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Results for “Parameter estimation using data”

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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Parameter estimation for incidence angle modifier models for photovoltaic modules

We present methods to estimate parameters for models for the incidence angle modifier for simulating irradiance on a photovoltaic array. The incidence angle modifier quantifies the fraction of direct irradiance that is reflected away at the array’s face, as a function of the direct irradiance’s angle of incidence. Parameters can be estimated from data and the fitting method can be used to convert between models. We show that the model conversion procedure results in models that produce similar annual insolation on a fixed plane.

14 SOLAR ENERGY↗
DOE OSTI2019

ldquants

1. Provide cleaned and filtered data stream from multiple ARM disdrometers; 2. Estimate commonly-used physical parameters of the Drop Size Distribution (DSD). 3. Calculate radar equivalent quantities such as the Radar Reflectivity Factor Z.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

vdisquants: Video Distrometer derived radar equivalent quantities. Retrievals from the VDIS instrument providing radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR).

1. Provide cleaned and filtered data stream from multiple ARM disdrometers; 2. Estimate commonly-used physical parameters of the Drop Size Distribution (DSD). 3. Calculate radar equivalent quantities such as the Radar Reflectivity Factor Z.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1967

Computer program reduces calculation time of normal response functions

FORTRAN 2 computer program rapidly calculates parameters of maximum likelihood estimates from sensitivity experiment data populations. The program uses the Newton-Raphson iterative procedure to calculate the mean and standard deviation of portions of the cumulative normal response function.

Alexander, M. J.↗
NASA NTRS1980

High-resolution Martian atmosphere modeling

A multilayer radiative transfer, high-spectral-resolution infrared model of the lower atmosphere of Mars has been constructed to assess the effect of scattering on line profiles. The model takes into accout aerosol scattering and absorption and includes a line-by-line treatment of scattering and absorption by CO2 and H2O. The aerosol complex indices of refraction used were those measured on montmorillonite and basalt chosen on the basis of Mars ir data from the NASA Lear Airborne Observatory. The particle sizes and distribution were estimated using Viking data. The molecular line treatment employs the AFGL line parameters and Voigt profiles. The modeling results indicate that the line profiles are only slightly affected by normal aerosol scattering and absorption, but the effect could be appreciable for heavy loading. The technique described permits a quantitative approach to assessing and correcting for the effect of aerosols on lineshapes in planetary atmospheres.

Egan, W. G.↗
NASA NTRS1981

The Theory and Practice of Estimating the Accuracy of Dynamic Flight-Determined Coefficients

Means of assessing the accuracy of maximum likelihood parameter estimates obtained from dynamic flight data are discussed. The most commonly used analytical predictors of accuracy are derived and compared from both statistical and simplified geometrics standpoints. The accuracy predictions are evaluated with real and simulated data, with an emphasis on practical considerations, such as modeling error. Improved computations of the Cramer-Rao bound to correct large discrepancies due to colored noise and modeling error are presented. The corrected Cramer-Rao bound is shown to be the best available analytical predictor of accuracy, and several practical examples of the use of the Cramer-Rao bound are given. Engineering judgement, aided by such analytical tools, is the final arbiter of accuracy estimation.

Maine, R. E.↗
NASA NTRS1982

Computed laser backscattering from turbid liquids - Comparison with laboratory results

A recently developed semianalytic Monte Carlo radiative transfer model applicable to oceanographic lidar systems (SALMON) has been used to simulate a series of laboratory experiments studying the backscatter of laser light from dispersions of Teflon spheres. Results obtained with SALMON, using best estimates of pertinent optical parameters, compared quite well with experimental data in both a qualitative and quantitative sense, with the largest relative discrepancies being approximately 30%. The results firmly establish the validity of SALMON in studying the performance of real oceanographic lidar systems.

Poole, L. R.↗
NASA NTRS1989

An optical model description of momentum transfer in heavy ion collisions

An optical model description of momentum transfer in relativistic heavy ion collisions, based upon composite particle multiple scattering theory, is presented. The imaginary component of the complex momentum transfer, which comes from the absorptive part of the optical potential, is identified as the longitudinal momentum downshift of the projectile. Predictions of fragment momentum distribution observables are made and compared with experimental data. Use of the model as a tool for estimating collision impact parameters is discussed.

Khan, F.↗
NASA NTRS1990

A case study of the Thunderstorm Research International Project storm of July 11, 1978. I - Analysis of the data base

The data obtained at the time of the Thunderstorm Research International Project storm at the Kennedy Space Center on July 11, 1978 are analyzed in a model-independent manner. The data base included data from three Doppler radars, a lightning detection and ranging system and a network of 25 electric field mills, and rain gages. Electric field measurements were used to analyze the charge moments transferred by lightning flashes, and the data were fitted to Weibull distributions; these were used to estimate statistical parameters of the lightning for both intracloud and cloud-to-ground flashes and to estimate the fraction of the flashes which were below the observation threshold. The displacement and the conduction current densities were calculated from electric field measurements between flashes. These values were used to derive the magnitudes and the locations of dipole and monopole generators by least squares fitting the measured Maxwell current densities to the displacement-dominated equations.

Nisbet, John S.↗
NASA NTRS1991

Optical model description of momentum transfer in relativistic heavy ion collisions

An optical model description of momentum transfer in relativistic heavy ion collisions, based upon composite particle multiple scattering theory, is presented. The imaginary component of the complex momentum transfer, which comes from the absorptive part of the optical potential, is identified as the longitudinal momentum downshift of the projectile. Predictions of fragment momentum distribution observables are made and compared with experimental data. Use of the model as a tool for estimating collision impact parameters is discussed.

