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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 505 records · Page 28

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Intrinsic dimensionality↗

UCO TRISO Minifuel FY23 NSUF-Kairos Power Post-Irradiation Examination Status Report

Irradiation of miniature tristructural isotropic (TRISO)–coated particle fuel compacts at high-power particle was performed in the Oak Ridge National Laboratory’s (ORNL’s) High Flux Isotope Reactor (HFIR) using the MiniFuel irradiation capability. Each compact comprised 20 TRISO particles with a low-enriched uranium carbide uranium oxide (UCO), natural UCO, or low-enriched UO 2 kernel within a graphitic matrix. After irradiation, the MiniFuel targets and subcapsules were disassembled to recover the irradiated fuel specimens and pursue post-irradiation examination (PIE) to inform Kairos Power on the fuel specimen performance. This report describes the PIE results collected to date, including dilatometry on the passive thermometry to confirm the irradiation temperature, fission gas release measurements, and gamma counting. This work was funded by the Nuclear Science User Facilities program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Modeling of DC spacecraft power systems

Future spacecraft power systems must be capable of supplying power to various loads. This delivery of power may necessitate the use of high-voltage, high-power dc distribution systems to transmit power from the source to the loads. Using state-of-the-art power conditioning electronics such as dc-dc converters, complex series and parallel configurations may be required at the interface between the source and the distribution system and between the loads and the distribution system. This research will use state-variables to model and simulate a dc spacecraft power system. Each component of the dc power system will be treated as a multiport network, and a state model will be written with the port voltages as the inputs. The state model of a component will be solved independently from the other components using its state transition matrix. A state-space averaging method is developed first in general for any dc-dc switching converter, and then demonstrated in detail for the particular case of the boost power stage. General equations for both steady-state (dc) and dynamic effects (ac) are obtained, from which important transfer functions are derived and applied to a special case of the boost power stage.

Berry, F. C.↗

A Novel Sparse Compositional Technique Reveals Microbial Perturbations

ABSTRACT The central aims of many host or environmental microbiome studies are to elucidate factors associated with microbial community compositions and to relate microbial features to outcomes. However, these aims are often complicated by difficulties stemming from high-dimensionality, non-normality, sparsity, and the compositional nature of microbiome data sets. A key tool in microbiome analysis is beta diversity, defined by the distances between microbial samples. Many different distance metrics have been proposed, all with varying discriminatory power on data with differing characteristics. Here, we propose a compositional beta diversity metric rooted in a centered log-ratio transformation and matrix completion called robust Aitchison PCA. We demonstrate the benefits of compositional transformations upstream of beta diversity calculations through simulations. Additionally, we demonstrate improved effect size, classification accuracy, and robustness to sequencing depth over the current methods on several decreased sample subsets of real microbiome data sets. Finally, we highlight the ability of this new beta diversity metric to retain the feature loadings linked to sample ordinations revealing salient intercommunity niche feature importance. IMPORTANCE By accounting for the sparse compositional nature of microbiome data sets, robust Aitchison PCA can yield high discriminatory power and salient feature ranking between microbial niches. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/DEICODE ; additionally, a QIIME 2 plugin is provided to perform this analysis at https://library.qiime2.org/plugins/q2-deicode .

59 BASIC BIOLOGICAL SCIENCES↗

Modeling and simulation of a Stewart platform type parallel structure robot

The kinematics and dynamics of a Stewart Platform type parallel structure robot (NASA's Dynamic Docking Test System) were modeled using the method of kinematic influence coefficients (KIC) and isomorphic transformations of system dependence from one set of generalized coordinates to another. By specifying the end-effector (platform) time trajectory, the required generalized input forces which would theoretically yield the desired motion were determined. It was found that the relationship between the platform motion and the actuators motion was nonlinear. In addition, the contribution to the total generalized forces, required at the actuators, from the acceleration related terms were found to be more significant than the velocity related terms. Hence, the curve representing the total required actuator force generally resembled the curve for the acceleration related force. Another observation revealed that the acceleration related effective inertia matrix I sub dd had the tendency to decouple, with the elements on the main diagonal of I sub dd being larger than the off-diagonal elements, while the velocity related inertia power array P sub ddd did not show such tendency. This tendency results in the acceleration related force curve of a given actuator resembling the acceleration profile of that particular actuator. Furthermore, it was indicated that the effective inertia matrix for the legs is more decoupled than that for the platform. These observations provide essential information for further research to develop an effective control strategy for real-time control of the Dynamic Docking Test System.

