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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Investigating Anomalies in Compute Clusters: An Unsupervised Learning Approach

As compute clusters continue to grow in scale and complexity, the frequency of detected anomalies in their operation significantly increases. Timely detection of anomalous events is vital to maintain system efficiency and availability. This study presents an attentionbased graph neural network (GNN) for detecting anomalies in clusters at the compute node level and for providing detailed root cause analysis. We show the effectiveness of attention-based GNNs to accurately detect and localize anomalies on real-world datasets.

Lu, Yiyang↗
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 OSTI2021

Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model

Abstract. We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50° S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr-1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr-1). The contrast in contribution from the Southern Ocean, 102 Gt yr-1, is even more significant compared to the interannual variability of 35 Gt yr-1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Investigating lab-scaled offshore wind aerodynamic testing failure and developing solutions for early anomaly detections

As offshore wind systems become more complex, the risk of human error or equipment malfunction increases during experimental testing. This study investigates a lab-scale incident involving a 1 : 50 scale 5 MW wind turbine, where a generator failure led to rotor overspeed and a blade–tower strike. To improve early fault detection, we propose a data-driven method based on multivariate long short-term memory (LSTM) models. High-frequency measurements are projected onto principal components, and anomalies are identified using reconstruction error and its time derivative. Two models are trained on different healthy datasets and tested using single- and multi-principal component (1PC and MPC) variations. Results show that combining both error and error derivative improves detection accuracy. The 1PC model detects faults faster, has a higher recall rate, and achieves a 43 % improvement in anomaly detection accuracy, while the MPC model yields higher precision. This approach provides a simple and effective tool for early anomaly detection in lab-scale experiments, helping to reduce the risk of future failures during the testing of new technologies.

17 WIND ENERGY↗
NASA NTRS1972

Use of the space shuttle to avoid spacecraft anomalies

An existing data base covering 304 spacecraft of the U.S. space program was analyzed to determine the effect on individual spacecraft failures and other anomalies that the space shuttle might have had if it had been operational throughout the period covered by the data. By combining the results of this analysis, information on the prelaunch activities of selected spacecraft programs, and shuttle capabilities data, the potential impact of the space shuttle on future space programs was derived. The shuttle was found to be highly effective in the prevention or correction of spacecraft anomalies, with 887 of 1,230 anomalies analyzed being favorably impacted by full utilization of shuttle capabilities. The shuttle was also determined to have a far-reaching and favorable influence on the design, development, and test phases of future space programs. This is documented in 37 individual statements of impact.

Source record↗
NASA NTRS1972

Effects of surface anomalies on certain model generated meteorological histories

The Mintz-Arakawa 2-level general circulation model has been used in a series of experiments to compute the response of the model atmosphere to: (1) a positive sea surface temperature anomaly in the North Pacific Ocean in summer and in winter, (2) an identical anomaly in the South Pacific Ocean in the Southern Hemisphere winter, and (3) anomalous northward and southward displacements of the Northern Hemisphere snow line over the continents. In each case computations were carried out for 90 forecast days. Results are shown in terms of the differences between anomaly and control histories. Time series of certain regional response indices, including area-average sea level pressure and 600 mb circulation indices, as well as 30-day mean sea level pressure maps are used in the analysis. Of particular interest is the evidence of significant interhemisphere influence.

Spar, J.↗
NASA NTRS1972

Supplementary notes on sea surface temperature anomalies and model-generated meteorological histories

In seasonal computations, the Mintz-Arakawa two-level model is found to be sensitive to a minor alteration in the computational program. Effects of the program change on monthly mean sea level pressure fields are small in the first month, but large in the second and third months, although the meteorological histories generated by both the original and modified programs are equally credible. The inherited effects of a transient (one month) sea surface temperature (SST) anomaly on the computed monthly mean sea level pressure fields over a period of a season are about as large in absolute magnitude as those generated in the model by a persistent (seasonal) SST anomaly. The effects of a transient SST anomaly in the North Pacific Ocean on monthly and seasonal temperature and precipitation in the eastern United States may be large enough to produce a change of one or two class intervals in these predicted weather elements. The model-generated precipitation in the equatorial region is also found to be sensitive to the sea surface temperature field in the North Pacific.

Spar, J.↗
NASA NTRS1973

Europium anomaly in plagioclase feldspar - Experimental results and semiquantitative model.

The partition of europium between plagioclase feldspar and magmatic liquid is considered in terms of the distribution coefficients for divalent and trivalent europium. A model equation is derived giving the europium anomaly in plagioclase as a function of temperature and oxygen fugacity. The model explains europium anomalies in plagioclase synthesized under controlled laboratory conditions as well as the variations of the anomaly observed in natural terrestrial and extraterrestrial igneous rocks.

Weill, D. F.↗
NASA NTRS1973

Some effects of surface anomalies in a global general circulation model.

