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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable with respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.

58 GEOSCIENCES↗
DOE OSTI2014

TU-C-BRE-05: Clinical Implications of AAA Commissioning Errors and Ability of Common Commissioning ' Credentialing Procedures to Detect Them

Purpose: To test the ability of the TG-119 commissioning process and RPC credentialing to detect errors in the commissioning process for a commercial Treatment Planning System (TPS). Methods: We introduced commissioning errors into the commissioning process for the Anisotropic Analytical Algorithm (AAA) within the Eclipse TPS. We included errors in Dosimetric Leaf Gap (DLG), electron contamination, flattening filter material, and beam profile measurement with an inappropriately large farmer chamber (simulated using sliding window smoothing of profiles). We then evaluated the clinical impact of these errors on clinical intensity modulated radiation therapy (IMRT) plans (head and neck, low and intermediate risk prostate, mesothelioma, and scalp) by looking at PTV D99, and mean and max OAR dose. Finally, for errors with substantial clinical impact we determined sensitivity of the RPC IMRT film analysis at the midpoint between PTV and OAR using a 4mm distance to agreement metric, and of a 7% TLD dose comparison. We also determined sensitivity of the 3 dose planes of the TG-119 C-shape IMRT phantom using gamma criteria of 3% 3mm. Results: The largest clinical impact came from large changes in the DLG with a change of 1mm resulting in up to a 5% change in the primary PTV D99. This resulted in a discrepancy in the RPC TLDs in the PTVs and OARs of 7.1% and 13.6% respectively, which would have resulted in detection. While use of incorrect flattening filter caused only subtle errors (<1%) in clinical plans, the effect was most pronounced for the RPC TLDs in the OARs (>6%). Conclusion: The AAA commissioning process within the Eclipse TPS is surprisingly robust to user error. When errors do occur, the RPC and TG-119 commissioning credentialing criteria are effective at detecting them; however OAR TLDs are the most sensitive despite the RPC currently excluding them from analysis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Back to Basics: First Principles of HRA

Human Reliability Analysis (HRA) continues to suffer from a myriad of technical gaps in its foundations. Core issues have been widely discussed but remain largely unaddressed, although the path taken to this point was paved with good intentions. Now, while this characterization may seem dramatic it is not intended to throw doubt onto HRA as a discipline or to diminish the value it has on increasing safety and resilience in nuclear power. Rather, it is intended to communicate that HRA has some serious challenges and is desperately in need of a critical evaluation. To quote Dougherty [1], “the misrepresentations that will undoubtedly arise may serve to provoke the necessary creativity.” What bears noting is that in the last thirty years since Alan Swain declared that “no adequate HRA had ever been done,” there has been little effort to correct the issues he highlighted. Human factors practice is still poorly implemented, many complex systems are fundamentally incompatible with reliable human performance, and there remains poor foundational support for many of the assumptions within HRA. We propose three categories of issues in HRA, philosophical, theoretical, and empirical and potential solutions to these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Simulating Z 2 lattice gauge theory on a quantum computer

The utility of quantum computers for simulating lattice gauge theories is currently limited by the noisiness of the physical hardware. Various quantum error mitigation strategies exist to reduce the statistical and systematic uncertainties in quantum simulations via improved algorithms and analysis strategies. We perform quantum simulations of Z 2 gauge theory with matter to study the efficacy and interplay of different error mitigation methods: readout error mitigation, randomized compiling, rescaling, and dynamical decoupling. We compute Minkowski correlation functions in this confining gauge theory and extract the mass of the lightest spin-1 state from fits to their time dependence. Quantum error mitigation extends the range of times over which our correlation function calculations are accurate by a factor of 6 and is therefore essential for obtaining reliable masses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Using artificial intelligence to detect human errors in nuclear power plants: A case in operation and maintenance

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

BOSS DR12 full-shape cosmology: Λ CDM constraints from the large-scale galaxy power spectrum and bispectrum monopole

