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Results for “Reliability Analysis”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Ion-pairing in aqueous CaCl 2 and RbBr solutions. Simultaneous structural refinement of XAFS and XRD data

We present a new methodology involving the simultaneous refinement of both x-ray absorption and x-ray diffraction spectra (X-ray Absorption/Diffraction Structural Refinement,XADSR), to study hydration and ion pair structure of CaCl 2 and RbBr salts in concentrated aqueous solutions. The XADSR analysis includes the XAFS spectra analysis of both the cation and anion as a probe of their short-range structure with an XRD spectral analysis as a probe of the global structural. Together they deliver a comprehensive picture of the cation and anion hydration, the contact ion pair (CIP) structure and the solvent-separated ion pair (SSIP) structure. XADSR analysis of 6.0 m aqueous CaCl 2 reveals that there are an insignificant number of Ca 2+ -Cl- CIP’s, but there are approximately 3.4 SSIP’s separated by about 4.99 Å. In contrast XADSR analysis of aqueous RbBr yields about 0.7 pair CIP at a bond length 3.51 Å. The present work demonstrates a new approach for a direct co-refinement of XRD and XAFS spectra in a simple and reliable fashion, opening new opportunities for analysis in various disordered and crystalline systems. This work was supported by the U.S. Department of Energy (DOE), Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences. Pacific Northwest National Laboratory (PNNL) is operated for the U.S. Department of Energy by Battelle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Simple new methods for deducing lifetimes in recoil distance Doppler-shift measurements

In this work, new approaches for lifetime determination using data from recoil distance Doppler-shift experiments are presented based on the fundamental properties of the functions describing the time evolution of the population of excited nuclear states. To some extent, one of them represents a contraction of the well-known Differential decay-curve method (DDCM) by using the most reliable data point [the maximum of the $n_i(t)$ function describing the population of level $\textit{i}$ in time] and a purely numerical procedure avoiding any fitting of decay curves. The combination with the standard DDCM analysis is promising for improving the reliability and the precision of the results for the lifetimes obtained. The novel part of the approach consists of using a chain of equations at the consecutive maxima of the ni(t) functions, which allow us to precisely determine the ratio of the lifetimes of two consecutive levels and, in the case where one of these lifetimes is known, to determine the unknown one. In addition, a simple integral derivation of the lifetime is presented involving the peak areas measured at different distances, and an application of the first moments (expectation values and centroids in time) of the $n_i(t)$ functions for determining lifetimes is also demonstrated to be useful.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Chaotic dynamics of flexible Euler-Bernoulli beams

Mathematical modeling and analysis of spatio-temporal chaotic dynamics of flexible simple and curved Euler-Bernoulli beams are carried out. The Kármán-type geometric non-linearity is considered. Algorithms reducing partial differential equations which govern the dynamics of studied objects and associated boundary value problems are reduced to the Cauchy problem through both Finite Difference Method with the approximation of O(c{sup 2}) and Finite Element Method. The obtained Cauchy problem is solved via the fourth and sixth-order Runge-Kutta methods. Validity and reliability of the results are rigorously discussed. Analysis of the chaotic dynamics of flexible Euler-Bernoulli beams for a series of boundary conditions is carried out with the help of the qualitative theory of differential equations. We analyze time histories, phase and modal portraits, autocorrelation functions, the Poincaré and pseudo-Poincaré maps, signs of the first four Lyapunov exponents, as well as the compression factor of the phase volume of an attractor. A novel scenario of transition from periodicity to chaos is obtained, and a transition from chaos to hyper-chaos is illustrated. In particular, we study and explain the phenomenon of transition from symmetric to asymmetric vibrations. Vibration-type charts are given regarding two control parameters: amplitude q{sub 0} and frequency ω{sub p} of the uniformly distributed periodic excitation. Furthermore, we detected and illustrated how the so called temporal-space chaos is developed following the transition from regular to chaotic system dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Rolling Element Bearing Dynamics in Wind Turbines

There are unique reliability challenges related to wind turbine drivetrains. Predominant failure modes are not accounted for in design standards, not attributable to material deficiencies or quality control, and are complex and independent of the component supplier. The team conducted testing and analysis to enable improvement of inherent reliability, an increase of availability with less effort and drama, and a reduction in wind plant operation and maintenance costs. The analytic model was validated through uptower experiments, and the bearing speed was directly affected by drivetrain load and speed. Bearing sliding is widely present during regular turbine operations and significant sliding occurs during transient events, which can lead to bearing failures and shortened life.

