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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Upgrade to Fixed and Translating Scintillation-Based Loss Detector System in the Fermilab Drift Tube Linac

The closed-off structure of the Fermilab Drift Tube Linac precludes a robust array of instrumentation from directly monitoring the H- beam that is accelerated from 750 keV to 116 MeV. To improve beam tuning and op-erational assessment of Drift Tube Linac performance, scintillator-based loss monitors were previously installed along the exterior of the first two accelerating cavities to assess low energy beam losses. Here we present a recent upgrade to the loss monitor system, including significant improvements in analog signal processing to address baseline-interfering noise; digitization of the signals to enable regular operational use and tuning; and a new remote operation upgrade of the translating loss monitor with precise positioning of the loss monitor along its nine-foot track. Data from the fixed and translating de-tectors collected under varying beam conditions validate the utility of the upgrade.

Chen, Erin V. [Fermilab] (ORCID:0000000215467899)↗
NASA NTRSDate not supplied

Recovery Traejctories for Inadvertent Departures from an NRHO

The current Gateway baseline orbit, a Near Rectilinear Halo Orbit (NRHO), is a nearly stable orbit that requires regular orbit maintenance (OM) maneuvers for long-term retention of a spacecraft. With missed OM maneuvers, particularly over extended intervals, spacecraft naturally depart from the baseline orbit. In response, a strategy to recover inadvertent departure trajectories and return a spacecraft to the NRHO is developed. A Monte Carlo-based approach is used to analyze departures that are recoverable using a standard OM approach. Dynamical structures in the vicinity of the NRHO are leveraged to design recovery trajectories for spacecraft that have departed further from the baseline.

Emily M Zimovan-Spreen↗
DOE OSTI2024

Southwest Regional Partnership on Carbon Sequestration (Phase III) Underground Source of Drinking Water Monitoring at the Farnsworth Unit

The Ogallala aquifer is identified as the only underground source of drinking water (USDW) aquifer in the vicinity of the FWU. Throughout the span of the SWP project at the FWU, groundwater samples from the Ogallala Aquifer were collected and analyzed on a regular basis to obtain information that reflects the water quality baseline and any potential leakage, and to facilitate effective simulations and risk assessment. To date, hundreds of samples have been collected and tested. The water analysis results suggest that the Ogallala groundwater quality maintains stable and potable, and no leakage is indicated by these data.

42 ENGINEERING↗
NASA NTRS2010

High Angular Resolution Observations of Episodic Dust Emission from Long Period Variable Stars Twenty Years of Observations with the Berkeley Infrared Spatial Interferometer

Over the past twenty years the U. C. Berkeley Infrared Spatial Interferometer has observed a number of Long Period Variable stars in the mid-infrared, obtaining information on the spatial distribution of dust around these stars with resolutions of the order of a few tens of milliarcseconds. The ISI is a heterodyne interferometer operating mostly at 11.15 microns, initially with two telescopes. In the last decade, it has been taking data regularly with three telescopes, thus obtaining visibility data on three baselines and also a closure phase. Over the course of the years, the ISI has been able to measure the physical properties of the dust shells surrounding these stars, in particular the inner radii of the dust shells, as well as the temperature and density distribution. For some stars, the ISI has also made precision measurements of their diameters in the mid-infrared. Closure phase measurements have revealed asymmetries in the dust distributions around many stars. Most surprisingly the ISI data has shown evidence for substantial changes in the amount of dust on time scales of 5-10 years, rather than being directly correlated with the stellar pulsation periods, which are of the order of one year. We discuss past results and new results from the ISI that highlight the dynamic environment around these stars.

