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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 OSTI2016

WE-FG-207B-07: Feasibility of Low Dose Lung Cancer Screening with a Whole-Body Photon Counting CT: First Human Results

Purpose: To evaluate the feasibility of using a whole-body photon counting detector (PCD) CT scanner for low dose lung cancer screening compared to a conventional energy integrating detector (EID) system. Methods: Radiation dose-matched EID and PCD scans of the COPDGene 2 phantom and 2 human volunteers were acquired. Phantom images were acquired at different radiation dose levels (CTDIvol: 3.0, 1.5, and 0.75 mGy) and different tube voltages (120, 100, and 80 kVp), while human images were acquired at vendor recommended low-dose lung cancer screening settings. EID and PCD images were compared for quantitative Hounsfield unit accuracy, noise levels, and contrast-to-noise ratios (CNR) for detection of ground-glass nodules (GGNs) and emphysema. Results: The PCD Hounsfield unit accuracy was better for water at all scan parameters, and for lung, GGN and emphysema equivalent regions of interest (ROIs) at 1.5 and 0.75 mGy. PCD attenuation accuracy was more consistent for all scan parameters (all P<0.01), while Hounsfield units for lung, GGN and emphysema ROIs changed significantly for EID with decreasing dose (all P<0.001). PCD showed lower noise levels at the lowest dose setting at 120, 100 and 80 kVp (15.2±0.3 vs 15.8±0.2, P=0.03; 16.1±0.3 vs 18.0±0.4, P=0.003; and 16.1±0.3 vs 17.9±0.3, P=0.001, respectively), resulting in superior CNR for the detection of GGNs and emphysema at 100 and 80 kVp. Significantly lower PCD noise levels were confirmed in volunteer images. Conclusion: PCD provided better Hounsfield unit accuracy for lung, ground-glass, and emphysema-equivalent foams at 1.5 and 0.75 mGy with less variability than EID. Additionally, PCD showed less noise, and higher CNR at 0.75 mGy for both 100 and 80 kVp. PCD technology may help reduce radiation exposure in lung cancer screening while maintaining diagnostic quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Optimizing a Multiple Right-Hand Side Dslash Kernel for Intel Knights Corner

Lattice Quantum Chromo-dynamics (LQCD) stands unique as the only computationally tractable, non-perturbative, and model-independent quantum field theory of the strong nuclear force. LQCD achieves tractability by discretizing our familiar 4-dimensional space-time onto a hypercubic lattice. The core component of the linear solver used in LQCD is the Wilson-Dirac operator whose finite difference component is called the Dslash operator. Dslash is a nearest neighbor stencil operator summing matrix-vector multiplications over lattice points. The arithmetic intensity of a regular Dslash operator acting on a single vector in single precision is between 0.88-2.29 (depending on the tricks employed) making it memory bandwidth bound on most current architectures, including Xeon Phi. Maximizing the performance of Dslash on Xeon Phi requires deliberate exploitation of its architectural features. One key feature of Xeon Phi is its powerful vector processing unit with lengthy vector registers. There is a class of LQCD computations which aims to solve the Dirac equation for the same lattice gauge fields multiple times. In this case one can gain additional reuse of the gauge field, and potentially simplified vectorization, through applying Dslash to several vectors at the same time; often referred to as Multiple Right Hand Side (MRHS) Dslash. Previous work in this area focused on applying this approach to the Highly Improved Staggered operator, and in cases to the multi-Grid algorithm for Wilson clover fermions. Here, we present two approaches to MRHS Dslash: a vector register blocking approach and one using the software package QPhiX with a custom Code Generator for low-level intrinsics. We explore the Knights Corner instruction set, memory hierarchy, and threading capabilities. For standard lattice sizes used in testing, we observed significant speedups, with sustained performance of over 700 GFLOPS (single precision) in one instance. We achieved up to 27% of theoretical peak performance compared to a maximum of 12% obtained by the previous single RHS method in QPhiX.

