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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Modal cost analysis for simple continua

The most popular finite element codes are based upon appealing theories of convergence of modal frequencies. For example, the popularity of cubic elements for beam-like structures is due to the rapid convergence of modal frequencies and stiffness properties. However, for those problems in which the primary consideration is the accuracy of response of the structure at specified locations, it is more important to obtain accuracy in the modal costs than in the modal frequencies. The modal cost represents the contribution of a mode in the norm of the response vector. This paper provides a complete modal cost analysis for simple continua such as beam-like structures. Upper bounds are developed for mode truncation errors in the model reduction process and modal cost analysis dictates which modes to retain in order to reduce the model for control design purposes.

Hu, A.↗
NASA NTRS1988

Uncertainties in large space systems

Uncertainties of a large space system (LSS) can be deterministic or stochastic in nature. The former may result in, for example, an energy spillover problem by which the interaction between unmodeled modes and controls may cause system instability. The stochastic uncertainties are responsible for mode localization and estimation errors, etc. We will address the effects of uncertainties on structural model formulation, use of available test data to verify and modify analytical models before orbiting, and how the system model can be further improved in the on-orbit environment.

Fuh, Jon-Shen↗
NASA NTRS2004

Global Precipitation Measurement (GPM) Ground Validation: Plans and Preparations

The Global Precipitation Measurement (GPM) program is an international partnership led by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM will improve climate, weather, and hydro-meteorological forecasts through more frequent and more accurate measurement of precipitation across the globe. This paper describes the concept, the planning, and the preparations for Ground Validation within the GPM program. Ground Validation (GV) plays an important role in the program by investigating and quantitatively assessing the errors within the satellite retrievals. These quantitative estimates of retrieval errors will assist the scientific community by bounding the errors within their research products. The two fundamental requirements of the GPM Ground Validation program are: (1) error characterization of the precipitation retrievals and (2) continual improvement of the satellite retrieval algorithms. These two driving requirements determine the measurements, instrumentation, and location for ground observations. This paper outlines GV plans for estimating the systematic and random components of retrieval error and for characterizing the spatial p d temporal structure of the error and plans for algorithm improvement in which error models are developed and experimentally explored to uncover the physical causes of errors within the retrievals. This paper discusses NASA locations for GV measurements as well as anticipated locations from international GPM partners. NASA's primary locations for validation measurements are an oceanic site at Kwajalein Atoll in the Republic of the Marshall Islands and a continental site in north-central Oklahoma at the U.S. Department of Energy's Atmospheric Radiation Measurement Program site.

Schwaller, M.↗
DOE OSTI2021

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗
NASA NTRS2008

Model Error Budgets

An error budget is a commonly used tool in design of complex aerospace systems. It represents system performance requirements in terms of allowable errors and flows these down through a hierarchical structure to lower assemblies and components. The requirements may simply be 'allocated' based upon heuristics or experience, or they may be designed through use of physics-based models. This paper presents a basis for developing an error budget for models of the system, as opposed to the system itself. The need for model error budgets arises when system models are a principle design agent as is increasingly more common for poorly testable high performance space systems.

error budgets↗
DOE OSTI2019

Effects of Inflow Spatiotemporal Discretization on Wake Meandering and Turbine Structural Response using FAST.Farm

FAST.Farm is a newly developed multiphysics, midfidelity engineering tool that can be used to predict turbine power and structural loads of wind turbines in a wind farm with minimal computational expense. Previous studies have shown similarities and differences in wind turbine performance between FAST.Farm and high-fidelity large-eddy simulations (LES) using both LES precursor-generated inflow and TurbSim-generated synthetic inflow. While conservative resolutions have been used to date, no formal spatial or temporal discretization study has been performed for the FAST.Farm model wind domains. This work aims to study the effects of varying the spatial and temporal discretization of the wind domains on wake meandering (low-resolution domain) and turbine structural response (high-resolution domains) and resulting wake and load calculations. The purpose of this study is to establish convergence criteria and recommendations for discretization values in terms of rotor diameter (D, expressed in meters) that will maximize computational efficiency. To ensure a percent error of ≤ 1% in standard deviation of wake center position relative to the finest included resolution, a low-resolution time step of 0.024D s, 0.016D s, and 0.0079D s and a low-resolution spatial discretization of 0.079D m, 0.16D m, and 0.24D m is recommended for 8 m/s, 12 m/s, and 18 m/s mean ambient wind speed at hub height, respectively. These guidelines are likely applicable to other implementations of the dynamic wake meandering model. To ensure a percent error of ≤ 1% in standard deviation of all considered structural response outputs, a high-resolution time step that captures the highest influential excitation and natural frequencies in the system and a high-resolution spatial discretization comparable to the maximum airfoil cord length is recommended. Lastly, these guidelines are likely applicable to any aeroelastic analysis.

