SEARCH · Search NASA

Results for “Reliability Prediction”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,531 records · Page 85

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Dark Energy Survey Year 3 results: Constraints on extensions to Λ CDM with weak lensing and galaxy clustering

We constrain six possible extensions to the Λ cold dark matter (CDM) model using measurements from the Dark Energy Survey’s first three years of observations, alone and in combination with external cosmological probes. The DES data are the two-point correlation functions of weak gravitational lensing, galaxy clustering, and their cross-correlation. We use simulated data vectors and blind analyses of real data to validate the robustness of our results to astrophysical and modeling systematic errors. In many cases, constraining power is limited by the absence of theoretical predictions beyond the linear regime that are reliable at our required precision. The Λ CDM extensions are dark energy with a time-dependent equation of state, nonzero spatial curvature, additional relativistic degrees of freedom, sterile neutrinos with eV-scale mass, modifications of gravitational physics, and a binned σ 8 ( z ) model which serves as a phenomenological probe of structure growth. For the time-varying dark energy equation of state evaluated at the pivot redshift we find ( w p , w a ) = ( - 0.9 9 - 0.17 + 0.28 , - 0.9 ± 1.2 ) at 68% confidence with z p = 0.24 from the DES measurements alone, and ( w p , w a ) = ( - 1.0 3 - 0.03 + 0.04 , - 0. 4 - 0.3 + 0.4 ) with z p = 0.21 for the combination of all data considered. Curvature constraints of Ω k = 0.0009 ± 0.0017 and effective relativistic species N eff = 3.1 0 - 0.16 + 0.15 are dominated by external data, though adding DES information to external low-redshift probes tightens the Ω k constraints that can be made without cosmic microwave background observables by 20%. For massive sterile neutrinos, DES combined with external data improves the upper bound on the mass m eff by a factor of 3 compared to previous analyses, giving 95% limits of ( Δ N eff , m eff ) ≤ ( 0.28 , 0.20 eV ) when using priors matching a comparable Planck analysis. For modified gravity, we constrain changes to the lensing and Poisson equations controlled by functions Σ ( k , z ) = Σ 0 Ω Λ ( z ) / Ω Λ , 0 and μ ( k , z ) = μ 0 Ω Λ ( z ) / Ω Λ , 0 , respectively, to Σ 0 = 0. 6 - 0.5 + 0.4 from DES alone and ( Σ 0 , μ 0 ) = ( 0.04 ± 0.05 , 0.0 8 - 0.19 + 0.21 ) for the combination of all data, both at 68% confidence. Overall, we find no significant evidence for physics beyond Λ CDM .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Measurement of the 2 ν β β Decay Rate and Spectral Shape of Mo 100 from the CUPID-Mo Experiment

Neutrinoless double beta decay (0νββ) is a yet unobserved nuclear process that would demonstrate Lepton number violation, a clear evidence of beyond standard model physics. The process two neutrino double beta decay (2νββ) is allowed by the standard model and has been measured in numerous experiments. In this Letter, we report a measurement of 2νββ decay half-life of 100 Mo to the ground state of 100 Ru of [7.07±0.02(stat)±0.11(syst)]×10 18 yr by the CUPID-Mo experiment. With a relative precision of ±1.6% this is the most precise measurement to date of a 2νββ decay rate in 100 Mo. In addition, we constrain higher-order corrections to the spectral shape, which provides complementary nuclear structure information. We report a novel measurement of the shape factor ξ 3,1 =0.45±0.03(stat)±0.05(syst) based on a constraint on the ratio of higher-order terms from theory, which can be reliably calculated. This is compared to theoretical predictions for different nuclear models. Finally, we also extract the first value for the effective axial vector coupling constant obtained from a spectral shape study of 2νββ decay.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

First-principles engineering of charged defects for two-dimensional quantum technologies

Charged defects in two-dimensional (2D) materials have emerging applications in quantum technologies such as quantum emitters and quantum computation. The advancement of these technologies requires a rational design of ideal defect centers, demanding reliable computation methods for the quantitatively accurate prediction of defect properties. Here, we present an accurate, parameter-free, and efficient procedure to evaluate the quasiparticle defect states and thermodynamic charge transition levels of defects in 2D materials. Importantly, we solve critical issues that stem from the strongly anisotropic screening in 2D materials, that have so far precluded the accurate prediction of charge transition levels in these materials. Using this procedure, we investigate various defects in monolayer hexagonal boron nitride (h-BN) for their charge transition levels, stable spin states, and optical excitations. We identify C B V N (nitrogen vacancy adjacent to carbon substitution of boron) to be the most promising defect candidate for scalable quantum bit and emitter applications.

