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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Real-time spatio-temporal coherence estimation for autonomous mode identification and invariance tracking

A general method of anomaly detection from time-correlated sensor data is disclosed. Multiple time-correlated signals are received. Their cross-signal behavior is compared against a fixed library of invariants. The library is constructed during a training process, which is itself data-driven using the same time-correlated signals. The method is applicable to a broad class of problems and is designed to respond to any departure from normal operation, including faults or events that lie outside the training envelope.

James, Mark L.↗
NASA NTRS1980

Global zones of energetic particle precipitation

The paper identifies global zones of energetic particle precipitation in the nighttime atmosphere during disturbed magnetic conditions in rocket, satellite, and ground-based measurements. The known equatorial zone of precipitated energetic ions and neutrals is found at altitudes above 170 km, with its origin in the double-charge-exchange process of hydrogen and helium with the ring current. The flux of electrons increases linearly with altitude in the region 100-300 km and correlates with the 391.4 nm radiation intensity and magnetic activity. Finally, it is shown that the South Atlantic magnetic anomaly provides additional support for the identification of distinct low and mid-latitude zones; poleward from the plasmapause the precipitation flux is nearly isotropic and variable, and it consists of electrons and ions with the maximum intensity of the proton auroral zone occurring about 5 deg equatorward of the maximum of the electron auroral zone.

Voss, H. D.↗
NASA NTRS2010

3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events

An analytical, advanced imaging method has been developed for the initial monitoring and identification of foam debris and similar anomalies that occur post-launch in reference to the space shuttle s external tank (ET). Remote sensing technologies have been used to perform image enhancement and analysis on high-resolution, true-color images collected with the DCS 760 Kodak digital camera located in the right umbilical well of the space shuttle. Improvements to the camera, using filters, have added sharpness/definition to the image sets; however, image review/analysis of the ET has been limited by the fact that the images acquired by umbilical cameras during launch are two-dimensional, and are usually nonreferenceable between frames due to rotation translation of the ET as it falls away from the space shuttle. Use of stereo pairs of these images can enable strong visual indicators that can immediately portray depth perception of damaged areas or movement of fragments between frames is not perceivable in two-dimensional images. A stereoscopic image visualization system has been developed to allow 3D depth perception of stereo-aligned image pairs taken from in-flight umbilical and handheld digital shuttle cameras. This new system has been developed to augment and optimize existing 2D monitoring capabilities. Using this system, candidate sequential image pairs are identified for transformation into stereo viewing pairs. Image orientation is corrected using control points (similar points) between frames to place the two images in proper X-Y viewing perspective. The images are then imported into the WallView stereo viewing software package. The collected control points are used to generate a transformation equation that is used to re-project one image and effectively co-register it to the other image. The co-registered, oriented image pairs are imported into a WallView image set and are used as a 3D stereo analysis slide show. Multiple sequential image pairs can be used to allow forensic review of temporal phenomena between pairs. The observer, while wearing linear polarized glasses, is able to review image pairs in passive 3D stereo.

Brown, Richard↗
NASA NTRS2012

Evaluation ofthe Middle East and North Africa Land Data Assimilation System

The Middle East and North Africa (MENA) region is dominated by dry, warm deserts, areas of dense population, and inefficient use of fresh water resources. Due to the scarcity, high intensity, and short duration of rainfall in the MENA, the region is prone to hydro climatic extremes that are realized by devastating floods and times of drought. However, given its widespread water stress and the considerable demand for water, the MENA remains relatively poorly monitored. This is due in part to the shortage of meteorological observations and the lack of data sharing between nations. As a result, the accurate monitoring of the dynamics of the water cycle in the MENA is difficult. The Land Data Assimilation System for the MENA region (MENA LDAS) has been developed to provide regional, gridded fields of hydrological states and fluxes relevant for water resources assessments. As an extension of the Global Land Data Assimilation System (GLDAS), the MENA LDAS was designed to aid in the identification and evaluation of regional hydrological anomalies by synergistically combining the physically-based Catchment Land Surface Model (CLSM) with observations from several independent data products including soil-water storage variations from the Gravity Recovery and Climate Experiment (GRACE) and irrigation intensity derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). In this fashion, we estimate the mean and seasonal cycle of the water budget components across the MENA.