The Mintz-Arakawa two-level general circulation model has been used in a series of experiments to compute the response of the atmosphere to certain persistent sea-surface temperature anomalies and to changes in the position of the continental Northern Hemisphere snow line over periods up to 90 days. Results are shown in terms of differences between anomaly and control histories are revealed by global, 30-day mean sea-level pressure maps, and time series of three regional indices of synoptic activity. The experiments show significant interhemispheric effects after about 1 month, phase shifts of 1 to 2 weeks in major cyclone developments, stronger reactions to sea-temperature anomalies in winter than in summer, and marked influence of the snow line on the winter monsoonal pressure difference between the continents and the North Atlantic Ocean.

Spar, J.↗
NASA NTRS1973

Volcanic activity and satellite-detected thermal anomalies at Central American volcanoes

The author has identified the following significant results. A large nuee ardente eruption occurred at Santiaguito volcano, within the test area on 16 September 1973. Through a system of local observers, the eruption has been described, reported to the international scientific community, extent of affected area mapped, and the new ash sampled. A more extensive report on this event will be prepared. The eruption is an excellent example of the kind of volcanic situation in which satellite thermal imagery might be useful. The Santiaguito dome is a complex mass with a whole series of historically active vents. It's location makes access difficult, yet its activity is of great concern to large agricultural populations who live downslope. Santiaguito has produced a number of large eruptions with little apparent warning. In the earlier ground survey large thermal anomalies were identified at Santiaguito. There is no way of knowing whether satellite monitoring could have detected changes in thermal anomaly patterns related to this recent event, but the position of thermal anomalies on Santiaguito and any changes in their character would be relevant information.

Stoiber, R. E.↗
NASA NTRS1974

A global magnetic anomaly map

A subset of POGO satellite magnetometer data has been formed that is suitable for analysis of crustal magnetic anomalies. Using a thirteenth order field model, fit to these data, magnetic residuals have been calculated over the world to latitude limits of plus 50 deg. These residuals averaged over one degree latitude-longitude blocks represent a detailed global magnetic anomaly map derived solely from satellite data. Preliminary analysis of the map indicates that the anomalies are real and of geological origin.

Regan, R. D.↗
NASA NTRS1973

Theory of the phase anomaly in the thermosphere

Discussion of the temperature-density phase anomaly on the basis of a quasi-three-dimensional model in which the thermosphere dynamics associated with wind circulation is considered in a self-consistent form. Included in this analysis are the first three harmonics, which involve nonlinear coupling between diurnal and semidiurnal tides. It is shown that the phase anomaly with exospheric temperature peaks near 1600 LT and mass density peaks between 1400 and 1445 LT can be reproduced in a self-consistent theory without invoking ad hoc assumptions and boundary conditions that would mask the physical processes to be explored. A number of factors and processes are found to contribute to the phase anomaly, including the semidiurnal and particularly the terdiurnal components, heat advection, diffusion, and energy coupling with the lower atmosphere.

Mayr, H. G.↗
NASA NTRS1976

On estimating gravity anomalies: A comparison of least squares collocation with least squares techniques

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described, and its numerical properties are compared with the numerical properties of the conventional least squares estimator.

Argentiero, P.↗
NASA NTRS1976

The 55 K specific heat anomaly in palladium hydride

A specific heat anomaly in PdH and PdD has been observed by Aston et al. (1957) close to 55 K. Its position was found to be independent of hydrogen concentration and its magnitude to be linear in hydrogen concentration. Ferguson's (1965) and Brodowsky's (1972) explanations of the anomaly are shown to be unsatisfactory. This is true also for the detailed mechanical statistical model proposed by Staford and McLellan (1974) for interstitial solid solutions of hydrogen in transition metals. It is shown that Gopal's (1966) simple Schottky model of specific heat anomaly, which considers a system of several levels with Boltzmann statistics, provides much better agreement with experiment than the more elaborate models, both in magnitude and in predicting a linear dependence on hydrogen concentration.

Jacobi, N.↗
NASA NTRS1977

Isotopic anomalies and proton irradiation in the early solar system

Nuclear cross sections relevant to the various isotopic-abundance anomalies found in solar-system objects are evaluated in an attempt to set constraints on the hypothesized mechanism of irradiation of forming planetesimals by energetic protons from the young sun. A power-law proton spectrum is adopted, attention is restricted to proton energies less than about 20 MeV, and average cross sections are calculated for several reactions that might be expected to lead to the observed anomalies. The following specific anomalies are examined in detail: Al-26, Na-22, Xe-126, I-129, Kr-80, V-50, Nb-92, La-138, Ta-180, Hg-196, K-40, Ar-36, O-17, O-18, N-15, C-13, Li, Be, and B. It is suggested that the picture of presolar-grain carriers accounts for the facts more naturally than do irradiation models.

Clayton, D. D.↗
NASA NTRS1977

On estimating gravity anomalies - A comparison of least squares collocation with conventional least squares techniques

The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator are described.

Argentiero, P.↗