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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Reconstruction of the Mars Science Laboratory Parachute Performance and Comparison to the Descent Simulation

The Mars Science Laboratory used a single mortar-deployed disk-gap-band parachute of 21.35 m nominal diameter to assist in the landing of the Curiosity rover on the surface of Mars. The parachute system s performance on Mars has been reconstructed using data from the on-board inertial measurement unit, atmospheric models, and terrestrial measurements of the parachute system. In addition, the parachute performance results were compared against the end-to-end entry, descent, and landing (EDL) simulation created to design, develop, and operate the EDL system. Mortar performance was nominal. The time from mortar fire to suspension lines stretch (deployment) was 1.135 s, and the time from suspension lines stretch to first peak force (inflation) was 0.635 s. These times were slightly shorter than those used in the simulation. The reconstructed aerodynamic portion of the first peak force was 153.8 kN; the median value for this parameter from an 8,000-trial Monte Carlo simulation yielded a value of 175.4 kN - 14% higher than the reconstructed value. Aeroshell dynamics during the parachute phase of EDL were evaluated by examining the aeroshell rotation rate and rotational acceleration. The peak values of these parameters were 69.4 deg/s and 625 deg/sq s, respectively, which were well within the acceptable range. The EDL simulation was successful in predicting the aeroshell dynamics within reasonable bounds. The average total parachute force coefficient for Mach numbers below 0.6 was 0.624, which is close to the pre-flight model nominal drag coefficient of 0.615.

Cruz, Juan R.↗
NASA NTRS2016

Orion Exploration Flight Test Reaction Control System Jet Interaction Heating Environment from Flight Data

The Orion Multi-Purpose Crew Vehicle (MPCV) Reaction Control System (RCS) is critical to guide the vehicle along the desired trajectory during re-­‐entry. However, this system has a significant impact on the convective heating environment to the spacecraft. Heating augmentation from the jet interaction (JI) drives thermal protection system (TPS) material selection and thickness requirements for the spacecraft. This paper describes the heating environment from the RCS on the afterbody of the Orion MPCV during Orion's first flight test, Exploration Flight Test 1 (EFT-1). These jet plumes interact with the wake of the crew capsule and cause an increase in the convective heating environment. Not only is there widespread influence from the jet banks, there may also be very localized effects. The firing history during EFT-1 will be summarized to assess which jet bank interaction was measured during flight. Heating augmentation factors derived from the reconstructed flight data will be presented. Furthermore, flight instrumentation across the afterbody provides the highest spatial resolution of the region of influence of the individual jet banks of any spacecraft yet flown. This distribution of heating augmentation across the afterbody will be derived from the flight data. Additionally, trends with possible correlating parameters will be investigated to assist future designs and ground testing programs. Finally, the challenges of measuring JI, applying this data to future flights and lessons learned will be discussed.

White, Molly E.↗
NASA NTRS2011

Binary-Signal Recovery

Binary communication through long cables, opto-isolators, isolating transformers, or repeaters can become distorted in characteristic ways. The usual solution is to slow the communication rate, change to a different method, or improve the communication media. It would help if the characteristic distortions could be accommodated at the receiving end to ease the communication problem. The distortions come from loss of the high-frequency content, which adds slopes to the transitions from ones to zeroes and zeroes to ones. This weakens the definition of the ones and zeroes in the time domain. The other major distortion is the reduction of low frequency, which causes the voltage that defines the ones or zeroes to drift out of recognizable range. This development describes a method for recovering a binary data stream from a signal that has been subjected to a loss of both higher-frequency content and low-frequency content that is essential to define the difference between ones and zeroes. The method makes use of the frequency structure of the waveform created by the data stream, and then enhances the characteristics related to the data to reconstruct the binary switching pattern. A major issue is simplicity. The approach taken here is to take the first derivative of the signal and then feed it to a hysteresis switch. This is equivalent in practice to using a non-resonant band pass filter feeding a Schmitt trigger. Obviously, the derivative signal needs to be offset to halfway between the thresholds of the hysteresis switch, and amplified so that the derivatives reliably exceed the thresholds. A transition from a zero to a one is the most substantial, fastest plus movement of voltage, and therefore will create the largest plus first derivative pulse. Since the quiet state of the derivative is sitting between the hysteresis thresholds, the plus pulse exceeds the plus threshold, switching the hysteresis switch plus, which re-establishes the data zero to one transition, except now at the logic levels of the receiving circuit. Similarly, a transition from a one to a zero will be the most substantial and fastest minus movement of voltage and therefore will create the largest minus first derivative pulse. The minus pulse exceeds the minus threshold, switching the hysteresis switch minus, which re-establishes the data one to zero transition. This innovation has a large increase in tolerance for the degradation of the binary pattern of ones and zeroes, and can reject the introduction of noise in the form of low frequencies that can cause the voltage pattern to drift up or down, and also higher frequencies that are beyond the recognizable content in the binary transitions.

