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At least 181 records · Page 10

Parameter Estimation for Viscoplastic Material Modeling

A key ingredient in the design of engineering components and structures under general thermomechanical loading is the use of mathematical constitutive models (e.g. in finite element analysis) capable of accurate representation of short and long term stress/deformation responses. In addition to the ever-increasing complexity of recent viscoplastic models of this type, they often also require a large number of material constants to describe a host of (anticipated) physical phenomena and complicated deformation mechanisms. In turn, the experimental characterization of these material parameters constitutes the major factor in the successful and effective utilization of any given constitutive model; i.e., the problem of constitutive parameter estimation from experimental measurements.

Saleeb, Atef F.

Aerodynamic Parameter Estimation Using Reconstructed Turbulence Measurements

A classical method for reconstructing atmospheric turbulence from onboard measurements of airdata and inertial sensors was improved and implemented for real-time computation. The reconstructed turbulence measurements were then included in a system identification analysis to estimate nondimensional stability and control derivatives in a longitudinal short period model using the maximum likelihood equation-error method in the frequency domain with Fourier-transform data. Flight test results using a subscale transport-type airplane showed that the power spectra for the reconstructed vertical gusts resembled the von Kármán turbulence model. Flight data in moderate and severe turbulence exhibited a decorrelation of the modeling data that increased the accuracy of parameter estimation results using the reconstructed turbulence. In particular, pitch rate and angle-of-attack rate derivatives could both be identified from flight data about straight and level flight without special maneuvers or prior information.

Jared A Grauer

Conformal duality of the nonlinear Schrödinger equation: Theory and applications to parameter estimation

The nonlinear Schrödinger equation (NLSE) in one spatial dimension has stationary solutions similar to those of the linear Schrödinger equation (LSE) as well as more exotic solutions such as solitary waves and quantum droplets. Here, we present a newly discovered conformal duality which unifies the stationary and time-dependent traveling-wave solutions of the one-dimensional cubic-quintic NLSE, the cubic NLSE and LSE. Any two systems that are classified by the same single number called the cross ratio are related by this symmetry. Notably, the conformal duality can also be adapted in Newtonian mechanics and serves as a powerful tool for investigating physical systems that otherwise cannot be directly accessed in experiments. Further, we show that the conformal symmetry is a valuable resource to substantially improve NLSE parameter estimation from noisy empirical data by introducing an optimization afterburner. The new method therefore has far reaching practical applications for nonlinear physical systems. Published by the American Physical Society 2025

Reinhardt, David B. (ORCID:0009000409812838)

Space shuttle propulsion parameter estimation using optimal estimation techniques

The first twelve system state variables are presented with the necessary mathematical developments for incorporating them into the filter/smoother algorithm. Other state variables, i.e., aerodynamic coefficients can be easily incorporated into the estimation algorithm, representing uncertain parameters, but for initial checkout purposes are treated as known quantities. An approach for incorporating the NASA propulsion predictive model results into the optimal estimation algorithm was identified. This approach utilizes numerical derivatives and nominal predictions within the algorithm with global iterations of the algorithm. The iterative process is terminated when the quality of the estimates provided no longer significantly improves.

Source record

Machine Learning Approach for Aircraft Performance Model Parameter Estimation for Trajectory Prediction Applications

Inaccurate prediction of aircraft trajectory by ground-based decision support tools (DST) is a major concern in air traffic management (ATM). Aircraft trajectory prediction tools rely on a simplified point-mass aircraft performance model (APM) to make their predictions. Even though the performance coefficients and weight of an aircraft are a vital part of the APM’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to DSTs. Current ATM research focuses on improving the estimate of some APM parameters by freezing all other coefficients. This simplified approach introduces unwanted sources of bias and negatively impacts the accuracy of the performance model. In this paper, we apply machine learning (ML) techniques for the simultaneous prediction of three key APM parameters (two drag coefficients and the initial aircraft weight). To accomplish this, we employ an ordinary differential equation (ODE) fitting approach to generate optimized APM parameter labels customized to each individual flight record. Subsequently, we train ML models to capture the relationship between the historical data and the optimized APM parameters. Two different ML model solutions are applied and APM coefficients are predicted for unseen flights. The results indicate that the ML models are able to capture the relationship between APM parameters and flight-related features with good accuracy.

trajectory prediction, machine learning, aircraft

An investigation of new methods for estimating parameter sensitivities

The method proposed for estimating sensitivity derivatives is based on the Recursive Quadratic Programming (RQP) method and in conjunction a differencing formula to produce estimates of the sensitivities. This method is compared to existing methods and is shown to be very competitive in terms of the number of function evaluations required. In terms of accuracy, the method is shown to be equivalent to a modified version of the Kuhn-Tucker method, where the Hessian of the Lagrangian is estimated using the BFS method employed by the RQP algorithm. Initial testing on a test set with known sensitivities demonstrates that the method can accurately calculate the parameter sensitivity.

Beltracchi, Todd J.

Global Mass Flux Solutions from GRACE: A Comparison of Parameter Estimation Strategies - Mass Concentrations Versus Stokes Coefficients

The differences between mass concentration (mas con) parameters and standard Stokes coefficient parameters in the recovery of gravity infonnation from gravity recovery and climate experiment (GRACE) intersatellite K-band range rate data are investigated. First, mascons are decomposed into their Stokes coefficient representations to gauge the range of solutions available using each of the two types of parameters. Next, a direct comparison is made between two time series of unconstrained gravity solutions, one based on a set of global equal area mascon parameters (equivalent to 4deg x 4deg at the equator), and the other based on standard Stokes coefficients with each time series using the same fundamental processing of the GRACE tracking data. It is shown that in unconstrained solutions, the type of gravity parameter being estimated does not qualitatively affect the estimated gravity field. It is also shown that many of the differences in mass flux derivations from GRACE gravity solutions arise from the type of smoothing being used and that the type of smoothing that can be embedded in mas con solutions has distinct advantages over postsolution smoothing. Finally, a 1 year time series based on global 2deg equal area mascons estimated every 10 days is presented.

