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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Effects of V-22 Blade Modifications on Whirl Flutter and Loads

A CAMRAD II model of the V-22 Osprey tiltrotor was constructed for the purpose of analyzing the effects of blade design changes on whirl flutter. The model incorporated a dual load-path grip/yoke assembly, a swashplate coupled to the transmission case, and a drive train. A multiple-trailer free wake was used for loads calculations. The effects of rotor design changes on whirl-mode stability were calculated for swept blades and offset tip masses. A rotor with swept tips and inboard tuning masses was examined in detail to reveal the mechanisms by which these design changes affect stability and loads. Certain combinations of design features greatly increased whirl-mode stability, with (at worst) moderate increases to loads.

Acree, C. W., Jr.↗
NASA NTRS2005

Effects of Swept Tips on V-22 Whirl Flutter and Loads

A CAMRAD II model of the V-22 Osprey tiltrotor was constructed for the purpose of analyzing the effects of blade design changes on whirl flutter. The model incorporated a dual load-path grip/yoke assembly, a swashplate coupled to the transmission case, and a drive train. A multiple-trailer free wake was used for loads calculations. The effects of rotor design changes on whirl-mode stability were calculated for swept blades and offset tip masses. A rotor with swept tips and inboard tuning masses was examined in detail to reveal the mechanisms by which these design changes affect stability and loads. Certain combinations of design features greatly increased whirl-mode stability, with (at worst) moderate increases to loads.

Acree, C. W., Jr.↗
NASA NTRS1981

Methods and models for predicting fatigue crack growth under random loading

Papers are presented in the volume summarizing the baseline data, methodology, procedures, and results of a round-robin analysis which was conducted to predict the fatigue crack growth in 2219-T851 aluminum center-cracked specimens subjected to flight loading in random cycle-by-cycle format. The objective of the analysis was to assess whether data from constant-amplitude fatigue crack growth tests on center-cracked specimens can be used to predict fatigue crack growth lives under random loading. The following approaches are discussed in detail: a root-mean-square approach, a crack-closure model, a multi-parameter yield zone model, and a load-interaction model.

Chang, J. B.↗
NASA NTRS1991

Fracture analysis of transverse crack-tip and free-edge delamination in laminated composites

A shear deformation model including hygrothermal effects is developed for the analysis of local delaminations originating from transverse cracks in 90-deg plies located in and around the laminate midplane. A sublaminate approach is used and the model is applied to (+/- 25/90n)s T300/934 graphite/epoxy laminates for n values between 0.5 and 8, along with previously developed edge-delamination shear-deformation models. Critical loads and delamination modes are identified and compared with experimental results. Hygrothermal effects are included in all the models to make the comparisons realistic.

Armanios, Erian A.↗
NASA NTRS1985

A review of fracture mechanics life technology

Current lifetime prediction technology for structural components subjected to cyclic loads was reviewed. The central objectives of the project were to report the current state of and recommend future development of fracture mechanics-based analytical tools for modeling and forecasting subcritical fatigue crack growth in structures. Of special interest to NASA was the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. A survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology were conducted. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include: development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Thomas, J. M.↗
NASA NTRS1994

Recent advances in the modelling of crack growth under fatigue loading conditions

Fatigue crack growth associated with cyclic (secondary) plastic flow near a crack front is modelled using an incremental formulation. A new description of threshold behaviour under small load cycles is included. Quasi-static crack extension under high load excursions is described using an incremental formulation of the R-(crack growth resistance)- curve concept. The integration of the equations is discussed. For constant amplitude load cycles the results will be compared with existing crack growth laws. It will be shown that the model also properly describes interaction effects of fatigue crack growth and quasi-static crack extension. To evaluate the more general applicability the model is included in the NASGRO computer code for damage tolerance analysis. For this purpose the NASGRO program was provided with the CORPUS and the STRIP-YIELD models for computation of the crack opening load levels. The implementation is discussed and recent results of the verification are presented.

