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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 37 records · Page 2

Multiple-time scales analysis of physiological time series under neural control

We discuss multiple-time scale properties of neurophysiological control mechanisms, using heart rate and gait regulation as model systems. We find that scaling exponents can be used as prognostic indicators. Furthermore, detection of more subtle degradation of scaling properties may provide a novel early warning system in subjects with a variety of pathologies including those at high risk of sudden death.

Non-NASA Center↗

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗

A Scaling Analysis of Post-Detonation Mixing With Detailed Chemical Kinetics

This report documents a scaling study of hemispherical pentaerythritol tetranitrate explosives detonated in ambient air. The focus is on the mixing layer and evolution of the chemical species. The HyBurn code developed at the University of Florida is used to simulate center initiated 12, 38, 120, and 1200 mm diameter charges. The results show blast structures commonly found in the literature. Azimuthal averaging is used to radially average the flow variables to get mean values. The charges exhibit self-similar behavior at early times in a primarily gas dynamic regime, but discrepancies between the scales form at later times due to the finite rate chemistry. The turbulent mixing layer is calculated and used to define a region to conditionally average by mixture fraction. The results of the conditional averages imply a transition from a kinetic-limited regime to a mixing-limited regime with increasing scale. The scaling of the total heat release rate confirms an early time gas dynamic regime, and a later time regime where mixing and chemistry becomes impactful.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time scale analysis of a closed-loop discrete optimal control system

A two-time scale discrete control system is considered. The closed-loop optimal linear quadratic (LQ) regulator for the system requires the solution of a full-order algebraic matrix Riccati equation. Alternatively, the original system is decomposed into reduced-order slow and fast subsystems. The closed-loop optimal control of the subsystems requires the solution of two algebraic matrix Riccati equations of order lower than that required for the full-order system. A composite, closed-loop suboptimal control is created from the sum of the slow and fast feedback optimal controls. Numerical results obtained for an aircraft model show a very close agreement between the exact (optimal) solutions and computationally simpler composite (suboptimal) solutions. The main advantage of the method is the considerable reduction in the overall computational requirements for the closed-loop optimal control of digital flight systems.

Naidu, D. S.↗

A Multi-scaled Analysis of Forest Structure using Individual-Based Modeling in a Costa Rican Rainforest

Consideration of scale is essential when examining structural relationships in forests. In this study, we present a parameterization of the FORMIND individual-based forest model for old growth Atlantic lowland rainforest in La Selva, Costa Rica. Results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest within 2.3% of aboveground biomass values, based on comparisons with CARBONO inventory plot data. The Costa Rica FORMIND simulation was then used to investigate the relationship between canopy height and aboveground biomass (AGB), leaf area index (LAI) and gross primary productivity (GPP) at different spatial scales (20 × 20 m, 60 × 60 m, 100mx100m). The relationship between aboveground biomass and height is of particular importance toward the calibration of various remote sensing products including lidar and radar, whereas the LAI and GPP relationships are understudied in this context. We found that the relationship between all three variables and height varies considerably: the relationship is stronger at finer scales and weaker at coarser resolution. However, in all three comparisons, RMSE also decreased as scales coarsened, with the largest difference shown between 100 m and 10 m resolutions in relating AGB to Lorey's height (R^2 decreased by 0.3; RMSE decreased by 114.5 Mg/ha). This suggests that a trade-off between accuracy and precision exists, and further highlights the importance of spatial scale in determining the relatability of forest structure variables.

