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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 613 records · Page 34

Machine learning based inverse modeling of full-field strain distribution for mechanical characterization of a linear elastic and heterogeneous membrane

Heterogeneous membranes or films are thin and soft structures with spatial variations in material property and thickness. Mechanical behavior of heterogeneous membranes is not well understood, mainly due to the difficulty in obtaining accurate and reliable material property data. To understand the mechanical behavior of these materials, accurate and efficient characterization methods for heterogeneous membranes are needed. Here, in this paper, an inverse method based on machine learning is developed to efficiently extract mechanical properties from full-field strain distributions. This approach is demonstrated on a flat heterogeneous membrane with uniform thickness formed by up to four linear elastic synthetic materials in a grid arrangement, and deforming in a moderate strain range (true strain ~10%). The results show that the machine learning method achieves accuracy comparable to the traditional inverse finite element method, and is 6 orders of magnitude faster in the demonstrated case studies.

36 MATERIALS SCIENCE↗

Neural Network Enhanced RKPM for Electrochemical-Mechanical Coupled Damage Modeling of Energy Storage Materials

Energy storage materials undergo significant charge cycling, which makes understanding their reliability and durability fundamental in predicting performance and service life. Strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking, largely along material interfaces and grain boundaries. For Li-ion batteries, for example, lithium moving between electrodes during charging and discharging process causes expansion and contraction of grains, and the strongly anisotropic and nonlinearly [Li]-dependent grain material properties can cause grains to expand into and contract away from each other, leading to chemo-mechanical cracking. In the first part of this work, a RKPM based computational framework for solving the coupled solid-phase lithium conservation with Fickian diffusion and the lithium concentration dependent anisotropic mechanical problem subjected to a highly nonlinear Butler-Volmer boundary condition is introduced. The choice of RKPM completeness conditions for lithium concentration and mechanical deformation fields, and the variational consistency condition for the domain integration of the coupled problem is first determined. In the second part of this work, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1] is leveraged to accurately capture damage and crack propagation throughout the material, by learning the location, orientation, and sharpness of discontinuity while allowing for a coarser nodal distribution than that is necessary for capturing sharp solution transitions using traditional mesh-based methods. NN-RKPM is used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure.

damage modeling↗

Effect of solution concentration on ethylene propylene diene monomer (EPDM) nonmetallic components used in caustic liquid waste transfer lines

The hose-in-hose transfer lines (HIHTL) used to transfer waste at the United States Department of Energy’s Hanford Site Tank Farm are fabricated from an ethylene propylene diene monomer (EPDM) synthetic rubber. During waste transport, these hoses are exposed to several stressors including caustic solutions at high temperatures and high pressures, as well as β and γ radiation. The aging behavior of HIHTL and dog-bone shaped EPDM specimens were evaluated by exposure to solutions at 77 °C containing 0.00, 6.25, 12.50, and 25.00 % (v/v) sodium hydroxide (NaOH) for 12-months. After the exposure, the material properties of the specimens were measured and compared to the unaged samples. The material properties evaluated included the tensile strength of the EPDM dog-bone samples and the burst pressure of the HIHTL. Both the tensile strength of the EPDM dog-bone samples and the burst pressure of the HIHTL specimens exposed to the 6.25 % NaOH solution exhibited the most significant deterioration and those exposed to 25.00 % NaOH solution had the least deterioration. Finally, examination of the HIHTL and the EPDM dog-bone specimens with scanning electron microscopy showed that the deterioration for the specimens exposed to 6.25 % NaOH solution were the most severe and the samples exposed to 25.00 % NaOH solution had the least deterioration.

42 ENGINEERING↗

Prediction of initiation of low and high explosive fillers due to fragment or projectile impact

A methodology is presented which provides predictions for the probability of initiation of explosion in high explosive filled warheads and in propellant filled rocket motor cases given the impact of compact fragments or of small projectiles. Equations of velocities at which 50 percent of the explosive filled cases will initiate either high or low order are developed for compact fragments, and for projectiles. These data are used to establish the standard deviation of the data from the 50 percent initiation line. Standard deviation is used to provide predictions of the probability of initiation given the impact velocity and other pertinent parameters using equations and logic which are established in a computer model. This computer model uses fragment material properties and encounter parameters to predict fragment impact initiation, and projectile and casing material properties and encounter parameters to predict projectile impact initiation.

