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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 649 records · Page 36

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NASA NTRS2014

The Broad-Band X-Ray Spectrum of IC 4329A from a Joint NuSTAR/Suzaku Observation

We have obtained a deep, simultaneous observation of the bright, nearby Seyfert galaxy IC 4329A with Suzaku and NuSTAR (Nuclear Spectroscopic Telescope Array). Through a detailed spectral analysis, we are able to robustly separate the continuum, absorption, and distant reflection components in the spectrum. The absorbing column is found to be modest (approximately 6 times 10 (sup 21) per square centimeter), and does not introduce any significant curvature in the Fe K band. We are able to place a strong constraint on the presence of a broadened Fe K alpha line (E (sub rest) equals 6.46 (from plus 0.08 to minus 0.07) kiloelectronvolts with sigma equals 0.33 (from plus 0.08 to minus 0.07) kiloelectronvolts and EW equals 34 (from plus 8 to minus 7) electronvolts), though we are not able to constrain any of the parameters of a relativistic reflection model. These results highlight the range in broad Fe K line strengths observed in nearby, bright, active galactic nuclei (roughly an order of magnitude), and imply a corresponding range in the physical properties of the inner accretion disk in these sources. We have also updated our previously reported measurement of the high-energy cutoff of the hard X-ray emission using both observatories rather than just NuSTAR alone: E (sub cut) equals 186 plus or minus 14 kiloelectronvolts. This high-energy cutoff acts as a proxy for the temperature of the coronal electron plasma, enabling us to further separate this parameter from the plasmas optical depth and to update our results for these parameters as well. We derive kT 50 (from plus 6 to minus 3) kiloelectronvolts with tau equals 2.34 (from plus +0.16 to minus 0.11) using a spherical geometry, kT equals 61 plus or minus1 kiloelectronvolt with tau equals 0.68 plus or minus 0.02 for a slab geometry, with both having an equivalent goodness-of-fit.

Dynamics - stars↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

This paper presents a technical approach to improve the confidence in the systems analysis process by integrating Uncertainty Quantification (UQ) techniques within a Model-Based Systems Analysis and Engineering (MBSA&E) framework. The MBSA&E architecture uses system models and multidisciplinary analytical solutions as central artifacts for system design and analysis. The integration of UQ enables engineers to assess and mitigate uncertainties associated with a system model, design parameters, and constraint inputs, leading to more complete design studies and further informed decision-making processes. The proposed approach leverages the strengths of MBSA&E and extends it with a UQ methodology to quantify uncertainties in the input parameters and to trace the uncertainties as they propagate throughout the system model. To demonstrate the effectiveness of an integrated MBSA&E-UQ approach, a case study involving a simplified analysis of a Transonic Truss-Braced Wing (TTBW) concept vehicle is performed. This integration enables a more comprehensive evaluation of system performance and behavior under uncertainty and a more robust approach for system design and analysis. Lastly, the paper addresses the challenges and considerations associated with integrating UQ into an MBSA&E framework.

systems analysis↗

NASA NTRSDate not supplied

Integration of Uncertainty Quantification in a Model-Based Systems Analysis and Engineering Framework

systems analysis↗

DOE OSTI2018

Automated Behavior Analysis of Malware: A Case Study of WannaCry Ransomware

Ransomware, a class of self-propagating malware that uses encryption to hold the victims’ data ransom, has emerged in recent years as one of the most dangerous cyber threats, with widespread damage; e.g., zero-day ransomware WannaCry has caused world-wide catastrophe, from knocking U.K. National Health Service hospitals offline to shutting down a Honda Motor Company in Japan [1]. Our close collaboration with security operations of large enterprises reveals that defense against ransomware relies on tedious analysis from high-volume systems logs of the first few infections. Sandbox analysis of freshly captured malware is also commonplace in operation. We introduce a method to identify and rank the most discriminating ransomware features from a set of ambient (non-attack) system logs and at least one log stream containing both ambient and ransomware behavior. These ranked features reveal a set of malware actions that are produced automatically from system logs, and can help automate tedious manual analysis. We test our approach using WannaCry and two polymorphic samples by producing logs with Cuckoo Sandbox during both ambient, and ambient plus ransomware executions. Our goal is to extract the features of the malware from the logs with only knowledge that malware was present. We compare outputs with a detailed analysis of WannaCry allowing validation of the algorithm’s feature extraction and provide analysis of the method’s robustness to variations of input data—changing quality/quantity of ambient data and testing polymorphic ransomware. Most notably, our patterns are accurate and unwavering when generated from polymorphic WannaCry copies, on which 63 (of 63 tested) antivirus (AV) products fail.