17 WIND ENERGY↗
NASA NTRS1995

Effect of the nonlinearity of the carbonate system on partial pressure of carbon dioxide in the oceans

Partial pressure of CO2 is a nonlinear function of several seawater properties. Due to the nonlinearity in this relationship, the partial pressure of a uniform ocean would be different from that of a nonuniform ocean with the same bulk seawater properties. Assuming uniformity of seawater properties at some temporal and spatial scales in carbon models leads to systematic errors in partial pressure of CO2. In this paper we evaluate the magnitude of these errors. We partition the Geochemical Ocean Sections Study and Transient Tracers in the Oceans data according to the horizontal structure of several box models from the literature. Our results suggest that assumption of uniformity at large scales leads to understanding of underestimation of global surface ocean partial pressure of CO2 by at least 3 - 12 microatm. Nonlinear effects also introduce systematic errors in the buffer factor estimated from bulk seawater properties. We find the standard deviation of partial pressure of CO2 to be an indicator of the magnitude of the nonlinear effects. We discuss the implications of these errors for some conclusions drawn from carbon models. Biogeochemical processes, such as mixing, gas exchange, or biological activity, influence the distribution of the seawater properties. A shift in spatial or temporal patterns of these processes can modify the nonuniformity of the seawater properties and thus alter the partial pressure of the surface waters, even if the mean intensities of the processes remain constant.

Trela, Piotr↗
NASA NTRS1992

Experimental measurement and theoretical modeling of microwave scattering and the structure of the sea surface influencing radar observations from space

The electromagnetic bias is an error present in radar altimetry of the ocean due to the non-uniform reflection from wave troughs and crests. A study of the electromagnetic bias became necessary to permit error reduction in mean sea level measurements of satellite radar altimeters. Satellite radar altimeters have been used to find the upper and lower bounds for the electromagnetic bias. This report will present a theory using physical optics scattering and an empirical model of the short wave modulation to predict the electromagnetic bias. The predicted electromagnetic bias will be compared to measurements at C and Ku bands.

Arnold, David↗
NASA NTRS1992

Damage detection in elastic structures using vibratory residual forces and weighted sensitivity

A methodology is presented for detecting structural damage in elastic structures by nondestructive means. Measured modal test data along with a correlated analytical structural model are used to locate potentially damaged regions using residual modal force vectors and to conduct a weighted sensitivity analysis to assess the extent of mass and/or stiffness variations, where damage is characterized as a stiffness reduction. The current approach is unique among other approaches in that it accounts for (1) variations in system mass, system stiffness, and mass center (locations), (2) perturbations of both the natural frequencies and modal vectors, and (3) statistical confidence factors for the structural parameters and potential experimental instrumentation error. Moreover, this procedure can be used with either full or reduced models. A wide variety of numerical examples are presented that show that the current method provides a precise indication of both the location and the extent of structural damage.

Ricles, J. M.↗
NASA NTRS1990

Obtaining consistent models of helicopter flight-data measurement errors using kinematic-compatibility and state-reconstruction methods

A new method was developed for application of Kalman Filter/Smoothers to post-flight processing of helicopter flight test dynamic measurements. This processing includes checking for kinematic compatibility among the measurements, identification of a measurement error model, and reconstruction of both measured and unmeasured time histories. Emphasis is placed on identification of a parametric measurement error model which is valid for a set of flight test data. This is facilitated through a new method of concatenating several maneuver time histories. The method also includes a model structure determination step which ensures that a physically realistic parameterization has been achieved. Application of the method to a set of BO-105 flight test data is illustrated. The resulting minimally parameterized error model is shown to characterize the measurement errors of the entire data set with very little variation in the parameter values. Reconstructed time histories are shown to have increased bandwidths and signal to noise ratios.

Fletcher, Jay W.↗
NASA NTRS1992

Validation and upgrading of physically based mathematical models

The validation of the results of physically-based mathematical models against experimental results was discussed. Systematic techniques are used for: (1) isolating subsets of the simulator mathematical model and comparing the response of each subset to its experimental response for the same input conditions; (2) evaluating the response error to determine whether it is the result of incorrect parameter values, incorrect structure of the model subset, or unmodeled external effects of cross coupling; and (3) modifying and upgrading the model and its parameter values to determine the most physically appropriate combination of changes.

Duval, Ronald↗
DOE OSTI2023

Analysis of picosecond coherent anti-Stokes Raman spectra for gas-phase diagnostics