Joó, Bálint↗
DOE OSTI2025

Robustness of Deep Learning Classification to Adversarial Input on GPUs: Asynchronous Parallel Accumulation Is a Source of Vulnerability

The ability of machine learning (ML) classification models to resist small, targeted input perturbations—known as adversarial attacks—is a key measure of their safety and reliability. We show that floating-point non associativity (FPNA) coupled with asynchronous parallel programming on GPUs is sufficient to result in misclassification, without any perturbation to the input. Additionally, we show that this misclassification is particularly significant for inputs close to the decision boundary and that standard adversarial robustness results may be overestimated up to 4.6 when not considering machine-level details. We first study a linear classifier, before focusing on standard Graph Neural Network (GNN) architectures and datasets used in robustness assessments. We develop a novel black-box attack using Bayesian optimization to discover external workloads that can change the instruction scheduling which bias the output of reductions on GPUs and reliably lead to misclassification. Motivated by these results, we present a new learnable permutation (LP) gradient-based approach to learning floating-point operation orderings that lead to misclassifications. The LP approach provides a worst-case estimate in a computationally efficient manner, avoiding the need to run identical experiments tens of thousands of times over a potentially large set of possible GPU states or architectures. Finally, using instrumentation-based testing, we investigate parallel reduction ordering across different GPU architectures under external background workloads, when utilizing multi-GPU virtualization, and when applying power capping. Our results demonstrate that parallel reduction ordering varies significantly across architectures under the first two conditions, substantially increasing the search space required to fully test the effects of this parallel scheduler-based vulnerability. These results and the methods developed here can help to include machine-level considerations into adversarial robustness assessments, which can make a difference in safety and mission critical applications.

Shanmugavelu, Sanjif [Maxeler Technologies, a Groq↗
DOE OSTI2021

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Exploratory Visual Analysis of Anomalous Runtime Behavior in Streaming High Performance Computing Applications

Online analysis of runtime behavior is essential for performance tuning in streaming scientific workflows. Integration of anomaly detection and visualization is necessary to support human-centered analysis, such as verification of candidate anomalies utilizing domain knowledge. In this work, we propose an efficient and scalable visual analytics system for online performance analysis of scientific workflows toward the exascale scenario. Here, our approach uses a call stack tree representation to encode the structural and temporal information of the function executions. Based on the call stack tree features (e.g., execution time of the root function or vector representation of the tree structure), we employ online anomaly detection approaches to identify candidate anomalous function executions. We also present a set of visualization tools for verification and exploration in a level-of-detailed manner. General information, such as distribution of execution times, are provided in an overview visualization. The detailed structure (e.g., function invocation relations) and the temporal information (e.g., message communication) of the execution call stack of interest are also visualized. The usability and efficiency of our methods are verified in a real-world HPC application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

An optimization approach to design monitoring schemes for CO 2 leakage detection

This paper demonstrates an approach to identify optimal monitoring designs that minimize the time to first detection of CO 2 leakage from a subsurface storage formation. This research is part of the National Risk Assessment Partnership (NRAP), a DOE project tasked with conducting risk and uncertainty analysis in the areas of reservoir performance, natural leakage pathways, wellbore integrity, groundwater protection, monitoring, and systems level modeling. Our approach applies a simulated annealing algorithm that searches the solution space by iteratively mutating potential monitoring designs. An example application is provided to demonstrate the effectiveness and efficiency of this method compared to an exhaustive search of the entire solution space. We took into account uncertainty by evaluating the performance of potential monitoring designs across a set of simulated leakage realization. A flexible two-tiered signature was implemented to infer that CO 2 leakage had occurred. This approach was ~50 times faster than an exhaustive search. A user-friendly tool, MDLD, is being developed for use on personal computers to make this method available to stakeholders, regulators, and researchers.

03 NATURAL GAS↗
DOE OSTI2025

Characterization and prediction of the electromechanical wear of contact tips during wire arc additive manufacturing of 316L stainless steel

Here, this study seeks to better understand the degradation of the contact tip with respect to WAAM for a 316L wire electrode as well as explore methods of monitoring the contact tip state from process data. The contact tip, a consumable component, positions the wire and serves as the electrical contact surface between the wire electrode and the welding power supply. The wear of the contact tip was characterized in terms of material loss and material contamination for a set of tips worn to discrete levels as measured by the amount of wire fed or arc time. Geometrical characterization found a 49% increase in the bore exit area at 180 meters of wire fed. Machine learning models were developed to predict the relative bore exit area of the contact tip from arc-based process data and a random forest classifier exhibited favorable performance with a cross-validated f1-score of 0.84. The regression architecture implemented a multi-layer perceptron with the ability to predict the relative exit area with an $R^2$ score of 0.75. Key features used in the prediction include the standard deviation of the voltage and the time between shorts.

