshall Space Flight Center

In-space manufacturing (ISM) is emerging as a field vital to continued access and capabilities in the space environment. NASA Marshall Space Flight Center (MSFC) is advancing the frontier of in-space laser manufacturing (ISLM) techniques through work initially focused on maturing laser beam welding (LBW) and laser forming (LF) for use in space. Such techniques proffer the ability to assemble and join structures in space from sheet metal or other stock – extant satellites, in situ resource utilization of Lunar regolith, etc. – by forming to desired shapes and then joining via in-space welding (ISW). ISLM processes are useful for assembly, joining, modification, and repair of structures in free space and on the Lunar surface such as large observatories, antennas, trusses, blast/thermal/radiation shields, pressure vessels, and more. However, these techniques are not yet qualified & certified (Q&C) for regular application in space. It would be prohibitively expensive, laborious, and time-consuming to perform Q&C via traditional experimental approaches as data collection & experimentation in space is resource-intensive. As such, benchmark experiments and focused, properly instrumented technology demonstration efforts in space can collect sufficient data that – when combined with verified computational models in an integrated computational materials engineering (ICME) approach – can validate ICME tools capable of translating more readily obtained ground data to in-space, in situ, computationally informed Q&C of ISLM techniques. Several ISLM projects at MSFC are obtaining the data required to validate ICME tools through both ground and flight experiments. A parabolic flight experiment of LBW under vacuum is manifested for August 2024, including both microgravity and Lunar gravity profiles. This collaboration with the Ohio State University is investigating common aerospace alloys such as 316L stainless steel, 2219 aluminum alloy, and Ti64 titanium alloy. In situ data collection includes videography, thermography, and reference thermocouples to build a thermal model of the welds. This will elucidate the relevant physics when combined with post-flight microstructural examination and mechanical testing. MSFC is also progressing towards a suborbital flight experiment of LBW under vacuum, which could provide reams of data on ISW during sustained, high-quality reduced gravity. The effect of combined thermal (cryogenic and high-temperature) and vacuum exposure on both LBW (NASA-funded) and LF (DARPA-funded) is being investigated through ground experiments. In addition to the copious data collected during these ground experiments, ruggedization of LBW hardware will also be pursued. The datasets from these experiments will be used to validate computational models which will inform future ISLM efforts in an ICME framework. A variety of techniques across lengths scales, from CALPHAD-driven thermodynamics & kinetics to phase field modeling of solidification to kinetic Monte Carlo simulations of grain evolution at the mesoscale, will be employed to accelerate the infusion and eventual Q&C of LBW and LF for use in space. The development of data-driven surrogate models to bridge ground to flight experiments and thereby reduce the need for resource-intensive experiments in space will also be investigated. These ICME techniques, surrogate models, and datasets from ground testing can also be employed to advance manufacturing in terrestrial environments.

in-space welding↗
DOE OSTI2017

Multi-Scale Modeling of Swelling in Accident-Tolerant U 3 Si 2 Fuel

U 3 Si 2 is a promising candidate for use as an accident-tolerant fuel for light water reactors. A multi-scale computational approach was used to calculate swelling in pellet-form U 3 Si 2 fuel. Swelling was assumed to be equal to the volume fraction of fission gas bubbles in the fuel, and the evolution of bubble volume fraction was determined from phase-field simulations. To parameterize the phase-field model, density-functional theory and molecular dynamics simulations were performed. To enable molecular dynamics simulations, a new interatomic potential for the U-Si system was developed based on the modified embedded atom method. A new phase-field model based on a grand-potential functional was also developed. The model is applicable to both intergranular and intragranular bubbles. To calculate the volume fraction of bubbles, the microstructure was decomposed into regions consisting of only intragranular or intergranular bubbles based on a truncated octahedral grain structure, and growth of the bubbles in the two regions was simulated separately. The total swelling was then calculated based on a a weighted average of bubble volume fraction in the two regions. Total swelling was of the same order of magnitude, but larger than that predicted by the existing empirical swelling model used in BISON and a rate-theory based model. Limitations of the present approach and suggestions for improvement are presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Effect of sample size on the maximum value distribution of fatigue driving forces in metals and alloys

An analytical framework is presented to predict the effects of sample size on the maximum value distribution (MVD) of the driving forces for fatigue crack formation in metals and alloys. The distribution of the maximum driving force for fatigue crack formation over the domain follows the generalized extreme value theory in the limit as the domain size increases to infinity. Here, a simulation-based analysis of microstructure influences on fatigue resistance for polycrystalline metals and alloys is very costly, and reaching those limits is intractable. This work models the MVD of Fatigue Indicator Parameters (FIPs), which serve as surrogate measures for the driving force for fatigue crack formation, at finite sample sizes prior to their convergence to a limiting extreme value distribution. Large-scale crystal plasticity finite element (CPFE) simulations of FCC Al 7075-T6 with microstructure realizations of various sizes are incorporated to calibrate and evaluate the developed framework, and a total of ∼6.5 million grains of Al 7075-T6 are examined. The calibrated analytical solution agrees well with the brute force Monte Carlo simulation results extracted from the CPFE simulations. Furthermore, the developed formulation can predict the MVD of FIPs for different sample sizes using a size-dependent parameter, and it is capable of accurately extrapolating the MVD of FIPs for much larger microstructure sample sizes than the size used for its calibration.