Lim, Gee Kwang↗

Spatio-Temporal Deep Graph Network for Event Detection, Localization, and Classification in Cyber-Physical Electric Distribution System

This work proposes a deep graph learning framework to identify, locate, and classify power, cyber, and cyber power events at the distribution system level. The proposed algorithm jointly exploits spatial, temporal, and node-level cyber and physical data features. The developed graph neural network, together with a deep autoencoder, utilizes physical measurements from distribution level phasor measurement units and cyber data from communication network logs. The spatial structure of the synchrophasor measurements and network is incorporated through a weighted adjacency matrix. The temporal structure is incorporated by defining a spatial operation in the gated recurrent unit. This spatio-temporal learning element resides inside a power event detection, localization, and classification module that provides the degree of confidence for an event label. To accurately pinpoint the location of an event to the nearest bus equipped with a measurement unit, a combination of squared error and proximity score is utilized. Also included is a cyber event detection module that employs heteroskedasticity to analyze the significance of various cyber features during different types of attacks. Finally, a dual-bit cyber-power decision table determines the nature of the event. The proposed method is validated on two distribution systems modeled in OPAL-RT/Hypersim with limited phasor measurement units for different possible physical and cyber events. Further analyses include comparison with other state-of-the-art methods and validation in the presence of measurement noise. As a result, our method outperforms existing approaches and achieves an average detection accuracy of 97.97%, F1-score of 96.88%, precision of 96.53%, and recall of 98.57%.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Behavior of helium cavities in ion-irradiated W-Ni-Fe ductile-phase toughened tungsten

This study reports on the distribution of helium (He) cavities in a hot-rolled W-Ni-Fe ductile-phase toughened tungsten (DPT W) composite irradiated to a dose and a helium concentration that are comparable to those in the material after 5-year irradiation in a conceptual fusion power plant. Here, the DPT W sample consists of W particles embedded in a ductile-phase NiFeW matrix with a nominal composition of 90W-7Ni-3Fe by weight. It was hot-rolled to a thickness reduction by 87% (87R DPT W). Sequential irradiation of the material with 1.2 MeV Ni + ions to a fluence of 2.15×10 16 Ni + /cm 2 and 90 keV He + ions to 6.5×10 15 He + /cm 2 was performed at 973 K. Larger He cavities with a lower number density are observed in NiFeW than W. Helium cavities are aggregated preferentially along the NiFeW/W interphase boundary. This behavior is not observed along the W/W grain boundary under the same irradiation conditions. A similar distribution of He cavities with comparable sizes is observed in 87R DPT W irradiated with He + ions only, suggesting that the He cavity distribution is not significantly affected by pre-irradiation of Ni + ions at 973 K. The data from this study does not provide any evidence for formation of visible voids or Ni precipitates in W phase irradiated with Ni + ions only. Diffusion and clustering of He atoms and mobile vacancies during ion irradiation at 973 K are responsible for the formation and growth of the He cavities.

36 MATERIALS SCIENCE↗

Generalized parton distributions from lattice QCD with asymmetric momentum transfer: Axial-vector case

Recently, we made significant advancements in improving the computational efficiency of lattice QCD calculations for generalized parton distributions (GPDs). This progress was achieved by adopting calculations of matrix elements in asymmetric frames, deviating from the computationally-expensive symmetric frame typically used, and allowing freedom in the choice for the distribution of the momentum transfer between the initial and final states. A crucial aspect of this approach involves the adoption of a Lorentz covariant parametrization for the matrix elements, introducing Lorentz-invariant amplitudes. This approach also allows us to propose an alternative definition of quasi-GPDs, ensuring frame independence and potentially reduce power corrections in matching to light cone GPDs. In our previous work, we presented lattice QCD results for twist-2 unpolarized GPDs ( H and E ) of quarks obtained from calculations performed in asymmetric frames at zero skewness. Building upon this work, we now introduce a novel Lorentz covariant parametrization for the axial-vector matrix elements. We employ this parametrization to compute the axial-vector GPD H ˜ at zero skewness, using an N f = 2 + 1 + 1 ensemble of twisted mass fermions with clover improvement. The light-quark masses employed in our calculations correspond to a pion mass of approximately 260 MeV. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Online Voltage Event Detection Using Synchrophasor Data with Structured Sparsity-Inducing Norms

This paper develops an accurate and computationally efficient data-driven framework to detect voltage events from PMU data streams. It develops an innovative Proximal Bilateral Random Projection (PBRP) algorithm to quickly decompose the PMU data matrix into a low-rank matrix, a row-sparse event-pattern matrix and a noise matrix. Here, the row-sparse pattern matrix significantly distinguishes events from normal behavior. These matrices are then fed into a clustering algorithm to separate voltage events from normal operating conditions. Large-scale numerical study results on real-world PMU data show that the proposed algorithm is computationally more efficient and achieves higher F scores than state-of-the-art benchmarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Three-dimension heat transfer program

An IBM 7094, three dimensional, heat transfer program for satellite application is discussed. The program may be applied to all phases of spacecraft life, from launch to orbital quasi-steady state. Launch phase heating includes inputs by radiation from the hot fairing and free molecule flow heating after nose cone ejection. Orbital heat fluxes are accounted for by direct sunlight, earth-reflected sunlight, and earth-emitted input to the satellite. Internal heat exchange by conduction and radiation is determined, provided the appropriate conductances, radiation view factors, and effective emittances are known. A simplified analysis of an active thermal controlled spacecraft is incorporated into the program. One or more surfaces may contain shutter systems which have optical properties specified as a function of shutter opening. The program evaluates the feasibility of any configuration based upon maintaining an internal component within its tolerable temperature limits. The program employs a matrix inversion subroutine (Gauss Elimination Method) to solve the heat balance equations.