Contact tip wear↗
DOE OSTI2014

Fast and accurate CMB computations in non-flat FLRW universes

We present a new method for calculating CMB anisotropies in a non-flat Friedmann universe, relying on a very stable algorithm for the calculation of hyperspherical Bessel functions, that can be pushed to arbitrary precision levels. We also introduce a new approximation scheme which gradually takes over in the flat space limit and leads to significant reductions of the computation time. Our method is implemented in the Boltzmann code class. It can be used to benchmark the accuracy of the camb code in curved space, which is found to match expectations. For default precision settings, corresponding to 0.1% for scalar temperature spectra and 0.2% for scalar polarisation spectra, our code is two to three times faster, depending on curvature. We also simplify the temperature and polarisation source terms significantly, so the different contributions to the C{sub ℓ} 's are easy to identify inside the code.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spatiotemporal predictions of toxic urban plumes using deep learning

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic plumes by solving fluid dynamical equations. However, these models can be computationally expensive due to the need for many grid cells to simulate turbulent flow and resolve individual buildings and streets. In emergency response situations, alternative methods are needed that can run quickly and adequately capture important spatiotemporal features. Here, we present a novel deep learning model called ST-GasNet inspired by the mathematical equations that govern the behavior of plumes as they disperse through the atmosphere. ST-GasNet learns the spatiotemporal dependencies from a limited set of temporal sequences of ground-level toxic urban plumes generated by a high-resolution large eddy simulation model. On independent sequences, ST-GasNet accurately predicts the late-time spatiotemporal evolution, given the early-time behavior as an input, even when a building splits a large plume into smaller plumes. By incorporating large-scale wind boundary condition information, ST-GasNet achieves a prediction accuracy of at least 90% on test data for the entire prediction period.

Civil and Environmental Engineering↗
DOE OSTI2016

Active Power Control of Wind Turbines for Ancillary Services: A Comparison of Pitch and Torque Control Methodologies

As wind energy generation becomes more prevalent in some regions, there is increased demand for wind power plants to provide ancillary services, which are essential for grid reliability. This paper compares two different wind turbine control methodologies to provide active power control (APC) ancillary services, which include derating or curtailing power generation, providing automatic generation control (AGC), and providing primary frequency control (PFC). The torque APC controller provides all power control through the power electronics whereas the pitch APC controller uses the blade pitch actuators as the primary means of power control. These controllers are simulated under various wind conditions with different derating set points and AGC participation levels. The metrics used to compare their performance are the damage equivalent loads (DELs) induced on the structural components and AGC performance metrics, which are used to determine the payments for AGC services by system operators in the United States. The simulation results show that derating the turbine reduces structural loads for both control methods, with the APC pitch control providing larger reductions in DELs, lower AGC performance scores, and higher root-mean-square pitch rates. Providing AGC increases the structural loads when compared to only derating the turbine, but even the AGC DELs are generally lower than those of the baseline control system. The torque APC control methodology also allows for more sustained PFC responses under certain derating conditions.

17 WIND ENERGY↗
DOE OSTI2022

Behavioral and Population Data-Driven Distribution System Load Modeling

Distribution system residential load modeling and analysis for different geographic areas within a utility or an independent system operator territory are critical for enabling small-scale, aggregated distributed energy resources to participate in grid services under Federal Energy Regulatory Commission Order No. 2222 [1]. In this study, we develop a methodology of modeling residential load profiles in different geographic areas with a focus on human behavior impact. First, we construct a behavior-based load profile model leveraging state-of-the-art appliance models. We simulate human activity and occupancy using Markov chain Monte Carlo methods calibrated with the American Time Use Survey data set. Second, we link our model with cleaned Current Population Survey data from the U.S. Census Bureau. Finally, we populate two sets of 500 households using California and Texas census data, respectively, to perform an initial analysis of the load in different geographic areas with various group features (e.g., different income levels). To distinguish the effect of population behavior differences on aggregated load, we simulate load profiles for both sets assuming fixed physical household parameters and weather data. Analysis shows that average daily load profiles vary significantly by income and income dependency varies by locality.