Danchi, William↗
DOE OSTI2023

PSTN-055: Survey Cadence Optimization Committee's Phase 2 Recommendations

This document describes the recommendations formulated by the Survey Cadence Optimization Committee (SCOC) of Vera C. Rubin Observatory for the observing strategy of the Legacy Survey of Space and Time (LSST). These "Phase 2" recommendations follow the initial "Phase 1" recommendations released in December 2021 as PSTN-053, and convey the current recommendations for the initial implementation of the LSST. These recommendations are based on the SCOC analysis of LSST simulations generated according to PSTN-053 and the feedback received from the scientific community on those simulations. These recommendations should be considered as the current guidance for implementing the LSST observing survey at the start of the survey, a strategy to be reviewed regularly over the survey lifetime, and are accompanied by a simulation, baseline_v3.0, which represents a specific implementation of these recommendations. While these recommendations dramatically narrow the possible LSST observing parameter choices, we emphasize that at this stage they do not yet represent a final or complete set of recommendations for the survey strategy, and several details are still to be refined. Furthermore, the strategy should be considered "living" and subject to evolution throughout the survey. The SCOC continues to engage with the community to finalize its recommendations. At the time of the release of this document, the final phases of construction of Rubin Observatory are ongoing with an expected first light in mid-2024. We expect the SCOC recommendations to be revised as needed, as knowledge of the system as built and the outcome of commissioning and Science Verification mature. This document describes the Phase 2 SCOC recommendations —highlighting elements that can be considered final and elements that remain to be finalized—, the process through which the SCOC has converged on these recommendations, and the working plan for the SCOC starting in January 2023 through the start of the survey to finalize the initial implementation of the Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2019

Evaluating Combinations of Sentinel-2 Data and Machine-Learning Algorithms for Mangrove Mapping in West Africa

Creating a national baseline for natural resources, such as mangrove forests, and monitoring them regularly often requires a consistent and robust methodology. With freely available satellite data archives and cloud computing resources, it is now more accessible to conduct such large-scale monitoring and assessment. Yet, few studies examine the reproducibility of such mangrove monitoring frameworks, especially in terms of generating consistent spatial extent. Our objective was to evaluate a combination of image processing approaches to classify mangrove forests along the coast of Senegal and The Gambia. We used freely available global satellite data (Sentinel-2), and cloud computing platform (Google Earth Engine) to run two machine learning algorithms, random forest (RF), and classification and regression trees (CART). We calibrated and validated the algorithms using 800 reference points collected using high-resolution images. We further re-ran 10 iterations for each algorithm, utilizing unique subsets of the initial training data. While all iterations resulted in thematic mangrove maps with over 90% accuracy, the mangrove extent ranges between 827-2807 km2 for Senegal and 245-1271 km2 for The Gambia with one outlier for each country. We further report "Places of Agreement" (PoA) to identify areas where all iterations for both methods agree (506.6 km2 and 129.6 km2 for Senegal and The Gambia, respectively), thus have a high confidence in predicting mangrove extent. While we acknowledge the time- and cost-effectiveness of such methods for the landscape managers, we recommend utilizing them with utmost caution, as well as post-classification on-the-ground checks, especially for decision making.

Mondal, Pinki↗
DOE OSTI2020

Design and Evaluation of a Tethered, Open Port Sampling Interface for Liquid Extraction-Mass Spectrometry Chemical Analysis

Presented in this work is a tethered, liquid-extraction-sampling interface designed for the mass spectrometric surface sampling/analysis of 3D objects. The tethered, open port sampling interface (TOPSI) incorporates a vacuum line between the sampling probe and ionization source, which enables the ability for an extended, tethered sample transfer line. Herein, several designs of the hand-held TOPSI are presented and evaluated on the basis of the analytical metrics of analyte transport time, peak width, and analyte sensitivity. The best analytical metrics were obtained with capillary flow resistances arranged in a particular order and the vacuum region set at 6.2 kPa. This TOPSI design incorporated a transfer capillary 1 m in length, while retaining a fast analyte transport time (12 s), short signal peak width (5 s baseline-to-baseline), and high analyte signal at 90% of that obtained with a regular open port sampling interface (OPSI). The hand-held TOPSI was demonstrated for the characterization of extracted small molecules and metabolites from the surface of mint and rosemary leaves.