Dekoning, A. U.↗
DOE OSTI2023

Stochastic Models, Indices & Optimization Algorithms for Pricing & Hedging Reliability Risks in Modern Power Grids: Data Plan - Princeton

We collected and cleaned the synthetic grid data produced by NREL for the Texas and New York synthetic grids. We developed a high dimensional joint stochastic model for load at the zone level, and solar and wind power productions at the asset level, capturing the spatial and temporal dependencies between all the variables, and demonstrated how such a model could be fitted to historical data. We designed and implemented a simulation engine which can produce Monte Carlo scenarios for the hourly day-ahead values of load, and solar and wind power productions at the spatial and temporal resolutions of the historical data used to fit the model. Finally we developed an open-source Python package which can, from an input grid model, efficiently use forecasts and large numbers of Monte Carlo scenarios to provide unit commitment and economic dispatch for each of these scenarios. The high dimensional stochastic model and the subsequent Monte Carlo simulation engine were implemented in the package PGscen and the corresponding UC and ED optimization programs in the package Vatic.

14 SOLAR ENERGY↗
DOE OSTI2019

Distribution Systems Planning and Analysis Framework for Indian Feeders - Partnership with BSES/BRPL

Integration of distributed energy resources (DER) such as photovoltaics, electric vehicles (EVs) and battery energy storage systems (BESS) is expected to rapidly increase in distribution systems in India. These grid edge resources can have adverse impacts on the grid and can provide additional revenue streams as well. To mitigate these impacts distribution planning and analysis is required. So this paper presents a framework which can be used to complete all steps involved in distribution planning and analysis. This framework uses data in the same format as is readily available with Indian utilities and processes it to generate detailed feeder models and loading profiles. This framework already includes multiple DER use cases such as peak shaving for BESS and EV demand modelling and can be easily extended to simulate a number of additional use cases. All of these use cases can be simulated in parallel for multi-year time series simulations using an integrated command line interface. A suit of grid readiness metrics are then evaluated for each simulation to determine required network upgrades and associated costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Distribution Systems Planning and Analysis Framework for Indian Feeders: Preprint

Integration of distributed energy resources (DER) such as photovoltaics, electric vehicles (EVs) and battery energy storage systems (BESS) is expected to rapidly increase in distribution systems in India. These grid edge resources can have adverse impacts on the grid and can provide additional revenue streams as well. To mitigate these impacts distribution planning and analysis is required. So this paper presents a framework which can be used to complete all steps involved in distribution planning and analysis. This framework uses data in the same format as is readily available with Indian utilities and processes it to generate detailed feeder models and loading profiles. This framework already includes multiple DER use cases such as peak shaving for BESS and EV demand modelling and can be easily extended to simulate a number of additional use cases. All of these use cases can be simulated in parallel for multi-year time series simulations using an integrated command line interface. A suit of grid readiness metrics are then evaluated for each simulation to determine required network upgrades and associated costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
NASA NTRS2003

Three-Dimensional Magnetic Analysis Technique Developed for Evaluating Stirling Convertor Linear Alternators

The Department of Energy, the Stirling Technology Company (STC), and the NASA Glenn Research Center are developing Stirling convertors for Stirling radioisotope generators to provide electrical power for future NASA deep space missions. STC is developing the 55-We technology demonstration convertor (TDC) under contract to the Department of Energy. The Department of Energy recently named Lockheed Martin as the system integration contractor for the Stirling radioisotope generator development project. Lockheed Martin will develop the Stirling radioisotope generator engineering unit and has contract options to develop the qualification unit and the first flight unit. Glenn s role includes an in-house project to provide convertor, component, and materials testing and evaluation in support of the overall power system development. As a part of this work, Glenn has established an in-house Stirling research laboratory for testing, analyzing, and evaluating Stirling machines. STC has built four 55-We convertors for NASA, and these are being tested at Glenn. A cross-sectional view of the 55-We TDC is shown in the figure. Of critical importance to the successful development of the Stirling convertor for space power applications is the development of a lightweight and highly efficient linear alternator. In support, Glenn has been developing finite element analysis and finite element method tools for performing various linear alternator thermal and electromagnetic analyses and evaluating design configurations. A three-dimensional magnetostatic finite element model of STC's 55-We TDC linear alternator was developed to evaluate the demagnetization fields affecting the alternator magnets. Since the actual linear alternator hardware is symmetric to the quarter section about the axis of motion, only a quarter section of the alternator was modeled. The components modeled included the mover laminations, the neodymium-iron-boron magnets, the stator laminations, and the copper coils. The three-dimensional magnetostatic model was then coupled with a circuit simulator model of the alternator load and convertor controller. The coupled model was then used to generate alternator terminal voltage and current predictions. The predicted voltage and current waveforms agreed well with the experimental data, which tended to validate the accuracy of the coupled model. The model was then used to generate predictions of the demagnetization fields acting on the alternator magnets for the alternator under load. The preliminary model predictions indicate that the highest potential for demagnetization is along the inside surface of the uncovered magnets. The demagnetization field for the uncovered magnets when the mover is positioned at the end of a stroke is higher than it is when the mover is at the position of maximum induced voltage or maximum alternator current. Assuming normal load conditions, the model predicted that the onset of demagnetization is most likely to occur for magnet temperatures above 101 C.