17 WIND ENERGY↗
DOE OSTI2019

Capturing Maize Stand Heterogeneity Across Yield-Stability Zones Using Unmanned Aerial Vehicles (UAV)

Despite the new equipment capabilities, uneven crop stands are still common occurrences in crop fields, mainly due to spatial heterogeneity in soil conditions, seedling mortality due to herbivore predation and disease, or human error. Non-uniform plant stands may reduce grain yield in crops like maize. Thus, detecting signs of variability in crop stand density early in the season provides critical information for management decisions and crop yield forecasts. Processing techniques applied on images captured by unmanned aerial vehicles (UAVs) has been used successfully to identify crop rows and estimate stand density and, most recently, to estimate plant-to-plant interval distance. Here, we further test and apply an image processing algorithm on UAV images collected from yield-stability zones in a commercial crop field. Our objective was to implement the algorithm to compare variation of plant-spacing intervals to test whether yield differences within these zones are related to differences in crop stand characteristics. Our analysis indicates that the algorithm can be reliably used to estimate plant counts (precision >95% and recall >97%) and plant distance interval (R2 ~0.9 and relative error <10%). Analysis of the collected data indicated that plant spacing variability differences were small among plots with large yield differences, suggesting that it was not a major cause of yield variability across zones with distinct yield history. This analysis provides an example of how plant-detection algorithms can be applied to improve the understanding of patterns of spatial and temporal yield variability.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Follow-Up from the Photovoltaic Reliability Workshop (PVRW): Cost Modeling Capabilities to Evaluate Trends in PV Technologies

NREL's Solar and Storage Techno-Economic Analysis (TEA) team reviews live polling results from the Photovoltaic Reliability Workshop (PVRW) related to module technology trends believed to have the greatest reliability impacts. Then, the team reviews the publicly available tools and inputs necessary for evaluating reliability tradeoffs between initial module and system costs, degradation profiles, and levelized cost of energy (LCOE). These tools include the online Detailed Cost Analysis Models (DCAM) and the DuraMAT LCOE calculator.

cost modeling↗
DOE OSTI2016

Gearbox Reliability Collaborative Phase 3 Gearbox 2 Test

The National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC) was established by the U.S. Department of Energy in 2006; its key goal is to understand the root causes of premature gearbox failures and improve their reliability. The GRC uses a combined gearbox testing, modeling, and analysis approach disseminating data and results to the industry and facilitating improvement of gearbox reliability. This test data describes the tests of GRC gearbox 2 in the National Wind Technology Center dynamometer and documents any modifications to the original test plan. It serves as a guide to interpret the publicly released data sets with brief analyses to illustrate the data. TDMS viewer and Solidworks software required to view data files.

17 WIND ENERGY↗
DOE OSTI2014

SU-E-J-235: Varian Portal Dosimetry Accuracy at Detecting Simulated Delivery Errors

Purpose: To use receiver operating characteristic (ROC) analysis to quantify the Varian Portal Dosimetry (VPD) application's ability to detect delivery errors in IMRT fields. Methods: EPID and VPD were calibrated/commissioned using vendor-recommended procedures. Five clinical plans comprising 56 modulated fields were analyzed using VPD. Treatment sites were: pelvis, prostate, brain, orbit, and base of tongue. Delivery was on a Varian Trilogy linear accelerator at 6MV using a Millenium120 multi-leaf collimator. Image pairs (VPD-predicted and measured) were exported in dicom format. Each detection test imported an image pair into Matlab, optionally inserted a simulated error (rectangular region with intensity raised or lowered) into the measured image, performed 3%/3mm gamma analysis, and saved the gamma distribution. For a given error, 56 negative tests (without error) were performed, one per 56 image pairs. Also, 560 positive tests (with error) with randomly selected image pairs and randomly selected in-field error location. Images were classified as errored (or error-free) if percent pixels with γ<κ was < (or ≥) τ. (Conventionally, κ=1 and τ=90%.) A ROC curve was generated from the 616 tests by varying τ. For a range of κ and τ, true/false positive/negative rates were calculated. This procedure was repeated for inserted errors of different sizes. VPD was considered to reliably detect an error if images were correctly classified as errored or error-free at least 95% of the time, for some κ+τ combination. Results: 20mm{sup 2} errors with intensity altered by ≥20% could be reliably detected, as could 10mm{sup 2} errors with intensity was altered by ≥50%. Errors with smaller size or intensity change could not be reliably detected. Conclusion: Varian Portal Dosimetry using 3%/3mm gamma analysis is capable of reliably detecting only those fluence errors that exceed the stated sizes. Images containing smaller errors can pass mathematical analysis, though may be detected by visual inspection. This work was not funded by Varian Oncology Systems. Some authors have other work partly funded by Varian Oncology Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Understanding the many-body expansion for large systems. I. Precision considerations