Rowlands, D. D.

LISA Parameter Estimation using Numerical Merger Waveforms

Coalescing supermassive black holes are expected to provide the strongest sources for gravitational radiation detected by LISA. Recent advances in numerical relativity provide a detailed description of the waveforms of such signals. We present a preliminary study of LISA's sensitivity to waveform parameters using a hybrid numerical/analytic waveform describing the coalescence of two equal-mass, nonspinning black holes. The Synthetic LISA software package is used to simulate the instrument response and the Fisher information matrix method is used to estimate errors in the waveform parameters. Initial results indicate that inclusion of the merger signal can significantly improve the precision of some parameter estimates. For example, the median parameter errors for an ensemble of systems with total redshifted mass of 10(exp 6) deg M solar mass at a redshift of z is approximately 1 were found to decrease by a factor of slightly more than two when the merger was included.

Thorpe, J. I.

Nonconservative force model parameter estimation strategy for TOPEX/Poseidon precision orbit determination

The TOPEX/Poseidon spacecraft was launched on August 10, 1992 to study the Earth's oceans. To achieve maximum benefit from the altimetric data it is to collect, mission requirements dictate that TOPEX/Poseidon's orbit must be computed at an unprecedented level of accuracy. To reach our pre-launch radial orbit accuracy goals, the mismodeling of the radiative nonconservative forces of solar radiation, Earth albedo an infrared re-radiation, and spacecraft thermal imbalances cannot produce in combination more than a 6 cm rms error over a 10 day period. Similarly, the 10-day drag modeling error cannot exceed 3 cm rms. In order to satisfy these requirements, a 'box-wing' representation of the satellite has been developed in which, the satellite is modelled as the combination of flat plates arranged in the shape of a box and a connected solar array. The radiative/thermal nonconservative forces acting on each of the eight surfaces are computed independently, yielding vector accelerations which are summed to compute the total aggregate effect on the satellite center-of-mass. Select parameters associated with the flat plates are adjusted to obtain a better representation of the satellite acceleration history. This study analyzes the estimation of these parameters from simulated TOPEX/Poseidon laser data in the presence of both nonconservative and gravity model errors. A 'best choice' of estimated parameters is derived and the ability to meet mission requirements with the 'box-wing' model evaluated.

Luthcke, S. B.

Ensemble‐Based Spatially Distributed CLM5 Hydrological Parameter Estimation for the Continental United States

Abstract One of the major challenges in large‐domain hydrological modeling efforts lies in the estimation of spatially distributed hydrological parameters while simultaneously accounting for their associated uncertainties. Addressing this challenge is particularly difficult in ungauged locations. With growing societal demands for large‐scale streamflow projections to inform water resource management and long‐term planning, evaluating and constraining hydrological parameter uncertainty is increasingly vital. This study introduces a hybrid regionalization approach to enhance hydrological predictions of the Community Land Model version 5 (CLM5) across the Continental United States (CONUS), with a total of 50,629 1/8° grid cells. This hybrid method combines the strengths of two existing techniques: parameter regionalization and streamflow signature regionalization. It identifies ensemble behavioral parameters for each 1/8° grid cell across the CONUS domain, tailored to three distinct streamflow signatures focused on low flows, high flows, and annual water balance. Evaluating this hybrid method for 464 CAMELS (Catchment Attributes and Meteorology for Large‐sample Studies) basins demonstrates a significant improvement in CLM5 hydrological predictions, even in challenging arid regions. In CONUS applications, the derived spatially distributed parameter sets capture both spatial continuity and variation of parameters, highlighting their heterogeneous nature within specific regions. Overall, this hybrid regionalization approach offers a promising solution to the complex task of improving hydrological modeling over large domains for important hydrological applications.

CLM5

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.

The effect of turbulence on atmospheric gradient parameters estimated from ground-based radiometric and space geodetic measurements

A straightforward expression for the covariance of a general vector of atmospheric parameters is employed to calculate the effects of estimates of spatial gradients for a frozen Kolmogorov turbulence field moving over a site at constant velocities. Numerical calculations are performed to investigate the implications for three techniques: ground-based microwave radiometry, geodesy with the Global Positioning System, and VLBI. It is found that a prevailing wind with no true static gradients may give rise to apparent azimuthal asymmetries when gradient parameters are estimated. The standard deviation of the estimated north gradient parameter as a function of wind direction, for various wind speeds, is illustrated.

Davis, James L.

Timoshenko beam modeling for parameter estimation of NASA Mini-Mast truss

In this paper a distributed parameter model for the estimation of modal characteristics of NASA Mini-Mast truss is proposed. A closed-form solution of the Timoshenko beam equation, for a uniform cantilevered beam with two concentrated masses, is derived so that the procedure and the computational effort for the estimation of modal characteristics are improved. A maximum likelihood estimator for the Timoshenko beam model is also developed. The resulting estimates from test data by using Timoshenko beam model are found to be comparable to those derived from other approaches.

Shen, Ji Y.