Khan, F.↗
NASA NTRS2011

Validation of Methods to Predict Vibration of a Panel in the Near Field of a Hot Supersonic Rocket Plume

This paper describes the measurement and analysis of surface fluctuating pressure level (FPL) data and vibration data from a plume impingement aero-acoustic and vibration (PIAAV) test to validate NASA s physics-based modeling methods for prediction of panel vibration in the near field of a hot supersonic rocket plume. For this test - reported more fully in a companion paper by Osterholt & Knox at 26th Aerospace Testing Seminar, 2011 - the flexible panel was located 2.4 nozzle diameters from the plume centerline and 4.3 nozzle diameters downstream from the nozzle exit. The FPL loading is analyzed in terms of its auto spectrum, its cross spectrum, its spatial correlation parameters and its statistical properties. The panel vibration data is used to estimate the in-situ damping under plume FPL loading conditions and to validate both finite element analysis (FEA) and statistical energy analysis (SEA) methods for prediction of panel response. An assessment is also made of the effects of non-linearity in the panel elasticity.

Bremner, P. G.↗
NASA NTRS2005

Aerodynamic Parameter Estimation for the X-43A (Hyper-X) from Flight Data

Aerodynamic parameters were estimated based on flight data from the third flight of the X-43A hypersonic research vehicle, also called Hyper-X. Maneuvers were flown using multiple orthogonal phase-optimized sweep inputs applied as simultaneous control surface perturbations at Mach 8, 7, 6, 5, 4, and 3 during the vehicle descent. Aerodynamic parameters, consisting of non-dimensional longitudinal and lateral stability and control derivatives, were estimated from flight data at each Mach number. Multi-step inputs at nearly the same flight conditions were also flown to assess the prediction capability of the identified models. Prediction errors were found to be comparable in magnitude to the modeling errors, which indicates accurate modeling. Aerodynamic parameter estimates were plotted as a function of Mach number, and compared with estimates from the pre-flight aerodynamic database, which was based on wind-tunnel tests and computational fluid dynamics. Agreement between flight estimates and values computed from the aerodynamic database was excellent overall.

Morelli, Eugene A.↗
DOE OSTI2025

Statistical estimates of the binary properties of rotational variables

ABSTRACT We present a model to estimate the average primary masses, companion mass ranges, the inclination limit for recognizing a rotational variable, and the primary mass spreads for populations of binary stars. The model fits a population’s binary mass function distribution and allows for a probability that some mass functions are incorrectly estimated. Using tests with synthetic data, we assess the model’s sensitivity to each parameter, finding that we are most sensitive to the average primary mass and the minimum companion mass, with less sensitivity to the inclination limit and little to no sensitivity to the primary mass spread. We apply the model to five populations of binary spotted rotational variables identified in ASAS-SN, computing their binary mass functions using RV data from APOGEE. Their average primary mass estimates are consistent with our expectations based on their CMD locations ($\sim 0.75 \, {\rm M}_{\odot }$ for lower main sequence primaries and $\sim 0.9$–$1.2 \, {\rm M}_{\odot }$ for RS CVn and sub-subgiants). Their companion mass range estimates allow companion masses down to $M_2/M_1\simeq 0.1$, although the main sequence population may have a higher minimum mass fraction ($\sim 0.4$). We see weak evidence of an inclination limit $\gtrsim 50^{\circ }$ for the main sequence and sub-subgiant groups and no evidence of an inclination limit in the other groups. No groups show strong evidence for a preferred primary mass spread. We conclude by demonstrating that the approach will provide significantly better estimates of the primary mass and the minimum mass ratio and reasonable sensitivity to the inclination limit with 10 times as many systems.

Phillips, Anya (ORCID:000900051914974X)↗
DOE OSTI2021

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

MEDLI2: MISP Inferred Aerothermal Environment and Flow Transition Assessment

The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite on the Mars2020 mission contained multiple sensors on the aeroshell to measure the aerothermal environment during entry into the Martian atmosphere. These sensors performed superbly and successfully returned forebody and aftbody heating measurements. Analysis of MEDLI2 data indicated flow transitioning from a laminar to turbulent state on the heatshield. No evidence of flow transition was observed on the backshell. Two methods were used to estimate flow transition times on the heatshield: (1) temperature gradient of near-surface thermocouple data and (2) heat flux gradient from an inverse reconstruction approach using thermocouple data and material response modeling. Both methods produced similar transition times with an estimated accuracy of ±1 s. To assess various transition criteria, transition parameters were evaluated at each sensor location using flow field solutions from computational fluid dynamics (CFD) simulations. The idea was to use conservative values inferred from MEDLI2 data as transition criteria for other Mars missions. To test this hypothesis, MEDLI data from the Mars Science Laboratory (MSL) mission was used to compare predicted vs. actual flow transition times. The comparisons suggest smooth wall transition criteria are not well-suited in modeling the rapid progression of a turbulent transition front. Transition criteria containing a roughness element parameter agreed better with the flight data. In summary, critical transition values derived from MEDLI2 data may be used as a starting point in constructing a flow transition model for future Mars missions.

Chun Y Tang↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Autonomous Modal Identification of the Space Shuttle Tail Rudder

Autonomous modal identification automates the calculation of natural vibration frequencies, damping, and mode shapes of a structure from experimental data. This technology complements damage detection techniques that use continuous or periodic monitoring of vibration characteristics. The approach shown in the paper incorporates the Eigensystem Realization Algorithm (ERA) as a data analysis engine and an autonomous supervisor to condense multiple estimates of modal parameters using ERA's Consistent-Mode Indicator and correlation of mode shapes. The procedure was applied to free-decay responses of a Space Shuttle tail rudder and successfully identified the seven modes of the structure below 250 Hz. The final modal parameters are a condensed set of results for 87 individual ERA cases requiring approximately five minutes of CPU time on a DEC Alpha computer.

Pappa, Richard S.↗