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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Separating Sensor Anomalies From Process Anomalies in Data-Driven Anomaly Detection

Data-driven anomaly detection over time series data is studied from the perspective of separating data anomalies—corresponding to sensor failures—from process anomalies—that arise from equipment or operational failures. Herein, a semi-supervised approach is proposed that utilizes two predictive models trained on non-anomalous data using two different sensor groups as inputs, and a nested hypothesis test to reliably classify data or process anomalies. Conditions are derived on choice of sensor groups to guarantee reliable detection, and a case study is presented to demonstrate the proposed classification approach.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Effects of Longwave Cloud Radiative Forcing Anomalies on the Atmospheric Response to Equatorial Pacific Sea Surface Temperature Anomalies

The latest version of the National Center for Atmospheric Research community climate model (CCM2) has been used to investigate cloud radiative forcing (CRF) anomalies associated with equatorial Pacific sea surface temperature (SST) anomalies and the effects of the longwave CRF (LWCRF) anomalies on the atmospheric response to the SST anomalies. The SST anomalies cause large CRF anomalies, both longwave and shortwave, as well as latent heat anomalies at low latitudes on a global scale. The relative magnitude of the simulated longwave and shortwave CRF anomalies is consistent with the result of the Earth Radiation Budget Experiment (ERBE), implying that cloud height and cloud radiative properties such as emissivity and reflectivity are well simulated by the model. The LWCRF anomaly strongly enhances the precipitation anomaly in the whole tropical belt. The positive (negative) LWCRF anomaly warms (cools) the troposphere and destabilizes (stabilizes) the upper troposphere. The LWCRF anomaly enhances the Southern Oscillation and the related Walker circulation anomaly. The effects of the LWCRF anomaly are essential to the northern hemispheric extratropical circulation anomaly, the Pacific/North American pattern.

Chen, M.↗
DOE OSTI2025

Anomaly Identification of Synchronized Voltage Waveform for Situational Awareness of Low Inertia Systems

Inverter-based resources (IBRs) such as photovoltaics (PVs), wind turbines, and battery energy storage systems (BESSs) are widely deployed in low-carbon power systems. However, these resources typically do not provide the inertia needed for grid stability, resulting in a low-inertia power system. IBRs and lack of inertia have been known to cause anomalies such as waveform distortions and wideband oscillations in power systems due to the limited inertia level, leading to increased generation trips and load shedding. Here, to achieve effective anomaly identification, this paper proposes a synchro-waveform-based algorithm utilizing real-time synchronized voltage waveform measurements from waveform measurement units (WMUs). In the proposed method, different physical characteristics, as well as statistical features, are extracted from synchronized voltage waveform measurements to filter anomalies. Then, the anomaly identification approach based on the random forest is developed and deployed into the FNET/GridEye system considering trade-offs among accuracy, computational burden, and deployment cost. Moreover, four WMUs are specially designed and deployed on Kauai Island to receive instantaneous synchronized voltage waveform measurements. To verify the performance of the proposed algorithm, different experiments are carried out with collected field test data. The result demonstrates that the performance of the proposed synchro-waveform-based anomaly categorization algorithm can accurately identify anomalies 95.35% of the time, which has comparable performance among benchmarking algorithms.

Situational awareness↗
NASA NTRS1982

Gravity and geoid anomalies of the Philippine Sea: Evidence on the depth of compensation for the negative residual water depth anomaly

A negative free-air gravity anomaly which occurs in the central part of the Philippine Sea was examined to determine the distribution and nature of possible regional mass excesses or deficiencies. Geoid anomalies from GEOS-3 observation were positive. A negative residual geoid anomaly consistent with the area of negative free-air gravity anomalies were found. Theoretical gravity-topography and geoid-topography admittance functions indicated that high density mantle at about 60 km dept could account for the magnitudes of the gravity and residual geoid anomaly and the 1 km residual water depth anomaly in the Philippine Sea. The negative residual depth anomaly may be compensated for by excess density in the uppermost mantle, but the residual geoid and regional free-air gravity anomalies and a slow surface wave velocity structure might result from low-density warm upper mantle material lying beneath the zone of high-density uppermost mantle. From a horizontal disk approximation, the depth of the low-density warm mantle was estimated to be on the order of 200 km.