47 OTHER INSTRUMENTATION↗
NASA NTRS2023

Two Air Quality Regimes in Total Column NO2 over the Gulf of Mexico in May 2019: Shipboard and Satellite Views

The Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf of Mexico was conducted in May 2019 by NASA and the Bureau of Ocean Energy Management to determine the feasibility of using satellite data to measure air quality in a region of concentrated oil and natural gas (ONG) operations. SCOAPE addressed both technological and scientific issues related to measuring NO2 columns over the Outer Continental Shelf. Featured were nitrogen dioxide (NO 2 ) instruments (Pandora, Teledyne API analyzer) at Cocodrie, LA (29.26°, -90.66°), and on the Research Vessel Point Sur operating off the Louisiana coast with measurements of ozone, carbon monoxide and volatile organic compounds (VOC). The findings: (1) All NO 2 observations revealed two atmospheric regimes over the Gulf, the first influenced by tropical air in 10-14 May, the second influenced by flow from urban areas on 15-17 May; (2) Comparisons of OMI v4 and TROPOMI v1.3 TC (total column) NO 2 data with shipboard Pandora NO 2 column observations averaged 13% agreement with the largest difference during 15-17 May (~20%). At Cocodrie, the satellite-Pandora agreement was ~5%. (3) Three new-model Pandora instruments displayed a TC NO 2 precision of 0.01 Dobson Units (~5%); (4) Regions of smaller, older natural gas operations showed high methane readings from leakage; elevated VOC were also detected. Neither satellite nor spectrometer captured the magnitude of ambient NO 2 variability near ONG platforms. Given an absence of regular air quality monitoring over the Gulf of Mexico, SCOAPE data constitute a baseline against which future observations can be compared.

Nitrogen dioxide↗
DOE OSTI2021

Inverse Design of Two-Dimensional Airfoils Using Conditional Generative Models and Surrogate Log-Likelihoods

Abstract This paper shows how to use conditional generative models in two-dimensional (2D) airfoil optimization to probabilistically predict good initialization points within the vicinity of the optima given the input boundary conditions, thus warm starting and accelerating further optimization. We accommodate the possibility of multiple optimal designs corresponding to the same input boundary condition and take this inversion ambiguity into account when designing our prediction framework. To this end, we first employ the conditional formulation of our previous work BézierGAN–Conditional BézierGAN (CBGAN)—as a baseline, then introduce its sibling conditional entropic BézierGAN (CEBGAN), which is based on optimal transport regularized with entropy. Compared with CBGAN, CEBGAN overcomes mode collapse plaguing conventional GANs, improves the average lift-drag (Cl/Cd) efficiency of airfoil predictions from 80.8% of the optimal value to 95.8%, and meanwhile accelerates the training process by 30.7%. Furthermore, we investigate the unique ability of CEBGAN to produce a log-likelihood lower bound that may help select generated samples of higher performance (e.g., aerodynamic performance). In addition, we provide insights into the performance differences between these two models with low-dimensional toy problems and visualizations. These results and the probabilistic formulation of this inverse problem justify the extension of our GAN-based inverse design paradigm to other inverse design problems or broader inverse problems.

Engineering↗
DOE OSTI2025

Dynamic Low-Rank Training with Spectral Regularization: Achieving Robustness in Compressed Representations

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94\% compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗
DOE OSTI2025

Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks

Deployment of neural networks on resource-constrained devices demands models that are both compact and robust to adversarial inputs. However, compression and adversarial robustness often conflict. In this work, we introduce a dynamical low-rank training scheme enhanced with a novel spectral regularizer that controls the condition number of the low-rank core in each layer. This approach mitigates the sensitivity of compressed models to adversarial perturbations without sacrificing clean accuracy. The method is model- and data-agnostic, computationally efficient, and supports rank adaptivity to automatically compress the network at hand. Extensive experiments across standard architectures, datasets, and adversarial attacks show the regularized networks can achieve over 94 compression while recovering or improving adversarial accuracy relative to uncompressed baselines.

