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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 OSTI2024

Nanosecond anomaly detection with decision trees and real-time application to exotic Higgs decays

Abstract We present an interpretable implementation of the autoencoding algorithm, used as an anomaly detector, built with a forest of deep decision trees on FPGA, field programmable gate arrays. Scenarios at the Large Hadron Collider at CERN are considered, for which the autoencoder is trained using known physical processes of the Standard Model. The design is then deployed in real-time trigger systems for anomaly detection of unknown physical processes, such as the detection of rare exotic decays of the Higgs boson. The inference is made with a latency value of 30 ns at percent-level resource usage using the Xilinx Virtex UltraScale+ VU9P FPGA. Our method offers anomaly detection at low latency values for edge AI users with resource constraints.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Cy-Phy ADS: Cyber Physical Anomaly Detection Framework for EV Charging Systems

Today’s large-scale Electric Vehicle (EV) infrastructures are heavily dependent on information communication technologies to maintain their operation and to support communication within sub-system components as well as the outside world. These technologies are vulnerable to various cyber and physical threats. Timely identification and mitigation of these threats are critical for improving human safety, avoiding economic losses, and preventing catastrophic system failures. By addressing this, our work presents a ResNet Autoencoder (AE) based Cyber-Physical Anomaly Detection System (Cy-Phy ADS) for detecting anomalies in EV Controller Area Network (CAN) protocol communication. It consists of four main components: Cyber-Physical Feature Extractor, ResNet AE-based Anomaly Detection Framework, Cyber-Physical Health Metric (CPHM), and Visualization Dashboard. The presented framework was trained and tested using CAN data collected from the EV charging system testbed at the Idaho National Laboratory. The presented Cy-Phy ADS compared against six widely used unsupervised anomaly detection algorithms: One Class Support Vector Machine (OCSVM), Variational Autoencoder (VAE), LSTM Autoencoder (LSTM AE), Isolation Forest (IForest), Principle Component Analysis (PCA) and Local Outlier Factor (LOF). Here the presented approach showed the highest accuracy among the compared methods. Further, the proposed approach showed comparable performance in terms of precision, F1, and False positive rate. It also showed the lowest training and inference time compared to the neural network-based baseline algorithms compared against with. Additionally, the Cy-Phy ADS has advantages such as unsupervised training, the ability to provide a holistic metric for system health characterization, and non-linear feature extraction.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

SU-E-J-128: 3D Surface Reconstruction of a Patient Using Epipolar Geometry

Purpose: To obtain a 3D surface data of a patient in a non-invasive way can substantially reduce the effort for the registration of patient in radiation therapy. To achieve this goal, we introduced the multiple view stereo technique, which is known to be used in a 'photo tourism' on the internet. Methods: 70 Images were taken with a digital single-lens reflex camera from different angles and positions. The camera positions and angles were inferred later in the reconstruction step. A sparse 3D reconstruction model was locating by SIFT features, which is robust for rotation and shift variance, in each image. We then found a set of correspondences between pairs of images by computing the fundamental matrix using the eight-point algorithm with RANSAC. After the pair matching, we optimized the parameter including camera positions to minimize the reprojection error by use of bundle adjustment technique (non-linear optimization). As a final step, we performed dense reconstruction and associate a color with each point using the library of PMVS. Results: Surface data were reconstructed well by visual inspection. The human skin is reconstructed well, althogh the reconstruction was time-consuming for direct use in daily clinical practice. Conclusion: 3D reconstruction using multi view stereo geometry is a promising tool for reducing the effort of patient setup. This work was supported by JSPS KAKENHI(25861128)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Optimization for Peptide Sample Preparation for Urine Peptidomics

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput ‘peptidomics’ methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.