Zabel, P. H.↗

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↗

Properties of materials in high pressure hydrogen at room and elevated temperatures

Experimental efforts in this program for this period. Mechanical property tests of wrought and cast nickel-base alloys and one wrought cobalt-base alloy were conducted in 34.5 MN/sq m (5000-psig) helium and hydrogen or hydrogen mixtures. Comparison of test results was made to determine degradation of properties due to the hydrogen environments. All testing was conducted on solid specimens exposed to external gaseous pressure. Specific mechanical properties determined and the testing methods used are summarized.

Harris, J. A., Jr.↗

Properties of materials in high pressure hydrogen at cryogenic, room, and elevated temperatures

Various tests were conducted to determine the mechanical properties of 12 alloys that are commonly used or proposed for use in pressurized gaseous hydrogen or hydrogen containing environments. Properties determined in the hydrogen environments were compared to properties determined in a pure helium environment at the same conditions to establish environmental degradation. The specific mechanical properties tested include: high-cycle fatigue, low-cycle fatigue, fracture mechanics, creep-rupture, and tensile.

Harris, J. A., Jr.↗

Learning robust parameter inference and density reconstruction in flyer plate impact experiments

Estimating physical parameters or material properties from experimental observations is a common objective in many areas of physics and material science. In many experiments, especially in shock physics, radiography is the primary means of observing the system of interest. However, radiography does not provide direct access to key state variables, such as density, which prevents the application of traditional parameter estimation approaches. Here we focus on flyer plate impact experiments on porous materials, and resolving the underlying parameterized equation of state (EoS) and crush porosity model parameters given radiographic observation(s). We use machine learning as a tool to demonstrate with high confidence that using only high impact velocity data does not provide sufficient information to accurately infer both EoS and crush model parameters, even with fully resolved density fields or a dynamic sequence of images. We thus propose an observable data set consisting of low and high impact velocity experiments/simulations that capture different regimes of compaction and shock propagation, and proceed to introduce a generative machine learning approach which produces a posterior distribution of physical parameters directly from radiographs. We demonstrate the effectiveness of the approach in estimating parameters from simulated flyer plate impact experiments, and show that the obtained estimates of EoS and crush model parameters can then be used in hydrodynamic simulations to obtain accurate and physically admissible density reconstructions. Finally, we examine the robustness of the approach to model mismatches, and find that the learned approach can provide useful parameter estimates in the presence of out-of-distribution radiographic noise and previously unseen physics, thereby promoting a potential breakthrough in estimating material properties from experimental radiographic images.

97 MATHEMATICS AND COMPUTING↗

Optimal design of acoustic metamaterial cloaks under uncertainty

In this work, we consider the problem of optimal design of an acoustic cloak under uncertainty and develop scalable approximation and optimization methods to solve this problem. The design variable is taken as an infinite-dimensional spatially-varying field that represents the material property, while an additive infinite-dimensional random field represents the variability of the material property or the manufacturing error. Discretization of this optimal design problem results in high-dimensional design variables and uncertain parameters. To solve this problem, we develop a computational approach based on a Taylor approximation and an approximate Newton method for optimization, which is based on a Hessian derived at the mean of the random field. We show our approach is scalable with respect to the dimension of both the design variables and uncertain parameters, in the sense that the necessary number of acoustic wave propagations is essentially independent of these dimensions, for numerical experiments with up to one million design variables and half a million uncertain parameters. Additionally, we demonstrate that, using our computational approach, an optimal design of the acoustic cloak that is robust to material uncertainty is achieved in a tractable manner. The optimal design under uncertainty problem is posed and solved for the classical circular obstacle surrounded by a ring-shaped cloaking region, subjected to both a single-direction single-frequency incident wave and multiple-direction multiple-frequency incident waves. Finally, we apply the method to a deterministic large-scale optimal cloaking problem with complex geometry, to demonstrate that the approximate Newton method’s Hessian computation is viable for large, complex problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Radar determination of Mars surface properties

Radar studies of Mars have provided measurements of surface texture on scales of centimeters to hundreds of meters and measurements of surface material properties. Texture (rms surface tilts and estimates of small-scale roughness) may be inferred from dispersion and/or polarization of the radar echo; material properties (reflectivity of dielectric constant) are derived from echo strength. Mars is a diverse target; depending on location, rms surface tilts have been found to vary over the range 0.25 to 10 deg while reflectivity covers at least 3 to 13 percent. Plains units are the most variable, having both the smoothest and roughest surfaces, cratered terrain can be considered predictable and 'average' by comparison. Recent data identify scattering by small structures (perhaps rocks on or near the surface) as playing a more important role than previously recognized. Scattering by the residual ice cap near Mars' south pole is particularly unusual. The present state of radar surface studies is summarized.