Chen, Qian↗

DOE OSTI2022

A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation: Preprint

This paper proposes a hybrid data and model-based anomaly detection for securing the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders (AE) are set up at the edge level by taking local DER data and detect anomalous operations by leveraging the reconstruction ability. In parallel, model-based state estimation (SE) is running at the system level by taking system models and measurements, the anomalies are identified by analyzing the measurements residual. The hybrid scheme preserves the benefits of both data-driven and model-based analysis and thus improves the robustness and accuracy of anomaly detection. It can be established by getting full use of the existing infrastructures in distribution grids. Numerical tests on a realistic distribution feeder in Southern California highlight the effectiveness as well as benefits of the proposed scheme.

anomaly detection↗

DOE OSTI2019

Dynamics of Multilayer Complex Infrastructure Networks

Our research effort models critical infrastructure systems as complex and interdependent networks, allowing for dynamic analysis of the resilience and robustness of these connected systems.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

CAMFeND: Credibility-Aware Multimodal Fake News Detection with Rotational Attention

In the evolving digital landscape, fake news is a significant challenge, influencing public perception and decision-making. Traditional detection approaches focus on single-modal data or simple multimodal fusion, often overlooking deeper interactions and news credibility. We propose a novel model addressing these limitations by introducing rotational attention and news domain information as a feature. Unlike static attention mechanisms, our rotational attention dynamically shifts query, key, and value roles across text and image inputs, enabling richer cross-modal interaction. Incorporating news domain information further enhances the model’s reliability by associating news posts with top domains extracted from Google search results, reducing false detections. This approach assesses both the content and the broader web context in which the news is discussed. Our model outperforms existing state-of-the-art methods by providing deeper, layered multimodal integration and domain information analysis, resulting in a more robust and adaptive fake news detection system.

Gupta, Nidhi↗

NASA NTRS1987

Image-analysis techniques for determination of morphology and kinematics in arctic sea ice

SAR data have been used to study sea ice with respect to its motion and formation/deformation. With the prospect of the Alaska SAR Facility development in the near future, there is a great need for robust and efficient sea-ice analysis techniques. This paper presents a sea-ice motion analysis technique that can be used for: (1) local motion analysis of a selected ice patch, and (2) a global ice motion over the entire image area. In order to meet the operational speed requirement (over fifty images per day) a sea-ice motion analysis technique has been developed which requires very little human interaction. The proposed technique uses a subset of easily distinguishable features to predict global motion characteristics. The developed technique is applied to two pairs of SEASAT SAR images, one pair with a minor motion of 'ice pack' and another with a larger and discontinuous motion of 'fast ice'. The new approach enables the development of a set of computer-aided tools for feature selection and registration and the implementation of an optimal search strategy for automatic template matching via a motion prediction model.

Lee, Meemong↗

NASA NTRS2001

Aeroservoelastic Uncertainty Model Identification from Flight Data

Uncertainty modeling is a critical element in the estimation of robust stability margins for stability boundary prediction and robust flight control system development. There has been a serious deficiency to date in aeroservoelastic data analysis with attention to uncertainty modeling. Uncertainty can be estimated from flight data using both parametric and nonparametric identification techniques. The model validation problem addressed in this paper is to identify aeroservoelastic models with associated uncertainty structures from a limited amount of controlled excitation inputs over an extensive flight envelope. The challenge to this problem is to update analytical models from flight data estimates while also deriving non-conservative uncertainty descriptions consistent with the flight data. Multisine control surface command inputs and control system feedbacks are used as signals in a wavelet-based modal parameter estimation procedure for model updates. Transfer function estimates are incorporated in a robust minimax estimation scheme to get input-output parameters and error bounds consistent with the data and model structure. Uncertainty estimates derived from the data in this manner provide an appropriate and relevant representation for model development and robust stability analysis. This model-plus-uncertainty identification procedure is applied to aeroservoelastic flight data from the NASA Dryden Flight Research Center F-18 Systems Research Aircraft.

