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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Efficient generation and amplification of intense vortex and vector laser pulses via strongly-coupled stimulated Brillouin scattering in plasmas

The past decade has seen tremendous progress in the production and utilization of vortex and vector laser pulses. Although both are considered as structured light beams, the vortex lasers have helical phase fronts and phase singularities, while the vector lasers have spatially variable polarization states and polarization singularities. In contrast to the vortex pulses that carry orbital angular momentum (OAM), the vector laser pulses have a complex spin angular momentum (SAM) and OAM coupling. Despite many potential applications enabled by such pulses, the generation of high-power/-intensity vortex and vector beams remains challenging. Here, we demonstrate using theory and three-dimensional simulations that the strongly-coupled stimulated Brillouin scattering (SC-SBS) process in plasmas can be used as a promising amplification technique with up to 65% energy transfer efficiency from the pump beam to the seed beam for both vortex and vector pulses. We also show that SC-SBS is strongly polarization-dependent in plasmas, enabling an all-optical polarization control of the amplified seed beam. Additionally, the interaction of such structured lasers with plasmas leads to various angular momentum couplings and decouplings that produce intense new light structures with controllable OAM and SAM. This scheme paves the way for novel optical devices such as plasma-based amplifiers and light field manipulators.

Physics↗
NASA NTRS2020

TESS Data Release Notes: Sector 21 DR 29

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel les, light curve les, collateral pixel les, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml les. These data products were generated by the TESS Science Processing Operations Center (SPOC, Jenkins et al., 2016) at NASA Ames Research Center from data collected by the TESS instrument, which is managed by the TESS Payload Operations Center (POC) at Massachusetts Institute of Technology (MIT). The format and content of these data products are documented in the Science Data Products Description Document (SDPDD)1. The SPOC science algorithms are based heavily on those of the Kepler Mission science pipeline, and are described in the Kepler Data Processing Handbook (Jenkins, 2017).2 The Data Validation algorithms are documented in Twicken et al. (2018) and Li et al. (2019). The TESS Instrument Handbook (Vanderspek et al., 2018) contains more information about the TESS instrument design, detector layout, data properties, and mission operations. The TESS Mission is funded by NASA's Science Mission Directorate.

Michael M. Fausnaugh↗
NASA NTRS1999

Improved Modeling in a Matlab-Based Navigation System

An innovative approach to autonomous navigation is available for low earth orbit satellites. The system is developed in Matlab and utilizes an Extended Kalman Filter (EKF) to estimate the attitude and trajectory based on spacecraft magnetometer and gyro data. Preliminary tests of the system with real spacecraft data from the Rossi X-Ray Timing Explorer Satellite (RXTE) indicate the existence of unmodeled errors in the magnetometer data. Incorporating into the EKF a statistical model that describes the colored component of the effective measurement of the magnetic field vector could improve the accuracy of the trajectory and attitude estimates and also improve the convergence time. This model is identified as a first order Markov process. With the addition of the model, the EKF attempts to identify the non-white components of the noise allowing for more accurate estimation of the original state vector, i.e. the orbital elements and the attitude. Working in Matlab allows for easy incorporation of new models into the EKF and the resulting navigation system is generic and can easily be applied to future missions resulting in an alternative in onboard or ground-based navigation.

Deutschmann, Julie↗
NASA NTRS1989

Parallel processing of a rotating shaft simulation

A FORTRAN program describing the vibration modes of a rotor-bearing system is analyzed for parellelism in this simulation using a Pascal-like structured language. Potential vector operations are also identified. A critical path through the simulation is identified and used in conjunction with somewhat fictitious processor characteristics to determine the time to calculate the problem on a parallel processing system having those characteristics. A parallel processing overhead time is included as a parameter for proper evaluation of the gain over serial calculation. The serial calculation time is determined for the same fictitious system. An improvement of up to 640 percent is possible depending on the value of the overhead time. Based on the analysis, certain conclusions are drawn pertaining to the development needs of parallel processing technology, and to the specification of parallel processing systems to meet computational needs.

Arpasi, Dale J.↗
NASA NTRS1988

Applications of Digital Image Processing 11

A new technique, digital image velocimetry, is proposed for the measurement of instantaneous velocity fields of time dependent flows. A time sequence of single-exposure images of seed particles are captured with a high-speed camera, and a finite number of the single-exposure images are sampled within a prescribed period in time. The sampled images are then digitized on an image processor, enhanced, and superimposed to construct an image which is equivalent to a multiple exposure image used in both laser speckle velocimetry and particle image velocimetry. The superimposed image and a single-exposure Image are digitally Fourier transformed for extraction of information on the velocity field. A great enhancement of the dynamic range of the velocity measurement is accomplished through the new technique by manipulating the Fourier transform of both the single-exposure image and the superimposed image. Also the direction of the velocity vector is unequivocally determined. With the use of a high-speed video camera, the whole process from image acquisition to velocity determination can be carried out electronically; thus this technique can be developed into a real-time capability.

