SEARCH · Search NASA

Results for “Intrinsic Plasticity”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

122 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Linking constituent phase properties to ductility and edge stretchability of two DP 980 steels

Two DP 980 steels were characterized with multiple methods to determine its microstructure characteristics, tensile properties and edge stretchability. The first (DP980-B) is a commercial grade DP980 steel produced by AK Steel, while the second (DP980-T) is a modification of the first one by a tempering process. Both contain two individual phases: ferrite and martensite with body centered cubic (BCC) and tetragonal (BCT) crystal structure respectively. ASTM standard tensile tests were performed for both materials, revealing that DP980-B has higher work hardening and larger total elongation than DP980-T. Standard hole piercing and subsequent hole expansion and extrusion tests were also performed. The critical hole expansion ratio (HER) of hole pierced sheet at different nominal clearances, on the other hand, show an opposite trend: the HER of DP980-T almost doubles that of DP980-B. This indicates the tensile ductility and edge stretchability are determined by different mechanisms due to different deformation modes. The ductility of sheet metal during uniaxial tension is determined by deformation instability, i.e. necking, due to less constraint at the region of deformation and fracture will occur quickly after necking. The contribution of post-necking deformation to the total elongation is insignificant for the high strength grades such as DP980 steels. The ductility during hole-expansion, however, is mainly determined by material fracture behavior that is dependent on phase property disparity and material intrinsic fracture parameters. With the individual phase properties for both DP steels determined by in situ tensile tests under high energy X-ray diffraction, the results show that DP980-T steel has lower property disparities between the two phases than DP980-B steel, due to the tempering process. This explains why the DP980-T steel has higher HER than DP980-B steel: lower phase disparity will lead to less local deformation during loading. The higher work hardening rate for DP980-B steel contributes to its higher uniform elongation compared with DP980-T steel based on the maximum load condition of deformation instability. An integrated finite element simulation framework for studying hole expansion is also presented here, based on the calculated individual phase properties from the combined high energy x-ray diffraction (HEXRD) and elastic plastic self-consistent modeling. The simulation results correlate well with the experimental results on the HER difference between the two materials.

36 MATERIALS SCIENCE↗

NASA NTRS2008

Composite Materials for Low-Temperature Applications

Composite materials with improved thermal conductivity and good mechanical strength properties should allow for the design and construction of more thermally efficient components (such as pipes and valves) for use in fluid-processing systems. These materials should have wide application in any number of systems, including ground support equipment (GSE), lunar systems, and flight hardware that need reduced heat transfer. Researchers from the Polymer Science and Technology Laboratory and the Cryogenics Laboratory at Kennedy Space Center were able to develop a new series of composite materials that can meet NASA's needs for lightweight materials/composites for use in fluid systems and also expand the plastic-additive markets. With respect to thermal conductivity and physical properties, these materials are excellent alternatives to prior composite materials and can be used in the aerospace, automotive, military, electronics, food-packaging, and textile markets. One specific application of the polymeric composition is for use in tanks, pipes, valves, structural supports, and components for hot or cold fluid-processing systems where heat flow through materials is a problem to be avoided. These materials can also substitute for metals in cryogenic and other low-temperature applications. These organic/inorganic polymeric composite materials were invented with significant reduction in heat transfer properties. Decreases of 20 to 50 percent in thermal conductivity versus that of the unmodified polymer matrix were measured. These novel composite materials also maintain mechanical properties of the unmodified polymer matrix. These composite materials consist of an inorganic additive combined with a thermoplastic polymer material. The intrinsic, low thermal conductivity of the additive is imparted into the thermoplastic, resulting in a significant reduction in heat transfer over that of the base polymer itself, yet maintaining most of the polymer's original properties. Normal polymer processing techniques can turn these composite materials into unique, custom parts for ground support, Shuttle, and Constellation needs. We fabricated test specimens of the composite and base materials for thermal and mechanical characterization and found that the strength of the composite material at nominal-percentage loading remained relatively unchanged from the base material.