Brenner, Martin J.↗

NASA NTRS2014

Seasonal Ventilation of the Stratosphere: Robust Diagnostics from One-Way Flux Distributions

We present an analysis of the seasonally varying ventilation of the stratosphere using one-way flux distributions. Robust transport diagnostics are computed using GEOSCCM subject to fixed present-day climate forcings. From the one-way flux, we determine the mass of the stratosphere that is in transit since entry through the tropical tropopause to its exit back into the troposphere, partitioned according to stratospheric residence time and exit location. The seasonalities of all diagnostics are quantified with respect to the month of year (a) when air enters the stratosphere, (b) when the mass of the stratosphere is partitioned, and (c) when air exits back into the troposphere. We find that the return flux, within 3 months since entry, depends strongly on when entry occurred: (34 +/- 10)% more of the air entering the stratosphere in July leaves poleward of 45 deg N compared to air that enters in January. The month of year when the air mass is partitioned is also found to be important: The stratosphere contains about six times more air of tropical origin during late summer and early fall that will leave poleward of 45 deg within 6 months since entering the stratosphere compared to during late winter to late spring. When the entire mass of the air that entered the stratosphere at the tropics regardless of its residence time is considered, we find that (51 +/- 1)% and (39 +/- 2)% will leave poleward of 10 deg in the Northern Hemisphere (NH) and Southern Hemisphere (SH), respectively.

Stratosphere-Troposphere Exchange↗

DOE OSTI2025

BLADE: An Automated Framework for Classifying Light Curves from the Center for Near-Earth Object Studies Fireball Database

Fireballs (bolides) are high-energy luminous phenomena produced when meteoroids and small asteroids enter Earth’s atmosphere at hypersonic speeds, often resulting in fragmentation or complete disintegration accompanied by significant energy release. The resulting bolide light curves capture temporal brightness variations as these objects traverse increasingly dense atmospheric layers, providing essential information on meteoroid entry dynamics, fragmentation behavior, and atmospheric energy deposition processes. The Center for Near-Earth Object Studies’ (CNEOS) continuously expanding fireball database offers a globally comprehensive archive of bolide events, including light curves and associated metadata. Events associated with infrasound detections allow direct correlations between acoustic signatures and light curve features, therefore enabling detailed analyses of fragmentation dynamics and energy deposition. Here, we introduce Bolide Light-curve Analysis and Discrimination Explorer (BLADE), a robust and high-fidelity framework specifically designed to analyze bolide light curves for objects detected from space. BLADE incorporates a processing pipeline integrating Savitzky–Golay filtering, prominence-based peak detection, and gradient analysis, enabling systematic identification and classification of fragmentation events and their associated energy release characteristics. Preliminary results demonstrate that BLADE reliably distinguishes distinct bolide behaviors, providing an objective, scalable methodology for characterization and analysis of large bolide light curve data sets. This foundational work establishes a novel pathway for advanced bolide research, with promising applications in planetary defense and global atmospheric monitoring. Future research should adopt an integrative approach combining CNEOS optical data with complementary infrasound measurements, further clarifying relationships between bolide energy deposition and acoustic signatures, thus refining our understanding of meteoroid and asteroid atmospheric entry processes.

Asteroids↗

DOE OSTI2021

Quantifying experimental edge plasma evolution via multidimensional adaptive Gaussian process regression

The edge density and temperature of tokamak plasmas are strongly correlated with energy and particle confinement and their quantification is fundamental to understanding edge dynamics. These quantities exhibit behaviours ranging from sharp plasma gradients and fast transient phenomena (e.g. transitions between low and high confinement regimes) to nominal stationary phases. Analysis of experimental edge measurements therefore require robust fitting techniques to capture potentially stiff spatiotemporal evolution. Additionally, fusion plasma diagnostics inevitably involve measurement errors and data analysis requires a statistical framework to accurately quantify uncertainties. This paper outlines a generalized multidimensional adaptive Gaussian process routine capable of automatically handling noisy data and spatiotemporal correlations. We focus on the edge-pedestal region in order to underline advancements in quantifying time-dependent plasma profiles including transport barrier formation on the Alcator C-Mod tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2009