biomarker↗
DOE OSTI2016

Lighting the dark molecular gas: H{sub 2} as a direct tracer

Robust knowledge of molecular gas mass is critical for understanding star formation in galaxies. The H{sub 2} molecule does not emit efficiently in the cold interstellar medium, hence the molecular gas content of galaxies is typically inferred using indirect tracers. At low metallicity and in other extreme environments, these tracers can be subject to substantial biases. We present a new method of estimating total molecular gas mass in galaxies directly from pure mid-infrared rotational H{sub 2} emission. By assuming a power-law distribution of H{sub 2} rotational temperatures, we can accurately model H{sub 2} excitation and reliably obtain warm (T ≳ 100 K) H{sub 2} gas masses by varying only the power law’s slope. With sensitivities typical of Spitzer/IRS, we are able to directly probe the H{sub 2} content via rotational emission down to ∼80 K, accounting for ∼15% of the total molecular gas mass in a galaxy. By extrapolating the fitted power-law temperature distributions to a calibrated single lower cutoff temperature, the model also recovers the total molecular content within a factor of ∼2.2 in a diverse sample of galaxies, and a subset of broken power-law models performs similarly well. In ULIRGs, the fraction of warm H{sub 2} gas rises with dust temperature, with some dependency on α {sub CO}. In a sample of five low-metallicity galaxies ranging down to 12+log[O/H]=7.8, the model yields molecular masses up to ∼100× larger than implied by CO, in good agreement with other methods based on dust mass and star formation depletion timescale. This technique offers real promise for assessing molecular content in the early universe where CO and dust-based methods may fail.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Errors in nanoparticle growth rates inferred from measurements in chemically reacting aerosol systems

In systems in which aerosols are being formed by chemical transformations,individual particles grow due to the addition of molecular species. Efforts to improve our understanding of particle growth often focus on attempts to reconcile observed growth rates with values calculated from models. However,because it is typically not possible to measure the growth rates of individual particles in chemically reacting systems, they must be inferred from measurements of aerosol properties such as size distributions, particle number concentrations, etc. Furthermore this work discusses errors in growth rates obtained using methods that are commonly employed for analyzing atmospheric data. We analyze “data” obtained by simulating the formation of aerosols in a system in which a single chemical species is formed at a constant rate, R . We show that the maximum overestimation error in measured growth rates occurs for collision-controlled nucleation in a single-component system in the absence of a preexisting aerosol, wall losses, evaporation or dilution,as this leads to the highest concentrations of nucleated particles. Those high concentrations lead to high coagulation rates that cause the nucleation mode to grow faster than would be caused by vapor condensation alone. We also show that preexisting particles, when coupled with evaporation, can significantly decrease the concentration of nucleated particles. This can lead to decreased discrepancies between measured growth rate and true growth rate by reducing coagulation among nucleated particles. However, as particle sink processes become stronger, measured growth rates can potentially be lower than true particle growth rates. We briefly discuss nucleation scenarios in which the observed growth rate approaches zero while the true growth rate does not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

The effect of multiple encounters on short-period comet orbits.

The observed orbital elements of short-period comets are found to be consistent with the hypothesis of derivation from long-period comets as long as two assumptions are made. First, the distribution of short-period comets has been randomized by multiple encounters with Jupiter and second, the short-period comets have low velocities of encounter with Jupiter. Some 16% of the observed short-period comets have lower encounter velocities than is allowed mathematically using Laplace's method. This may be due to double-encounter processes with Jupiter and Saturn. The distribution of unobservable short-period comets can be inferred in part from the observed comets. It is shown that there may be many short-period comets having orbits between Jupiter and Saturn with somewhat higher inclinations than those with perihelia near the earth.

Lowrey, B. E.↗
NASA NTRS1974

Determination of optical parameters of atmospheric particulates from ground-based polarimeter measurements

This paper describes the theoretical analysis that is required to infer, from polarimeter measurements of skylight, the size distribution, refractive index and abundance of particulates in the atmosphere. To illustrate the viability of the method, some data obtained at UCLA is analyzed and the atmospheric parameters are derived. The explicit demonstration of the redundancy in the description of aerosol distributions suggests that radiation field measurements will not uniquely determine the modal radius of the size distribution. In spite of this nonuniqueness information useful to heat budget calculations can be derived.