Electronic structure methods based on low-order “n-body” expansions are an increasingly popular means to defeat the highly nonlinear scaling of ab initio quantum chemistry calculations, taking advantage of the inherently distributable nature of the numerous subsystem calculations. Here, we examine how the finite precision of these subsystem calculations manifests in applications to large systems, in this case, a sequence of water clusters ranging in size up to (H{sub 2}O){sub 47}. Using two different computer implementations of the n-body expansion, one fully integrated into a quantum chemistry program and the other written as a separate driver routine for the same program, we examine the reproducibility of total binding energies as a function of cluster size. The combinatorial nature of the n-body expansion amplifies subtle differences between the two implementations, especially for n ⩾ 4, leading to total energies that differ by as much as several kcal/mol between two implementations of what is ostensibly the same method. This behavior can be understood based on a propagation-of-errors analysis applied to a closed-form expression for the n-body expansion, which is derived here for the first time. Discrepancies between the two implementations arise primarily from the Coulomb self-energy correction that is required when electrostatic embedding charges are implemented by means of an external driver program. For reliable results in large systems, our analysis suggests that script- or driver-based implementations should read binary output files from an electronic structure program, in full double precision, or better yet be fully integrated in a way that avoids the need to compute the aforementioned self-energy. Moreover, four-body and higher-order expansions may be too sensitive to numerical thresholds to be of practical use in large systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Design Power Control Strategies of Grid-Forming Inverters for Microgrid Application

This paper develops and compares two control schemes in the application control layer of a non-phase-locked loop (non-PLL) grid-forming (GFM) inverter to gain insight and understanding into how the two schemes affect the dynamic responses of GFM inverters and the transition operation of microgrids. The first scheme adopts power tracking based on an outer current loop in grid-connected mode and droop control in islanded mode, and the second uses droop control in both grid-connected and islanded modes. Analytical study is developed to compare the performance of these two strategies from various aspects, including fundamental differences, transition operation, power tracking, and P-Q capability with low point-of-common-coupling (PCC) voltages. Extensive simulation testing is carried out to validate the control performance of these two control strategies, and the simulation testing confirms the findings of the analytic study. Finally, the second strategy is recommended because of its superior control performance and ease of implementation. The analysis and results are useful in developing reliable control schemes for non-PLL GFM inverters because increasing numbers of inverters will work as non-PLL grid-forming sources in future grids because of their improved stability and reliability.

grid-forming↗
DOE OSTI2023

Polarity effects on wake–up behavior of Al 0.94 B 0.06 N ferroelectrics

Wurtzite ferroelectric materials are promising candidates for energy-efficient memory technologies, particularly for applications requiring high operating temperatures. Asymmetric wake-up behaviors, in which the polarization reversal depends both on polarity and cycle number for the first few dozen cycles, must be better understood for reliable device operation. Here, the detailed analysis of the asymmetric wake-up behavior of thin film Al 0.94 B 0.06 N was performed combining time-resolved switching measurements with Rayleigh analysis, piezoelectric measurements, and etching experiments of progressively switched samples. Furthermore, the analysis shows that the gradual opening of the polarization hysteresis loops associated with wake-up is driven by a gradual increase in the domain-wall density and/or domain-wall mobility with electric field cycle to the polarity opposite to the growth polarity. The insights of this discovery will help to guide interface and polarity design in the eventual deployment of reliable devices based on these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Performance and Stability Characterization of the ICARUS Light Detection System

The ICARUS detector, a key component of the Short Baseline Neutrino (SBN) Program at Fermilab, consists of two identical T300 modules filled with liquid argon. It is equipped with a Light Detection System (LDS) based on 360 8-inch Hamamatsu R5912-MOD photomultiplier tubes (PMTs) arranged behind the wire planes to collect Vacuum Ultraviolet (VUV, $\sim$ 128 nm) scintillation light. Operating under cryogenic conditions ( $\sim$ 87 K), the LDS is essential for determining the event start time (t0) with nanosecond precision for beam spill synchronization, improving longitudinal spatial resolution, and contributing to the event trigger and cosmic-ray mitigation. The performance of the LDS was investigated addressing both hardware and data analysis aspects. Following a progressive degradation in PMT gain observed during operations at FNAL, systematic gain measurements were first carried out from room temperature down to low temperatures. The results show stable performance at room temperature but a significant, irreversible reduction in gain at low temperatures. Based on these findings, a series of mitigation strategies were implemented in the ICARUS detector to preserve PMT performance and ensure reliable cryogenic operation. Currently, ongoing waveform analysis of the PMT signals is being performed to characterize signal shape, charge integration, and timing properties, aiming to refine and improve the agreement between experimental data and Monte Carlo simulations.

