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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Pattern formation in odd viscoelastic fluids

Nonreciprocal interactions fueled by local energy consumption can be found in biological and synthetic active matter at scales where viscoelastic forces are important. Such systems can be described by “odd” viscoelasticity, which assumes fewer material symmetries than traditional theories. Here we study odd viscoelasticity analytically and using lattice Boltzmann simulations. We identify a pattern-forming instability which produces an oscillating array of fluid vortices, and we elucidate which features govern the growth rate, wavelength, and saturation of the vortices. Our observation of pattern formation through odd mechanical response can inform models of biological patterning and guide engineering of odd dynamics in soft active matter systems. Published by the American Physical Society 2024

Floyd, Carlos (ORCID:0000000262707250)↗
DOE OSTI2021

Stiff and strong, lightweight bi-material sandwich plate-lattices with enhanced energy absorption

Plate-based lattices are predicted to reach theoretical Hashin–Shtrikman and Suquet upper bounds on stiffness and strength. However, simultaneously attaining high energy absorption in these plate-lattices still remains elusive, which is critical for many structural applications such as shock wave absorber and protective devices. In this article, we present bi-material isotropic cubic + octet sandwich plate-lattices composed of carbon fiber-reinforced polymer (stiff) skins and elastomeric (soft) core. This bi-material configuration enhances their energy absorption capability while retaining stretching-dominated behavior. We investigate their mechanical properties through an analytical model and finite element simulations. Our results show that they achieve enhanced energy absorption approximately 2–2.8 times higher than their homogeneous counterparts while marginally compromising their stiffness and strength. When compared to previously reported materials, these materials achieve superior strength-energy absorption characteristics, making them an excellent candidate for stiff and strong, lightweight energy absorbing applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

AI to Automate ModEx for Optimal Predictive Improvement and Scientific Discovery

Focal Areas: Data acquisition and assimilation enabled by machine learning, AI, advanced experimental optimization, unsupervised learning, and hardware-related AI efforts; Predictive modeling through AI techniques and AI-derived model components; Using AI to design a hierarchical model prediction system consisting and model selection; and, Interrogating complex data (observed and simulated) using AI, big data analytics, and other advanced methods such as explainable AI and physics- or knowledge-guided AI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AI-Constrained Bottom-Up Ecohydrology and Improved Prediction of Seasonal, Interannual, and Decadal Flood and Drought Risks

Focal Areas: (2) Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system composed of a hierarchy of models (3)Insight gleaned from complex data (both observed & simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Assessing Teleconnections-Induced Predictability of Regional Water Cycle on Seasonal to Decadal Timescales Using Machine Learning Approaches

Focal Area: (3) Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: Predictive understanding of the regional water cycle based on teleconnections of climate modes of variability using AI methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improve wildfire predictability driven by extreme water cycle with interpretable physically-guided ML/AI

Focal Area(s): Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models (Primary); insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics or knowledge-guided AI (Secondary). Science Challenge: Wildfires modify land surface characteristics, such as vegetation composition, soil and litter carbon stocks, and surface albedo, with significant consequences for the regional carbon cycle. For example, tropical regions (i.e., African and South America) are particularly vulnerable to wildfire, account for more than 80% of the global burned area, and emit ~1.4 PgC y -1 into the atmosphere together with other dust and aerosols that strongly affect regional climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Representing the Unrepresented Impact of River Ice on Hydrology, Biogeochemistry, Vegetation, and Geomorphology: A Hybrid Physics-Machine Learning Approach

Focal areas include: Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system composed of a hierarchy of models (e.g., AI driven model/component/parameterization selection). Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Microscopy X-ray imaging enriched with small angle X-ray scattering for few nanometer resolution reveals shock waves and compression in intense short pulse laser irradiation of solids

Understanding how laser pulses compress solids into high-energy-density states requires diagnostics that simultaneously resolve macroscopic geometry and nanometer-scale structure. Here we present a combined X-ray imaging (XRM) and small-angle X-ray scattering (SAXS) approach that bridges this diagnostic gap. Using the Matter in Extreme Conditions end station at LCLS, we irradiated 25 μm copper wires with 45 fs, 0.9 J, 800 nm pulses at 3.5 × 10 19 W/cm 2 while probing with 8.2 keV XFEL pulses. XRM visualizes the evolution of ablation, compression, and inward-propagating fronts with ∼ 200 nm resolution, while SAXS quantifies their nanometer-scale sharpness via the time-resolved evolution of scattering streaks. The joint analysis reveals that an initially smooth compression steepens into a nanometer-sharp shock front after t sh ≈ (18 ± 3) ps, consistent with an analytical steepening model and hydrodynamic simulations. The front reaches a velocity of c sh ≈ 25 k m / s and a lateral width of several tens of microns, demonstrating direct observation of shock formation and decay at solid density for the first time with few-nanometer precision. This integrated XRM–SAXS method establishes a quantitative, multi-scale diagnostic of laser-driven shocks in dense plasmas relevant to inertial confinement fusion, warm dense matter, and planetary physics.