A.H.Armstrong↗

Structural Requirements and Scaling Analysis of a Fluidic Mirror Space Telescope Support Structure

The NASA FLUTE project proposes large-scale (50m) fluidic telescopes for astronomy applications. To continue to explore the universe, astronomers require larger and larger telescope apertures. The highest priority astrophysics targets such as exoplanets and early galaxies are extremely faint, motivating larger telescope apertures. However, mission costs depend on aperture diameter, and scaling apertures beyond 10-m apertures faces economic and technological viability challenges. An unsegmented primary mirror made in space via fluidic microgravity shaping would provide a scalable and cost-effective method to scale apertures to 50-m scale while achieving sub-nanometer (root mean square) surface quality. Such microgravity fluidic shaping has been demonstrated in laboratory neutral buoyance environments, parabolic microgravity experiments, as well aboard the International Space Station. One of the main components of a fluidic observatory is the mirror frame. The frame must provide a stable bounding circular ring which the edges of the fluid mirror surface can wet. The frame can optionally provide a ‘floor’ surface on the interior of the ring to provide additional fluid support and reduce required fluid volume. In this work, we evaluate several classes of structural frame architectures potentially suitable for a fluidic telescope support structure. We start by estimating stability requirements, orbital, station keeping, and slew loads based on a notional CONOPS. The scaling of overall fluid mass required for each architecture is evaluated. Preliminary results elucidate the importance of a support floor for overall mission viability above 10-m diameter. We then investigate the scaling of a tetrahedral truss frame support structure. We show that segmented solid shell support surfaces can provide sufficient stability at modest mass fractions. We estimate that the total fluid and frame mass for a 50-m telescope could be on the order of 15,000 kg. Finally, implementation considerations are discussed, including deployment/assembly methodologies. The results of this study establish feasibility of a large-scale fluidic telescope and will guide further architecture development and detailed structural design.

Christine Gregg↗

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual’s response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

59 BASIC BIOLOGICAL SCIENCES↗

A continental scale analysis reveals widespread root bimodality

An improved understanding of root vertical distribution is crucial for assessing plant-soil-atmosphere interactions and their influence on the land carbon sink. Here, we analyze a continental-scale dataset of fine roots reaching 2 meters depth, spanning from Alaskan tundra to Puerto Rican forests. Contrary to the expectation that fine root abundance decays exponentially with depth, we found root bimodality at ~20% of 44 sites, with secondary biomass peaks often below 1m. Root bimodality was more likely in areas with low total fine root biomass and was more frequent in shrublands than grasslands. Notably, secondary peaks coincided with high soil nitrogen content at depth. Our analyses suggest that deep soil nutrients tend to be underexploited, while root bimodality offers plants a mechanism to tap into deep soil resources. Our findings add to the growing recognition that deep soil dynamics are systematically overlooked, and calls for more research attention to this deep frontier in the face of global environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

Instability of non-zonal baroclinic flows - Multiple-scale analysis

The linear instability of a non-zonal flow can be reduced to an eigenvalue-eigenfunction problem, governed by a nonseparable partial differential equation (Niehaus, 1980). Approximate solutions, found by the method of multiple scales, are derived here and compared with earlier results found using a spectral method. The amplitude maxima are correctly located. The zonal variations of local wavenumber and of amplitude are qualitatively correct, but not sufficiently extreme. Because the method is oversensitive to local conditions, and less sensitive to global constraints, this comparison provides theoretical limits to the possibility of parameterizing transient eddies in terms of the local time mean state of the atmosphere. The method can be extended easily to flows with more realistic vertical structure.

Niehaus, M. C. W.↗

Influence of non steady gravity on natural convection during micro-gravity solidification of semiconductors. I - Time scale analysis. II - Implications for crystal growth experiments

Consideration is given to the influence of temporal variations in the magnitude of gravity on natural convection during unidirectional solidification of semiconductors. It is shown that the response time to step changes in g at low Rayleigh numbers is controlled by the momentum diffusive time scale. At higher Rayleigh numbers, the response time to increases in g is reduced because of inertial effects. The degree of perturbation of flow fields by transients in the gravitational acceleration on the Space Shuttle and the Space Station is determined. The analysis is used to derive the requirements for crystal growth experiments conducted on low duration low-g vehicles. Also, the effectiveness of sounding rockets and KC-135 aircraft for microgravity experiments is examined.