Bolten, John D.↗
DOE OSTI2025

Reinforcement Learning for Anomaly Detection in Nuclear Power Plant Operation and Maintenance

In nuclear power plants (NPPs), timely identification of sensor and human errors is critical to ensure safe and efficient plant operations. Anomaly detection models can be employed for this task. However, traditional anomaly detection approaches may have high dependency on labeled datasets and struggle with adaptability in complex, dynamic environments. Reinforcement learning (RL) has demonstrated significant potential in fault diagnosis and anomaly detection; however, its application to anomaly detection in NPPs remains a relatively underexplored research direction. Hence, to address this gap, in this study, we present a novel physics-informed reinforcement learning model, PIRL-AD: Physics-Informed Reinforcement Learning for Anomaly Detection, that integrates domain knowledge from calorimetric equations into the RL framework for enhanced sensor and human error anomaly detection. We evaluate the performance of PIRL-AD against a non-physics informed RL benchmark and a support vector machine (SVM) on data collected from a forced flow loop testbed. Experimental results suggest that PIRL-AD outperforms other baselines on a range of anomalous datasets that include both sensor and human-induced anomalies across key performance metrics, statistically outperforming the RL and SVM benchmarks with respect to geometric mean (respectively, 92.96% vs. 91.06% vs. 83.01%) and F1-score (respectively, 89.23% vs. 86.98% vs. 77.01%). Furthermore, the findings suggest the potential of physics-integrated reinforcement learning models for enhanced anomaly detection performance in NPPs.

Reinforcement learning↗
DOE OSTI2026

SMEFT ATLAS: The landscape beyond the Standard Model

The Standard Model Effective Field Theory (SMEFT) based on the unbroken gauge group SU(3) 𝐶 ⊗SU(2) 𝐿 ⊗U(1) 𝑌 and containing only particles of the Standard Model (SM) has developed in the last decade to a mature field. It is the framework to be used in the energy gap from scales sufficiently higher than the electroweak scale up to the lowest energy scale at which new particles show up. We summarize the present status of this theory with a particular emphasize on its role in the indirect search for new physics (NP). While flavour physics of both quarks and leptons is the main topic of our review, we also discuss electric dipole moments, anomalous magnetic moments (𝑔−2) 𝜇,𝑒 , 𝑍-pole observables, Higgs observables and high-𝑝𝑇 scattering processes within the SMEFT. We group the observables into ten classes and list for each class the most relevant operators and the corresponding renormalization group equations (RGEs). We exhibit the correlations between different classes implied both by the operator mixing and the SU(2) 𝐿 gauge symmetry. Our main goal is to provide an insight into the complicated operator structure of this framework which hopefully will facilitate the identification of valid ultraviolet completions behind possible anomalies observed in future data. Numerous colourful charts, and 85 tables, while representing rather complicated RG evolution from the NP scale down to the electroweak scale, beautify the involved SMEFT landscape. Over 1000 references to the literature underline the importance and the popularity of this field. We discuss both top-down and bottom-up approaches as well as their interplay. This allows us eventually to present an atlas of different landscapes beyond the SM that includes heavy gauge bosons and scalars, vector-like quarks and leptons and leptoquarks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

A data base describing low-gravity fluids and materials processing experiments

A data base documenting information on approximately 600 fluids and materials processing experiments performed in a low-gravity environment has been prepared at NASA Marshall Space Flight Center (MSFC). The compilation was designed to document all such experimental efforts performed: (1) on U.S. manned space vehicles; (2) on payloads deployed from U.S. manned space vehicles; and (3) on all domestic and international sounding rocket programs (excluding those of the U.S.S.R. and China). Identification of major (reported) sources of significant anomalies during 100 of the experiments is reported and discussed. Further, a preliminary summary of the number of these 100 investigations which experienced an anomaly affecting a certain percentage of the experimental results/objectives is presented.

Winter, C. A.↗
NASA NTRS1999

Wind Speed Measurement from Bistatically Scattered GPS Signals

Instrumentation and retrieval algorithms are described which use the forward, or bistatically scattered range-coded signals from the Global Positioning System (GPS) radio navigation system for the measurement of sea surface roughness. This roughness is known to be related directly to the surface wind speed. Experiments were conducted from aircraft along the TOPEX ground track, and over experimental surface truth buoys. These flights used a receiver capable of recording the cross correlation power in the reflected signal. The shape of this power distribution was then compared against analytical models derived from geometric optics. Two techniques for matching these functions were studied. The first recognized the most significant information content in the reflected signal is contained in the trailing edge slope of the waveform. The second attempted to match the complete shape of the waveform by approximating it as a series expansion and obtaining the nonlinear least squares estimate. Discussion is also presented on anomalies in the receiver operation and their identification and correction.