2D materials↗

DOE OSTI2017

A Data-Driven Methodology for Probabilistic Wind Power Ramp Forecasting

With increasing wind penetration, wind power ramps (WPRs) are currently drawing great attention to balancing authorities, since these wind ramps largely affect power system operations. To help better manage and dispatch the wind power, this paper develops a data-driven probabilistic WPR forecasting (p-WPRF) method based on a large number of simulated scenarios. A machine learning technique is first adopted to forecast the basic wind power forecasting scenario and produce the historical forecasting errors. To accurately model the distribution of wind power forecasting errors, a generalized Gaussian mixture model is developed and the cumulative distribution function (CDF) is also analytically deduced. The inverse transform method based on the CDF is used to generate a large number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The p-WPRF is generated based on all generated scenarios under different weather and time conditions. Numerical simulations on publicly available wind power data show that the developed p-WPRF method can predict WPRs with a high level of reliability and accuracy.

17 WIND ENERGY↗

DOE OSTI2018

A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps

Efficient management of wind ramping characteristics can significantly reduce wind integration costs for balancing authorities. By considering the stochastic dependence of wind power ramp (WPR) features, this paper develops a conditional probabilistic wind power ramp forecast (cp-WPRF) model based on Copula theory. The WPRs dataset is constructed by extracting ramps from a large dataset of historical wind power. Each WPR feature (e.g., rate, magnitude, duration, and start-time) is separately forecasted by considering the coupling effects among different ramp features. To accurately model the marginal distributions with a copula, a Gaussian mixture model (GMM) is adopted to characterize the WPR uncertainty and features. The Canonical Maximum Likelihood (CML) method is used to estimate parameters of the multivariable copula. The optimal copula model is chosen based on the Bayesian information criterion (BIC) from each copula family. Finally, the best conditions based cp-WPRF model is determined by predictive interval (PI) based evaluation metrics. Numerical simulations on publicly available wind power data show that the developed copula-based cp-WPRF model can predict WPRs with a high level of reliability and sharpness.

17 WIND ENERGY↗

DOE OSTI2021

Examination of the Extreme Cold Weather Event Affecting the Power System in Texas - February 2021 [Slides]

This presentation examines the extreme cold weather event that affected the power system in Texas in February 2021. The Texas load-shedding events were caused by a combination of record-high demand and cold weather issues that reduced the output from all types of generation. While some wind turbines were shutting down due to cold temperatures and icing and a lack of cold-weather packages, hourly wind output was accurately predicted. Extreme weather events historically drive grid reliability. Additional examination of more extreme events is needed to understand their impacts on the power system. As a national lab, NREL has the capabilities and facilities to help the industry address these types of challenges. NREL also has significant simulation and analysis capabilities (such as NAERM) that can help understand the impacts of extreme events. NREL also developed the Advanced Research on Integrated Energy Systems (ARIES) Research Platform, which enables evaluation of technologies that smooth grid operations during events like this.

17 WIND ENERGY↗

DOE OSTI2022

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Uncertainty-Driven Rapid Thermodynamic Assessment of Nb-Ta-Zr System and Effects of C impurities (L25GF9298S): Annual Progress Report

An integrated computational materials engineering (ICME) method is in development for rapid thermodynamic experimental investigation and high-fidelity computational modeling of refractory multi-principal element alloys (RMPEAs). These ultra-high-temperature (UHT) alloys are of interest for structural applications in extreme environments, but deficiency of reliable data, especially melting temperatures, impedes the prediction of alloys with favorable properties. The method leverages UHT capabilities and computational expertise of LLNL’s Materials Science Division and the McCormack Lab’s UHT conical nozzle levitation (CNL) system to iteratively map the Nb-Ta-Zr phase space, with focus on the liquidus surface, through targeted experiments selected by quantifying uncertainty in the thermodynamic model fitting parameters. This method will reduce the time to map uncharted RMPEA phase space and thereby accelerate discovery and development of advanced materials for applications in extreme environments.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Experimental Observation of Inertial Particles through Idealized Hydroturbine Distributor Geometry

To increase and maintain existing hydropower capacity within biological performance-based regulations, predictive simulation methods are needed that can reliably estimate the risk to fish passing through flow passage routes at hydropower facilities. One of the central challenges is to validate the software capabilities for simulating the trajectories, including collisions, of inertial particles against laboratory data. In this work, neutrally buoyant spherical- and rod-shaped beads were released upstream of laboratory-scale geometries representative of the distributor of a hydroturbine. The experimental campaign involved a test matrix of 24 configurations with variations in bead geometry, collision target geometry, flow speeds, and release locations. A total of more than 10,000 beads were recorded using high-speed video cameras and analyzed using particle tracking software. Collision rates from 1–7% were observed for the cylinder geometry and rates of 1–23% were observed for the vane array over the range of test configurations.