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Bakhtiari-Nejad, Maryam↗

NASA NTRS1999

Flow of GE90 Turbofan Engine Simulated

The objective of this task was to create and validate a three-dimensional model of the GE90 turbofan engine (General Electric) using the APNASA (average passage) flow code. This was a joint effort between GE Aircraft Engines and the NASA Lewis Research Center. The goal was to perform an aerodynamic analysis of the engine primary flow path, in under 24 hours of CPU time, on a parallel distributed workstation system. Enhancements were made to the APNASA Navier-Stokes code to make it faster and more robust and to allow for the analysis of more arbitrary geometry. The resulting simulation exploited the use of parallel computations by using two levels of parallelism, with extremely high efficiency.The primary flow path of the GE90 turbofan consists of a nacelle and inlet, 49 blade rows of turbomachinery, and an exhaust nozzle. Secondary flows entering and exiting the primary flow path-such as bleed, purge, and cooling flows-were modeled macroscopically as source terms to accurately simulate the engine. The information on these source terms came from detailed descriptions of the cooling flow and from thermodynamic cycle system simulations. These provided boundary condition data to the three-dimensional analysis. A simplified combustor was used to feed boundary conditions to the turbomachinery. Flow simulations of the fan, high-pressure compressor, and high- and low-pressure turbines were completed with the APNASA code.

Veres, Joseph P.↗

DOE OSTI2017

Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling

Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Establishing Cost-Effective Allocation of Proton Therapy for Breast Irradiation

Purpose: Cardiac toxicity due to conventional breast radiation therapy (RT) has been extensively reported, and it affects both the life expectancy and quality of life of affected women. Given the favorable oncologic outcomes in most women irradiated for breast cancer, it is increasingly paramount to minimize treatment side effects and improve survivorship for these patients. Proton RT offers promise in limiting heart dose, but the modality is costly and access is limited. Using cost-effectiveness analysis, we provide a decision-making tool to help determine which breast cancer patients may benefit from proton RT referral. Methods and Materials: A Markov cohort model was constructed to compare the cost-effectiveness of proton versus photon RT for breast cancer management. The model was analyzed for different strata of women based on age (40 years, 50 years, and 60 years) and the presence or lack of cardiac risk factors (CRFs). Model entrants could have 1 of 3 health states: healthy, alive with coronary heart disease (CHD), or dead. Base-case analysis assumed CHD was managed medically. No difference in tumor control was assumed between arms. Probabilistic sensitivity analysis was performed to test model robustness and the influence of including catheterization as a downstream possibility within the health state of CHD. Results: Proton RT was not cost-effective in women without CRFs or a mean heart dose (MHD) <5 Gy. Base-case analysis noted cost-effectiveness for proton RT in women with ≥1 CRF at an approximate minimum MHD of 6 Gy with a willingness-to-pay threshold of $100,000/quality-adjusted life-year. For women with ≥1 CRF, probabilistic sensitivity analysis noted the preference of proton RT for an MHD ≥5 Gy with a similar willingness-to-pay threshold. Conclusions: Despite the cost of treatment, scenarios do exist whereby proton therapy is cost-effective. Referral for proton therapy may be cost-effective for patients with ≥1 CRF in cases for which photon plans are unable to achieve an MHD <5 Gy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2013

Lorentz Invariance Violation: the Latest Fermi Results and the GRB-AGN Complementarity

Because they are bright and distant, Gamma-ray Bursts (GRBs) have been used for more than a decade to test propagation of photons and to constrain relevant Quantum Gravity (QG) models in which the velocity of photons in vacuum can depend on their energy. With its unprecedented sensitivity and energy coverage, the Fermi satellite has provided the most constraining results on the QG energy scale so far. In this talk, the latest results obtained from the analysis of four bright GRBs observed by the Large Area Telescope will be reviewed. These robust results, cross-checked using three different analysis techniques set the limit on QG energy scale at E(sub QG,1) greater than 7.6 times the Planck energy for linear dispersion and E(sub QG,2) greater than 1.3 x 10(exp 11) gigaelectron volts for quadratic dispersion (95% CL). After describing the data and the analysis techniques in use, results will be discussed and confronted to latest constraints obtained with Active Galactic Nuclei.

Quantum gravity↗

NASA NTRS1990

Analysis of gain scheduled control for nonlinear plants

Gain scheduling has proven to be a successful design methodology in many engineering applications. In the absence of a sound theoretical analysis, these designs come with no guarantees of the robustness, performance, or even nominal stability of the overall gain-scheduled design. An analysis is presented for two types of nonlinear gain-scheduled control systems: (1) scheduling on a reference trajectory and (2) scheduling on the plant output. Conditions which guarantee stability, robustness, and performance properties of the global gain schedule designs are given. These conditions confirm and formalize popular notions regarding gain-scheduled designs, such as that the scheduling variable should vary slowly and capture the plant's nonlinearities.

Shamma, Jeff S.↗