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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bayesian Calibration of Stochastic Agent Based Model via Random Forest

Agent-based models (ABM) provide an excellent framework for modeling outbreaks and interventions in epidemiology by explicitly accounting for diverse individual interactions and environments. However, these models are usually stochastic and highly parametrized, requiring precise calibration for predictive performance. When considering realistic numbers of agents and properly accounting for stochasticity, this high-dimensional calibration can be computationally prohibitive. This paper presents a random forest-based surrogate modeling technique to accelerate the evaluation of ABMs and demonstrates its use to calibrate an epidemiological ABM named CityCOVID via Markov chain Monte Carlo (MCMC). The technique is first outlined in the context of CityCOVID's quantities of interest, namely hospitalizations and deaths, by exploring dimensionality reduction via temporal decomposition with principal component analysis (PCA) and via sensitivity analysis. The calibration problem is then presented, and samples are generated to best match COVID-19 hospitalization and death numbers in Chicago from March to June in 2020. Further, these results are compared with previous approximate Bayesian calibration (IMABC) results, and their predictive performance is analyzed, showing improved performance with a reduction in computation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

The Influence of Charge Correlation and Ion Solvation on the Phase Behavior of Single-Ion Conducting Polymer Blend Electrolytes Using SAXS/SANS

Single-ion conducting polymer blends (SICPBs) have demonstrated exceptional electrochemical performance as solid-state battery electrolytes; however, their nanoscale morphology and thermodynamic behavior remain unexplored. In this work, we investigate blends composed of deuterated poly(ethylene oxide) and poly[lithium sulfonyl(trifluoromethane sulfonyl)imide methacrylate], dPEO/P(LiMTFSI), and report the first experimental study of the nanostructures of charge-neutral polymer blends using small-angle neutron scattering (SANS) and small-angle X-ray scattering (SAXS). Despite the macroscopic miscibility indicated by a single glass-transition temperature, SANS and SAXS results reveal disordered, charge-correlated nanostructures that are strongly influenced by blend composition and temperature. At low concentrations of charge polymer, the scattering is dominated by concentration fluctuations, and the random phase approximation is applied to extract values of the Flory–Huggins interaction parameter, χ SC . At higher charged polymer content, concentration fluctuations are suppressed, and a correlation model is used to characterize the nanostructures of the charge correlations. We find that the structures of the charge correlations are highly dependent on blend composition─consistent with predictions from Sing’s self-consistent field theory-liquid state models. Understanding these features is essential for uncovering the ion transport mechanism that leads to improved electrochemical performance previously reported in SICPB systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Progress toward picosecond on-chip magnetic memory

Here, we offer a perspective on the prospects of ultrafast spintronics and opto-magnetism as a pathway to high-performance, energy-efficient, and non-volatile embedded memory in digital integrated circuit applications. Conventional spintronic devices, such as spin-transfer-torque magnetic-resistive random-access memory (STT-MRAM) and spin–orbit torque MRAM, are promising due to their non-volatility, energy-efficiency, and high endurance. STT-MRAMs are now entering into the commercial market; however, they are limited in write speed to the nanosecond timescale. Improvement in the write speed of spintronic devices can significantly increase their usefulness as viable alternatives to the existing CMOS-based devices. In this article, we discuss recent studies that advance the field of ultrafast spintronics and opto-magnetism. An optimized ferromagnet–ferrimagnet exchange-coupled magnetic stack, which can serve as the free layer of a magnetic tunnel junction (MTJ), can be optically switched in as fast as ~3 ps. Integration of ultrafast magnetic switching of a similar stack into an MTJ device has enabled electrical readout of the switched state using a relatively larger tunneling magnetoresistance ratio. Purely electronic ultrafast spin–orbit torque induced switching of a ferromagnet has been demonstrated using ~6 ps long charge current pulses. We conclude our Perspective by discussing some of the challenges that remain to be addressed to accelerate ultrafast spintronics technologies toward practical implementation in high-performance digital information processing systems.