American Time Use Survey↗
DOE OSTI2016

WE-FG-BRA-08: Potential Role of the Glycolytic Oscillator in Acute Hypoxia in Tumors

Purpose: Oscillatory dynamics in acute hypoxia have been observed, but poorly understood. They have mostly been attributed to vascular perturbations, but no link has yet been made to metabolic causes. We set out to determine the fundamental frequencies and test for coherence in tumor oxygen dynamics and spatial properties. Methods: Severe combined immunodeficient (SCID) mice were inoculated onto bilateral flanks with human derived head and neck carcinoma (UW-SCC22) cell line xenografts. Oxygen dynamics were monitored in the tumor every minute for an hour using three modalities: blood oxygen level dependent - magnetic resonance imaging (BOLD-MRI), hemoglobin oxygen saturation photoacoustic, and locally manufactured optical probes for spectral fitting. A statistical test was used to separate fluctuating from non-fluctuating voxels and pixels in BOLD-MRI and photoacoustic data respectively. The power spectrum density (PSD) and the autocorrelation functions were calculated for the time series of each voxel, pixel and region, of the BOLD-MRI, photoacoustic or fiber optic data respectively. Results: Using all three techniques, intermittent oxygen dynamics with both coherent and incoherent signatures was observed in the tumors. Upon averaging the PSDs of fluctuating voxels and pixels, it was found that these oscillations occurred with periods of minutes to tens of minutes from all three approaches. Observations from the BOLD-MRI and photoacoustic data showed that clusters of voxels oscillated in a synchronized manner. Conclusion: We were able to use three different modalities to show that fluctuation in tumor oxygen is both coherent and incoherent, with periods of minutes to tens of minutes. These periods are very similar to those from the well-established metabolic, non-linear biomechanical phenomenon called the glycolytic oscillator. This may provide an additional explanation to the cause of cyclic hypoxia. Such dynamics could have profound implications in hypofractionated radiotherapy regiments and could help guide treatment and make it more patient specific. The authors would like to thank the University of Wisconsin Carbone Cancer Center (UWCCC) for the funds to complete this project. This work is also supported in part by NIH/NCI P30 CA014520- UW Comprehensive Cancer Center Support”.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Diagnosing United States hurricane landfall risk: An alternative to count-based methodologies: Diagnosing U.S. Hurricane Landfall Risk

Assessing hurricane landfall risk is of immense public utility, yet extant methods of diagnosing annual tropical cyclone (TC) activity demonstrate no skill in diagnosing U.S. hurricane landfalls. Atlantic TC count itself has limited skill, explaining less than 20% of interannual variance in landfall incidence. Using extended landfall activity and reanalysis data sets, we employed empirical Poisson modeling to produce a landfall diagnostic index (LDI), incorporating spatially and temporally averaged upper level divergence, relative sea surface temperature, meridional wind, and zonal shear vorticity. LDI captures 31% of interannual variability of U.S. hurricane landfalls and offers physical insight into why indices that successfully capture TC activity fail to diagnose landfalls: there is inherent tension between conditions likely to steer hurricanes toward the U.S. and conditions favorable for TC development. Given this tension, attempting to diagnose, predict, or understand TC count is inadequate for quantifying societal impacts due to landfalling hurricanes.

Geology↗
DOE OSTI2015

Bias-free lateral terahertz emitters—A simulation study

The design and performance of bias-free InN-based THz emitters that exploit lateral photocurrents is studied by means of numerical simulations. We use a drift-diffusion model with adjusted carrier temperatures and mobilities. The applicability of this approach is demonstrated by a comparison with results from Monte-Carlo simulations. We consider a simple but robust lateral emitter concept using metal stripes with two different thicknesses with one of them being thin enough to be transparent for THz radiation. This arrangement can be easily multiplexed and the efficiency of this concept has already been demonstrated by experiment for GaAs substrates. In the present study, we consider InN, which is known to be an efficient photo-Dember emitter because of its superior transport properties. Our main focus is on the impact of the emitter design on the emission efficiency assuming different operation principles. Both the lateral photo-Dember (LPD) effect and built-in lateral field effects are considered. The appropriate choice of the metal stripe and window geometry as well as the impact of surface Fermi level pinning are investigated in detail, and design guidelines for efficient large area emitters using multiplexed structures are provided. We find that InN LPD emitters do not suffer from Fermi level pinning at the InN surface. The optimum emission efficiency is found for LPD emitter structures having 200 nm wide illumination windows and mask stripes. Emitter structures in which lateral electric fields are induced by the metal mask contacts can have a considerably higher efficiency than pure LPD emitters. In the best case, the THz emission of such structures is increased by one order of magnitude. Their optimum window size is 1 μm without the necessity of a partially transparent set of mask stripes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