Cho, Y. -C.↗
NASA NTRS1988

On the expansion of ionospheric plasma into the near-wake of the Space Shuttle Orbiter

During the Spacelab 2 mission, while the Plasma Diagnostics Package was attached to the Remote Manipulator System, differential ion vector measurements were obtained in the near wake at a distance of 4-5 Shuttle radii. The Orbiter's wake was found to fill in at a much faster rate than can be explained by simple thermal motion. The measurements strongly suggest that filling of the Orbiter's wake is produced by the process of 'collisionless plasma expansion into a vacuum' and that, for oblique angles of the magnetic field and velocity vectors, the near wake plasma depletion a few radii downstream is not sensitive to the body scale size.

Stone, N. H.↗
DOE OSTI2022

A Decision-Making Machine Learning Approach in Hermite Spectral Approximations of Partial Differential Equations

The accuracy and effectiveness of Hermite spectral methods for the numerical discretization of partial differential equations on unbounded domains are strongly affected by the amplitude of the Gaussian weight function employed to describe the approximation space. This is particularly true if the problem is under-resolved, i.e., there are no enough degrees of freedom. The issue becomes even more crucial when the equation under study is time-dependent, forcing in this way the choice of Hermite functions where the corresponding weight depends on time. In order to adapt dynamically the approximation space, it is here proposed an automatic decision-making process that relies on machine learning techniques, such as deep neural networks and support vector machines. The algorithm is numerically tested with success on a simple 1D problem, but the main goal is its exportability in the context of more serious applications. Here we also show at the end an application in the framework of plasma physics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Search for a new heavy resonance decaying to a top quark and a neutral scalar boson in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A first search at the LHC for a new heavy resonance decaying to a top quark and a neutral scalar boson ϕ in the fully hadronic final state is presented, where the ϕ boson is identified by its decay into a bottom quark-antiquark pair. The search is focused on final states in which the decay products of the highly Lorentz boosted top quark and ϕ boson are each reconstructed as a single, large-radius jet with distinct substructure. The analysis is performed using proton-proton collision data at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb −1 , recorded with the CMS detector at the LHC in 2016–2018. The single production of a vector-like top quark, T′, is used as a benchmark model for the signal process. The results of this search are combined with those of a previous CMS search in which semileptonic decays of the top quark were used. No significant excess of data is observed with respect to the background prediction. For the case where the neutral scalar is a standard model Higgs boson and the T′ quark width is 5% of its mass, T′ quark masses between 0.85 and 1.3 TeV are excluded at 95% confidence level and the most stringent limits to date are set for masses above 2 TeV . For other ϕ boson masses, upper limits as low as 0.1 fb are set on the product of the T′ quark production cross section and branching fraction for its decay to a top quark and a ϕ boson.

Boosted↗
DOE OSTI2019

Electron-Phonon Coupling from Ab Initio Linear-Response Theory within the G W Method: Correlation-Enhanced Interactions and Superconductivity in Ba 1 - x K x BiO 3

We present a new first-principles linear-response theory of changes due to perturbations in the quasiparticle self-energy operator within the GW method. This approach, named GW perturbation theory ( GW PT), is applied to calculate the electron-phonon ( e -ph) interactions with the full inclusion of the GW nonlocal, energy-dependent self-energy effects, going beyond density-functional perturbation theory. Avoiding limitations of the frozen-phonon technique, GW PT gives access to e -ph matrix elements at the GW level for all phonons and scattering processes, and the computational cost scales linearly with the number of phonon modes (wave vectors and branches) investigated. We demonstrate the capabilities of GW PT by studying the e -ph coupling and superconductivity in Ba 0.6 K 0.4 BiO 3 . We show that many-electron correlations significantly enhance the e -ph interactions for states near the Fermi surface, and explain the observed high superconductivity transition temperature of Ba 0.6 K 0.4 BiO 3 as well as its doping dependence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Photonuclear tomography in ultraperipheral heavy-ion collisions