Saia, Clara [U. Catania (main); INAF, Catania; Cat↗
DOE OSTI2020

Efficient Binary Static Code Data Flow Analysis Using Unsupervised Learning

The ever increasing need to ensure that code is reliably, efficiently and safely constructed has fueled the evolution of popular static binary code analysis tools. In identifying potential coding flaws in binaries, tools such as IDA Pro are used to disassemble the binaries into an opcode/assembly language format in support of manual static code analysis. Because of the highly manual and resource intensive nature involved with analyzing large binaries, the probability of overlooking potential coding irregularities and inefficiencies is quite high. In this paper, a light-weight data, unsupervised data flow methodology is described which uses highly-correlated data flow graph (CDFGs) to identify coding irregularities such that analysis time and required computing resources are minimized. Such analysis accuracy and efficiency gains are achieved by using a combination of graph analysis and unsupervised machine learning techniques which allows an analyst to focus on the most statistically significant flow patterns while performing binary static code analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
DOE OSTI2017

Potentialities of laser systems for remote sensing of the atmosphere at a wide variability of optical and physical characteristics: dimensionless-parametric modelling

Within the framework of generalisation of different approaches to the modelling of atmospheric lidars, the methodology capabilities for dimensionless-parametric analysis are expanded. The developed approach simplifies the analysis of the signal-to-noise ratio and potential capabilities of existing and newly developed monitoring systems with a wide variability of atmospheric and optical conditions and a great variety of modern lidars. Its applicability to the problems of remote atmospheric sensing, environmental monitoring and lidar navigation in providing the eye safety, noise immunity and reliability is discussed. (paper)

42 ENGINEERING↗
DOE OSTI2024

Transmission Operator Workflows for Real-Time Reliability Studies: A Review of Control Room Practices and Naturalistic Decision Making

This report provides an overview of real-time reliability study tools and their use by power system operators in the control room environment. After introducing some of the nuances of the control room environment and the differences in perspectives between power system engineers and operators, the roles and responsibilities of key entities involved in RTCA workflows are introduced. These are specifically the transmission system operator (TOP) and reliability coordinator (RC), which are required to run tools such as real-time contingency analysis (RTCA) as part of a real-time reliability assessment every 30 minutes, as dictated by a series of standards issued by the North American Electric Reliability Corporation (NERC). The process by which power systems operators operate the grid is discussed in terms of naturalistic decision making (NDM) and the recognition-primed decision-making (RPD) model. This cognitive model describe how experts working in high-risk, high-stress environments make safety-critical decisions under uncertainty and time pressure. For power system operators, the mental simulations involved in the traditional RPD model are supplemented by physics-based simulations using numerical tools, such as RTCA, to improve situational awareness and effectiveness of control actions. Next, a generic workflow is introduced to describe operator decision making for running RTCA tools and responding to system violations on a pre-contingent basis. The types of analysis performed and control actions chosen by power system operators are described in detail. The overall high-level workflow is then expanded in subsequent sections, with special attention given to high-voltage violations, low-voltage violations, and thermal overloads. Each type of violation is described in detail, with explanations of common causes, impacts on equipment and customers, and mitigation strategies. An additional workflow diagram is provided for each type of violation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Uncertainty Quantification for Quantitative Imaging Holdup Measurements

In nuclear fuel cycle safeguards, special nuclear material "held up" in pipes, ducts, and glove boxes causes significant uncertainty in material-unaccounted-for estimates. Quantitative imaging is a proposed non-destructive assay technique with potential to estimate the holdup mass more accurately and reliably than current techniques. However, uncertainty analysis for quantitative imaging remains a significant challenge. In this work we demonstrate an analysis approach for data acquired with a fast-neutron coded aperture imager. The work includes a calibrated forward model of the imager. Cross-validation indicates that the forward model predicts the imager data typically within 23%; further improvements are forthcoming. A new algorithm based on the chi-squared goodness-of-fit metric then uses the forward model to calculate a holdup confidence interval. The new algorithm removes geometry approximations that previous methods require, making it a more reliable uncertainty estimator.

holdup measurement↗