Crystal plasticity↗
DOE OSTI2022

Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics

X-ray photon correlation spectroscopy (XPCS) allows for the resolution of dynamic processes within a material across a wide range of length and time scales. X-ray speckle visibility spectroscopy (XSVS) is a related method that uses a single diffraction pattern to probe ultrafast dynamics. Interpretation of the XPCS and XSVS data in terms of underlying physical processes is necessary to establish the connection between the macroscopic responses and the microstructural dynamics. To aid the interpretation of the XPCS and XSVS data, we present a computational framework to model these experiments by computing the X-ray scattering intensity directly from the atomic positions obtained from molecular dynamics simulations. We compare the efficiency and accuracy of two alternative computational methods: the direct method computing the intensity at each diffraction vector separately, and a method based on fast Fourier transform that computes the intensities at all diffraction vectors at once. Furthermore, the computed X-ray speckle patterns capture the density fluctuations over a range of length and time scales and are shown to reproduce the known properties and relations of experimental XPCS and XSVS for liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding the Effect of Electrochemical Properties and Microstructure on the Microgalvanic Corrosion of Mg Alloys via Phase-Field Simulations

In this work, we apply a phase-field model to gain insights into the corrosion behavior of Mg alloys. Specifically, we study the effect of electrochemical properties of the materials and their environment and the spatial distribution of second phases in a magnesium alloy. To this end, we perform sensitivity analyses in which we separately vary the exchange current density and corrosion potential of the second phase, as well as the electrolyte conductivity. We describe the effects of these parameters on the corrosion current and the resulting corrosion-front morphology. We also confirm that the ratio between the Wagner length, calculated for the anodic phase, and the initial width of the anodic domain is a good predictor of the morphological characteristic of the corroding surface. In addition, we examine the effect of the microstructure on the corrosion behavior in both 2D and 3D systems by varying the shape, size, and distribution of the second-phase regions. Our findings provide insights into the influence of the two-phase microstructure on the corrosion behavior in a magnesium alloy.

Electrochemistry↗
DOE OSTI2017

Summary report on UO 2 thermal conductivity model refinement and assessment studies

Uranium dioxide (UO 2 ) is the most commonly used fuel in light water nuclear reactors and thermal conductivity controls the removal of heat produced by fission, therefore, governing fuel temperature during normal and accident conditions. The use of fuel performance codes by the industry to predict operational behavior is widespread. A primary source of uncertainty in these codes is thermal conductivity, and optimized fuel utilization may be possible if existing empirical models were replaced with models that incorporate explicit thermal conductivity degradation mechanisms during fuel burn-up. This approach is able to represent the degradation of thermal conductivity due to each individual defect type, rather than the overall burn-up measure typically used which is not an accurate representation of the chemical or microstructure state of the fuel that actually governs thermal conductivity and other properties. To generate a mechanistic thermal conductivity model, molecular dynamics (MD) simulations of UO 2 thermal conductivity including representative uranium and oxygen defects and fission products are carried out. These calculations employ a standard Buckingham type interatomic potential and a potential that combines the many-body embedded atom method potential with Morse-Buckingham pair potentials. Potential parameters for UO 2+x and ZrO 2 are developed for the latter potential. Physical insights from the resonant phonon-spin scattering mechanism due to spins on the magnetic uranium ions have been introduced into the treatment of the MD results, with the corresponding relaxation time derived from existing experimental data. High defect scattering is predicted for Xe atoms compared to that of La and Zr ions. Uranium defects reduce the thermal conductivity more than oxygen defects. For each defect and fission product, scattering parameters are derived for application in both a Callaway model and the corresponding high-temperature model typically used in fuel performance codes. The model is validated by comparison to low-temperature experimental measurements on single crystal hyper-stoichiometric UO 2+x samples and high-temperature literature data. Ongoing works include investigation of the effect of phase separation to UO 2 +U 4 O 9 on the low temperature thermal conductivity of UO 2+x , and modeling of thermal conductivity using the Green-Kubo method. Ultimately, this work will enable more accurate fuel performance simulations as well as extension to new fuel types and operating conditions, all of which improve the fuel economics of nuclear energy and maintain high fuel reliability and safety.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Electrochemically-Driven Phase Transformations in Battery Compounds (Final Technical Report)