Griebeler, Elmer L.↗
NASA NTRS1991

Chaos in the sunspot cycle - Analysis and prediction

The variability of solar activity over long time scales, given semiquantitatively by measurements of sunspot numbers, is examined as a nonlinear dynamical system. First, a discussion of the data set used and the techniques utilized to reduce the noise and capture the long-term dynamics inherent in the data is presented. Subsequently, an attractor is reconstructed from the data set using the method of time delays. The reconstructed attractor is then used to determine both the dimension of the underlying system and also the largest Lyapunov exponent, which together indicate that the sunspot cycle is indeed chaotic and also low dimensional. In addition, recent techniques of exploiting chaotic dynamics to provide accurate, short-term predictions are utilized in order to improve upon current forecasting methods and also to place theoretical limits on predictability extent. The results are compared to chaotic solar-dynamo models as a possible physically motivated source of this chaotic behavior.

Mundt, Michael D.↗
DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗
DOE OSTI2024

Correction to: Imaging Light–Induced Migration of Dislocations in Halide Perovskites with 3D Nanoscale Strain Mapping

Owing to an error in properly normalizing the reconstruction phase data into atomic displacements, the strain values that we used to calculate the root mean squared local strain, ε rms , and to calculate the fraction of the crystals more strain than 1%, f, quoted in the original paper, are roughly one order of magnitude too large. This error was only discovered recently whilst performing further analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning of networked spreading models from noisy and incomplete data

Recent years have seen a lot of progress in algorithms for learning parameters of spreading dynamics from both full and partial data. Some of the remaining challenges include model selection under the scenarios of unknown network structure, noisy data, missing observations in time, as well as an efficient incorporation of prior information to minimize the number of samples required for an accurate learning. Here, in this work, we introduce a universal learning method based on a scalable dynamic message-passing technique that addresses these challenges often encountered in real data. The algorithm leverages available prior knowledge on the model and on the data, and reconstructs both network structure and parameters of a spreading model. We show that a linear computational complexity of the method with the key model parameters makes the algorithm scalable to large network instances.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

NuGraph2: A Graph Neural Network for Neutrino Event Reconstruction

Neutrino experiments are set to probe some of the most important open questions in physics, from CP violation and the nature of dark matter. The technology of choice for many of these experiments is the liquid argon time projection chamber (LArTPC). In current LArTPC experiments, reconstruction performance often represents a limiting factor for the sensitivity. New developments are therefore needed to unlock the full potential of LArTPC experiments. NuGraph2 is a state of the art Graph Neural Network for reconstruction of data in LArTPC experiments. NuGraph2 utilizes a heterogeneous graph structure, with separate subgraphs of 2D nodes (hits in each plane) connected across planes via 3D nodes (space points). The model provides a consistent description of the neutrino interaction across all planes. NuGraph2 is a multi-purpose network, with a common message-passing attention engine connected to multiple decoders with different classification or regression tasks. These include the classification of detector hits according to the particle type that produced them (semantic segmentation) and the separation of hits from the neutrino interaction from hits due to noise or cosmic-ray background. Additional decoders are being developed, performing tasks such as the regression of the neutrino interaction vertex position. Performance results will be presented based on publicly available samples from MicroBooNE. These include both physics performance metrics, achieving 95% accuracy for semantic segmentation and 98% classification of neutrino hits, as well as computational metrics for training and for inference on CPU or GPU. The status of the NuGraph integration in the LArSoft software framework will be presented, as well as initial studies about model interpretability and injection of domain knowledge.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Optical potential uncertainties on exclusive tens-of-MeV Ar cross sections