Source record↗

DOE OSTI2021

Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments

Mención Internacional en el título de doctorDeep-learning methods are playing a crucial role in numerous scientific and industrialapplications. Over the past two decades, these techniques have helped in the collection,reconstruction, and analysis of large data samples in particle physics experiments. Themain topic of this PhD research is the study of deep-learning techniques in long-baselineneutrino oscillation experiments. Neutrinos are mysterious light elementary particles,and their investigation is essential to shed light on some of the remaining open questionsin physics. The work presented here describes an algorithm based on a convolutionalneural network developed to provide highly accurate and efficient selections of electronneutrino and muon neutrino interactions in the Deep Underground Neutrino Experiment(DUNE). With this algorithm, the electron neutrino (antineutrino) selection efficiencypeaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between2-5 GeV. The selection efficiency for muon neutrino (antineutrino) interactions is foundto have a maximum of 96% (97%) and exceeds 90% (95%) efficiency for reconstructedneutrino energies above 2 GeV. When considering all electron neutrino and antineutrinointeractions as signal (both those appearing from oscillations and those intrinsic tothe beam), a selection purity of 90% is achieved. These event selections are criticalto maximise the sensitivity of the experiment to CP-violating effects, key to furtherunderstand the matter-antimatter asymmetry of the Universe.In high-energy physics experiments, deep learning has also been explored for producingfast simulations and physically-motivated manipulations of simulated images. Some ofthose simulations, such as the light production and detection, are very computationallyexpensive and require novel methods to produce the necessary samples while controllingthe varied underlying physics model parameters. To do so, we invented the model-assistedgenerative adversarial network (MAGAN), first validated on simple generic case studiesand then successfully applied to the DUNE photon-detector simulation.Moreover, we also developed graph neural networks for 3D-voxel classification ofambiguities and optical crosstalk for a different particle physics experiment, most preciselyfor the proposed SuperFGD. This novel 3D-granular plastic-scintillator neutrino detectorwill be used to upgrade the near detector of the T2K neutrino oscillation experiment, and our method reports efficiencies and purities of 94-96% per event in the classificationof particle track voxels.Due to the growth and complexity of deep neural networks, researchers have beeninvestigating techniques to train those networks in a more computationally-efficient way.Many efforts have been made by the community to optimise deep-learning models byparallelising or distributing their training computation across multiple devices. In thisthesis, we study an approach based on data locality for those neural networks that cannotbenefit from scaling their computation due to a significant bottleneck in the data I/O.The research also includes a detailed study on the performance of deep neural networkson hardware accelerator boards.Los métodos de aprendizaje profundo son cada vez más utilizados en numerosas aplicacionescientíficas e industriales hoy en día. Durante las dos últimas décadas, estastécnicas se han empleado en la recolección, reconstrucción y análisis de la gran cantidadde datos generados por experimentos de física de partículas. El tema principal de estatesis doctoral es el uso de estos modelos de aprendizaje profundo en experimentos defísica de neutrinos, en concreto en los experimentos de larga distancia DUNE y T2K. Losneutrinos, partículas fundamentales neutras, de las más ligeras del Universo, pueden serclave para explicar algunas de las cuestiones todavía sin resolver en física fundamental.Entre las diferentes contribuciones que esta tesis ha hecho a su estudio, cabe destacar eldesarrollo de un algoritmo basado en una red de neuronas convolucional para seleccionarcon gran eficiencia y precisión las interacciones de neutrinos electrónicos y muónicos enel Deep Underground Neutrino Experiment (DUNE). La eficiencia de selección obtenidapara neutrinos (antineutrinos) electrónicos alcanza un máximo del 90% (94%) y supera el85% (90%) para neutrinos con energías reconstruidas en el rango 2-5 GeV. La selección deneutrinos (antineutrinos) muónicos tiene una eficiencia máxima del 96% (97%) y excedeel 90% (95%) para neutrinos con energías reconstruidas de más de 2 GeV. Considerandocomo señal todas las interacciones de neutrinos y antineutrinos electrónicos (procedentestanto de oscilaciones como intrínsecos en el haz inicial), se logra una pureza en la seleccióndel 90%. Dichas selecciones de eventos son fundamentales para maximizar la sensibilidaddel experimento a los efectos de violació...

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Pure- and mixed-gas transport properties of a microporous Tröger's Base polymer (PIM-EA-TB)