Ion-insertion compounds for advanced batteries frequently exhibit phase transformations as the concentration of the working ion varies. Under the large electrochemical driving forces inherent to practical use, systems are often driven far from equilibrium and exhibit phase transition behavior not seen in other materials. An improved understanding of phase transformation pathways in electrode materials upon cycling will lead to new materials design concepts and electrochemical duty cycle management strategies that improve capacity utilization at high charge/discharge rates, reduce voltage and capacity hysteresis, and extend battery life. The main goal of this project is to develop a predictive understanding of the phase transition behavior of battery compounds when electrochemically driven far from equilibrium through a combined experimental- theoretical approach. Research focuses on elucidating how the phase transition behaviors in a diverse group of selected model systems (olivines, lithium metal, etc.) are regulated by various factors including transformation strains, plasticity, metastable transformation pathways, electrode microstructure, surface reaction and ion diffusion kinetics, and what are the unique features of phase transitions in battery compounds. To this end, operando X-ray-based characterization techniques are applied to interrogate the structure and composition evolution of electrode materials and interfaces at nano- and meso-scales. Mesoscale modeling techniques such as phase-field simulation are employed to shed light on the experimental observations and establish a unified framework for describing phase transition behaviors in battery compounds.

25 ENERGY STORAGE↗
DOE OSTI2018

Mechanical Properties and Strain-Induced Martensite Transformation in Cold Rolling of 304L Stainless Steel Plate

In this work, cold rolling behavior of stainless steel 304L is investigated and the effects of different process parameters on the occurrence of strain-induced martensite and mechanical properties are studied. The rolling experiments are conducted under different rolling speeds and reductions in which a set of samples is deformed at room temperature and the other set is first cooled to the temperature of − 10 °C and then rolled. Afterward, the developed microstructures and mechanical properties of the rolled steel are evaluated employing different testing techniques. In order to justify the results, mathematical modeling of cold rolling operation is also performed using Abaqus/Explicit to estimate the distribution of equivalent plastic strain and temperature rise during rolling. The results show that strain-induced martensite may occur during cold rolling and it efficiently alters microstructure and mechanical performance of the rolled plate. The amount of reduction, initial temperature, rolling layout, and, to a lesser extent, rolling speed can affect the kinetics of martensite transformation as well as microstructure and mechanical properties of the rolled steel.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Fission gas bubbles and recrystallization-induced degradation of the effective thermal conductivity in U-7Mo fuels

We have developed a mesoscale model to calculate the degradation of the effective thermal conductivity in irradiated U-Mo alloys caused by the fission-induced gas bubbles and recrystallization. The phase-field approach is employed to generate the grain microstructures of U-7Mo fuels with intra- and inter-granular gas bubbles. Based on the phase-field microstructures, the thermal conductivities of U-7Mo as a function of the fission density can be predicted by the developed mesoscale model. The predicted values of effective thermal conductivities are consistent with available experimental data. Results show that the effective thermal conductivity decreases rapidly with recrystallization compared to the one prior to recrystallization, which can be attributed to the sudden increase of grain boundary densities and corresponding intergranular gas bubbles at high fission densities. Smaller grain size fuel structure has a lower thermal conductivity at the same fission density due to the increased grain boundary density. The current study can provide a better understanding of the fission-induced degradation mechanism of the thermal conductivity in U-Mo fuels.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Effect of intermediate annealing time on microstructure, texture and mechanical properties of Al-Mg-Si-Cu alloy

Highlights: • Long intermediate annealing time could be beneficial to the improvement of deep drawability. • Long intermediate annealing time could give rise to more particles with a larger average size. • As intermediate annealing time increases, strength will change and it has no positive correlation with annealing time, • A particle dissolution model is proposed to illustrate the variation of the strengths with intermediate annealing time. - Abstract: The effect of intermediate annealing time on the microstructure, texture and mechanical properties of Al-Mg-Si-Cu alloys was studied by mechanical properties, microstructure and texture characterization in the present study. The results show that the intermediate annealing time has some influence on the microstructure, recrystallization texture, and final mechanical properties. After the pre-aging treatment and natural aging treatment (T4P treatment), in contrast to the sheet with short intermediate annealing time, the sheet with long intermediate annealing time possesses higher plastic strain ratio r value. Strength has no positive correlation with annealing time, and when applying the annealing time of 16 h, the strength is highest. Before solution treatment, the sheet with long intermediate annealing time has more particles with a larger average size, compared with the sheet with short intermediate annealing time. After solution treatment, they possess the similar recrystallization equiaxed grain structure and recrystallization texture. The sheet with short intermediate annealing time is comprised of Cube{sub ND} {001} <310>, Goss {110}<001> and P {011}<122> orientations, while the sheet with long intermediate annealing time possesses weak texture including Cube{sub ND} {001}<310>, Goss {110}<001> and {015}<751> orientations. Finally, a particle dissolution model during solution treatment is proposed to explain the variation of strength with annealing time.

36 MATERIALS SCIENCE↗