Griffin, P. R.↗

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

Validation of the DESI-DR1 3x2-pt analysis: scale cut and shear ratio tests

Combined survey analyses of galaxy clustering and weak gravitational lensing (3x2-pt studies) will allow new and accurate tests of the standard cosmological model. However, careful validation is necessary to ensure that these cosmological constraints are not biased by uncertainties associated with the modelling of astrophysical or systematic effects. In this study we validate the combined 3x2-pt analysis of the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) spectroscopic galaxy clustering and overlapping weak lensing datasets from the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper-Suprime-Cam Survey (HSC). By propagating the modelling uncertainties associated with the non-linear matter power spectrum, non-linear galaxy bias and baryon feedback, we design scale cuts to ensure that measurements of the matter density and the amplitude of the matter power spectrum are biased by less than 30% of the statistical error. We also test the internal consistency of the data and weak lensing systematics by performing new measurements of the lensing shear ratio. We demonstrate that the DESI-DR1 shear ratios can be successfully fit by the same model used to describe cosmic shear correlations, and analyse the additional information that can be extracted about the source redshift distributions and intrinsic alignment parameters. This study serves as crucial preparation for the upcoming cosmological parameter analysis of these datasets.

Emas, N. [Swinburne U., Ctr. Astrophys. Supercompu↗

Automatically Finding Ship-Tracks to Enable Large-Scale Analysis of Aerosol-Cloud Interactions

Ship tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship tracks from satellite data on a large scale is prohibitively costly while a large number of samples are required to improve our understanding. Here we train a deep neural network to automate finding ship tracks. The neural network model generalizes well as it not only finds ship tracks labeled by human experts but also detects those that are occasionally missed by humans. It finds more ship tracks than all previous studies combined and produces a map of ship track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship tracks on a large scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.

aerosol cloud interactions↗

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Scale Analysis of Effective Mechanical Properties of Porous 3D Woven Composite Materials

This work aims to compute and analyze the mechanical properties of 3D woven composite materials that share the same yarn structure but differ in their matrix porosity and yarn's fiber volume fraction. Assuming linear elastic behavior, NASA's PuMA software was used to characterize the different composites from their constituents' data, averaging their elastic properties in three main directions to obtain their effective orthotropic mechanical properties. This was performed in three steps: firstly, the porous matrix phase was analyzed at the micro-scale; then, these results were used, along with the mechanical properties of the fibers, to model the yarns at the meso-scale; finally, results from the constituents were homogenized and used to model the mechanical behavior of the unit cell at the macro-scale. The 3D woven composite materials selected for this study are made of a mixture of phenolic resin with porosity values between 0 and 0.6, and infiltrated carbon fiber yarns with fiber volume fractions between 0.5 and 0.8. Results from this study show the effect of different matrix porosities and fiber volume fractions on the macro-scale mechanical properties, and were validated through theoretical and semi-empirical expressions found in the literature.

3D woven materials↗

Multi-Scale Analysis of Effective Mechanical Properties of 3D Woven Composite Materials

This work aims to compute and analyze the mechanical properties of 3D woven composite materials that share the same yarn structure but differ in their matrix porosity and fiber volume fraction. Assuming linear elastic behavior, the software PuMA, developed at NASA, was used to characterize the different composites from their constituents' data averaging their elastic properties in three main directions to obtain their effective orthotropic mechanical properties. This was performed in three steps: firstly, the different phases (yarns/matrix) were analyzed as anisotropic materials separately at the micro-scale; then, the results from these analyses were homogenized and used to obtain the anisotropic elasticity tensor at the meso-scale for the different woven materials; and finally, assuming orthotropic mechanical behavior for the unit cell the mechanical properties were obtained at the macro-scale. The 3D woven composite materials selected for this study are made of phenolic resin with porosity values between 0 and 0.6, and resin infiltrated carbon fiber with volume fractions between 0.5 and 0.9 for the yarns. Results from PuMA were validated with external FEA simulations for the non-porous 3D woven material with a fiber volume fraction of 0.9 in the yarns. Results will be included in the final paper after completing the study detailed in Section II.

Sergio Fraile Izquierdo↗