We present a theoretical investigation of photonuclear tomography as a novel technique for probing the internal structure of nuclei. In this approach, ultraperipheral heavy-ion collisions (UPCs) serve as a source of intense fluxes of virtual photons, which induce coherent production of vector mesons. By analyzing the probabilities and cross sections of these photon-induced processes, we propose a methodology for reconstructing the spatial distribution of nucleons within the nucleus. Our framework provides a systematic way to access information on the nuclear geometry probed in UPCs, offering new opportunities for studies of nuclear structure using particle production as a probe. Numerical calculations for selected examples illustrate the feasibility and potential of this method.

particle & resonance production↗
DOE OSTI2024

NSTXU Diagnostic Disruption Dynamic Loading Represented by Response Spectra

This article presents the results of transient dynamic simulations of loads due to disruption eddy currents on the NSTXU vacuum vessel. Dynamic loading at diagnostic mounting locations is expressed as response spectra derived from the time history results of the dynamic structural simulations of a variety of disruption scenarios. The disruption simulations draw on a history of the project assessments of worst case disruptions for specific components. Major efforts to assess disruption loading have included the vacuum vessel which is the major structural support for the machine, as well as the passive plates (PPs), high harmonic fast wave (HHFW) antenna, and centerstack casing. Each one of these efforts included transient electromagnetic simulations producing time-dependent eddy current Lorentz loads (and in some cases halo loads) which then were applied to time-dependent structural dynamic analyses intended to obtain the proper dynamic amplification factors. In some instances, the EM model and structural model were identical allowing direct transfer of EM forces to the structural model. In other cases, the EM and structural model were not identical and the vector potential (VP) transfer method was used. The results files from these analyses were available (or re-run) to post process in ANSYS Classic time history postprocessor. In conclusion, the ANSYS command is used to create response spectra from time history data at desired points on the vessel.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Braneworld cosmological effect on freeze-in dark matter density and lifetime frontier

In the 5-dimensional braneworld cosmology, the Friedmann equation of our 4-dimensional universe on a brane is modified at high temperatures while the standard Big Bang cosmology is reproduced at low temperatures. Based on two well-known scenarios, the Randall–Sundrum and Gauss–Bonnet braneworld cosmologies, we investigate the braneworld cosmological effect on the relic density of a non-thermal dark matter particle whose interactions with the Standard Model particles are so weak that its relic density is determined by the freeze-in mechanism. For dark matter production processes in the early universe, we assume a simple scenario with a light vector-boson mediator for the dark matter particle to communicate with the Standard Model particles. We find that the braneworld cosmological effect can dramatically alters the resultant dark matter relic density from the one in the standard Big Bang cosmology. As an application, we consider a right-handed neutrino dark matter in the minimal B – L extended Standard Model with a light B – L gauge boson (Z') as a mediator. We find an impact of the braneworld cosmological effect on the search for the long-lived Z' boson at the planned/proposed Lifetime Frontier experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Commissioning of SRF Cavity Analyzer System

Research and development in Superconducting Radio Frequency (SRF) cavities manufacturing, surface treatment, preparation, and doping techniques for the improvement of cavities performance necessitate reliable cavities’ intrinsic quality factor measurement with accurate and repeatable results. Fermilab Vertical Test Stand facility (VTS) performs ~270 cavities tests per year, including R&D cavities as well as production cavities at each step of their preparation for the placement in accelerator’s cryomodules. Current Fermilab VTS testing system is based on the scalar approach of power measurement, which neglects potential error factors of the RF networks with distributed parameters, hence the assessed measurement errors of such a system might be slightly underestimated. Alternative approach, utilizing a vector measurement (amplitude and phase) of RF signals in the setup with a cavity as a device under test, promises an enhanced accuracy and results traceability. New cavity an alyser system based on this approach (Vector VTS) was developed by D. Frolov et al. and currently undergoes a commissioning process. Basic underlying principles of the system will be presented with the methods of quality factor extraction from S-parameters measurement of multiport cavities and brief error analysis will be discussed. The system architecture will be shown with main components parameters and ensuing testing capabilities. Multiple tests results will be discussed with a cross-check comparison of the results obtained with a conventional testing method. System advantages such as automated calibration process and additional features as a built- in microphonics measurement capability will be presented.

