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At least 757 records · Page 42

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NASA NTRS1983

Robot arm geometric link parameter estimation

A general method for estimating serial link manipulator geometric parameter errors is proposed in this paper. The positioning accuracy of the end-effector may be increased significantly by updating the nominal link parameters in the control software to represent the physical system more accurately. The proposed method is applicable for serial link manipulators with any combination of revolute or prismatic joints, and is not limited to a specific measurement technique.

Hayati, S. A.↗

DOE OSTI2026

Evapotranspiration partitioning estimates from 8 methods from 47 NEON sites, 2019-2021

This dataset provides daily estimates of evapotranspiration (ET) and the transpiration-to-evapotranspiration ratio (T/ET) across 47 terrestrial National Ecological Observatory Network (NEON) sites spanning diverse environmental and biome conditions in the United States across three years of data (2019-2021). Daily ET is reported in both energy units (MJ m⁻² day⁻¹) and equivalent water depth (mm day⁻¹), assuming a constant latent heat of vaporization of 2.45 MJ/kg. The primary method uses a hybrid recurrent neural network–Penman–Monteith framework (RNN-PM), which integrates physically based surface energy balance constraints with data-driven learning to partition ET into transpiration and evaporation components. Model inputs include in situ meteorological observations (air temperature, vapor pressure deficit, wind speed, and radiation) combined with satellite-derived land surface temperature, leaf area index, and soil moisture. For benchmarking and uncertainty assessment, T/ET estimates from seven additional models are included: Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), Penman-Monteith (P-M), Two-Source Energy Balance (TSEB), Support Vector Regression (SVR), and Categorical Boosting (CatBoost), among others—spanning empirical, machine-learning, and process-based approaches (see methods section or linked publication for detailed descriptions). Data Package Contents: The dataset a csv files containing daily ET and T/ET estimates for each site and model, along with associated metadata files these variables. Data can be accessed using common spreadsheet software (e.g., Microsoft Excel, LibreOffice) or programming environments such as R or Python. Together, these data support cross-site comparisons of ecosystem water use, evaluation of ET partitioning methods, and development of improved land–atmosphere exchange models.

EARTH SCIENCE > ATMOSPHERE↗

NASA NTRS1989

Method for detection and correction of errors in speech pitch period estimates

A method of detecting and correcting received values of a pitch period estimate of a speech signal for use in a speech coder or the like. An average is calculated of the nonzero values of received pitch period estimate since the previous reset. If a current pitch period estimate is within a range of 0.75 to 1.25 times the average, it is assumed correct, while if not, a correction process is carried out. If correction is required successively for more than a preset number of times, which will most likely occur when the speaker changes, the average is discarded and a new average calculated.

Bhaskar, Udaya↗

NASA NTRS2015

A New Formulation of the Filter-Error Method for Aerodynamic Parameter Estimation in Turbulence

A new formulation of the filter-error method for estimating aerodynamic parameters in nonlinear aircraft dynamic models during turbulence was developed and demonstrated. The approach uses an estimate of the measurement noise covariance to identify the model parameters, their uncertainties, and the process noise covariance, in a relaxation method analogous to the output-error method. Prior information on the model parameters and uncertainties can be supplied, and a post-estimation correction to the uncertainty was included to account for colored residuals not considered in the theory. No tuning parameters, needing adjustment by the analyst, are used in the estimation. The method was demonstrated in simulation using the NASA Generic Transport Model, then applied to the subscale T-2 jet-engine transport aircraft flight. Modeling results in different levels of turbulence were compared with results from time-domain output error and frequency- domain equation error methods to demonstrate the effectiveness of the approach.

Grauer, Jared A.↗

NASA NTRS1996

Analytical Fuselage and Wing Weight Estimation of Transport Aircraft

A method of estimating the load-bearing fuselage weight and wing weight of transport aircraft based on fundamental structural principles has been developed. This method of weight estimation represents a compromise between the rapid assessment of component weight using empirical methods based on actual weights of existing aircraft, and detailed, but time-consuming, analysis using the finite element method. The method was applied to eight existing subsonic transports for validation and correlation. Integration of the resulting computer program, PDCYL, has been made into the weights-calculating module of the AirCraft SYNThesis (ACSYNT) computer program. ACSYNT has traditionally used only empirical weight estimation methods; PDCYL adds to ACSYNT a rapid, accurate means of assessing the fuselage and wing weights of unconventional aircraft. PDCYL also allows flexibility in the choice of structural concept, as well as a direct means of determining the impact of advanced materials on structural weight. Using statistical analysis techniques, relations between the load-bearing fuselage and wing weights calculated by PDCYL and corresponding actual weights were determined.

Chambers, Mark C.↗

NASA NTRS2005

Comparison of Response Surface Construction Methods for Derivative Estimation Using Moving Least Squares, Kriging and Radial Basis Functions

Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.