42 ENGINEERING↗
DOE OSTI2021

Spatially inhomogeneous magnetic superconductors

Here we consider a problem of superconductivity coexistence with the spin-density-wave order in disordered multiband metals. It is assumed that random variations of the disorder potential on short length scales render the interactions between electrons to become spatially correlated. As a consequence, both superconducting and magnetic order parameters become spatially inhomogeneous and are described by the universal phenomenological quantities, whereas all the microscopic details are encoded in the correlation function of the coupling strength fluctuations. We consider a minimal model with two nested two-dimensional Fermi surfaces and disorder potentials which include both intra- and interband scattering. The model is analyzed using the quasiclassical approach to show that short-scale pairing-potential disorder leads to a broadening of the coexistence region.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1992

Nongyrotropy as a source of instability and mode coupling

Nongyrotropic particle populations can bring about linear mode coupling in homogeneous media among the three eigen-modes of parallel propagation in gyrotropic magnetoplasmas. These interactions stimulate, in general, wave activity that does not occur in corresponding (random gyrophase) gyrotropic ambients. Solutions of the dispersion equation illustrate that simple introduction of gyrophase organization can (1) excite electrostatic (and electromagnetic) perturbations in media whose free energy sources are solely electromagnetic, and (3) drive hybrid (both electrostatic and electromagnetic) wave growth in thoroughly stable Maxwellian plasmas.

Brinca, A. L.↗
NASA NTRS1992

JPL activities on development of acousto-optic tunable filter imaging spectrometer

Recent activities of JPL in the development of a new type of imaging spectrometers for earth observation and planetary exploration are reported. This instrument uses the acousto-optic tunable filter (AOTF) as high resolution and fast programmable bandpass filter. AOTF operates in the principle of acousto-optic interaction in an anisotropic medium. This filter can be tuned in sequential, random, and multiwavelength access modes, providing observational flexibility. The diffraction process in the filter generates two diffracted monochromatic beams with polarization orthogonal to each other, creating a unique capability to measure both polarimetric and spectral properties of the incoming light simultaneously with a single instrument. The device gives wide wavelength operations with reasonably large throughput. In addition, it is in a compact solid-state structure without moving parts, providing system reliability. These attractive features give promising opportunities to develop a new generation of airborne/spaceborne and ground, real-time, imaging spectrometer systems for remote sensing applications.

Cheng, Li-Jen↗
NASA NTRS2002

Evaluating the Effectiveness of the 2000-2001 NASA "Why?" Files Program

NASA 'Why?' Files, a research and standards-based, Emmy-award winning series of 60-minute instructional programs for grades 3-5, introduces students to NASA; integrates mathematics, science, and technology by using Problem-Based Learning (PBL), scientific inquiry, and the scientific method; and motivates students to become critical thinkers and active problem solvers. All four 2000-2001 NASA 'Why?' Files programs include an instructional broadcast, a lesson guide, an interactive web site, plus numerous instructional resources. In March 2001, 1,000 randomly selected program registrants participated in a survey. Of these surveys, 185 (154 usable) met the established cut-off date. Respondents reported that (1) they used the four programs in the 2000-2001 NASA 'Why?' Files series; (2) series goals and objectives were met; (3) programs met national mathematics, science, and technology standards; (4) program content was developmentally appropriate for grade level; and (5) programs enhanced/enriched the teaching of mathematics, science, and technology.

Pinelli, Thomas E.↗
DOE OSTI2021

Numerical calculation of the particle–fluid–particle stress in random arrays of fixed particles

Based on the nearest particle statistics [Zhang, J. Fluid Mech. 910, A16 (2021)], the phase interaction force in a multiphase flow is decomposed into a particle–mean-field force and the divergence of the particle–fluid–particle (PFP) stress. The PFP stress is proportional to the correlation product of the distance from a particle to its nearest neighbor and the force on the particle conditionally averaged on the nearest-neighbor location. In this work, a functional form of the stress is obtained corrected to the first order of the ratio between the interparticle distance and the macroscopic length scale of the flow. Particle-resolved numerical simulations are used to calculate the PFP stress in random arrays of fixed particles and to explore the physics represented by the stress. The numerical results show that the PFP stress is attractive along the direction of the flow and is repulsive in the directions perpendicular to the flow. In the flow regime simulated, this PFP stress can be considered as a macroscopic representation of the drafting–kissing–tumbling mechanism. Finally, the Reynolds stress for the fluid phase is also calculated and compared with the PFP stress.