13 HYDRO ENERGY↗

DOE OSTI2016

Reverberation mapping of the broad line region: application to a hydrodynamical line-driven disk wind solution

The latest analysis efforts in reverberation mapping are beginning to allow reconstruction of echo images (or velocity-delay maps) that encode information about the structure and kinematics of the broad line region (BLR) in active galactic nuclei (AGNs). Such maps can constrain sophisticated physical models for the BLR. The physical picture of the BLR is often theorized to be a photoionized wind launched from the AGN accretion disk. Previously we showed that the line-driven disk wind solution found in an earlier simulation by Proga and Kallman is virialized over a large distance from the disk. This finding implies that, according to this model, black hole masses can be reliably estimated through reverberation mapping techniques. However, predictions of echo images expected from line-driven disk winds are not available. Here, after presenting the necessary radiative transfer methodology, we carry out the first calculations of such predictions. We find that the echo images are quite similar to other virialized BLR models such as randomly orbiting clouds and thin Keplerian disks. We conduct a parameter survey exploring how echo images, line profiles, and transfer functions depend on both the inclination angle and the line opacity. We find that the line profiles are almost always single peaked, while transfer functions tend to have tails extending to large time delays. The outflow, despite being primarily equatorially directed, causes an appreciable blueshifted excess on both the echo image and line profile when seen from lower inclinations (i≲45{sup ∘}). This effect may be observable in low ionization lines such as Hβ.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Linking large-scale weather patterns to observed and modeled turbine hub-height winds offshore of the US West Coast

The US West Coast holds great potential for wind power generation, although its potential varies due to the complex coastal climate. Characterizing and modeling turbine hub-height winds under different weather conditions are vital for wind resource assessment and management. This study uses a two-stage machine learning algorithm to identify five large-scale meteorological patterns (LSMPs): post-trough, post-ridge, pre-ridge, pre-trough, and California high. The LSMPs are linked to offshore wind patterns, specifically at lidar buoy locations within lease areas for future wind farm development off Humboldt and Morro Bay. While each LSMP is associated with characteristic large-scale atmospheric conditions and corresponding differences in wind direction, diurnal variation, and jet features at the two lidar sites, substantial variability in wind speeds can still occur within each LSMP. Wind speeds at Humboldt increase during the post-trough, pre-ridge, and California-high LSMPs and decrease during the remaining LSMPs. Morro Bay has smaller responses in mean speeds, showing increased wind speed during the post-trough and California-high LSMPs. Besides the LSMPs, local factors, including the land–sea thermal contrast and topography, also modify mean winds and diurnal variation. The High-Resolution Rapid Refresh model analysis does a good job of capturing the mean and variation at Humboldt but produces large biases at Morro Bay, particularly during the pre-ridge and California-high LSMPs. The findings are anticipated to guide the selection of cases for studying the influence of specific large-scale and local factors on California offshore winds and to contribute to refining numerical weather prediction models, thereby enhancing the efficiency and reliability of offshore wind energy production.

17 WIND ENERGY↗

NASA NTRS1979

Assessment and preliminary design of an energy buffer for regenerative braking in electric vehicles

Energy buffer systems, capable of storing the vehicle energy during braking and reusing this stored energy during acceleration, were examined. Some of these buffer systems when incorporated in an electric vehicle would result in an improvement in the performance and range under stop and go driving conditions. Buffer systems considered included flywheels, hydropneumatic, pneumatic, spring, and regenerative braking. Buffer ranking and rating criteria were established. Buffer systems were rated based on predicted range improvements, consumer acceptance, driveability, safety, reliability and durability, and initial and life cycle costs. A hydropneumatic buffer system was selected.