Here, we present a full Λ CDM analysis of the BOSS DR12 dataset, including information from the power spectrum multipoles, the real-space power spectrum, the reconstructed power spectrum and the bispectrum monopole. This is the first analysis to feature a complete treatment of the galaxy bispectrum, including a consistent theoretical model and without large-scale cuts. Unlike previous works, the statistics are measured using window-free estimators: this greatly reduces computational costs by removing the need to window-convolve the theory model. Our pipeline is tested using a suite of high-resolution mocks and shown to be robust and precise, with systematic errors far below the statistical thresholds. Inclusion of the bispectrum yields consistent parameter constraints and shrinks the σ 8 posterior by 13% to reach < 5 % precision; less conservative analysis choices would reduce the error bars further. Our constraints are broadly consistent with Planck: in particular, we find H 0 = 69.6$^{+1.1}_{–1.3}$ km s –1 Mpc –1 , σ 8 = 0.692$^{+0.035}_{–0.041}$ and n s = 0.870$^{+0.067}_{–0.064}$, including a BBN prior on the baryon density. When n s is set by Planck, we find H 0 = 68.31$^{+0.83}_{–0.86}$ km s –1 Mpc –1 and σ 8 = 0.722$^{+0.032}_{–0.036}$. Our S 8 posterior, 0.751 ± 0.039, is consistent with weak lensing studies, but lower than Planck. Constraints on the higher-order bias parameters are significantly strengthened from the inclusion of the bispectrum, and we find no evidence for deviation from the dark matter halo bias relations. These results represent the most complete full-shape analysis of BOSS DR12 to-date, and the corresponding spectra will enable a variety of beyond-Λ CDM analyses, probing phenomena such as the neutrino mass and primordial non-Gaussianity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Error field identification through torque balance on a saturated island in DIII-D

Measurement of the electromagnetic torque on a magnetic island could be an attractive method for error field identification in the early phase of ITER operation. Previous DIII-D experiments (Strait 2014 Nucl. Fusion 54 073004; Shiraki et al 2015 Plasma Phys. Control. Fusion 57 025016) have demonstrated the principle of this approach using a stationary or slowly rotating island, while recent developments in magnetic data analysis (Sweeney and Strait 2019 Phys. Plasmas 26 012509) allow the field of a rapidly rotating island to be readily distinguished from that of the wall currents induced by its rotation. In a recent experiment, a rotating n = 1 magnetic perturbation forced a saturated magnetic island to rotate, thus sampling all toroidal phases periodically in a single discharge. The phase and amplitude of the error field are inferred from analysis of the time-dependent torque balance on the island, including torques from the error field, the applied magnetic perturbation, and the wall currents induced by rotation of the applied perturbation and the island. Furthermore, results agree well with those from more conventional methods.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

SU-E-T-261: Development of An Automated System to Detect Patient Identification and Positioning Errors Prior to Radiotherapy Treatment

Purpose: To develop a system that can automatically detect patient identification and positioning errors using 3D computed tomography (CT) setup images and kilovoltage CT (kVCT) planning images. Methods: Planning kVCT images were collected for head-and-neck (H&N), pelvis, and spine treatments with corresponding 3D cone-beam CT (CBCT) and megavoltage CT (MVCT) setup images from TrueBeam and TomoTherapy units, respectively. Patient identification errors were simulated by registering setup and planning images from different patients. Positioning errors were simulated by misaligning the setup image by 1cm to 5cm in the six anatomical directions for H&N and pelvis patients. Misalignments for spine treatments were simulated by registering the setup image to adjacent vertebral bodies on the planning kVCT. A body contour of the setup image was used as an initial mask for image comparison. Images were pre-processed by image filtering and air voxel thresholding, and image pairs were assessed using commonly-used image similarity metrics as well as custom -designed metrics. A linear discriminant analysis classifier was trained and tested on the datasets, and misclassification error (MCE), sensitivity, and specificity estimates were generated using 10-fold cross validation. Results: Our workflow produced MCE estimates of 0.7%, 1.7%, and 0% for H&N, pelvis, and spine TomoTherapy images, respectively. Sensitivities and specificities ranged from 98.0% to 100%. MCEs of 3.5%, 2.3%, and 2.1% were obtained for TrueBeam images of the above sites, respectively, with sensitivity and specificity estimates between 96.2% and 98.4%. MCEs for 1cm H&N/pelvis misalignments were 1.3/5.1% and 9.1/8.6% for TomoTherapy and TrueBeam images, respectively. 2cm MCE estimates were 0.4%/1.6% and 3.1/3.2%, respectively. Vertebral misalignment MCEs were 4.8% and 4.9% for TomoTherapy and TrueBeam images, respectively. Conclusion: Patient identification and gross misalignment errors can be robustly and automatically detected using 3D setup images of two imaging modalities across three commonly-treated anatomical sites.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A precise non-invasive blood glucose measurement system using NIR spectroscopy and Huber’s regression model