Geng, Steven M.↗
DOE OSTI2015

Use of Combined Biogeochemical Model Approaches and Empirical Data to Assess Critical Loads of Nitrogen

Empirical and dynamic biogeochemical modelling are complementary approaches for determining the critical load (CL) of atmospheric nitrogen (N) or other constituent deposition that an ecosystem can tolerate without causing ecological harm. The greatest benefits are obtained when these approaches are used in combination. Confounding environmental factors can complicate the determination of empirical CLs across depositional gradients, while the experimental application of N amendments for estimating the CL does not realistically mimic the effects of chronic atmospheric N deposition. Biogeochemical and vegetation simulation models can provide CL estimates and valuable ecosystem response information, allowing for past and future scenario testing with various combinations of environmental factors, pollutants, pollutant control options, land management, and ecosystem response parameters. Even so, models are fundamentally gross simplifications of the real ecosystems they attempt to simulate. Empirical approaches are vital as a check on simulations and CL estimates, to parameterize models, and to elucidate mechanisms and responses under real world conditions. In this chapter, we provide examples of empirical and modelled N CL approaches in ecosystems from three regions of the United States: mixed conifer forest, desert scrub and pinyon- juniper woodland in California; alpine catchments in the Rocky Mountains; and lakes in the Adirondack region of New York state.

Fenn, Mark E.↗
NASA NTRS1986

A review of fracture mechanics life technology

Lifetime prediction technology for structural components subjected to cyclic loads is examined. The central objectives of the project are: (1) to report the current state of the art, and (2) recommend future development of fracture mechanics-based analytical tools for modeling subcritical fatigue crack growth in structures. Of special interest is the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. The authors conducted a survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Besuner, P. M.↗
DOE OSTI2014

The effect of molecular mobility on electronic transport in carbon nanotube-polymer composites and networks

A multiscale modeling approach to the prediction of electrical conductivity in carbon nanotube (CNT)–polymer composite materials is developed, which takes into account thermally activated molecular mobility of the matrix and the CNTs. On molecular level, a tight-binding density functional theory and non-equilibrium Green's function method are used to calculate the static electron transmission function in the contact between two metallic carbon nanotubes that corresponds to electron transport at 0 K. For higher temperatures, the statistical distribution of effective contact resistances is considered that originates from thermal fluctuations of intermolecular distances caused by molecular mobility of carbon nanotube and the polymer matrix. Based on this distribution and using effective medium theory, the temperature dependence of macroscopic electrical resistivity for CNT-polymer composites and CNT mats is calculated. The predicted data indicate that the electrical conductivity of the CNT-polymer composites increases linearly with temperature above 50 K, which is in a quantitative agreement with the experiments. Our model predicts a slight nonlinearity in temperature dependence of electric conductivity at low temperatures for percolated composites with small CNT loading. The model also explains the effect of glass transition and other molecular relaxation processes in the polymer matrix on the composite electrical conductivity. The developed multiscale approach integrates the atomistic charge transport mechanisms in percolated CNT-polymer composites with the macroscopic response and thus enables direct comparison of the prediction with the measurements of macroscopic material properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Differentially Private K -Means Clustering Applied to Meter Data Analysis and Synthesis

The proliferation of smart meters has resulted in a large amount of data being generated. It is increasingly apparent that methods are required for allowing a variety of stakeholders to leverage the data in a manner that preserves the privacy of the consumers. The sector is scrambling to define policies, such as the so called ‘15/15 rule’, to respond to the need. However, the current policies fail to adequately guarantee privacy. Here, in this paper, we address the problem of allowing third parties to apply K-means clustering, obtaining customer labels and centroids for a set of load time series by applying the framework of differential privacy. We leverage the method to design an algorithm that generates differentially private synthetic load data consistent with the labeled data. We test our algorithm’s utility by answering summary statistics such as average daily load profiles for a 2-dimensional synthetic dataset and a real-world power load dataset.

24 POWER TRANSMISSION AND DISTRIBUTION↗