Buchholz, R.↗

NASA NTRS1981

Identification and evaluation of software measures

A large scale, systematic procedure for identifying and evaluating measures that meaningfully characterize one or more elements of software development is described. The background of this research, the nature of the data involved, and the steps of the analytic procedure are discussed. An example of the application of this procedure to data from real software development projects is presented. As the term is used here, a measure is a count or numerical rating of the occurrence of some property. Examples of measures include lines of code, number of computer runs, person hours expended, and degree of use of top down design methodology. Measures appeal to the researcher and the manager as a potential means of defining, explaining, and predicting software development qualities, especially productivity and reliability.

Card, D. N.↗

NASA NTRS1982

Stability and control of the Gossamer human powered aircraft by analysis and flight test

The slow flight speed, very light wing loading, and neutral stability of the Gossamer Condor and the Gossamer Albatross emphasized apparent-mass aerodynamic effects and unusual modes of motion response. These are analyzed, approximated, and discussed, and the resulting transfer functions and dynamic properties are summarized and compared. To verify these analytical models, flight tests were conducted with and electrically powered Gossamer Albatross II. Sensors were installed and their outputs were telemetered to records on the ground. Frequency sweeps of the various controls were made and the data were reduced to frequency domain measures. Results are given for the response of: pitch rate, airspeed and normal acceleration from canard-elevator deflection; roll rate and yaw rate from canard-rudder tilt; and roll rate and yaw rate from wing warp. The reliable data are compared with the analytical predictions.

Jex, H. R.↗

NASA NTRS1985

Evaluation of half wave induction motor drive for use in passenger vehicles

Research performed at the University of Missouri-Columbia to devise and design a lower cost inverter induction motor drive for electrical propulsion of passenger vehicles is described. A two phase inverter motor system is recommended. The new design is predicted to provide comparable vehicle performance, improved reliability and a cost advantage for a high production vehicle, decreased total rating of the power semiconductor switches, and a somewhat simpler control hardware compared to the conventional three phase bridge inverter motor drive system. The major disadvantages of the two phase inverter motor drive are that it is larger and more expensive than a three phase machine, the design of snubbers for the power leakage inductances produce higher transient voltages, and the torque pulsations are relatively large because of the necessity to limit the inverter switching frequency to achieve high efficiency.

Hoft, R. G.↗

NASA NTRS1985

Development of an unsteady aerodynamics model to improve correlation of computed blade stresses with test data

A reliable rotor aeroelastic analysis operational that correctly predicts the vibration levels for a helicopter is utilized to test various unsteady aerodynamics models with the objective of improving the correlation between test and theory. This analysis called Rotor Aeroelastic Vibration (RAVIB) computer program is based on a frequency domain forced response analysis which utilizes the transfer matrix techniques to model helicopter/rotor dynamic systems of varying degrees of complexity. The results for the AH-1G helicopter rotor were compared with the flight test data during high speed operation and they indicated a reasonably good correlation for the beamwise and chordwise blade bending moments, but for torsional moments the correlation was poor. As a result, a new aerodynamics model based on unstalled synthesized data derived from the large amplitude oscillating airfoil experiments was developed and tested.

Gangwani, S. T.↗

NASA NTRS1985

Reliability and engineering of thin-film photovoltaic modules

Objectives were to: examine thin-film cell attributes that influence module performance and reliability, explore the lessons and applicability of crystalline-silicon module technology to thin-film modules, review the current status of thin-film module technologies, and identify problem areas and needed research. A major need is to separate the effects and resons for reversible degradatin from nonreversible degradation. Amorphous-silicon (a-Si) reliability investigations are focusing on exploratory research investigations, accelerated Arrhenius-type testing of a-Si cells, real-time outdoor exposure testing of a-Si cells, cell failure analysis, and failure mechanism research. Studies included the reduction in strength of glass by high temperature depositions on glass and laser scribing, encapsulation materials development needs, and the testing of modules. The new materials and processes in thin-film modules will require a delinquent reliability effort, including: establishment of mechanism-specific reliability goals; quantification of mechanism parameter dependencies; prediction of expected long-term degradation; identification of cost-effective solutions; and testing and failure analysis of trial solutions.

Royal, E. L.↗

NASA NTRS1988

Environment assisted degradation mechanisms in advanced light metals

The general goals of the research program are to characterize alloy behavior quantitatively and to develop predictive mechanisms for environmental failure modes. Successes in this regard will provide the basis for metallurgical optimization of alloy performance, for chemical control of aggressive environments, and for engineering life prediction with damage tolerance and long term reliability.

Gangloff, Richard P.↗