COMPUTER PROGRAM↗

Digital techniques for ULF wave polarization analysis

Digital power spectral and wave polarization analysis are powerful techniques for studying ULF waves in the earth's magnetosphere. Four different techniques for using the spectral matrix to perform such an analysis have been presented in the literature. Three of these techniques are similar in that they require transformation of the spectral matrix to the principal axis system prior to performing the polarization analysis. The differences in the three techniques lie in the manner in which determine this transformation. A comparative study of these three techniques using both simulated and real data has shown them to be approximately equal in quality of performance. The fourth technique does not require transformation of the spectral matrix. Rather, it uses the measured spectral matrix and state vectors for a desired wave type to design a polarization detector function in the frequency domain. The design of various detector functions and their application to both simulated and real data will be presented.

Arthur, C. W.↗

Low-Power Architectures for Large Radio Astronomy Correlators

The architecture of a cross-correlator for a synthesis radio telescope with N greater than 1000 antennas is studied with the objective of minimizing power consumption. It is found that the optimum architecture minimizes memory operations, and this implies preference for a matrix structure over a pipeline structure and avoiding the use of memory banks as accumulation registers when sharing multiply-accumulators among baselines. A straw-man design for N = 2000 and bandwidth of 1 GHz, based on ASICs fabricated in a 90 nm CMOS process, is presented. The cross-correlator proper (excluding per-antenna processing) is estimated to consume less than 35 kW.

signal processing↗

Biochar as a Building Material: Sequestering Carbon and Strengthening Concrete

It is possible to offset the carbon footprint of concrete by 60 kg (132 lbs) per cubic yard of ready-mix by deeply sequestering carbon with an engineered biochar additive. Our multidisciplinary team specializing in char production and cementitious materials has demonstrated that for every ton of cement, adding 100 kg of engineered biochar will not only lock in carbon, but also strengthen concrete in all key dimensions via enhancements to hydration and integration into the hardened matrix. As a non-chemical, inert additive the cement sequestration (CemSeq) char product can fully complement other powerful tools to reduce cement emissions and unlock the possibility for carbon negative concrete by 2050. The key findings of our initial research have shown that to achieve this the following are required: tailored milling of the char, using fast pyrolysis to produce the char, and modulating the cement flowability.

biochar↗

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗

Addressable inverter matrix for process and device characterization

The addressable inverter matrix consists of 222 inverters each accessible with the aid of a shift register. The structure has proven useful in characterizing the variability of inverter transfer curves and in diagnosing processing faults. For good 3-micron CMOS bulk inverters investigated, the percent standard deviation of the inverter threshold voltage was less than one percent and the inverter gain (the slope of the inverter transfer curve at the inverter threshold vltage) was less than 3 percent. The average noise margin for the inverters was near 2 volts for a power supply voltage of 5 volts. The specific faults studied included undersize pull-down transistor widths and various open contacts in the matrix.

Buehler, M. G.↗

Flap-lag-torsion aeroelastic stability of a circulation control rotor in forward flight

The aeroelastic stability of a circulation control rotor blade undergoing three degrees of motion (flap, lag, and torsion) is investigated in forward flight. Quasi-steady strip theory is used to evaluate the aerodynamics forces; and the airfoil characteristics are from data tables. The propulsive and the auxiliary power trims are calculated from vehicle and rotor equilibrium equations through the numerical integration of element forces in azimuth as well as in radial directions. The nonlinear time dependent periodic blade response is calculated using an iterative procedure based on Floquet theory. The periodic perturbation equations are solved for stability using Floquet transition matrix theory. The effects of several parameters on blade stability are examined, including advance ratio, collective pitch, thrust level, shaft tilt, structural stiffnesses variation, and propulsive and auxiliary power trims.

Chopra, Inderjit↗

Addressable inverter matrix for process and device characterization

The addressable inverter matrix consists of 222 inverters each accessible with the aid of a shift register. The structure has proven useful in characterizing the variability of inverter transfer curves and in diagnosing processing faults. For good 3-micron CMOS bulk inverters investigated in this study, the percent standard deviation of the inverter threshold voltage was less than one percent and the inverter gain (the slope of the inverter transfer curve at the inverter threshold voltage) was less than 3 percent. The average noise margin for the inverters was near 2 volts for a power supply voltage of 5 volts. The specific faults studied included undersize pull-down transistor widths and various open contacts in the matrix.

Buehler, M. G.↗