Bowin, C.↗
DOE OSTI2022

Condition monitoring and anomaly detection in cyber-physical systems

The modern industrial environment is equipping myriads of smart manufacturing machines where the state of each device can be monitored continuously. Such monitoring can help identify possible future failures and develop a cost-effective maintenance plan. However, it is a daunting task to perform early detection with low false positives and negatives from the huge volume of collected data. This requires developing a holistic machine learning framework to address the issues in condition monitoring of high priority components and develop efficient techniques to detect anomalies that can detect and possibly localize the faulty components. This paper presents a comparative analysis of recent machine learning approaches for robust, cost-effective anomaly detection in cyber-physical systems. While detection has been extensively studied, very few researchers have analyzed the localization of the anomalies. We show that supervised learning outperforms unsupervised algorithms. For supervised cases, we achieve near-perfect accuracy of 98% (specifically for tree-based algorithms). In contrast, the best-case accuracy in the unsupervised cases was 63%—the area under the receiver operating characteristic curve (AUC) exhibits similar outcomes as an additional metric.

Marfo, William↗
NASA NTRS1985

Satellite magnetic anomalies over subduction zones - The Aleutian Arc anomaly

Positive magnetic anomalies seen in MAGSAT average scalar anomaly data overlying some subduction zones can be explained in terms of the magnetization contrast between the cold subducted oceanic slab and the surrounding hotter, nonmagnetic mantle. Three-dimensional modeling studies show that peak anomaly amplitude and location depend on slab length and dip. A model for the Aleutian Arc anomaly matches the general trend of the observed MAGSAT anomaly if a slab thickness of 7 km and a relatively high (induced plus viscous) magnetization contrast of 4 A/m are used. A second source body along the present day continental margin is required to match the observed anomaly in detail, and may be modeled as a relic slab from subduction prior to 60 m.y. ago.

Clark, S. C.↗
DOE OSTI2022

Cosmology intertwined: A review of the particle physics, astrophysics, and cosmology associated with the cosmological tensions and anomalies

The standard Λ Cold Dark Matter (ΛCDM) cosmological model provides a good description of a wide range of astrophysical and cosmological data. However, there are a few big open questions that make the standard model look like an approximation to a more realistic scenario yet to be found. In this paper, we list a few important goals that need to be addressed in the next decade, taking into account the current discordances between the different cosmological probes, such as the disagreement in the value of the Hubble constant H 0 , the σ 8 – S 8 tension, and other less statistically significant anomalies. While these discordances can still be in part the result of systematic errors, their persistence after several years of accurate analysis strongly hints at cracks in the standard cosmological scenario and the necessity for new physics or generalisations beyond the standard model. In this paper, we focus on the 5.0 σ tension between the Planck CMB estimate of the Hubble constant H 0 and the SH0ES collaboration measurements. After showing the H 0 evaluations made from different teams using different methods and geometric calibrations, we list a few interesting new physics models that could alleviate this tension and discuss how the next decade's experiments will be crucial. Moreover, we focus on the tension of the Planck CMB data with weak lensing measurements and redshift surveys, about the value of the matter energy density Ω m , and the amplitude or rate of the growth of structure ( σ 8 , f σ 8 ). We list a few interesting models proposed for alleviating this tension, and we discuss the importance of trying to fit a full array of data with a single model and not just one parameter at a time. Additionally, we present a wide range of other less discussed anomalies at a statistical significance level lower than the H 0 – S 8 tensions which may also constitute hints towards new physics, and we discuss possible generic theoretical approaches that can collectively explain the non-standard nature of these signals. Finally, we give an overview of upgraded experiments and next-generation space missions and facilities on Earth that will be of crucial importance to address all these open questions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Enhancing Network Anomaly Detection Using Graph Neural Networks

In the world of Internet of Things (IoT) networks, where devices are constantly communicating, keeping them secure from cyber threats is critical. This paper introduces a novel approach to detecting unusual and potentially harmful activities in these networks using graph neural networks (GNNs). We combine two specific types of GNNs-GraphSAGE and graph attention networks (GAT)-to create a model that understands and represents the behaviors and interactions in a network. GraphSAGE creates an embedding of network activities by examining local data interactions, while GAT directs the model's focus to the most critical interactions. By integrating these two methods in a single model that considers different types of interactions (both host and flow nodes), we aim to create a system that accurately represents the current state of a network and can also spot anomalies effectively while reducing false positives and negatives. Our innovative approach has demonstrated promising results, achieving an accuracy of 98% on the UNSW-NB15 dataset, significantly outperforming standalone GraphSAGE and GAT models. This underscores its potential as a robust framework for securing IoT networks against cyber threats and anomalies.