42 ENGINEERING↗
DOE OSTI2020

Accelerating Ab Initio Simulation via Nested Monte Carlo and Machine Learned Reference Potentials

As a corollary of the rapid advances in computing, ab initio simulation is playing an increasingly important role in modeling materials at the atomic scale. Two strategies are possible, ab initio Monte Carlo (AIMC) and molecular dynamics (AIMD) simulation. The former benefits from exact sampling from the correct thermodynamic distribution, while the latter is typically more efficient with its collective all-atom coordinate updates. In this study, using a relatively simple test model comprised of helium and argon, we show that AIMC can be brought up to, and even above, the performance levels of AIMD via a hybrid nested sampling/machine learning (ML) strategy. Here, ML provides an accurate classical reference potential (up to three-body explicit interactions) that can pilot long collective Monte Carlo moves that are accepted or rejected in toto à la nested Monte Carlo (NMC); this is in contrast to the single move nature of a naive implementation. Our proposed method only requires a small up front expense from evaluating the ab initio energies and forces of (100) random configurations for training. Importantly, our method does not totally rely on the trained, assuredly imperfect, interaction. We show that high performance and exact sampling at the desired level of theory can be realized even when the trained interaction has appreciable differences from the ab initio potential. Remarkably, at the highest levels of performance realized via our approach, a pair of statistically uncorrelated atomic configurations can be generated with (1) ab initio calculations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Mixed-Polarity Copolymers Based on Ethylene Oxide and Cyclic Carbonate: Insights into Li-Ion Solvation and Conductivity

Here, this study investigates the relationship between polarity and ionic conductivity in random and block copolymer electrolytes comprising highly flexible oligo(ethylene oxide) methyl ether methacrylate (OEM) and highly polar but glassy glycerol carbonate methacrylate (GCMA) monomers, blended with either lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) or lithium triflate. Interestingly, the high polarity of GCMA did not significantly enhance ionic dissociation, and the random copolymers (POEM-r-PGCMA) showed similar or lower ionic conductivities than the POEM homopolymer. Further analysis revealed that Li + only interacts with OEM and its counterion, not with GCMA. The less-intermixed and weakly phase-separated block copolymer (POEM-b-PGCMA) exhibited even lower conductivities than the random copolymer. Our results suggest that Li + solvation occurs only in the POEM-rich phase and that the larger PGCMA regions, depleted of Li + , disrupt long-range ion transport. These findings provide valuable insights into the design of polymer electrolytes and how segmental mobility and functional groups with contrasting polarities affect ion transport.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sequence-dependent self-assembly of supramolecular nanofibers in periodic dynamic block copolymers

Block copolymers (BCPs) can spontaneously self-assemble into various nanostructured morphologies which enable their diverse applications in selective membranes, polymer electrolytes, and optoelectronics. To expand the range of nanostructures accessible to block copolymers, we designed dynamic block copolymers (DBCPs) that combine the phase separation of traditional block copolymers with the supramolecular self-assembly of periodic dynamic polymers. We demonstrate that DBCPs synthesized with a periodic block sequence self-assemble into high aspect ratio supramolecular nanofibers with well-ordered PEG and PDMS domains, in contrast to those synthesized with a random sequence which do not form nanofibers but have disordered morphologies. The periodicity of the block sequence ensures regular placement of dynamic bonds along the polymer chain, which enables stacking of the hydrogen bonding units into ordered 1D supramolecular nanofibers and delays the onset of terminal flow by up to 60 °C compared to the random block sequence. The hierarchically assembled supramolecular nanofibers display complex mechanical and thermal phase behavior arising from the interplay between phase separation of the dissimilar polymer backbones and supramolecular interactions between dynamic bonds. Despite identical bulk composition, the periodic DBCPs demonstrate ionic conductivity values over two orders of magnitude higher than their random counterparts due to the formation of well-ordered, interconnected, high aspect ratio ion-transporting PEG domains. In conclusion, these results highlight the potential for DBCPs as an emerging material platform to achieve advanced, self-assembled nanostructured morphologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nanocomposites Based on Coil-Comb Diblock Copolymers