Polymers of intrinsic microporosity (PIMs) offer tantalizing combinations of high selectivity and permeability in initial gas permeation measurements. Here, we report characterization of pure- and mixed-gas permeation properties of a thick (~80 μm) PIM consisting of Tröger's Base (TB) and Ethanoanthracene (EA) films. The effects of feed pressure and temperature on pure-gas permeabilities of CH 4 , N 2 , O 2 , H 2 , and CO 2 were investigated. The physical aging behavior of the thick film was tracked via pure-gas O 2 , N 2 , and CH 4 permeability at 35 °C. Gas permeability decreased noticeably and selectivity increased as aging time increased. Particular attention was given to mixed-gas measurements of CO 2 and CH 4 (50/50) permeabilities at 35 °C and fugacities ranging from 2 to 18 atm to explore whether the rigid, bridged, bicyclic TB and EA units could resist CO 2 -induced plasticization. These results are presented along with pure-gas CO 2 and CH 4 results for membrane samples aged at different times. PIM-EA-TB aged for ~24 h did not show signs of plasticization across the fugacity range considered. Furthermore, dual-mode competitive sorption presumably caused the CO 2 /CH 4 mixed-gas selectivity to be slightly higher than its corresponding pure-gas selectivity. However, as aging time increased, aged films underwent progressively more rapid and extensive CO 2 -induced plasticization with increasing fugacity, suggesting a systematic relationship between physical aging and plasticization in PIMs. Consequently, physical aging caused less improvement in mixed-gas CO 2 /CH 4 selectivity than it did in pure-gas selectivity, due mainly to plasticization effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1991

Lightning protection design and testing of an all composite wet wing for the Egrett

The Egrett aircraft has an all composite wing comprising CFC(carbon fiber composite)/Nomex sandwich skins, full length CFC main spar caps, and GFRP (glass fiber reinforced plastics) main and auxiliary spar webs. It also has short inboard CFC auxiliary spar caps. It has fine aluminum wires woven into the surface for protection. It has an integral fuel tank using the CFC/Nomex skins as the upper and lower tank walls, and lies between the forward auxiliary spar and the forward of the two main spar webs. The fuel tank is not bagged, i.e., it is in effect a wet wing tank. It has conventional capacitive type fuel gauging. The aircraft was cleared to IFR standards and so required full lightning protection and demonstration that it would survive the lightning environment. The lightning protection was designed for the wing (and also for the remainder of the aircraft). An inner wing test samples (which included a part of the fuel tank) were tested as part of the proving program. The protection design and the testing process are described. The intrinsic structural features are indicated that improve lightning protection design and which therefore minimize the weight and cost of any added lightning protection components.

Burrows, B. J. C.↗

DOE OSTI2024

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids (Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

Effects of g-Jitter on Diffusion in Binary Liquids

The microgravity environment offers the potential to measure the binary diffusion coefficients in liquids without the masking effects introduced by buoyancy-induced flows due to Earth s gravity. However, the background g-jitter (vibrations from the shuttle, onboard machinery, and crew) normally encountered in many shuttle experiments may alter the benefits of the microgravity environment and introduce vibrations that could offset its intrinsic advantages. An experiment during STS-85 (August 1997) used the Microgravity Vibration Isolation Mount (MIM) to isolate and introduce controlled vibrations to two miscible liquids inside a cavity to study the effects of g-jitter on liquid diffusion. Diffusion in a nonhomogeneous liquid system is caused by a nonequilibrium condition that results in the transport of mass (dispersion of the different kinds of liquid molecules) to approach equilibrium. The dynamic state of the system tends toward equilibrium such that the system becomes homogeneous. An everyday example is the mixing of cream and coffee (a nonhomogeneous system) via stirring. The cream diffuses into the coffee, thus forming a homogeneous system. At equilibrium the system is said to be mixed. However, during stirring, simple observations show complex flow field dynamics-stretching and folding of material interfaces, thinning of striation thickness, self-similar patterns, and so on. This example illustrates that, even though mixing occurs via mass diffusion, stirring to enhance transport plays a major role. Stirring can be induced either by mechanical means (spoon or plastic stirrer) or via buoyancy-induced forces caused by Earth s gravity. Accurate measurements of binary diffusion coefficients are often inhibited by buoyancy-induced flows. The microgravity environment minimizes the effect of buoyancy-induced flows and allows the true diffusion limit to be achieved. One goal of this experiment was to show that the microgravity environment suppresses buoyancy-induced convection, thereby mass diffusion becomes the dominant mechanism for transport. Since g-jitter transmitted by the shuttle to the experiment can potentially excite buoyancy-induced flows, we also studied the effects of controlled vibrations on the system.