Marfo, William↗
DOE OSTI2022

Network Anomaly Detection Using Federated Learning

The internet is turning out to be an integral part of every-one's lives as more and more devices are being connected to serve societal needs. Our work is motivated by two ma-jor observations. Firstly, one drawback of connecting to the network is the threat of network attacks that can compromise users' private information, leading to data loss and adversely affecting productivity. There are several traditional security mechanisms to defend against these attacks, such as firewalls, virtual private networks (VPNs), demilitarized zones (DMZs), and vulnerability scanners. One way to prevent these attacks is early detection and prevention. However, these kinds of architecture do not scale very well because of their centralized nature. Secondly, we observe from heuristics and data set distributions that the majority of the requests made to a server are innocuous. Therefore, almost all server request data sets are highly imbalanced, weighted highly towards the harmless requests.

Marfo, William↗
NASA NTRS1986

Large Ca-48 anomalies are associated with Ti-50 anomalies in Murchison and Murray hibonites

Ion microprobe measurements of the Ca isotopic compositions of eight individual hibonite grains from the Ca chondrites Murray and Murchison are reported. Large Ca-48 anomalies two orders of magnitude larger than those observed in normal inclusions and at least a factor of four larger than in the FUN inclusions are found. These anomalies are qualitatively correlated with the Ti-50 anomalies in the sense that the delta Ca-48 and delta Ti-50 values have the same sign. These results confirm previous conclusions concerning the presence of a nucleosynthetic component produced by neutron-rich nuclear statistical equilibrium processes. They suggest the preservation of the isotopic anomalies with interstellar dust grains as carriers of the n-rich Ca and Ti components. The large variation in the delta Ca-48/delta Ti-50 ratios indicates multiple nucleosynthetic components and/or chemical fractionation between Ca and Ti prior to hibonite formation.

Zinner, Ernst K.↗
NASA NTRS2006

Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

McIntosh, Dawn↗
NASA NTRS1975

An investigation of thermal anomalies in the Central American volcanic chain and evaluation of the utility of thermal anomaly monitoring in the prediction of volcanic eruptions

The author has identified the following significant results. Ground truth data collection proves that significant anomalies exist at 13 volcanoes within the test site of Central America. The dimensions and temperature contrast of these ten anomalies are large enough to be detected by the Skylab 192 instrument. The dimensions and intensity of thermal anomalies have changed at most of these volcanoes during the Skylab mission.

Stoiber, R. E.↗
DOE OSTI2024

Pulsar timing anomalies: a window into baryon number violation

Here, we investigate the influence of a specific class of slow Baryon Number Violation (BNV)—one that induces quasi-equilibrium evolution — on pulsar spin characteristics. This work reveals how BNV can potentially alter observable parameters, including spin-down rates, the second derivative of spin frequency, and braking indices of pulsars. Moreover, we demonstrate that BNV could lead to anomalies in pulsar timing, along with a wide array of braking indices, both positive and negative. In addition, we examine the possibility of pulsar spin-up due to BNV, which may result in a novel mechanism for the revival of “dead” pulsars. We conclude by assessing the sensitivity required for future pulsar timing efforts to detect such BNV effects, thus highlighting the potential for pulsars to serve as laboratories for testing fundamental physics.

cosmology↗
NASA NTRS1990

Life cycles of persistent anomalies. II - The development of persistent negative height anomalies over the North Pacific Ocean

Consideration is given to the potential sources for the development of cases defined by strong and persistent negative height anomalies over the central North Pacific. The analyses of Dole (1986) are extended by providing a more complete synoptic description of the developments and additional diagnostic analysis to identify dynamical mechanisms responsible for the developments. The synoptic characteristics of the developments are reviewed and the barotropic and baroclinic processes of the developments are analyzed. The reproducibility and representativeness of the results are examined. The observed characteristics suggest that the large-scale flow anomalies develop as a result of an instability of three-dimensional wintertime mean flow.

Dole, Randall M.↗
NASA NTRS1992

An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model

The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.

Peterson, Thomas C.↗