The benzene radical anion: A computationally demanding prototype for aromatic anions

The benzene radical anion is studied with ab initio coupled-cluster theory in large basis sets. Unlike the usual assumption, we find that, at the level of theory investigated, the minimum energy geometry is non-planar with tetrahedral distortion at two opposite carbon atoms. The anion is well known for its instability to auto-ionization which poses computational challenges to determine its properties. Despite the importance of the benzene radical anion, the considerable attention it has received in the literature so far has failed to address the details of its structure and shape-resonance character at a high level of theory. Here, we examine the dynamic Jahn-Teller effect and its impact on the anion potential energy surface. We find that a minimum energy geometry of C{sub 2} symmetry is located below one D{sub 2h} stationary point on a C{sub 2h} pseudo-rotation surface. The applicability of standard wave function methods to an unbound anion is assessed with the stabilization method. The isotropic hyperfine splitting constants (A{sub iso}) are computed and compared to data obtained from experimental electron spin resonance experiments. Satisfactory agreement with experiment is obtained with coupled-cluster theory and large basis sets such as cc-pCVQZ.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

The ADAQ framework: An integrated toolkit for data acquisition and analysis with real and simulated radiation detectors

Here, the ADAQ framework is a collection of software tools that is designed to streamline the acquisition and analysis of radiation detector data produced in modern digital data acquisition (DAQ) systems and in Monte Carlo detector simulations. The purpose of the framework is to maximize user scientific pro-ductivity by minimizing the effort and expertise required to fully utilize radiation detectors in a variety of scientific and engineering disciplines. By using a single set of tools to span the real and simulation domains, the framework eliminates redundancy and provides an integrated workflow for high-fidelity comparison between experimental and simulated detector performance. Built on the ROOT data analysis framework, the core of the ADAQ framework is a set of Cþþ and Python libraries that enable high-level control of digital DAQ systems and detector simulations with data stored into standardized binary ROOT files for further analysis. Two graphical user interface programs utilize the libraries to create powerful tools: ADAQAcquisition handles control and readout of real-world DAQ systems and ADAQAnalysis provides data analysis and visualization methods for experimental and simulated data. At present, the ADAQ framework supports digital DAQ hardware from CAEN S.p.A. and detector simulations performed in Geant4; however, the modular design will facilitate future extension to other manufacturers and simulation platforms.

detector simulation↗
DOE OSTI2023

The multichannel i -propyl + O2 reaction system: A model of secondary alkyl radical oxidation

The i-propyl + O2 reaction mechanism has been investigated by definitive quantum chemical methods to establish this system as a benchmark for the combustion of secondary alkyl radicals. Focal point analyses extrapolating to the ab initio limit were performed based on explicit computations with electron correlation treatments through coupled cluster single, double, triple, and quadruple excitations and basis sets up to cc-pV5Z. The rigorous coupled cluster single, double, and triple excitations/cc-pVTZ level of theory was used to fully optimize all reaction species and transition states, thus, removing some substantial flaws in reference geometries existing in the literature. The vital i-propylperoxy radical (MIN1) and its concerted elimination transition state (TS1) were found 34.8 and 4.4 kcal mol−1 below the reactants, respectively. Two β-hydrogen transfer transition states (TS2, TS2′) lie above the reactants by (1.4, 2.5) kcal mol−1 and display large Born–Oppenheimer diagonal corrections indicative of nearby surface crossings. An α-hydrogen transfer transition state (TS5) is discovered 5.7 kcal mol−1 above the reactants that bifurcates into equivalent α-peroxy radical hanging wells (MIN3) prior to a highly exothermic dissociation into acetone + OH. The reverse TS5 → MIN1 intrinsic reaction path also displays fascinating features, including another bifurcation and a conical intersection of potential energy surfaces. An exhaustive conformational search of two hydroperoxypropyl (QOOH) intermediates (MIN2 and MIN3) of the i-propyl + O2 system located nine rotamers within 0.9 kcal mol−1 of the corresponding lowest-energy minima.

Chemistry↗