Simpson, Richard A.↗

Material Extrusion Additive Manufacturing of Wood and Lignocellulosic Filled Composites

Wood and lignocellulosic-based material components are explored in this review as functional additives and reinforcements in composites for extrusion-based additive manufacturing (AM) or 3D printing. The motivation for using these sustainable alternatives in 3D printing includes enhancing material properties of the resulting printed parts, while providing a green alternative to carbon or glass filled polymer matrices, all at reduced material costs. Previous review articles on this topic have focused only on introducing the use of natural fillers with material extrusion AM and discussion of their subsequent material properties. This review not only discusses the present state of materials extrusion AM using natural filler-based composites but will also fill in the knowledge gap regarding state-of-the-art applications of these materials. Emphasis will also be placed on addressing the challenges associated with 3D printing using these materials, including use with large-scale manufacturing, while providing insight to overcome these issues in the future.

36 MATERIALS SCIENCE↗

Dehydration kinetics of nanoconfined water in beryl probed by high temperature single crystal synchrotron X-ray diffraction

Understanding changes in material properties through external stimuli plays a key role in validating the expected performance of materials and engineering material properties in a controlled manner. Here, we introduce a fundamental protocol to deduce dehydration reactions kinetics of water confined in nanopore channels, with the cyclosilicate beryl as the scaffold of interest, using time-resolved synchrotron X-ray diffraction (SXRD), in the temperature interval of 298–1038 K. The temperature-dependent intensity (I) of the strongest reflection (112) was used as the crystallite variable. An estimation of an isobaric thermal crystallite coefficient, k, analogous with the isobaric thermal expansion coefficient, established the rate of relative crystallization as a function of temperature, $\frac{∂I}{∂T}$. A plot of lnk and $\frac{1}{T}$ gives rise to two kinetic steps, indicating a slow dehydration stage up to ~ 700 K and a fast dehydration stage up to the investigated temperature 1038 K. The crystal structure of beryl determined up to 1038 K, in temperature increment as small as 10 K, indicates the presence of channel ions Na and Fe and a gradual decrease of water upon heating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fracture Mechanics Analysis of LH2 Feed Line Flow Liners

Inspections of the Space Shuttle Main Engine revealed fatigue cracks growing from slots in the flow liner of the liquid hydrogen (LH2) feed lines. During flight, the flow liners experience complex loading induced by flow of LH2 and the resonance characteristics of the structure. The flow liners are made of Inconel 718 and had previously not been considered a fracture critical component. However, fatigue failure of a flow liner could have catastrophic effect on the Shuttle engines. A fracture mechanics study was performed to determine if a damage tolerance approach to life management was possible and to determine the sensitivity to the load spectra, material properties, and crack size. The load spectra were derived separately from ground tests and material properties were obtained from coupon tests. The stress-intensity factors for the fatigue cracks were determined from a shell-dynamics approach that simulated the dominant resonant frequencies. Life predictions were obtained using the NASGRO life prediction code. The results indicated that adequate life could not be demonstrated for initial crack lengths of the size that could be detected by traditional NDE techniques.