Garrison, James L.↗
NASA NTRS2018

Probing Neodymium Isotopic Variations in the Inner Solar System

One of the key problems in planetary science is the identification of the building blocks of Earth, and whether they exist within our current collection of meteorites. Stable mass independent isotopic anomalies, usually nucleosynthetic in origin, are a key tool in fingerprinting material coming from different accretionary regions within the protoplanetary disk. For a number of isotopic systems such as O, Ni, Ti and Cr, enstatite chondrites (EC) appear to be the strongest candidates for Earth's building blocks, despite their low Mg/Si ratios relative to the bulk Earth. It has been proposed that Earth, the Moon-forming impactor and enstatite chondrites all were originally sourced from the same reservoir in the protoplanetary disk, but subsequently experienced divergent chemical evolution pathways. This was recently challenged by who used the correlation between Mo and Nd isotopes in bulk meteorites to argue that such a reservoir does not exist as the isotopic composition of enstatite chondrites is resolvable from Earth. However, in detail the Nd isotopic ratios of EC ((142)Nd/(144)Nd, (148)Nd/(144)Nd, (150)Nd/(144)Nd) show considerable variability, and overlap significantly with the isotopic composition of both the bulk Earth and ordinary chondrites (OC). previously identified Nd isotopic variability in EC, linking it to the degree of equilibration the meteorite had experienced, however they only focused on collecting high precision (142)Nd/(144)Nd, which also has contributions from the decay of the short-lived Sm-146 nuclide (t(sub 1/2) ~103 Myr), making identification of nucleosynthetic anomalies less clear. While the study of reports all the Nd isotopic ratios measured at high precision, only equilibrated EC were analyzed. Therefore, with the currently published data it is unclear to what extent thermal equilibration in the EC is responsible for the variation observed in the stable Nd isotopic ratios, and whether the EC reservoir can be resolved from Earth. In order to better understand the genetic relationship between enstatite chondrites and the Earth we are carrying out a more systematic study including both equilibrated and unequilibrated enstatite chondrites, focusing on high precision analysis of all the stable Nd isotopic ratios.

SOLAR SYSTEM↗
DOE OSTI2025

Coincident learning for beam-based rf station fault identification using phase information at the SLAC linac coherent light source

Anomalies in radio-frequency (rf) stations can result in unplanned downtime and performance degradation in linear accelerators such as SLAC’s Linac Coherent Light Source (LCLS). Detecting these anomalies is challenging due to the complexity of accelerator systems, high data volume, and scarcity of labeled fault data. Prior work identified faults using beam-based detection, combining rf amplitude and beam position monitor data. Due to the simplicity of the rf amplitude data, classical methods are sufficient to identify faults, but the recall is constrained by the low-frequency and asynchronous characteristics of the data. In this work, we leverage high-frequency, time-synchronous rf phase data to enhance anomaly detection in the LCLS accelerator. Due to the complexity of phase data, classical methods fail, and we instead train deep neural networks within the Coincident Anomaly Detection (CoAD) framework. We find that applying CoAD to phase data detects nearly 3 times as many anomalies as when applied to amplitude data, while achieving broader coverage across rf stations. Furthermore, the rich structure of phase data enables us to cluster anomalies into distinct physical categories. Through the integration of auxiliary system status bits, we link clusters to specific fault signatures, providing additional granularity for uncovering the root cause of faults. We also investigate interpretability via Shapley values, confirming that the learned models focus on the most informative regions of the data and providing insight for cases where the model makes mistakes. This work demonstrates that phase-based anomaly detection for rf stations improves both diagnostic coverage and root cause analysis in accelerator systems and that deep neural networks are essential for effective analysis.