Schotthoefer, Steffen [ORNL] (ORCID:00000002156965↗
NASA NTRS1992

Attenuation of human carotid-cardiac vagal baroreflex responses after physical detraining

Astronauts who are occupied with prelaunch schedules may have to limit their regular physical exercise routines. To assess a potential effect on blood pressure control, carotid baroreceptor-cardiac reflex responses of 16 men were evaluated before and after two weeks of exercise detraining that followed ten weeks of regular scheduled exercise (30 min/d, 4 d/week at 75 percent V(O2) max). After detraining, the baroreflex stimulus-response relationship had a reduced slope 0.4 msec/mmHg and range of response. In addition, there was a resetting of the relationship on the R-R interval axis. Both the minimum and maximum R-R interval responses to the stimulus were significantly reduced after detraining. Baseline systolic pressure did not change with detraining, and the carotid baroreceptor-cardiac response relationship did not shift on the pressure axis. These results suggest that detraining from regular exercise can compromise vagally-mediated mechanisms of blood pressure regulation.

Convertino, Victor A.↗
DOE OSTI2024

Effect of Cyclo-Pentane Impurities on the Autoignition Reactivity and Properties of a Gasoline Surrogate Fuel

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%–85% purity. Here, in the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied. Chemical kinetic simulations were performed to predict the effects of cyclo-pentane impurities on the properties, octane rating, and autoignition reactivity under homogeneous charge compression-ignition conditions of PACE-20. From the numerical results, cyclo-pentane with 85% purity or higher is required to reasonably match both the research octane number and motor octane number of the target gasoline. Finally, homogeneous charge compression-ignition engine simulations show that impurities have only a modest effect on reactivity at naturally aspirated conditions, but cyclo-pentane purity is critical to properly replicate the pressure dependency of the reactivity.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2010

A Geometric Approach to Modeling Microstructurally Small Fatigue Crack Formation: Simulation and Prediction of Crack Nucleation in AA 7075-T651 - 2

The objective of this paper is to develop further a framework for computationally modeling microstructurally small fatigue crack growth in AA 7075-T651 [1]. The focus is on the nucleation event, when a crack extends from within a second-phase particle into a surrounding grain, since this has been observed to be an initiating mechanism for fatigue crack growth in this alloy. It is hypothesized that nucleation can be predicted by computing a non-local nucleation metric near the crack front. The hypothesis is tested by employing a combination of experimentation and nite element modeling in which various slip-based and energy-based nucleation metrics are tested for validity, where each metric is derived from a continuum crystal plasticity formulation. To investigate each metric, a non-local procedure is developed for the calculation of nucleation metrics in the neighborhood of a crack front. Initially, an idealized baseline model consisting of a single grain containing a semi-ellipsoidal surface particle is studied to investigate the dependence of each nucleation metric on lattice orientation, number of load cycles, and non-local regularization method. This is followed by a comparison of experimental observations and computational results for microstructural models constructed by replicating the observed microstructural geometry near second-phase particles in fatigue specimens. It is found that orientation strongly influences the direction of slip localization and, as a result, in uences the nucleation mechanism. Also, the baseline models, replication models, and past experimental observation consistently suggest that a set of particular grain orientations is most likely to nucleate fatigue cracks. It is found that a continuum crystal plasticity model and a non-local nucleation metric can be used to predict the nucleation event in AA 7075-T651. However, nucleation metric threshold values that correspond to various nucleation governing mechanisms must be calibrated.

Hochhalter, Jake D.↗
DOE OSTI2022

Design, dynamic modeling and wave basin verification of a Hybrid Wave–Current Energy Converter

Massive and high-density Marine and Hydrokinetic (MHK) energy is contained in the ocean, including waves, tidal streams, and ocean currents. Traditional MHK energy converters harvest energy from only a single MHK energy source, which does not fully exploit the energy potential that co-exists in multiple forms of MHK energy in the ocean. This paper presents the design and dynamics of a Hybrid Wave–Current Energy Converter (HWCEC) that can simultaneously convert both wave and current energy to electricity with a single Power Take-off (PTO) through the engagement and disengagement of the three one-way clutches. The critical design parameters are analyzed through modeling and simulation, including the transmission ratios, the electrical impedance, and the turbine-heave plate distance. Water basin tests in a wave–current tank were conducted, which shows the prototyped HWCEC can improve the electric power output by 38%–71% for regular waves and 79% for irregular waves, while providing a 70% reduction of the Peak to Average Ratio (PAR) of power compared to the baseline Wave Energy Converter (WEC). Here we further analyze the occurring percentages of the instant power of both WEC and HWCEC in irregular wave tests, shedding new insight on how HWCEC reduces the PAR.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Surrogate model evaluation and building energy benchmarking for commercial buildings

