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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

An Unipolar Terminal-Attractor Based Neural Associative Memory with Adaptive Threshold and Perfect Convergence

For the first time, a unipolar terminal-attractor based neural associative memory (TABAM)system with adaptive threshold and perfect convergence is presented. By adaptively setting thethreshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors and inner-product approach, we demonstrate via computer simulation the achievement ofperfect convergence and correct retrieval. The simulation is completed with a small number of storedstates (M) and a small number of neurons (N) but a large M/N ratio. An experiment with exclusive-or logic operation using LCTV SLMs is used to show feasibility of the optoelectronic implementationof the models.

Associative↗
NASA NTRS2024

Development and Implementation of Large-Scale Numerical Models for Shape Memory Mars Spring Tires

The current work focuses on implementation of the user-defined shape memory alloy (SMA) model in the finite element analysis program ABAQUS for large-scale simulations of the Spring Tires made of SMA developed at the NASA Glenn Research Center. The main objective of this study was to improve and optimize the structural design of the SMA tires through in-depth numerical analysis and sensitivity studies. Various design variables (wire diam., coil diam., pitch, spring length, and bead angle) were varied to study their influence on the global load-displacement response of the tire construct. A detailed investigation of the three-dimensional stress states was also carried out to enhance understanding of the local changes as the tire goes through global deformation. It was concluded that a robust numerical model with a good predictive capability, together with a thoughtfully crafted sensitivity study, can result in reduced design iterations required to reach a desired tire performance. This will, in turn, lead to significantly reduced manufacturing time, required labor, and testing expense.

shape memory alloys↗
NASA NTRSDate not supplied

Optimized Entanglement Distribution Among Quantum Memories

We evaluate entanglement distribution performance when an optimized quantum memory encoding method is used for two sources, the standard spontaneous parametric down conversion source and the zero added loss multiplexing source. Physical non-idealities are considered.

Entanglement distribution↗
NASA NTRSDate not supplied

Additive Manufacturing and Experimental Characterization of Nickel-Titanium Shape-Memory Alloy Wick Structures and Heat Pipes for Spacecraft Thermal Control

Shape memory alloys (SMA), such as those based on nickel-titanium (NiTi), are increasingly being applied as multifunctional spacecraft components. For thermal management applications, NiTi flow tubing hinges and self-deploying loop heat pipes have been demonstrated. Emerging additive manufacturing (AM) processes are enabling more complex SMA devices than can be formed from conventional plain wire, tubing, and sheet stock materials. This paper presents our progress toward applying powder bed fusion AM to producing porous NiTi wicks and NiTi-H2O heat pipes, which could be embedded in thermally deploying radiators for spacecraft thermal management. AM near-equiatomic NiTi (55.1 wt% Ni) porous wick specimens were produced with a range of deposition parameters. Transient acetone rate-of-rise experiments were performed to estimate wick permeability (K) and average pore radius (r_pore) values and identify parameter sets with high capillary performance. Surface treatments were evaluated to achieve hydrophilic wick structures. Evaluated treatments included chemical oxide growth with H2O2, oxide and sodium titanate growth with NaOH solution, and ultrasonic cleaning with specialty detergents that can remove hydrocarbon contaminants. The most durable hydrophilic surface conditions were obtained with the NaOH treatment. High performing wick deposition parameters were used to produce a full AM NiTi heat pipe, which was treated with NaOH solution to activate the wick. This heat pipe was operated on a test stand in the inverted configuration (upper evaporator and lower condenser), and demonstrated stable nearly isothermal operation for 150 hrs.

Thermal management↗
NASA NTRSDate not supplied

Additive Manufacturing and Experimental Characterization of Nickel-Titanium Shape-Memory Alloy Wick Structures and Heat Pipes for Spacecraft Thermal Control

Shape memory alloys (SMA), such as those based on nickel-titanium (NiTi), are increasingly being applied as multifunctional spacecraft components. For thermal management applications, NiTi flow tubing hinges and self-deploying loop heat pipes have been demonstrated. Emerging additive manufacturing (AM) processes are enabling more complex SMA devices than can be formed from conventional plain wire, tubing, and sheet stock materials. This paper presents our progress toward applying powder bed fusion AM to producing porous NiTi wicks and NiTi-H2O heat pipes, which could be embedded in thermally deploying radiators for spacecraft thermal management. AM near-equiatomic NiTi (55.1 wt% Ni) porous wick specimens were produced with a range of deposition parameters. Transient acetone rate-of-rise experiments were performed to estimate wick permeability (K) and average pore radius (r_pore) values and identify parameter sets with high capillary performance. Surface treatments were evaluated to achieve hydrophilic wick structures. Evaluated treatments included chemical oxide growth with H2O2, oxide and sodium titanate growth with NaOH solution, and ultrasonic cleaning with specialty detergents that can remove hydrocarbon contaminants. The most durable hydrophilic surface conditions were obtained with the NaOH treatment. High performing wick deposition parameters were used to produce a full AM NiTi heat pipe, which was treated with NaOH solution to activate the wick. This heat pipe was operated on a test stand in the inverted configuration (upper evaporator and lower condenser), and demonstrated stable nearly isothermal operation for 150 hrs.