Accelerator Physics (physics.acc-ph)↗
NASA NTRS2012

Entry, Descent, and Landing Communications for the 2011 Mars Science Laboratory

The Mars Science Laboratory (MSL), established as the most advanced rover to land on the surface of Mars to date, launched on November 26th, 2011 and arrived to the Martian Gale Crater during the night of August 5th, 2012 (PDT). MSL will investigate whether the landing region was ever suitable to support carbon-based life, and examine rocks, soil, and the atmosphere with a sophisticated suite of tools. This paper addresses the flight system requirement by which the vehicle transmitted indications of the following events using both X-band tones and UHF telemetry to allow identification of probable root causes should a mission anomaly have occurred: Heat-Rejection System (HRS) venting, completion of the cruise stage separation, turn to entry attitude, atmospheric deceleration, bank angle reversal commanded, parachute deployment, heatshield separation, radar ground acquisition, powered descent initiation, rover separation from the descent stage, and rover release. During Entry, Descent, and Landing (EDL), the flight system transmitted a UHF telemetry stream adequate to determine the state of the spacecraft (including the presence of faults) at 8 kbps initiating from cruise stage separation through at least one minute after positive indication of rover release on the surface of Mars. The flight system also transmitted X-band semaphore tones from Entry to Landing plus one minute although since MSL was occulted, as predicted, by Mars as seen from the Earth, Direct-To-Earth (DTE) communications were interrupted at approximately is approx. 5 min after Entry ( approximately 130 prior to Landing). The primary data return paths were through the Deep Space Network (DSN) for DTE and the existing Mars network of orbiting assets for UHF, which included the Mars Reconnaissance Orbiter (MRO), Mars Odyssey (ODY), and Mars Express (MEX) elements. These orbiters recorded the telemetry data stream and returned it back to Earth via the DSN. The paper also discusses the total power received during EDL and the robustness of the telecom design strategy used to ensure EDL communications coverage.

relay operations↗
NASA NTRS2015

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

The El Nino-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with Coupled General Circulation Models (CGCMs) to investigate how regional precipitation in the 21st century may be affected by changes in both ENSO-driven precipitation variability and slowly-evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of 20th century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in 21st century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with 20th century observations and more stationary during the 21st century. Finally, the model-predicted 21st century rainfall response to cENSO is decomposed into the sum of three terms: 1) the 21st century change in the mean state of precipitation; 2) the historical precipitation response to the cENSO pattern; and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Celine J W Bonfils↗
NASA NTRS2015

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Simulation↗
DOE OSTI2025

Braxton Marlatt Intern Poster

The Internet of Things (IoT) encompasses a vast network of interconnected devices embedded with software, sensors, and network connectivity, enabling data collection and exchange. While IoT technology revolutionizes various industries, it also introduces significant security challenges. This research focuses on enhancing IoT security through the implementation of Zero Trust Architecture concepts, specifically targeting the Network and Device pillars of the Cybersecurity and Infrastructure Security Agency’s Zero Trust Maturity Model. By generating Codified Attack Surfaces (CAS) using custom Structured Threat Information eXpression bundles, this project aims to provide enhanced visibility into network communications, detect vulnerabilities in device firmware, and improve the overall security posture for IoT devices and networks. The methodology involves defining custom STIX schema and objects, collecting data from intra-IoT traffic, external network traffic, and firmware analysis, and automating the conversion and correlation of this data into STIX bundles. The automated generation of attack surfaces offers comprehensive insights into activity, vulnerabilities, and anomalies within an IoT environment, enabling proactive threat identification and mitigation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1997

Cryptoblemes: A New Discovery with Major Economic Implications and Profound Changes to the Geologic Paradigm

Cryptoblemes are subtle impact shock signatures imprinted by cosmic debris on the crustal surfaces of lunar planetary bodes. These signatures constitute a complex cumulative overprinting of topographic, structural geophysical, and tectonic patterns that have a conspicuous radial centric multiringed symmetry. The geometry and distribution of cryptoblemes on Earth is comparable to the size and density of impact features on lunar planetary surfaces. Analysis of satellite imagery, sea-floor sonar, side-looking radar and aerial photographs of specific sites reveals new criteria for the identification and confirmation of impact-shock signatures. These criteria include joint and foliation patterns with asbestiform minerals, ribbon-quartz, spheroidal weathering, domal exfoliation, pencil shale, and shock spheres, which may originate from hydrocavitation of water-saturated sedimentary rocks. Cryptoblemes may also be associated with breccia pipes, sinkholes, buttes, mesas, and bogs, high-Rn anomalies, nodular concentrations, and earthquake epicenters. Major implications of cryptobleme identification include exploratory targeting of hydrocarbon and mineral deposits and the explanation of their origins. Analysis of known mineral deposits, structural traps and sedimentary basins show a direct correlation with cryptobleme patterns. Significant geologic paradigm shifts related to cryptoblemes include mountain building processes, structural orogenies, induced volcanism, earthquake origins, hydrocarbon diagenesis, formation mineral deposits, continental rifting, and plate movements, magnetic overprinting and local regional, and global geologic extinction and speciation patterns. Two figures provide a comparison between a multiring impact overprint in water and multiring cryptobleme in the U.S. basin range. (Additional information is contained in the original document).