Building energy consumption benchmarking involves challenges associated with various energy patterns for different building types; heating, ventilating, and air-conditioning (HVAC) system types; and climates. Given significant variation in energy use patterns, accurate prediction of long-term energy use using surrogate models remains challenging. Multiple linear regression (MLR) is commonly used for building energy benchmarking because of its simple structure; however, it lacks accuracy compared to other black-box models. Although many studies have compared surrogate models and offer guidance on model selection based on metrics, they do not provide detailed analysis on improving the surrogate model accuracy. In this paper, we implement a surrogate model using polynomial ridge regression (i.e., MLR with interaction terms combined with ridge regularization) for small office and retail strip mall buildings across six HVAC system types and all climate zones, for electricity and natural gas in baseline and proposed scenarios. A simulation workflow is developed using OpenStudio TM /EnergyPlus TM to generate simulation data using measures over a wide range of efficiency inputs. Enhancements based on statistical insights are used for improving the model accuracy using filters, input transformations, and change points. Surrogate models achieved average coefficient of variation of the root mean squared error (CVRMSE) values of 2.17, 1.06, 2.05, and 3.26 for proposed electricity, proposed natural gas, baseline electricity, and baseline natural gas, respectively, with enhancements reducing CVRMSE by an average of 14.9% across all combinations. We provide model interpretation via Shapley additive explanations to determine which input variables most influence energy consumption and provide supportive arguments for enhancements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Dark Matter Reconstruction in LBAI Experiments with Imperfect Data

Long-baseline atom interferometer (LBAI) experiments offer unprecedented sensitivity to ultralight scalar dark matter (DM) [1], however reconstruction of a putative DM signal with traditional frequency-domain analysis requires ``perfect data (i.e., regularly-sampled with no missing samples). In a real LBAI experiment, there will undoubtedly be imperfections in the data leading to downtime. This downtime can arise from operational considerations (e.g., maintenance), the operational environment (motion of people and animals [2] or elevators), and robustness of the experimental apparatus (e.g., bad atom launches). In this work, we investigate the impact of various downtime models on the overall DM sensitivity of such an experiment. We compare the sensitivity for each downtime model as determined by a ``compound FFT analysis to a baseline no-downtime case. We also show how much sensitivity can be regained by moving to a Lomb-Scargle frequency analysis, as in [2]. Furthermore, we demonstrate reconstruction of the DM wave s phase as well as its frequency. [1] D. Antypas, et al, ``New Horizons: Scalar and Vector Ultralight Dark Matter (2022). arXiv:2203.14915 [2] J. Carlton and C. McCabe, ``From RATs to riches: mitigating anthropogenic and synanthropic noise in atom interferometer searches for ultra-light dark matter (2023). arXiv:2308.101731

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1994

A long-baseline method for HST gyro drift rate bias calibration

The routine on-orbit calibration of the Hubble Space Telescope (HST) rate gyro assemblies (RGA's) has depended on several related algorithms for drift rate bias calibration. The gyros have exhibited time-varying biases, which must be regularly corrected to maintain pointing stability. Currently, gyro drift parameters are uplinked to the spacecraft every 1-2 days for low rate mode and every 7 days for high rate mode. In order to minimize the impact of frequent calibrations on the HST science schedule, we have refined the gyro calibration algorithms and data collection schemes to reduce the amounts of telemetry data and processing time required for accurate bias calibration. We present a review of the evolution of the gyro calibration algorithms, with particular attention to what we have called the long-baseline bias (LBBIAS) technique, and describe the relative success of these methods in maintaining spacecraft stability.

Boia, John J.↗