Thermal management↗
NASA NTRSDate not supplied

Segmented Solid Surface Reflector Concentrically Stacked With Tubular Shape Memory Composite Hinges

A new architecture for solid surface reflector antennas scalable to sizes greater than 10 m is presented. The design uses compact, light, and simple advanced deployable structures to create sub-reflectors that can be assembled in space into larger units using a robotic arm. The seven-panel hexagonal sub-reflector is divided into hexagonal panels that stack concentrically and vertically. The central panel is connected to each side panel on the back side by a pair of tubular shape memory composite hinges that enable the required deployment kinematics with controlled dynamics. A secondary mechanism closes the interpanel gap. The focus of the paper is on the development of the sub-reflector elements, namely the tubular hinges that use embedded heaters and sensors for triggering and control, the actuation mechanisms, and the lightweight sandwich construction reflector panels. A parametric study using finite element analyses was conducted to assess how design features of the hinge affect its stowage and deployment dynamics. The preliminary component fabrication and testing results for the two-panel assembly breadboard model are outlined. Finally, the results of the test campaign with the brassboard reflector model are presented. A comparison of deployed reflector surface deviation between the measured surface after the stowage and deployment process and the pre-test scans and the nominal surface revealed root mean square errors of less than 1 mm, as required by X-band radiofrequency transmission.

gravity offloading↗
NASA NTRSDate not supplied

Segmented Hexagonal Antenna Reflector Concentrically Stacked Using Shape Memory Composite Tubular Hinges

A new architecture for solid surface reflector antennas scalable to sizes greater than 10 m is presented. The design uses compact, light, and simple advanced deployable structures to create sub-reflectors that can be assembled in space into larger units using a robotic arm. The seven-panel hexagonal sub-reflector is divided into hexagonal panels that stack concentrically and vertically. The central panel is connected to each side panel on the back side by a pair of tubular shape memory composite hinges that enable the required deployment kinematics with controlled dynamics. A secondary mechanism closes the interpanel gap. The focus of the paper is on the development of the sub-reflector elements, namely the tubular hinges that use embedded heaters and sensors for triggering and control, the actuation mechanisms, and the lightweight sandwich construction reflector panels. A parametric study using finite element analyses was conducted to assess how design features of the hinge affect its stowage and deployment dynamics. The preliminary component fabrication and testing results for the two-panel assembly breadboard model are outlined. Finally, the results of the test campaign with the brassboard reflector model are presented. A comparison of deployed reflector surface deviation between the measured surface after the stowage and deployment process and the pre-test scans and the nominal surface revealed root mean square errors of less than 1 mm, as required by X-band radiofrequency transmission.

gravity offloading methods↗
DOE OSTI2025

Ultra-Fast Non-Volatile Resistive Switching Devices with Over 512 Distinct and Stable Levels for Memory and Neuromorphic Computing

Low-current multilevel programmability with inherent non-volatility and high stability of resistance states is required for both multi-bit memory storage and deep learning accelerators but is difficult to achieve. Here, in a resistive switching system, this work realizes >512 (>9 bits) distinct non-volatile conductance levels with stable retention for each state with current levels down to the nanoampere range, highly promising for potential integration with small processing nodes with ultra-low power consumption requirements. This is achieved by demonstrating a new thin film design concept that encompasses three key features: an ultra-thin epitaxial oxygen ionic switching layer that provides a tunable energy barrier at the bottom electrode, an overcoat amorphous layer that acts as an ion migration barrier for stable state retention, and a partial conductive filament as a localized electronic transport channel to the epitaxial switching layer. A large dynamic resistance range of up to seven orders of magnitude is achieved with reset-free transitions among intermediate states, and programmability is demonstrated with ultra-fast (20 ns) pulses. Artificial neural network (ANN) simulations, based on the experimental performance and its non-idealities, demonstrate close-to-ideal inference accuracies for various Modified National Institute of Standards and Technology (MNIST) data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machine Learning Reveals Memory of the Parent Phases in Ferroelectric Relaxors Ba(Ti$_{1-x}$,Zr x )O 3