Duval, Walter M. B.↗

DOE OSTI2021

Highly Recyclable, Mechanically Isotropic and Healable 3D-Printed Elastomers via Polyurea Vitrimers

Delamination of three-dimensional (3D) printed polymer materials by fused deposition modeling (FDM) is a long-standing challenge in additive manufacturing (AM). With numerous efforts devoted to modification of commercially available thermoplastic FDM filaments, developing printing polymeric materials with new chemical design that could intrinsically improve interlayer adhesion, especially combined with other benefits, is in high demand. Herein, we developed a polyurea vitrimer with heat-driven malleability, which is printed to different 3D geometries using FDM. Significantly improved interlayer adhesion was observed by post-annealing the printed samples close to its topology-freezing transition temperature upon which fast associative dynamic covalent bonds exchange reaction occurs. Isotropic mechanical properties were achieved as demonstrated with printed tensile samples with different infill directions. Finally, the printed materials could be fully recycled for five generations with retained mechanical properties. Furthermore, the mechanical performance of the printed sample could also be repaired after damage.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Coalescence dynamics of prismatic dislocation loops due to vacancy supersaturation

Recovery processes in metals with a high defect concentration are at the heart of a structural alloy's usability in engineering applications. However, such processes take place via nonconservative mechanisms mediated by point defect diffusion and are governed by their interactions with the underlying microstructure. Indeed, one of the main challenges in studying recovery processes is their intrinsic multiscale complexity, which often negates the direct use of experimental techniques. Here, in this Research Letter, we study the mechanism of dislocation loop coalescence in metals by simulating the interaction dynamics between vacancies and prismatic loops using a stochastic framework that seamlessly bridges point defect kinetics with dislocation mechanics. Our simulations reveal two fundamental discoveries: first, that climb processes are governed by local fluctuations that are not captured by continuum elastodiffusion models, and, second, that prismatic loops create internal traps for vacancies, leading to the formation of rings around the perimeter of the loops that affect how coalescence takes place. Our results show an excellent agreement with in situ experimental observations of loop coalescence in Fe under irradiation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Complexes of tubulin oligomers and tau form a viscoelastic intervening network cross-bridging microtubules into bundles

Abstract The axon-initial-segment (AIS) of mature neurons contains microtubule (MT) fascicles (linear bundles) implicated as retrograde diffusion barriers in the retention of MT-associated protein (MAP) tau inside axons. Tau dysfunction and leakage outside of the axon is associated with neurodegeneration. We report on the structure of steady-state MT bundles in varying concentrations of Mg 2+ or Ca 2+ divalent cations in mixtures containing αβ-tubulin, full-length tau, and GTP at 37 °C in a physiological buffer. A concentration-time kinetic phase diagram generated by synchrotron SAXS reveals a wide-spacing MT bundle phase (B ws ), a transient intermediate MT bundle phase (B int ), and a tubulin ring phase. SAXS with TEM of plastic-embedded samples provides evidence of a viscoelastic intervening network (IN) of complexes of tubulin oligomers and tau stabilizing MT bundles. In this model, αβ-tubulin oligomers in the IN are crosslinked by tau’s MT binding repeats, which also link αβ-tubulin oligomers to αβ-tubulin within the MT lattice. The model challenges whether the cross-bridging of MTs is attributed entirely to MAPs. Tubulin-tau complexes in the IN or bound to isolated MTs are potential sites for enzymatic modification of tau, promoting nucleation and growth of tau fibrils in tauopathies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Sulfonyl PIM–1: A diverse separation membrane with dilation resistance

A sulfone modified variant (soPIM–1) of the first polymer of intrinsic microporosity has been studied through molecular simulations to analyze its applicability for adsorption–based separations of diverse nonpolar, quadrupolar, and dipolar adsorbate species. Single component gas phase adsorption isotherms of each adsorbate are provided. Here, the adsorptive properties of soPIM–1 are reported from the application of two methods: (a) traditional grand canonical Monte Carlo (GCMC) simulations and (b) a combination of Monte Carlo and molecular dynamics (GCMC/MD) techniques, which accounts for sorption–induced polymer dynamics. The calculated isosteric heats of adsorption are compared to those from the parent PIM–1 structure and reveals increased CO2 affinity with relatively no change in hydrocarbon affinity. Moreover, to quantify soPIM–1's resistance to dilation the evolution of the microporous structure across the adsorption isotherm loading pressures has been evaluated. Relatedly, nonequilibrium MD simulations have been utilized to determine that soPIM–1 is approximately twice as stiff as PIM–1.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Dielectric-Engineered Monolayer MoS 2 Memtransistors for Brain-Inspired Computing with High Recognition Accuracy