The polymer chain architecture is an important factor determining the phase behavior of nanoparticle (NP) assembly in polymer matrices. Block copolymers (BCPs) containing a random copolymer (RCP) block present a convenient variation on traditional BCPs to tune the interaction parameters between the polymer blocks and the nanofillers as well as to evaluate the effect of the chain architecture on the NP arrangements within BCP microdomains. Here, we synthesized BCPs with a coil polystyrene (PS) block and a comb RCP block through reversible addition-fragmentation chain transfer polymerization. The RCP block consists of methyl- and lauryl acrylates, the latter of which confers a long-chain alkyl moiety to favorably interact with alkyl-passivated NPs. BCPs showing lamellar, cylindrical, and mixed morphologies were obtained by varying the volume fractions of the RCP block (f RCP ). In comparison to coil-coil BCP, the coil-comb BCPs show highly asymmetric phase behavior with respect to fRCP, where lamellar morphologies were observed at fRCP from 0.31 to 0.51. NPs in the size of 4-5 nm were successfully incorporated in the RCP block of the BCPs with periodicities of 30-60 nm. An order-to-order phase transition from lamellae to PS cylinders was observed after the addition of only 1-2 vol % 5 nm NPs into the BCP with a periodicity of 25 nm and f RCP of 0.51. Self-consistent field theory-density functional theory simulations qualitatively described the observed morphologies and phase transitions in the nanocomposites. Here, the current study presents a platform to fabricate nanocomposites with NP assemblies in coil-comb BCPs that contain a random copolymer block and provides insight into how polymer chain architectures can affect the phase behavior of BCPs and nanocomposites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

From Anderson localization on random regular graphs to many-body localization

Highlights: • Anderson transition from ergodicity to localization on random regular graphs (RRG). • Analytical, pool method, and exact-diagonalization study of correlations on RRG. • Many-body localization (MBL) to ergodicity transition: quantum dots and spin chains. • Dynamical eigenstate correlation functions in RRG and MBL problems. • Anderson localization on RRG as a toy model for MBL. The article reviews the physics of Anderson localization on random regular graphs (RRG) and its connections to many-body localization (MBL) in disordered interacting systems. Properties of eigenstate and energy level correlations in delocalized and localized phases, as well at criticality, are discussed. In the many-body part, models with short-range and power-law interactions are considered, as well as the quantum-dot model representing the limit of the “most long-range” interaction. Central themes – which are common to the RRG and MBL problems – include ergodicity of the delocalized phase, localized character of the critical point, strong finite-size effects, and fractal scaling of eigenstate correlations in the localized phase.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hybrid-BPR (Bayesian Personalized Ranking with Feature Embeddings and Explicit Negative Sampling) [SWR-26-039]

Hybrid-BPR is a Python library for Bayesian Personalized Ranking (BPR) with two key capabilities that go beyond standard BPR implementations: 1. User and item feature embeddings - incorporate content-based signals (genres, tags, metadata) alongside collaborative filtering. 2. Implicit negative interactions - use observed non-interactions (e.g. viewed-but-not-clicked) as negative training signal instead of random sampling from the full item space. The software is built for recommender systems research with MLflow experiment tracking, parallel hyperparameter sweeps, and standard ranking metrics.