Machine learning has been establishing its potential in multiple areas of condensed matter physics and materials science. Here, in this work, an unsupervised machine learning workflow is developed and used within a framework of first-principles-based atomistic simulations to investigate phases, phase transitions, and their structural origins in ferroelectric relaxors, Ba(Ti 1-x ,Zr x )O 3 . The applicability of the workflow is first demonstrated to identify phases and phase transitions in the parent compound, a prototypical ferroelectric BaTiO 3 . Then the workflow is applied for Ba(Ti 1-x ,Zrx)O 3 with x ≤ 0.25 to reveal i) that some of the compounds bear a subtle memory of BaTiO 3 phases beyond the point of the pinched phase transition, which could contribute to their enhanced electromechanical response; ii) the existence of peculiar phases with delocalized precursors of nanodomains—likely candidates for the controversial polar nanoregions; and iii) nanodomain phases for the largest concentrations of x.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

CeO 2 Doping of Hf 0.5 Zr 0.5 O 2 Thin Films for High Endurance Ferroelectric Memories

Ferroelectric switching is demonstrated in CeO 2 -doped Hf 0.5 Zr 0.5 O 2 (HZCO) thin films with application in back-end-of-line compatible embedded memories. At low cerium oxide doping concentrations (2.0–5.6 mol%), the ferroelectric orthorhombic phase is stabilized after annealing at temperatures below 400 °C. HZCO ferroelectrics show reliable switching characteristics beyond 10 11 cycles in TiN/HZCO/TiN capacitors, several orders of magnitude greater than identically processed Hf 0.5 Zr 0.5 O 2 (HZO) capacitors, without sacrificing polarization and retention. Internal photoemission and photoconductivity experiments show that CeO 2 -doping introduces in-gap states in HZCO that are nearly aligned with TiN Fermi level, facilitating electron injection through these states. Furthermore, the enhanced average bulk conduction, which may lead to more uniform thermal dissipation in the HZCO films, delays irreversible degradation via breakdown that leads to device failure after repeated programming cycles.

36 MATERIALS SCIENCE↗
DOE OSTI2023

ReaxFF reactive force field model enables accurate prediction of physiochemical and mechanical properties of crystalline and amorphous shape‐memory polyurethane

Abstract We investigate reactive force field (ReaxFF) prediction of physiochemical and mechanical properties, and stimuli response behavior of a shape‐memory polyurethane (SMPU) rigid segment. We used SMPUs as a platform to link the rigid/hard segment domain crystallinity with properties that can also be experimentally measured. Specifically, we developed models for crystalline and amorphous forms of a common rigid segment of SMPUs, for example, 4,4′‐diphenylmethane diisocyanate (MDI) with n‐butanediol (BDO), denoted as MDI‐BDO. ReaxFF molecular dynamics simulations with equilibrium dynamics are performed by controlling mass, temperature, and pressure or volume to predict the structural and physiochemical properties of crystalline and amorphous rigid segments of SMPU systems, followed by simulating their XRD and FTIR patterns, respectively. Non‐equilibrium ReaxFF simulations are implemented by using uniaxial box deformation technique to study response‐behavior of crystalline SMPU under tensile loading and during stress‐relaxation. The model and simulation scheme presented in this study demonstrates a robust theoretical pathway toward application‐dictated, on‐demand design of high‐performance SMPUs in applications such as soft robotics.

Afroz, Mohammad M.↗
DOE OSTI2024

Connectivity, Pathology, and ApoE4 Interactions Predict Longitudinal Tau Spatial Progression and Memory

ABSTRACT Tau pathology spread into neocortex indicates a transition from healthy aging to Alzheimer's disease (AD). Connectivity between tau epicenters and later accumulating regions of cortex has been proposed as a mechanism of tau spread, but how this relationship changes with greater AD pathology burden or genotype is not understood. We investigated tau accumulation in two key regions, precuneus and inferior temporal cortex, using resting state functional connectivity (rsFC) and longitudinal PET imaging from a multicohort sample of cognitively unimpaired older adults. We examined how baseline tau PET, Aβ PET, and ApoE4 genotype status interact with rsFC between hippocampus and these downstream regions to predict rate of tau accumulation in neocortex. We found that the 3‐way interaction between connectivity, baseline tau, and baseline Aβ or ApoE4 status was associated with neocortical tau accumulation in precuneus and inferior temporal cortex. In addition, baseline tau, Aβ, and ApoE4 status also moderated the association between connectivity and rate of memory decline. Together, these results suggest that the extent and distribution of future tau accumulation may be predicted by the interaction of baseline connectivity, AD pathology, and genetic risk.