James, Mark A.↗

Tuning the Morphology and Electronic Properties of Single-Crystal LiNi 0.5 Mn 1.5 O 4-δ : Exploring the Influence of LiCl–KCl Molten Salt Flux Composition and Synthesis Temperature

Single-crystal materials have played a unique role in the development of high-performance cathode materials for Li batteries due to their favorable chemomechanical stability. The molten salt synthesis method has become one of the most prominent techniques used to synthesize single-crystal layered and spinel materials. In this work, the molten salt synthesis method is used as a technique to tune both the morphology and Mn 3+ content of high-voltage LiNi 0.5 Mn 1.5 O 4 (LNMO) cathodes. The resulting materials are thoroughly characterized by a suite of analytical techniques, including synchrotron X-ray core-level spectroscopy, which are sensitive to the material properties on multiple length scales. Furthermore, the multidimensional characterization allows us to build a materials library according to the molten salt phase diagram as well as to establish the relationship among synthesis, material properties, and battery performance. The results of this work show that the Mn 3+ content is primarily dependent on the synthesis temperature and increases as the temperature is increased. Additionally, the particle morphology is mostly dependent on the composition of the molten salt flux, which can be tailored to obtain well-defined octahedrons enclosed by (111) facets, plates with predominant ($11\tilde{2}$) facets, irregularly shaped particles, or mixtures of these. The electrochemical measurements indicate that the Mn 3+ content has a larger contribution to the battery performance of LNMO than do morphological characteristics and that a significant amount of Mn 3+ could become detrimental to the battery performance. However, with similar Mn 3+ contents, morphology still plays a role in influencing the battery cycle life and rate performance. The insights of molten salt synthesis parameters on the formation of LNMO, with deconvolution of the roles of Mn 3+ and morphology, are crucial to continuing studies in the rational design of LNMO cathode materials for high-energy Li batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design and evaluation of an electromagnetic beam waveguide for measuring electrical properties of materials

A beam waveguide was designed that is based upon the propagation characteristics of the fundamental Gaussian beam and the focusing properties of spherical dielectric lenses. The 20-GHz, two-horn, four-lens system was constructed and experimentally evaluated by probing the field in a plane perpendicular to the beam axis at the center of the beam waveguide system. The critical parameters were determined by numerical sensitivity studies, and the lens-horn critical spacing was adjusted to better focus the beam at the probe plane. The measured performance was analyzed by consideration of higher order Gaussian-Laguerre beam modes. The beam waveguide system was successfully used in the measurements of the electromagnetic transmission properties of Shuttle thermal-protection tiles while the tile surface was being heated to reentry-level temperatures with a high-power laser.

Bailey, M. C.↗

JOINT APPOINTEE: Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries

Combinatorial spread libraries offer a innovative approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated Piezoresponse Force Microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling over macroscopic samples. The concentration dependence of pertinent ferroelectric parameters has been determined and used to develop the mathematical framework based on Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in the high-throughput materials discovery. We make the data sets open to the community and hope that this will stimulate other efforts to interpret and understand the physics of these systems.

Automated Microscopy, Combinatorial Library, Ferro↗

BISON microstructure-based pulverization criterion in high burnup structure

To improve the economics of commercial nuclear power production, utilities are seeking to increase the allowable burnup limit of UO$_2$ fuel. One of the main factors that contributes to the current burnup limit of 62 GWd/MTU in commercial light water reactors (LWRs) is the risk of fine fragmentation or pulverization during a loss of coolant accident (LOCA). Pulverization primarily occurs at high burnups, especially when the high burnup structure (HBS) has formed. To allow the industry to pursue increased burnup and develop mitigation strategies, it is essential to have improved capability to predict the onset of pulverization. However, the mechanism of pulverization is not well understood, and the existing predictive capabilities implemented in the BISON fuel performance code are empirical in nature. In this report, mesoscale simulations are used to improve understanding of the formation mechanism of the HBS and how it responds during a LOCA transient, and inform development of a BISON pulverization criterion. A phase-field model was used to simulate the evolution of bubble pressure as a result of HBS formation. The simulations showed that gas atoms diffuse from grain interiors to the new grain boundaries created during HBS formation, and diffuse rapidly along these grain boundaries to reach existing bubbles. This causes an increase in bubble pressure in existing bubbles, leading to bubble growth during steady-state operation. To simulate the response of HBS bubbles to a LOCA transient, a newly developed phase-field model was used; in agreement with preliminary results from FY20, bubble size did not change significantly during the duration of the transient. A phase-field fracture model was used to study fragmentation patterns in the HBS, including using input from the phase-field model as initial conditions. Phase-field fracture simulations were used to determine a pulverization criterion for BISON. A function for the critical pressure for pulverization to occur was fit to data from the phase-field fracture simulations, and this function was implemented as a material property in BISON. For comparison, an analytical criterion for pulverization was developed and implemented within the same material property.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