Kuriyan, J. G.↗
NASA NTRS1986

Measurement of Dynamic Bolt-Stress

Ultrasonic method provides record of changing stresses in dynamically loaded bolts. Makes available history of stress cycles, from which fatigue state and remaining bolt life inferred.

Barkhoundarian, S.↗
NASA NTRS1990

Radiometric calibration and monitoring of NOAA AVHRR visible data

Results and corrections to calibration for the NOAA-7, -8, -9, -10, and -11 AVHRR Channel 1 data, covering the period from July 1983 through December 1989, are presented. Results from the NOAA-7 and NOAA-9 analysis are used as examples to illustrate key points and present detailed results. In the AVHRR monitor procedure, the spatial variability index is calculated first to classify the data as CLEAR or CLOUD. This classification is then used to sort the data to produce three 1D radiance histograms for different surface types. The surface reflectances are retrieved from the radiances, and a set of reflectance filters are applied to sort the data into global surface reflectance maps. An examination of the NOAA-7 results shows that the NOAA-7 radiometer sensitivity actually decreased at a rate of about 0.5-1.0 percent per year. Trends inferred from the point measurements representing independent calibrations at different times, using models, known sites, and coincident aircraft measurements, agree well with the satellite methods.

Brest, Christopher L.↗
NASA NTRS2000

1DVAR Analysis of Temperature and Humidity Using GPS Radio Occultation Data

The Global Positioning System enables positioning in 3 dimensions about our planet. It has been operational since 1994. Twenty-four satellites are used to aclile\,e this performance. The signals sent by these satellites are electromagnetic waves travelling through our atmosphere down to the small receivers used by the civilian community and the military. Because of varying meteorological conditions (namely, temperature and humidity changes along the ray path), the rays do not travel in a straight line. They bend towards the surface. As a consequence, the ray path between two points is longer than a straight line, and the time it takes for a signal to travel this distance is longer. In 1995, a small GPS receiver was launched on a satellite (GPS/MET). It become possible to perform radio occultations around the Earth: the source - one of the 24 GPS satellites - is seen by the receiver as it rises or sets around the other side of the Earth. When the source disappears, the receiver progressively loses the signals. By measuring accurately the time delay between the emission and the reception of the signal, it is possible to infer which part of the delay is due to the atmosphere. We use GPS/MET data to retrieve temperature and humidity profiles simultaneously. A specific method is implemented: it combines information from numerical forecasts and GPS observations in an optimal way. Comparing the result with an independent source of observations (weather balloons), we demonstrate that GPS data have the potential to improve weather analyses. We also show that improved temperature and humidity profiles can be obtained using information from a forecast model. This confirms results obtained in this study using simulated data.

Poli, Paul↗
DOE OSTI2016

Reservoir response to thermal and high-pressure well stimulation efforts at Raft River, Idaho

An injection stimulation test begun at the Raft River geothermal reservoir in June, 2013 has produced a wealth of data describing well and reservoir response via high-resolution temperature logging and distributed temperature sensing, seismic monitoring, periodic borehole televiewer logging, periodic stepped flow rate tests and tracer injections before and after stimulation efforts. One of the primary measures of response to the stimulation is the relationship between fluid pressure and flow rate, short-term during forced flow rate changes and the long-term change in injectivity. In this paper we examine that hydraulic response using standard pumping test analysis methods, largely because pressure response to the stimulation was not detected, or measurable, in other wells. Analysis of stepped rate flow tests supports the inference from other data that a large fracture, with a radial extent of one to several meters, intersects the well in the target reservoir, suggests that the flow regime is radial to a distance of only several meters and demonstrates that the pressure build-up cone reaches an effective constant head at that distance. The well’s longer term hydraulic response demonstrated continually increasing injectivity but at a dramatically faster rate later from ~2 years out and continuing to the present. The net change in injectivity is significantly greater than observed in other longterm injectivity monitoring studies, with an approximately 150–fold increase occurring over ~2.5 years. While gradually increasing injectivity is a likely consequence of slow migration of a cooling front, and consequent dilation of fractures, the steady, ongoing, rate of increase is contrary to what would be expected in a radial or linear flow regime, where the cooling front would slow with time. As a result, occasional step-like changes in injectivity, immediately following high-flow rate tests suggest that hydro shearing during high-pressure testing altered the near-well permeability structure.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Tomography of the gamma-ray sky from cross-correlation with DESI DR2 and unWISE galaxies