Neurosciences & Neurology↗
DOE OSTI2026

Imputation of urban environmental sensor data using gated attention bidirectional long short-term memory (GA-BiLSTM): methods, performance, and implications

Urban environmental monitoring networks frequently encounter significant data gaps due to sensor malfunctions, environmental disturbances, and communication failures. Reliable approaches to address these gaps are essential for ensuring the continuity and quality of environmental data streams. In this study, we developed a gated attention bidirectional long short-term memory (GA-BiLSTM) model to impute missing data in a dense urban monitoring network. Using observations from the CROCUS network in Chicago, we evaluated GA-BiLSTM against widely used approaches (XGBoost and K-nearest neighbors) under scenarios of both short-term intermittent gaps and prolonged outages. GA-BiLSTM consistently outperformed comparative methods, particularly during extended outages of up to ten days, demonstrating its ability to capture spatiotemporal dependencies across sensor nodes. Beyond performance metrics, feature importance and spatial network analyses highlighted the unexpected but critical predictive role of peripheral rural nodes, underlining their strategic value for maintaining robust urban monitoring systems. These results emphasize that advanced imputation methods can substantially improve the reliability of environmental monitoring networks and support more resilient data infrastructures for urban sustainability.

Data imputation↗
DOE OSTI2025

A randomized sketching trust-region secant method for low-memory dynamic optimization

The numerical solution of dynamic optimization problems is often limited by the memory required to store the state trajectory, which is used to evaluate the objective function and its derivatives. Recently, [R. Muthukumar et al., SIAM Journal on Optimization 31(2), pp. 1242–1275 (2021)] introduced a trust-region method for dynamic optimization that employs randomized sketching to compress the state trajectory, resulting in inexact derivative computations. By adaptively learning the sketch rank, the trust-region algorithm achieves rigorous convergence guarantees. Here, we extend this approach to use secant Hessian approximations. Due to the randomness introduced by the sketch, the traditional secant update formulae can produce poor Hessian approximations. In particular, the difference of two gradients, computed from two different sketches, may be inconsistent. To overcome this, we employ a sketched approximation of the Hessian application, in lieu of computing the gradient difference. We numerically demonstrate the improved stability of this approach on an example from PDE-constrained optimization.

dynamic optimization↗
DOE OSTI2023

Caloric Effects Induced by Uniform and Non-uniform Stress in Shape-Memory Materials

A Ginzburg–Landau model is developed that is adequate to describe a square-to-rectangle martensitic transition with associated shape-memory and superelastic properties. Using this model we study caloric effects in the vicinity of the martensitic transition induced by stress and we compare the case of a uniform uniaxial stress and the case of a non-uniform continuous distribution of stresses that produce bending of the material. The former case corresponds to an elastocaloric effect and the latter corresponds to a flexocaloric effect. The aim of the work is to quantitatively compare both cases, which we show must be accomplished in terms of equal amounts of exchanged mechanical work. It is then obtained that the flexocaloric effect is more efficient for low exchanged work but less efficient for large exchanged work.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids

Here, we discuss the implementation of a finite element method, used to numerically solve the Euler equations of compressible flows, using an asynchronous runtime system (RTS). The algorithm is implemented for distributed-memory machines, using stationary unstructured 3D meshes, combining data-, and task-parallelism on top of the Charm++ RTS. Charm++’s execution model is asynchronous by default, allowing arbitrary overlap of computation and communication. Task-parallelism allows scheduling parts of an algorithm independently of, or dependent on, each other. Built-in automatic load balancing enables continuous redistribution of computational load by migration of work units based on real-time CPU load measurement. The RTS also features automatic checkpointing, fault tolerance, resilience against hardware failure, and supports power-, and energy-aware computation. We demonstrate scalability up to 25 x 10 9 cells at $\mathscr{O}$10 4 compute cores and the benefits of automatic load balancing for irregular workloads. The full source code with documentation is available at https://quinoacomputing.org.

42 ENGINEERING↗
DOE OSTI2023

Predictive model for real-time energy disaggregation using long short-term memory

To provide affordable energy-saving solutions for the small and medium-sized manufacturers (SMMs), we propose a unified framework for generating predictive models that support real-time disaggregation of power consumption from combined inputs, enabling automatic machine state identification simultaneously for joint analysis of energy usage patterns. Further, the proposed framework transforms raw power consumption into a time series with look-back and bootstrap capabilities for historical pattern detection, while a learning architecture utilizes the stacked long short-term memory (LSTM) layers as encoders for embedding generation with sequential awareness. Experimental results demonstrate 93.65% minimum accuracy in ideal case of real-time energy usage and machine state prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