Kluge, Thomas [Helmholtz-Zentrum Dresden-Rossendor↗
DOE OSTI2024

A Platform for Ultra-Fast Proton Probing of Matter in Extreme Conditions

Recent developments in ultrashort and intense laser systems have enabled the generation of short and brilliant proton sources, which are valuable for studying plasmas under extreme conditions in high-energy-density physics. However, developing sensors for the energy selection, focusing, transport, and detection of these sources remains challenging. This work presents a novel and simple design for an isochronous magnetic selector capable of angular and energy selection of proton sources, significantly reducing temporal spread compared to the current state of the art. The isochronous selector separates the beam based on ion energy, making it a potential component in new energy spectrum sensors for ions. Analytical estimations and Monte Carlo simulations validate the proposed configuration. Due to its low temporal spread, this selector is also useful for studying extreme states of matter, such as proton stopping power in warm dense matter, where short plasma stagnation time (<100 ps) is a critical factor. The proposed selector can also be employed at higher proton energies, achieving final time spreads of a few picoseconds. This has important implications for sensing technologies in the study of coherent energy deposition in biology and medical physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Quantifying the Impact of LSST u -band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies

The Vera C. Rubin Observatory will conduct the Legacy Survey of Space and Time (LSST), promising to discover billions of galaxies out to redshift 7, using six photometric bands (ugrizy) spanning the near-ultraviolet to the near-infrared. The exact number of and quality of information about these galaxies will depend on survey depth in these six bands, which in turn depends on the LSST survey strategy, i.e., how often and how long to expose in each band. u-band depth is especially important for photometric redshift (photo-z) estimation and for detection of high-redshift Lyman-break galaxies (LBGs). In this paper, we use a simulated galaxy catalog and an analytic model for the LBG population to study how recent updates and proposed changes to Rubin’s u-band throughput and LSST survey strategy impact photo-z accuracy and LBG detection. We find that proposed variations in u-band strategy have a small impact on photo-z accuracy for z < 1.5 galaxies, but the outlier fraction, scatter, and bias for higher-redshift galaxies vary by up to 50%, depending on the survey strategy considered. The number of u-band dropout LBGs at z ∼ 3 is also highly sensitive to the u-band depth, varying by up to 500%, while the number of griz-band dropouts is only modestly affected. Under the new u-band strategy recommended by the Rubin Survey Cadence Optimization Committee, we predict u-band dropout number densities of 110 deg −2 (3200 deg −2 ) in year 1 (10) of LSST. We discuss the implications of these results for LSST cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Magnetic Field Amplification by a Plasma Cavitation Instability in Relativistic Shock Precursors

Abstract Plasma streaming instabilities play an important role in magnetic field amplification and particle acceleration in relativistic shocks and their environments. However, in the far shock precursor region where accelerated particles constitute a highly relativistic and dilute beam, streaming instabilities typically become inefficient and operate at very small scales when compared to the gyroradii of the beam particles. We report on a plasma cavitation instability that is driven by dilute relativistic beams and can increase both the magnetic field strength and coherence scale by orders of magnitude to reach near-equipartition values with the beam energy density. This instability grows after the development of the Weibel instability and is associated with the asymmetric response of background leptons and ions to the beam current. The resulting net inductive electric field drives a strong energy asymmetry between positively and negatively charged beam species. Large-scale particle-in-cell simulations are used to verify analytical predictions for the growth and saturation level of the instability and indicate that it is robust over a wide range of conditions, including those associated with pair-loaded plasmas. These results can have important implications for the magnetization and structure of shocks in gamma-ray bursts, and more generally for magnetic field amplification and asymmetric scattering of relativistic charged particles in plasma astrophysical environments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1972

Stabilizing a spinning Skylab

The results are presented of a study of the dynamics of a spinning Skylab space station. The stability of motion of several simplified models with flexible appendages was investigated. A digital simulation model that more accurately portrays the complex Skylab vehicle is described, and simulation results are compared with analytically derived results.

Seltzer, S. M.↗
NASA NTRS1972

CSM docked DAP/orbital assembly bending interaction-axial case

A digital autopilot which can provide attitude control for the entire Skylab orbital assembly using the service module reaction control jets is described. An important consideration is the potential interaction of the control system with the bending modes of the orbital assembly. Two aspects of this potential interaction were considered. The first was the possibility that bending induced rotations feeding back through the attitude sensor into the control system could produce an instability or self-sustained oscillation. The second was whether the jet activity commanded by the control system could produce excessive loads at any of the critical load points of the orbital assembly. Both aspects were studied by using analytic techniques and by running simulations on the all-digital simulator.

Turnbull, J. F.↗
NASA NTRS1972

A class of all digital phase locked loops - Modelling and analysis.

An all digital phase locked loop which tracks the phase of the incoming signal once per carrier cycle is proposed. The different elements and their functions, and the phase lock operation are explained in detail. The general digital loop operation is governed by a non-linear difference equation from which a suitable model is developed. The lock range for the general model is derived. The performance of the digital loop for phase step, and frequency step inputs for different levels of quantization without loop filter, are studied. The analytical results are checked by simulating the actual system on the digital computer.

Reddy, C. P.↗