Two-dimensional transition metal dichalcogenides (2D-TMDs)-based memtransistors have emerged as promising candidates for neuromorphic hardware due to their exceptional ability to emulate synaptic behavior. However, many existing 2D-TMDs memtransistors rely on polycrystalline channels with grain boundaries or defects introduced through postgrowth treatments, raising concerns about material integrity and the preservation of intrinsic properties. Here, in this work, we demonstrate a monocrystalline monolayer MoS 2 memtransistor fabricated on a silicon nitride (SiN X ) substrate, achieving a large resistive switching ratio of 10 4 , a dynamic range exceeding 90, along with highly linear and symmetric weight updates, minimal cycle-to-cycle variability, and low device-to-device variability. These attributes are critical for enabling high-performance neuromorphic hardware. Based on experimental data, we further show that these artificial synapses enable a recognition accuracy of more than 97% on the MNIST handwritten digits data set. Our findings present a straightforward approach to realizing 2D-TMDs memtransistors through dielectric engineering, offering a promising platform for next-generation neuromorphic computing systems.

2D TMDs↗

DOE OSTI2024

Demystifying group-4 polyolefin hydrogenolysis catalysis: Gaseous propane hydrogenolysis mechanism over the same catalysts

A kinetic/mechanistic investigation of gaseous propane hydrogenolysis over the single-site heterogeneous polyolefin depolymerization catalysts AlS/ZrNp 2 and AlS/HfNp 2 (AlS = sulfated alumina, Np = neopentyl), is use to probe intrinsic catalyst properties without the complexities introduced by time- and viscosity-dependent polymer medium effects. In a polymer-free automated plug-flow catalytic reactor, propane hydrogenolysis turnover frequencies approach 3,000 h −1 at 150 °C. Both catalysts exhibit approximately linear relationships between rate and [H 2 ] at substoichiometric [H 2 ] with rate law orders of 0.66 ± 0.09 and 0.48 ± 0.07 for Hf and Zr, respectively; at higher [H 2 ], the rates approach zero-order in [H 2 ]. Reaction orders in [C 3 H 8 ] and [catalyst] are essentially zero-order under all conditions, with the former implying rapid, irreversible alkane binding/activation. This rate law, activation parameter, and DFT energy span analysis support a scenario in which [H 2 ] is pivotal in one of two plausible and competing rate-determining transition states—bimolecular metal-alkyl bond hydrogenolysis vs. unimolecular β-alkyl elimination. The Zr and Hf catalyst activation parameters, ΔH ‡ = 16.8 ± 0.2 kcal mol −1 and 18.2 ± 0.6 kcal mol −1 , respectively, track the relative turnover frequencies, while ΔS ‡ = −19.1 ± 0.8 and −16.7 ± 1.4 cal mol −1 K −1 , respectively, imply highly organized transition states. These catalysts maintain activity up to 200 °C, while time-on-stream data indicate multiday activities with an extrapolated turnover number ~92,000 at 150 °C for the Zr catalyst. This methodology is attractive for depolymerization catalyst discovery and process optimization.

03 NATURAL GAS↗

DOE OSTI2026

Energetics of the nucleation and glide of disconnection modes in symmetric tilt grain boundaries

Grain boundaries (GBs) evolve by the nucleation and glide of disconnections, which are dislocations with a step character. In this work, motivated by recent success in predicting GB properties such as the shear coupling factor and mobility from the intrinsic properties of disconnections, we develop a systematic method to calculate the energy barriers for the nucleation and glide of individual disconnection modes under arbitrary driving forces and a quasi-2D setting. This method combines tools from bicrystallography to enumerate disconnection modes and the Nudged elastic band (NEB) method to calculate their energetics, yielding minimum energy paths and atomistic mechanisms for the nucleation and glide of each disconnection mode. We apply the method to accurately predict shear coupling factors of $[001]$ symmetric tilt grain boundaries in Cu. Particular attention is paid to the boundaries where the dislocation-based disconnection nucleation model produces incorrect nucleation barriers. We demonstrate that the method can accurately compute energy barriers and predict shear-coupling factors in the low-temperature regime. For certain disconnection modes in which the assumptions underlying our method do not hold, we report upper bounds on the energy barriers for disconnection nucleation and glide. In addition, the NEB trajectories reveal interesting phenomena such as the dissociation of a higher energy mode into lower energy modes, and in some cases, shear coupling being mediated by partial disconnections, wherein the GB structure temporarily changes to a metastable state before reverting back to its original structure. Graphical abstract

36 MATERIALS SCIENCE↗