Windolph, J., Jr.↗
NASA NTRS2019

Ask-The-Expert: Minimizing Human Review for Big Data Analytics Through Active Learning

In this CIF project, we worked toward semi-automating knowledge discovery from anomaly detection algorithms through the use of active learning. Active learning is an area of research within machine learning that uses an "expert in the loop" to learn from large data sets that have very few annotations or labels available, and where providing such labels is expensive. In our case, the task can be defined as the identification of safety events from flight operational data. Since traditional anomaly detection algorithms cannot differentiate between operationally relevant and irrelevant statistical anomalies, Subject Matter Experts (SMEs) have a lengthy and expensive burden of investigating every example identified by the detection algorithm, classifying and labeling them as relevant or irrelevant. Active learningidentifies the unlabeled example for which a label would most improve the classifier, asks the domain expert for a label, and repeats this process until there are no more resources (time, budget) available for labeling or a minimum required performance is reached. A positive label indicates an operationally significant safety event whereas a negative label indicates otherwise. Based on these few labels we propose to build an active learning system that utilizes the SME's time in the most effective manner by iteratively asking for labels for as few informative instances as possible. Our work was proposed to be a stepping stone toward implementation and deployment of the system with user interface to be pursued by the Aviation Operations and Safety Program (AOSP) given its interest in safety monitoring and discovery of safety incidents.

aviation safety↗
NASA NTRS2020

In-Flight Detection of Vibration Anomalies in Unmanned Aerial Vehicles

Owing to the frequency of occurrence and high risk associated with bearings, identification and characterization of bearing faults in motors via nondestructive evaluation (NDE) methods have been studied extensively, amongst which vibration analysis has been found to be a promising technique for early diagnosis of anomalies. However, a majority of the existing techniques rely on vibration sensors attached onto or in close proximity to the motor in order to collect signals with a relatively high SNR. Due to weight and space restrictions, these techniques cannot be used in unmanned aerial vehicles (UAVs), especially during flight operations since accelerometers cannot be attached onto motors in small UAVs. Small UAVs are often subjected to vibrational disturbances caused by multiple factors such as weather turbulence, propeller imbalance or bearing faults. Such anomalies may not only pose risks to UAV's internal circuitry, components or payload, they may also generate undesirable noise level particularly for UAVs expected to fly in low-altitudes or urban canyon. This paper presents a detailed discussion of challenges in in-flight detection of bearing failure in UAVs using existing approaches and offers potential solutions to detect overall vibration anomalies in small UAV operations based on IMU data.

Portia Banerjee↗
DOE OSTI2026

Search for resonances decaying to an anomalous jet and a Higgs boson in proton–proton collisions at $\sqrt{s}=13\,\text {Te}\hspace{-.08em}\text {V}$

This paper presents a search for new physics through the process where a massive particle, X, decays into a Higgs boson and a second particle, Y. The Higgs boson subsequently decays into a bottom quark–antiquark pair, which is reconstructed as a single large-radius jet. The decay products of Yare also assumed to produce a single large-radius jet. The identification of the Yparticle is enhanced by computing the anomaly score of its candidate jet using an autoencoder, which measures deviations from typical quark- or gluon-induced jets. This allows a simultaneous search for multiple Ydecay scenarios within a single analysis. In the main benchmark process, Yis a scalar particle that decays into a Wboson pair. Two other scalar Ydecay processes are also considered as benchmarks: decays to a light quark–antiquark pair, and decays to a top quark–antiquark pair. A fourth benchmark process considers Yas a hadronically decaying top quark, arising from the decay of a vector-like quark into a top quark and a Higgs boson. Data recorded by the CMS experiment at a center-of-mass energy of 13 TeV in 2016–2018, corresponding to an integrated luminosity of 138 fb -1 , are analyzed. The search covers Xmasses between 1.4 and 3.0 TeV and Ymasses between 90 and 400 TeV, with all simulated signals produced in the narrow-width approximation. No significant excess above the standard model background expectation is observed. The most stringent upper limits to date are placed on benchmark signal cross sections for various masses of X and Y particles

Hayrapetyan, A. [Yerevan Physics Institute]↗