Sandhu, Rimple [National Laboratory of the Rockies↗
DOE OSTI2021

The color of magnetic monopole noise

We relate the anomaly in the noise color of spin ice to the emergent nature of its magnetic monopoles and their random walk. Monopoles are quasi-particles, and the spin vacuum in which they wander is not structureless. Rather, the underlying spin ensemble filters the thermal white noise, leading to non-trivial coevolution. Thus, monopoles can be considered as "dressed" random walkers, activated by a non-trivial stochastic noise that subsumes mutual interactions and the coevolution of their spin vacuum. From this, we suggest that recent experimental results are interpretable in terms of monopole subdiffusion. Furthermore, we then conjecture relations between the color of the noise and other observables, such as relaxation time, monopole density, the dynamic exponent, and the order of the annihilation reaction, which suggests to us the introduction of spin-ice-specific critical exponents in a neighborhood of the ice manifold criticality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1984

Automated mesoscale wind fields derived from GOES satellite imagery

A new multispectral image-processing system for extracting mesoscale wind fields automatically from sequences of GOES imagery is described. This system can produce equivalent or superior cloud-wind estimates compared to the time-consuming manual methods used on various interactive meteorological processing systems. Analysis of automated mesoscale cloud winds yield an estimated random error value of less than 1 m/s and produces both regional and mesoscale vector wind-field structure and divergence patterns that are consistent in time and highly correlated with subsequent severe thunderstorm development. As an example, the system is here applied to SMS II five-minute imagery from April 24, 1975 and the results are compared with manually obtained ones.

Wilson, G. S.↗
NASA NTRS1991

Reliability analysis of composite laminates with load sharing

By viewing a composite lamina as a homogeneous solid whose directional strengths are random variables, lamina reliability under multiaxial stresses may be determined using either an interactive or a noninteractive criterion. From the reliability values for the individual laminae comprising a given laminate, Thomas and Wetherhold (1991) have proposed a method for determining bounds for the overall laminate reliability. In this paper, simple physically plausible phenomenological rules are proposed for redistribution of load after a lamina has failed within the confines of a laminate. These rules are illustrated by application to (0/ +/-15)s and (90/ +/-45/0)s graphite/epoxy laminates, and the results are compared to the previously proposed bounds.

Wetherhold, Robert C.↗
NASA NTRS1998

Improved Modeling of Finite-Rate Turbulent Combustion Processes in Research Combustors

The objective of this thesis is to further develop and test a stochastic model of turbulent combustion in recirculating flows. There is a requirement to increase the accuracy of multi-dimensional combustion predictions. As turbulence affects reaction rates, this interaction must be more accurately evaluated. In this work a more physically correct way of handling the interaction of turbulence on combustion is further developed and tested. As turbulence involves randomness, stochastic modeling is used. Averaged values such as temperature and species concentration are found by integrating the probability density function (pdf) over the range of the scalar. The model in this work does not assume the pdf type, but solves for the evolution of the pdf using the Monte Carlo solution technique. The model is further developed by including a more robust reaction solver, by using accurate thermodynamics and by more accurate transport elements. The stochastic method is used with Semi-Implicit Method for Pressure-Linked Equations. The SIMPLE method is used to solve for velocity, pressure, turbulent kinetic energy and dissipation. The pdf solver solves for temperature and species concentration. Thus, the method is partially familiar to combustor engineers. The method is compared to benchmark experimental data and baseline calculations. The baseline method was tested on isothermal flows, evaporating sprays and combusting sprays. Pdf and baseline predictions were performed for three diffusion flames and one premixed flame. The pdf method predicted lower combustion rates than the baseline method in agreement with the data, except for the premixed flame. The baseline and stochastic predictions bounded the experimental data for the premixed flame. The use of a continuous mixing model or relax to mean mixing model had little effect on the prediction of average temperature. Two grids were used in a hydrogen diffusion flame simulation. Grid density did not effect the predictions except for peak temperature and tangential velocity. The hybrid pdf method did take longer and required more memory, but has a theoretical basis to extend to many reaction steps which cannot be said of current turbulent combustion models.

VanOverbeke, Thomas J.↗