We study the origin of extragalactic gamma-ray emission observed by Fermi-LAT, using the cross-correlation of the gamma-ray sky with maps of large-scale structure provided by the DESI and unWISE surveys. Tomographic cross-correlation reveals the bias-weighted redshift distributions of gamma-ray sources. We first illustrate this method by cross-correlating detected gamma-ray point sources with large-scale structure. We find a significant cross-correlation and infer a point source redshift distribution broadly consistent with the distribution of identified optical counterparts previously reported in the literature, as well as a similar linear bias ($b \approx 2$) to massive galaxies that host bright active galactic nuclei. We then study the clustering of the Fermi unresolved gamma-ray background (UGRB), both in auto-correlation and in cross-correlation with large-scale structure. We detect the cross-correlation of the UGRB and LSS at $\sim 10σ$ in total, with highly significant detections from both DESI and unWISE. Our measurements suggest that the redshift distribution of the UGRB is broadly consistent with the redshift distribution of detected point sources. Additionally, we find a relatively weak amplitude for the cross-correlation with large-scale structure at z < 2, suggesting a significant fraction of the UGRB does not come from z < 2 large-scale structure. A natural candidate is contamination of from residual Galactic emission, and our best estimate of the contamination level derived from the UGRB auto-spectrum suggests that the mean bias of UGRB sources is indeed quite similar to the bias of detected Fermi point sources. However, we cannot exclude additional emission from gamma-ray sources at high redshift, z > 2, and we suggest that cross-correlation with tracers at z > 2, including CMB lensing, would be the ideal way to determine the fraction of z > 2 emission.

Krolewski, Alex [Waterloo U., Math. Dept.; Waterlo↗
DOE OSTI2019

ENSEMBLE KALMAN FILTERS FOR RELIABILITY ESTIMATION IN PERFUSION INFERENCE

We consider the solution of inverse problems in dynamic contrast–enhanced imaging by means of ensemble Kalman filters. Our quantity of interest is blood perfusion, i.e., blood flow rates in tissue. While existing approaches to compute blood perfusion parameters for given time series of radiological measurements mainly rely on deterministic, deconvolution–based methods, we aim at recovering probabilistic solution information for given noisy measurements. To this end, we model radiological image capturing as a sequential data assimilation process and solve it by an ensemble Kalman filter. Thereby, we recover deterministic results as an ensemble–based mean and are able to compute reliability information such as probabilities for the perfusion to be in a given range. Our target application is the inference of blood perfusion parameters in the human brain. A numerical study shows promising results for artificial measurements generated by a digital perfusion phantom.