Krishnamurthy, Thiagarajan↗

NASA NTRS2014

Use of an OSSE to Evaluate Background Error Covariances Estimated by the 'NMC Method'

The NMC method has proven utility for prescribing approximate background-error covariances required by variational data assimilation systems. Here, untunedNMCmethod estimates are compared with explicitly determined error covariances produced within an OSSE context by exploiting availability of the true simulated states. Such a comparison provides insights into what kind of rescaling is required to render the NMC method estimates usable. It is shown that rescaling of variances and directional correlation lengths depends greatly on both pressure and latitude. In particular, some scaling coefficients appropriate in the Tropics are the reciprocal of those in the Extratropics. Also, the degree of dynamic balance is grossly overestimated by the NMC method. These results agree with previous examinations of the NMC method which used ensembles as an alternative for estimating background-error statistics.

Data Assimilation↗

NASA NTRS1994

Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods

Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.

Lin, Bing↗

DOE OSTI2017

Modelling bivariate extreme precipitation distribution for data-scarce regions using Gumbel-Hougaard copula with maximum entropy estimation

A new method of parameter estimation in data scarce regions is valuable for bivariate hydrological extreme frequency analysis. Here, this paper proposes a new method of parameter estimation (maximum entropy estimation, MEE) for both Gumbel and Gumbel–Hougaard copula in situations when insufficient data are available. MEE requires only the lower and upper bounds of two hydrological variables. To test our new method, two experiments to model the joint distribution of the maximum daily precipitation at two pairs of stations on the tributaries of Heihe and Jinghe River, respectively, were performed and compared with the method of moments, correlation index estimation, and maximum likelihood estimation, which require a large amount of data. Both experiments show that for the Ye Niugou and Qilian stations, the performance of MEE is nearly identical to those of the conventional methods. For the Xifeng and Huanxian stations, MEE can capture information indicating that the maximum daily precipitation at the Xifeng and Huanxian stations has an upper tail dependence, whereas the results generated by correlation index estimation and maximum likelihood estimation are unreasonable. Moreover, MEE is proved tobe generally reliable and robust by many simulations under three different situations. TheGumbel–Hougaard copula with MEE can also be applied to the bivariate frequency analysis ofother extreme events in data-scarce regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation

Automatic kinetic mechanism generation, virtual high-throughput screening, and automatic transition state search are currently trending applications requiring exploration of a large molecule space. Large-scale search requires fast and accurate estimation of molecules’ properties of interest, such as thermochemistry. Existing approaches are not satisfactory for large polycyclic molecules: considering the number of molecules being screened, quantum chemistry (even cheap density functional theory methods) can be computationally expensive, and group additivity, though fast, is not sufficiently accurate. Here, this paper provides a fast and moderately accurate alternative by proposing a polycyclic thermochemistry estimation method that extends the group additivity method with two additional algorithms: similarity match and bicyclic decomposition. It significantly reduces H f (298 K) estimation error from over 60 kcal/mol (group additivity method) to around 5 kcal/mol, C p (298 K) error from 9 to 1 cal/mol/K,and S(298 K) error from 70 to 7 cal/mol/K. This method also works well for heteroatomic polycyclics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2006

A Comparison of Methods Used to Estimate the Height of Sand Dunes on Mars

The collection of morphometric data on small-scale landforms from other planetary bodies is difficult. We assess four methods that can be used to estimate the height of aeolian dunes on Mars. These are (1) stereography, (2) slip face length, (3) profiling photoclinometry, and (4) Mars Orbiter Laser Altimeter (MOLA). Results show that there is good agreement among the methods when conditions are ideal. However, limitations inherent to each method inhibited their accurate application to all sites. Collectively, these techniques provide data on a range of morphometric parameters, some of which were not previously available for dunes on Mars. They include dune height, width, length, surface area, volume, and longitudinal and transverse profiles. Thc utilization of these methods will facilitate a more accurate analysis of aeolian dunes on Mars and enable comparison with dunes on other planetary surfaces.

Bourke, M. C.↗

NASA NTRS1987

On the representation and estimation of spatial uncertainty

This paper describes a general method for estimating the nominal relationship and expected error (covariance) between coordinate frames representing the relative locations of objects. The frames may be known only indirectly through a series of spatial relationships, each with its associated error, arising from diverse causes, including positioning errors, measurement errors, or tolerances in part dimensions. This estimation method can be used to answer such questions as whether a camera attached to a robot is likely to have a particular reference object in its field of view. The calculated estimates agree well with those from an independent Monte Carlo simulation. The method makes it possible to decide in advance whether an uncertain relationship is known accurately enough for some task and, if not, how much of an improvement in locational knowledge a proposed sensor will provide. The method presented can be generalized to six degrees of freedom and provides a practical means of estimating the relationships (position and orientation) among objects, as well as estimating the uncertainty associated with the relationships.