Large liquid argon time projection chamber (LArTPC) neutrino detectors, such as those planned for the Deep Underground Neutrino Experiment (DUNE), show considerable promise as a platform for next-generation measurements of supernova neutrinos. Thanks to the neutron excess in $^{40}$Ar as well as the detailed tracking possible with LArTPCs, these detectors are expected to be uniquely capable of measuring supernova electron neutrinos with high statistics and minimal backgrounds. However, these technological advantages come at the price of complexities in data interpretation; reconstruction of the incident energies of supernova neutrinos in a future LArTPC-based analysis will be subject to a variety of systematic uncertainties related to nuclear interaction modeling. In this talk, we present a study of a subset of these uncertainties as implemented in the MARLEY event generator used by DUNE and other LArTPC neutrino experiments. Variations to the optical potential used in the MARLEY nuclear de-excitation model are applied to the calculation of exclusive tens-of-MeV neutrino-nucleus cross sections for the first time, and the impact on observables of interest for supernova neutrino detection is examined. We also discuss prospects for quantifying other sources of uncertainty on the MARLEY neutrino interaction model.

El-Haj, Luca Abu↗
DOE OSTI2024

The Galaxy–Galaxy Strong Lensing Cross Section and the Internal Distribution of Matter in ΛCDM Substructure

Abstract Strong gravitational lensing offers a powerful probe of the detailed distribution of matter in lenses, while magnifying and bringing faint background sources into view. Observed strong lensing by massive galaxy clusters, which are often in complex dynamical states, has also been used to map their dark matter (DM) substructures on smaller scales. Deep high-resolution imaging has revealed the presence of strong lensing events associated with these substructures, namely galaxy-scale sub-halos. However, an inventory of these observed galaxy–galaxy strong lensing (GGSL) events is noted to be discrepant with state-of-the-art ΛCDM simulations. Cluster sub-halos appear to be over-concentrated compared to their simulated counterparts yielding an order-of-magnitude higher value of GGSL. In this paper, we explore the possibility of resolving this observed discrepancy by redistributing the mass within observed cluster sub-halos in ways that are consistent within the ΛCDM paradigm of structure formation. Lensing mass reconstructions from data provide constraints on the mass enclosed within apertures and are agnostic to the detailed mass profile within them. Therefore, as the detailed density profile within cluster sub-halos currently remains unconstrained by data, we are afforded the freedom to redistribute the enclosed mass. We investigate if rearranging the mass to a more centrally concentrated density profile helps alleviate the GGSL discrepancy. We report that refitting cluster sub-halos to the ubiquitous ΛCDM-motivated Navarro–Frenk–White profile, and further modifying them to include significant baryonic components, does not resolve this tension. A resolution to this persisting GGSL discrepancy may require more careful exploration of alternative DM models.

Astronomy & Astrophysics↗
NASA NTRS1976

Development and evaluation of a Hadamard transform imaging spectrometer and a Hadamard transform thermal imager

A spectrometric imager and a thermal imager, which achieve multiplexing by the use of binary optical encoding masks, were developed. The masks are based on orthogonal, pseudorandom digital codes derived from Hadamard matrices. Spatial and/or spectral data is obtained in the form of a Hadamard transform of the spatial and/or spectral scene; computer algorithms are then used to decode the data and reconstruct images of the original scene. The hardware, algorithms and processing/display facility are described. A number of spatial and spatial/spectral images are presented. The achievement of a signal-to-noise improvement due to the signal multiplexing was also demonstrated. An analysis of the results indicates both the situations for which the multiplex advantage may be gained, and the limitations of the technique. A number of potential applications of the spectrometric imager are discussed.