Engineering↗
DOE OSTI2014

SU-E-J-158: Experimental Investigation of Proton Radiography Based On Time-Resolved Dose Measurements

Purpose: To use proton radiography for i) in-vivo range verification of the brain fields of medulloblastoma patients in order to reduce the exit dose to the cranial skin and thus the risk of permanent alopecia; ii) for performing patient specific optimization of the calibration from CT-Hounsfield units to proton relative stopping power in order to minimize uncertainties of proton rang Methods: We developed and tested a prototype proton radiography system based on a single-plane scintillation screen coupled with a fast CCD camera (1ms sampling rate, 0.29x0.29 mm{sup 2} pixel size, 30×30 cm{sup 2} field of view). The method is based on the principle that, for passively scattered beams, the radiological depth of any point in the plateau of a spread-out Bragg-Peak (SOBP) can be inferred from the time-pattern of the dose rate measurements. We performed detector characterization measurements using complex-shape homogeneous phantoms and an Alderson phanto Results: Detector characterization tests confirmed the robustness of the technique. The results of the phantom measurements are encouraging in terms of achievable accuracy of the water equivalent thickness. A technique to minimize the degradation of spatial resolution due to multiple Coulomb scattering is discussed. Our novel radiographic technique is rapid (100 ms) and simultaneous over the whole field. The dose required to produce one radiograph, with the current settings, is ∼3 cG Conclusion: The results obtained with this simple and innovative radiography method are promising and motivate further development of technique. The system requires only a single-plane 2D dosimeter and it uses the clinical beam for a fraction of second with low dose to the patient.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Implications of Binary Black Hole Detections on the Merger Rates of Double Neutron Stars and Neutron Star–Black Holes

We show that the inferred merger rate and chirp masses of binary black holes (BBHs) detected by advanced LIGO (aLIGO) can be used to constrain the rate of double neutron star (DNS) and neutron star–black hole (NSBH) mergers in the universe. We explicitly demonstrate this by considering a set of publicly available population synthesis models of Dominik et al. and show that if all the BBH mergers, GW150914, LVT151012, GW151226, and GW170104, observed by aLIGO arise from isolated binary evolution, the predicted DNS merger rate may be constrained to be 2.3–471.0 Gpc{sup −3} yr{sup −1} and that of NSBH mergers will be constrained to 0.2–48.5 Gpc{sup −3} yr{sup −1}. The DNS merger rates are not constrained much, but the NSBH rates are tightened by a factor of ∼4 as compared to their previous rates. Note that these constrained DNS and NSBH rates are extremely model-dependent and are compared to the unconstrained values 2.3–472.5 Gpc{sup −3} yr{sup −1} and 0.2–218 Gpc{sup −3} yr{sup −1}, respectively, using the same models of Dominik et al. (2012a). These rate estimates may have implications for short Gamma Ray Burst progenitor models assuming they are powered (solely) by DNS or NSBH mergers. While these results are based on a set of open access population synthesis models, which may not necessarily be the representative ones, the proposed method is very general and can be applied to any number of models, thereby yielding more realistic constraints on the DNS and NSBH merger rates from the inferred BBH merger rate and chirp mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Nongeminate Radiative Recombination of Free Charges in Cation-Exchanged PbS Quantum Dot Films

Using photoluminescence (PL) spectroscopy we explore the radiative recombination pathways in PbS quantum dots (QDs) synthesized by two methods. We compare conventionally synthesized PbS from a PbO precursor to PbS synthesized using cation-exchange from CdS QDs. We show that strongly coupled films of PbS QDs from the cation-exchange luminesce with significant efficiency at room temperature. This is in stark contrast to conventional PbS QDs, which have exceedingly weak room temperature emission. Moreover, the power dependence of the emission is quadratic, indicating bimolecular radiative recombination that is reasonably competitive with trap-assisted recombination, a feature previously unreported in coupled PbS QD films. We interpret these results in terms of a greatly reduced defect concentration for cation-exchanged QDs that mitigates the influence of trap-assisted recombination. Cation-exchanged QDs have recently been employed in highly efficient and air-stable lead chalcogenide QD devices, and the reduced number of trap states inferred here may lead to improved current collection and higher open circuit voltage.

14 SOLAR ENERGY↗
DOE OSTI2015

Designing optimal greenhouse gas observing networks that consider performance and cost

Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH 2 FCF 3 , HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.

Lucas, D. D.↗