Diabetes is one of the prominent diseases around the world. Presently, invasive techniques need a finger prick blood sample . A repetitively painful procedure that produces the chance of infection. To resolve this issue, non-invasive measurement approach is proposed. In this paper, an efficient NIR wave based optical detection system is proposed with optimized post-processing regression model. After real-time data analysis, it has been found that the coefficient of determination (R{sup 2}) is improved with the value of 0.9084 using proposed regression model. Mean absolute derivative is also increased with 3.87 mg/dl corresponding to predicted blood glucose concentration. Mean absolute relative difference has exceeded to 3.25%, and average error is improved with 3.77% using proposed regression model. Average accuaracy has been analyzed 94–95% for predicted blood glucose concentration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Timestamp Shift Detection for Synchrophasor Data Based on Similarity Analysis between Relative Phase Angle and Frequency

Timestamp Shift (TS) in synchrophasor data can lead to false operation of synchrophasor-based wide-area monitoring, protection and control applications. The letter presents a method to detect TS of synchrophasor data based on similarity analysis between its own relative phase angle and frequency. Here, a linear correlation component, caused by TS, between relative phase angle and measured frequency is discovered via theoretical derivation. Then a detection method is developed utilizing this linear component for TS diagnosis. Firstly, system phase angle is leveraged as angle reference and then relative phase angle is calculated. Secondly, the correlation coefficient between relative phase angle and frequency is calculated for similarity analysis. Thirdly, the TS is detected via threshold criterion and corresponding time error is estimated. The effectiveness of this method is validated via experiments with actual synchrophasor data in FNET/Grideye.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

On-line monitoring for turbine bypass system based on real-time simulation - 108

Faults may occur in nuclear power plants, but it is difficult for operators to recognize the situation and take effective measures quickly. However, on-line monitoring may help operators to detect the abnormalities so that the safety of nuclear power plants will be improved. As Turbine Bypass System runs during transient processes, quantitative simulation model is utilized for on-line monitoring. In addition, analyzing for residual errors of simulated and corresponding measured values are done by principle component analysis. Under normal operation, the methodology allows real-time tracking to set dynamic thresholds. While a failure occurs, faults can be detected. Simulation analysis show the effectiveness and accuracy of this methodology. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

A method to correct coordinate distortion in EBSD maps

Drift during electron backscatter diffraction mapping leads to coordinate distortions in resulting orientation maps, which affects, in some cases significantly, the accuracy of analysis. A method, thin plate spline, is introduced and tested to correct such coordinate distortions in the maps after the electron backscatter diffraction measurements. The accuracy of the correction as well as theoretical and practical aspects of using the thin plate spline method is discussed in detail. By comparing with other correction methods, it is shown that the thin plate spline method is most efficient to correct different local distortions in the electron backscatter diffraction maps. - Highlights: • A new method is suggested to correct nonlinear spatial distortion in EBSD maps. • The method corrects EBSD maps more precisely than presently available methods. • Errors less than 1–2 pixels are typically obtained. • Direct quantitative analysis of dynamic data are available after this correction.

36 MATERIALS SCIENCE↗
DOE OSTI2017

CODEX weak lensing: concentration of galaxy clusters at z ~ 0.5

Here, we present a stacked weak-lensing analysis of 27 richness selected galaxy clusters at 0.40 ≤ z ≤ 0.62 in the COnstrain Dark Energy with X-ray galaxy clusters (CODEX) survey. The fields were observed in five bands with the Canada–France–Hawaii Telescope (CFHT). We measure the stacked surface mass density profile with a 14σ significance in the radial range 0.1 < RMpch -1 < 2.5. The profile is well described by the halo model, with the main halo term following a Navarro–Frenk–White profile (NFW) profile and including the off-centring effect. We select the background sample using a conservative colour–magnitude method to reduce the potential systematic errors and contamination by cluster member galaxies. We perform a Bayesian analysis for the stacked profile and constrain the best-fitting NFW parameters M 200c =6.6$+1.0\atop{-0.8}$×10 14 h -1 M⊙ and c 200c =3.7$+0.7\atop{-0.6}$. The off-centring effect was modelled based on previous observational results found for redMaPPer Sloan Digital Sky Survey clusters. Our constraints on M200c and c200c allow us to investigate the consistency with numerical predictions and select a concentration–mass relation to describe the high richness CODEX sample. Comparing our best-fitting values for M200c and c200c with other observational surveys at different redshifts, we find no evidence for evolution in the concentration–mass relation, though it could be mitigated by particular selection functions. Similar to previous studies investigating the X-ray luminosity–mass relation, our data suggest a lower evolution than expected from self-similarity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Cosmological measurements with general relativistic galaxy correlations