We present a hybrid frequency- and time-domain solution, applicable to the case of picosecond coherent anti-Stokes Raman scattering (CARS), for gas-phase diagnostics. A solution has been derived based on both physical arguments and four-wave mixing equations for picosecond CARS, with pulse durations that are comparable to the dephasing time scale for gas-phase Raman coherence—a regime where commonly employed solutions for impulsive (femtosecond) or cw (nanosecond) pump/Stokes forcing are not strictly valid. We present the ps-CARS spectrum in the form of incoherent sums of CARS intensity spectra, calculated from the fundamental solution for impulsive pump/Stokes Raman preparation. The solution was examined for temperatures from 1000–3000 K, for four plausible experimental configurations, with laser pulse durations of 50–150 ps, and probe pulse delays from −20 to 240 ps. Approximations based on cw and impulsive pump/Stokes preparation to fit picosecond CARS spectra at atmospheric pressure were examined and the relative thermometric accuracy and computational cost of these approximations were quantified for the case of a zero nonresonant CARS contribution, and a nonresonant susceptibility equal to 10% of the Raman-resonant value at the N 2 bandhead. The nanosecond CARS approximation can result in large fitting errors when the probe pulse time delay is less than the probe pulse duration. Errors as large as 10–20% are observed in the fit temperatures for a zero picosecond probe pulse delay, when the nonresonant background is neglected, largely due to an inability of the time-independent cw model to capture transient frequency spread dephasing effects at the Q -branch bandhead. The inclusion of a nonresonant background results in 40–60% thermometry errors with a nanosecond model at a zero-probe delay. Time-dependent impulsive calculations used for femtosecond CARS better approximate the structure of the N 2 bandhead, reducing temperature fitting errors to 5–10% at a short probe pulse delay. The impulsive approximation results in errors up to 10% at intermediate probe pulse delays, where the coherence of the pump and probe pulses leads to multiple terms in the picosecond CARS solution. Both approximations improve as the probe pulse delay exceeds the probe duration. The nanosecond approximation results in a 2–3% error, while the impulsive model results in differences of less than 1% in some cases. Fits to experimental data obtained using short, ∼60ps pulses at a zero probe time delay and longer 100 ps pulses at a substantial 200 ps delay are presented with accuracies of 1–3% in the fit temperature.

Kearney, Sean P.↗
DOE OSTI2022

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
NASA NTRS1980

Software reliability: Application of a reliability model to requirements error analysis

The application of a software reliability model having a well defined correspondence of computer program properties to requirements error analysis is described. Requirements error categories which can be related to program structural elements are identified and their effect on program execution considered. The model is applied to a hypothetical B-5 requirement specification for a program module.

Logan, J.↗
NASA NTRS2022

A Generalized Approach to Aircraft Trajectory Prediction via Supervised Deep Learning

As research advances diverse forms and missions of aircraft, the National Airspace System (NAS) will become increasingly crowded, limiting current communications resources to accommodate aviation operations. Ongoing research proposes a paradigm of airspace communications, such that resources are autonomously and dynamically allocated via intelligent agents; this allocation requires accurate representations of the NAS, including the predicted positions of aircraft. State-of-the-art research emphasizes the importance of a hybrid-recurrent framework for trajectory prediction and compares the impact of commonly considered weather data on prediction accuracy. However, current research has been limited in its scope of efforts, frequently utilizing a unique flight route, architecture, set of weather data, and date range. This article considers the challenges of generalizing hybrid-recurrent predictive models for flight trajectories. Results illustrate an increase in error variance when identical models are trained over a generalized set of flights; this may be mitigated with careful tuning of hyperparameters, both in the network structure and optimization algorithms. Even so, an irreducible vertical error was identified, resulting from the complex takeoff and landing procedures which can not be correlated to functions of weather or additional assumptions of aircraft behavior. Finally, the use of a test route indicates that generalized models still do not possess sufficient knowledge for general aircraft predictions, with mean error increases ranging from 70-500%. These results illustrate the need for continued efforts on improving model versatility, as well as potential limitations for spectrum allocation near airports and other centers.

Nathan Schimpf↗
NASA NTRS1994

Suboptimal schemes for atmospheric data assimilation based on the Kalman filter

This work is directed toward approximating the evolution of forecast error covariances for data assimilation. The performance of different algorithms based on simplification of the standard Kalman filter (KF) is studied. These are suboptimal schemes (SOSs) when compared to the KF, which is optimal for linear problems with known statistics. The SOSs considered here are several versions of optimal interpolation (OI), a scheme for height error variance advection, and a simplified KF in which the full height error covariance is advected. To employ a methodology for exact comparison among these schemes, a linear environment is maintained, in which a beta-plane shallow-water model linearized about a constant zonal flow is chosen for the test-bed dynamics. The results show that constructing dynamically balanced forecast error covariances rather than using conventional geostrophically balanced ones is essential for successful performance of any SOS. A posteriori initialization of SOSs to compensate for model - data imbalance sometimes results in poor performance. Instead, properly constructed dynamically balanced forecast error covariances eliminate the need for initialization. When the SOSs studied here make use of dynamically balanced forecast error covariances, the difference among their performances progresses naturally from conventional OI to the KF. In fact, the results suggest that even modest enhancements of OI, such as including an approximate dynamical equation for height error variances while leaving height error correlation structure homogeneous, go a long way toward achieving the performance of the KF, provided that dynamically balanced cross-covariances are constructed and that model errors are accounted for properly. The results indicate that such enhancements are necessary if unconventional data are to have a positive impact.

Todling, Ricardo↗
NASA NTRS2015

Method for Real-Time Model Based Structural Anomaly Detection

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Smith, Timothy A.↗
NASA NTRS1999

Implication of microdosimetry in estimation of radiation quality in space environment

Errors introduced using a tissue equivalent proportional counter to estimate radiation quality of an arbitrary ion field as related to space radiations are examined. This is accomplished by using a generalized analytic model to calculate the effect of energy loss straggling, track structure, and pathlength distribution on the microdosimetric distribution. The error can be as large as a factor of two, but no systematic trend could be found.

NASA Discipline Radiation Health↗