Netepenko, A.↗
DOE OSTI2026

Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events

Danovo Energy Solution's presented its paper named: Feature-Based PMU Event Classification under Variable PMU Participation and Overlapping Events at the 2026 Georgia Tech Fault & Disturbance Analysis Conference. The full paper can be found at OSTI ID# 3169150 Paper Abstract—Phasor Measurement Units (PMUs) stream time synchronized, high-resolution measurements from the grid, enabling data-driven techniques for event detection and classification. Accurate event classification improves grid reliability and stability. Events can be detected by varying numbers of PMUs and exhibit different durations depending on the event type. This variability challenges standard classifiers that require uniform input sizes. Moreover, multiple events may coincide, which increases classification complexity. Standard classifiers assign each instance to the class with the highest predicted probability, whereas overlapping events may exhibit comparable probabilities across multiple classes. In this study, to handle data size variability, we extract a wide range of time–frequency domain features from all available PMUs for each event into a fixed-length vector, facilitating the application of standard machine learning classifiers, including Random Forest, XGBoost, LightGBM, Support Vector Machine, and Multilayer Perceptron. To account for overlapping events, a probabilistic post-processing step is applied. For a given data instance, if multiple predicted class probabilities exceed 30% and the differences between them are less than 10%, the event is assigned to multiple classes. Experiments using real-world PMU data demonstrate that the Random Forest and XGBoost models achieve the highest accuracy, while the proposed post-processing method yields perfect classification performance on external unseen test sets.

Nematirad, Reza [Danova Energy Solutions]↗
DOE OSTI2026

Machine Learning-Based Anomaly Detection for PMT Data Quality Monitoring in the SBN and DUNE

Maintaining high-quality detector data is essential for achieving the scientific objectives of the Short-Baseline Neutrino (SBN) Program at Fermilab. Current data quality monitoring (DQM) procedures rely primarily on threshold-based metrics and manual inspection of detector monitoring plots, making the detection of subtle or gradually developing anomalies both time-consuming and dependent on expert interpretation. This project developed and evaluated a machine-learning workflow for automatically identifying anomalous photomultiplier tube (PMT) channels in the Short-Baseline Near Detector (SBND) using optical-hit amplitude data. A Python-based analysis program was developed to process ROOT files, extract statistical features describing individual PMT amplitude distributions, and generate feature vectors for anomaly detection. These features were used to train an Isolation Forest model using data representing normal detector operation. The trained model was subsequently applied to independent detector runs to identify channels exhibiting statistically unusual behavior relative to the learned reference response. To support expert interpretation, the workflow generated complementary diagnostic products, including anomaly score distributions, normalized amplitude comparisons, decision-tree visualizations, and principal component analysis (PCA) projections. This project demonstrated the feasibility of integrating unsupervised machine learning into detector data-quality monitoring and developed a complete workflow for automated PMT performance assessment to aid expert-driven review. Beyond its technical contributions, the VFP appointment fostered a research collaboration between Aurora University and Fermilab and provided direct workforce development benefits by training the visiting faculty member in detector-scale machine-learning methods that are now being incorporated into undergraduate coursework and research. The methodology developed here provides a foundation for future applications to ProtoDUNE and other liquid argon time projection chamber (LArTPC) detectors, contributing to ongoing efforts to improve detector reliability, reduce manual monitoring requirements, and enable scalable data quality monitoring for future large-scale neutrino experiments, including the Deep Underground Neutrino Experiment (DUNE).

Colón Santana, Juan A. [Unlisted, US, IL]↗
DOE OSTI2022

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗
NASA NTRS1980

Research on the application of a decoupling algorithm for structure analysis

The mathematical theory for decoupling mth-order matrix differential equations is presented. It is shown that the decoupling precedure can be developed from the algebraic theory of matrix polynomials. The role of eigenprojectors and latent projectors in the decoupling process is discussed and the mathematical relationships between eigenvalues, eigenvectors, latent roots, and latent vectors are developed. It is shown that the eigenvectors of the companion form of a matrix contains the latent vectors as a subset. The spectral decomposition of a matrix and the application to differential equations is given.

Denman, E. D.↗
NASA NTRS1981

Failure detection and isolation analysis of a redundant strapdown inertial measurement unit

The objective of this study was to define and develop techniques for failure detection and isolation (FDI) algorithms for a dual fail/operational redundant strapdown inertial navigation system are defined and developed. The FDI techniques chosen include provisions for hard and soft failure detection in the context of flight control and navigation. Analyses were done to determine error detection and switching levels for the inertial navigation system, which is intended for a conventional takeoff or landing (CTOL) operating environment. In addition, investigations of false alarms and missed alarms were included for the FDI techniques developed, along with the analyses of filters to be used in conjunction with FDI processing. Two specific FDI algorithms were compared: the generalized likelihood test and the edge vector test. A deterministic digital computer simulation was used to compare and evaluate the algorithms and FDI systems.

Motyka, P.↗