We investigate the cosmological dependence and the constraining power of large-scale galaxy correlations, including all redshift-distortions, wide-angle, lensing and gravitational potential effects on linear scales. We analyze the cosmological information present in the lensing convergence and in the gravitational potential terms describing the so-called ''relativistic effects'', and we find that, while smaller than the information contained in intrinsic galaxy clustering, it is not negligible. We investigate how neglecting them does bias cosmological measurements performed by future spectroscopic and photometric large-scale surveys such as SKA and Euclid. We perform a Fisher analysis using the CLASS code, modified to include scale-dependent galaxy bias and redshift-dependent magnification and evolution bias. Our results show that neglecting relativistic terms, especially lensing convergence, introduces an error in the forecasted precision in measuring cosmological parameters of the order of a few tens of percent, in particular when measuring the matter content of the Universe and primordial non-Gaussianity parameters. The analysis suggests a possible substantial systematic error in cosmological parameter constraints. Therefore, we argue that radial correlations and integrated relativistic terms need to be taken into account when forecasting the constraining power of future large-scale number counts of galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Supervised detection of anomalous light curves in massive astronomical catalogs

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Mass variance from archival X-ray properties of Dark Energy Survey Year-1 galaxy clusters

ABSTRACT Using archival X-ray observations and a lognormal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behaviour of X-ray temperatures, TX, with optical richness, λRM, for clusters in the redshift range 0.2 < z < 0.7. X-ray temperatures are obtained from Chandra and XMM observations for 58 and 110 redMaPPer systems, respectively. Despite non-uniform sky coverage, the TX measurements are $\gt 50{{\ \rm per\ cent}}$ complete for clusters with λRM > 130. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $\sigma _{\ln T \, |\, \lambda }= 0.275 \pm 0.019$. Joined with constraints for TX scaling with halo mass from the Weighing the Giants program and richness–temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $\sigma _{\ln M \, |\, \lambda }= 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 100. Uncertainties in external parameters, particularly the slope and variance of the TX–mass relation and the covariance of TX and λRM at fixed mass, dominate the systematic error. The $95{{\ \rm per\ cent}}$ confidence region from joint sample analysis is relatively broad, $\sigma _{\ln M \, |\, \lambda }\in [0.14, \, 0.55]$, or a factor 10 in variance.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Deployment of neural-network-based neutron microscopic cross sections in the Griffin reactor physics application

The capability to utilize neural networks to predict macroscopic and microscopic cross section parametric spaces has been developed for the Griffin reactor physics application. The LibTorch interface enables Griffin's MOOSE-based materials to interact with LibTorch-trained models, allowing for the evaluation of complex macroscopic or microscopic cross section spaces, which are then used to evaluate the neutronic properties of the Griffin finite element model. This study benchmarks traditional ISOXML-formatted tabulation libraries against neural network-based models for 279 nuclides on 20,160 grid points for zero-dimensional and two-dimensional reactor models. Benchmark metrics include the fundamental mode eigenvalue, fission and absorption rates, and various temperature coefficients of reactivity (isothermal, fuel, and moderator). From the perspective of storage space, the complete set of LibTorch models uses 11 MB on disk, compared to the 10 GB for the ISOXML multigroup library that covers the same grid space. For the two-dimensional performance case considered in Griffin, the Torch model uses 97% less RAM than the reference ISOXML dataset while runtime increases by a factor of 3 when using the LibTorch model compared to the ISOXML dataset with multi-linear interpolation. The LibTorch model consistently yields errors within 0.01% for most analyzed quantities except for the temperature coefficients of reactivity where the maximum discrepancies are up to 0.3 $\frac{pcm}{K}$. Due to the neural network attempting to best predict quantities with no regard for a positive or negative bias for any given quantity, predictions may experience random fluctuations, resulting in both positive and negative errors. Future work will entail both depletion and coupled transient analysis to determine the predictive capabilities of Griffin with neural network-based cross sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

High-Accuracy Mesh-Free Quadrature for Trimmed Parametric Surfaces and Volumes

This work presents a high-accuracy, mesh-free, generalized Stokes theorem-based numerical quadrature scheme for integrating functions over trimmed parametric surfaces and volumes. The algorithm relies on two fundamental steps: (1) We iteratively reduce the dimensionality of integration using the generalized Stokes theorem to line integrals over trimming curves, and (2) we employ numerical antidifferentiation in the generalized Stokes theorem using high-order quadrature rules. Additionally, the scheme achieves exponential convergence up to trimming curve approximation error and has applications to computation of geometric moments, immersogeometric analysis, conservative field transfer between high-order curvilinear meshes, and initialization of multi-material simulations. We compare the quadrature scheme to commonly-used quadrature schemes in the literature and show that our scheme is much more efficient in terms of number of quadrature points used. We provide an open-source implementation of the scheme in MATLAB as part of QuaHOG, a software package for Quadrature of High-Order Geometries.

97 MATHEMATICS AND COMPUTING↗