Harwit, M.↗
NASA NTRS1976

Hadamard transform imager and imaging spectrometer

An imager and a spectrometric imager, which achieve multiplexing by the use of binary optical encoding masks, have been built and tested. The masks are based on orthogonal, pseudorandom digital codes derived from Hadamard matrices. The spatial (and/or spectral) data are therefore obtained in the form of a Hadamard transform of the spatial (and/or spectral) scene. Computer algorithms are used to decode the data and reconstruct images of the original scene. The hardware, algorithms processing and display facility are described. A number of spatial and spatial/spectral images, obtained in the laboratory, are presented.

Swift, R. D.↗
NASA NTRS1978

A recommended entry reconstruction process for the Pioneer Venus multi-probe mission

A method for determining the entry trajectories for the Pioneer Venus multi-probe mission is presented that utilizes earth based Doppler and onboard accelerometry as observables to provide updates for the spacecraft state and atmospheric parameters. The evolution of this method, based on error analyses and actual simulation results, is discussed. A derivative of the Viking radio science orbit determination software is recommended for the reconstruction. Telemetry data pre-processing requirements were defined. A cubic spline derivative routine is recommended to extract accelerations from the accumulated velocity decrements.

Findlay, J. T.↗
NASA NTRS1980

Pulsed holography for combustion diagnostics

Image reconstruction and data extraction techniques were considered with respect to their application to combustion diagnostics. A system was designed and constructed that possesses sufficient stability and resolution to make quantitative data extraction possible. Example data were manually processed using the system to demonstrate its feasibility for the purpose intended. The system was interfaced with the PDP-11-04 computer for maximum design capability. It was concluded that the use of specialized digital hardware controlled by a relatively small computer provides the best combination of accuracy, speed, and versatility for this particular problem area.

Klein, N.↗
NASA NTRS1983

Solar system history as recorded in the Saturnian ring structure

Holberg's analysis of the Voyager Saturn photographs in reflected and transparent light, and occultation data of stars seen through the rings are discussed. A hyperfine structure, with 10,000 ringlets can be explained by the Baxter-Thompson negative diffusion. This gives the ringlets a stability which makes it possible to interpret them as fossils, which originated at cosmogonic times. It is shown that the bulk structure can be explained by the combined cosmogonic shadows of the satellites Mimas, Janus and the Shepherd satellites. This structure originated at the transition from the plasma phase to the planetesimal phase. The shadows are not simple void regions but exhibit a characteristic signature. Parts of the fine structure, explained by Holberg as resonances with satellites, are interpreted as cosmogonic shadow effects. However, there are a number of ringlets which can neither be explained by cosmogonic nor by resonance effects. Analysis of ring data can reconstruct the plasma-planetesimal transition with an accuracy of a few percent.

Alfven, H.↗
NASA NTRS1983

Solar system history as recorded in the Saturnian ring structure

Holberg's analysis of the Voyager Saturn photographs in reflected and transparent light, and occultation data of stars seen through the rings are discussed. A hyperfine structure with 10,000 ringlets can be explained by the Baxter-Thompson negative diffusion. This gives the ringlets a stability which makes it possible to interpret them as fossils which originated at cosmogonic times. It is shown that the bulk structure can be explained by the combined cosmogonic shadows of the satellites Mimas and Janus and the Shepherd satellites. This structure originated at the transition from the plasma phase to the planetesimal phase. The shadows are not simple void regions but exhibit a characteristic signature. Parts of the fine structure, explained by Holberg as resonances with satellites, are interpreted as cosmogonic shadow effects. However, there are a number of ringlets which can neither be explained by cosmogonic nor by resonance effects. Analysis of ring data can reconstruct the plasma-planetesimal transition with an accuracy of a few percent. Previously announced in STAR as N84-12013

Alfven, H.↗