Smith, Randall C.↗

NASA NTRS2003

Fan Beam Emission Tomography for Estimating Scalar Properties in Laminar Flames

A new method of estimating temperatures and gas species concentrations (CO2 and H2O) in a laminar flame is reported. The path-integrated, spectral radiation intensities emitted from a laminar flame at multiple wavelengths and view angles are calculated using a narrow band radiation model. Synthetic data, in the form of radial profiles of temperature and gas concentrations, are used in these calculations. The calculations mimic measurements that would theoretically be obtained using a mid-infrared spectrometer with a scanner. The path integrated spectral radiation intensities are deconvoluted using a maximum likelihood estimation method in conjunction with an iterative scheme. The deconvolution algorithm accounts for the self-absorption of radiation by the intervening gases, and provides the local temperature and gas species concentrations. The deconvoluted temperatures and gas concentrations are compared with the synthetic data used for calculating the spectral radiation intensities. The deconvoluted temperatures and gas species concentrations are within 0.5 % of the synthetic data. The deconvolution algorithm is expected to provide combustion researchers with an easy method of obtaining the radial profiles of major gas species concentrations and temperatures in laminar flames non-intrusively using a mid-infrared spectrometer with a scanner.

Lim, Jongmook↗

DOE OSTI2023

Novel method for accurately estimating membrane transport properties and mass transfer coefficients in reverse osmosis

Here, we present a simple and robust method to simultaneously characterize the water and salt permeability (A, B) of reverse osmosis (RO) membranes and mass transfer coefficient (k) in membrane modules. The proposed methodology comprises a set of RO experiments performed at different operating pressures or stages. The measured water and salt fluxes in each stage are simultaneously fitted to the RO transport equations by performing a non-linear regression, using A, B, and k as regression parameters. We first perform a systematic accuracy analysis of the proposed method across the full operational range of RO. The assessment shows that the method accuracy is substantially higher than current methods and increases with number of experimental stages and driving forces. This assessment is used to inform the design of an experimental protocol that minimizes errors in estimated A, B, and k. We then evaluate two commercial RO membranes following the new protocol. For both membranes, A and B parameters decrease by 17% and 15% from the dilute solution to seawater concentrations, whereas the k parameter remains constant. Our study demonstrates that the proposed method, informed by data-driven experimental designs, provides a new approach for accurately characterizing transport phenomenon in membrane processes with feeds of less than 100 g/L total dissolved solids.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Bilinear modeling and nonlinear estimation

New methods are illustrated for online nonlinear estimation applied to the lateral deflection of an elastic beam on board measurements of angular rates and angular accelerations. The development of the filter equations, together with practical issues of their numerical solution as developed from global linearization by nonlinear output injection are contrasted with the usual method of the extended Kalman filter (EKF). It is shown how nonlinear estimation due to gyroscopic coupling can be implemented as an adaptive covariance filter using off-the-shelf Kalman filter algorithms. The effect of the global linearization by nonlinear output injection is to introduce a change of coordinates in which only the process noise covariance is to be updated in online implementation. This is in contrast to the computational approach which arises in EKF methods arising by local linearization with respect to the current conditional mean. Processing refinements for nonlinear estimation based on optimal, nonlinear interpolation between observations are also highlighted. In these methods the extrapolation of the process dynamics between measurement updates is obtained by replacing a transition matrix with an operator spline that is optimized off-line from responses to selected test inputs.

Dwyer, Thomas A. W., III↗

NASA NTRS1991

Estimated accuracy of method of characteristics viscous plume solutions for an orbit plume induced environment prediction

A study has been performed to determine an estimate of the accuracy of rocket exhaust plume induced spacecraft environments calculated with the more widely used computational methods. Calculations of plume flowfields and plume induced environments using Method of Characteristic (MOC) based models are compared with both experimental results and direct simulation Monte Carlo (DSMC) results to determine the applicability and accuracy of Method of Characteristic models.

Smith, Sheldon D.↗

NASA NTRS1990

The augmented Lagrangian method for parameter estimation in elliptic systems

In this paper a new technique for the estimation of parameters in elliptic partial differential equations is developed. It is a hybrid method combining the output-least-squares and the equation error method. The new method is realized by an augmented Lagrangian formulation, and convergence as well as rate of convergence proofs are provided. Technically the critical step is the verification of a coercivity estimate of an appropriately defined Lagrangian functional. To obtain this coercivity estimate a seminorm regularization technique is used.

Ito, Kazufumi↗

NASA NTRS1984

Early season spring small grains proportion estimation

An accurate, automated method for estimating early season spring small grains from Landsat MSS data is discussed. The method is summarized and the results of its application to 100 sample segment-years of data from the US Northern Great Plains in 1976, 1977, 1978, and 1979 are summarized. The results show that this estimator provides accurate estimates earlier in the growing season than previous methods. Ground truth is required only in the estimator development, and data storage, transmission, preprocessing, and processing requirements are minimal.

Phinney, D. E.↗