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At least 217 records · Page 12

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DOE OSTI2021

Spherical Parameter Estimation and MPDV Applications

A new algebraic least square approach is presented for estimating effective zero center for verification of MPDV(Multichannel Photon Doppler Velocimetry) probe designs. Unlike previous algebraic least square methods for spherical parameter estimation, the new method can be shown to be concise in mathematic formulations, easy of computations, invariant under rigid -body transformations, no need for numerical approximations, and precise in dealing with precise data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Femtosecond pulse parameter estimation from photoelectron momenta using machine learning

Abstract Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we test CNNs on strong-field ionization photoelectron spectra, training on theoretical data sets to ‘invert’ experimental data. Pulse characterization is used as a ‘testing ground’, specifically we retrieve the laser intensity, where ‘traditional’ measurements typically lead to 20% uncertainty. We report on crucial data augmentation techniques required to successfully train on theoretical data and return consistent results from experiments, including accounting for detector saturation. The same procedure can be repeated to apply CNNs in a range of scenarios for strong-field ionization. Using a predictive uncertainty estimation, reliable laser intensity uncertainties of a few percent can be extracted, which are consistently lower than those given by traditional techniques. Using interpretability methods can reveal parts of the distribution that are most sensitive to laser intensity, which can be directly associated with holographic interferences. The CNNs employed provide an accurate and convenient ways to extract parameters, and represent a novel interpretational tool for strong-field ionization spectra.

Szołdra, Tomasz (ORCID:0000000228970506)↗

DOE OSTI2022

Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference

Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will increase that number by 1-2 orders of magnitude. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. To leverage the increased statistical power of the lenses that will be discovered through upcoming surveys, automated lens analysis techniques are necessary. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate the successful application of Neural Posterior Estimation (NPE) to automate the inference of a 12-parameter lens mass model for DES-like ground-based imaging data. We compare our NPE constraints to a Bayesian Neural Network (BNN) and find that it outperforms the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Application of an equation‐oriented framework to formulate and estimate parameters of chemical looping reaction models

Abstract Accurate, predictive reaction models are critical for the design and optimization of chemical looping combustion (CLC) reactors. The formulation and estimation of kinetic parameters for these reaction models using a first‐principles equation‐oriented (EO) approach is particularly beneficial as large amounts of experimental data spanning process‐relevant conditions can be used to estimate parameters in a computationally tractable way. This work demonstrates the application of a novel EO framework to develop reduction reaction kinetic models of an iron‐based CLC oxygen carrier (OC). An optimization problem is formulated to estimate kinetic parameters that provide the best fit to the experimental data. The model predicts the state of the OC with mean square error values of 2.5%–4.4% across the full range of validation data, including multiple reduction cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1977

A parameter estimation subroutine package

Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. FORTRAN subroutines have been developed to facilitate analyses of a variety of parameter estimation problems. Easy to use multipurpose sets of algorithms are reported that are reasonably efficient and which use a minimal amount of computer storage. Subroutine inputs, outputs, usage and listings are given, along with examples of how these routines can be used.

Bierman, G. J.↗

NASA NTRS2018

Real-Time Parameter Estimation for Flexible Aircraft

A method for estimating aeroelastic stability and control derivatives for flexible aircraft is developed and demonstrated using flight test data for the X-56A subscale demonstrator. The method uses the equation-error approach with frequency-domain data, and can be applied post-flight or in real time during flight. The non-dimensional aeroelastic forces and moments and the explanatory variables (including generalized displacement, rate, and acceleration states for the vibration modes) are estimated using a finite element model and onboard sensor measurements in both a least squares and Kalman filtering framework. The data are then transformed into the frequency domain for parameter estimation using equation error. This method can result in a more efficient analysis than with other iterative methods, and can leverage existing statistical tools for model structure determination, data collinearity detection, combining multiple maneuvers or prior information, and others to improve model quality.

Grauer, Jared A.↗

NASA NTRS2011

Flight Test of Orthogonal Square Wave Inputs for Hybrid-Wing-Body Parameter Estimation

As part of an effort to improve emissions, noise, and performance of next generation aircraft, it is expected that future aircraft will use distributed, multi-objective control effectors in a closed-loop flight control system. Correlation challenges associated with parameter estimation will arise with this expected aircraft configuration. The research presented in this paper focuses on addressing the correlation problem with an appropriate input design technique in order to determine individual control surface effectiveness. This technique was validated through flight-testing an 8.5-percent-scale hybrid-wing-body aircraft demonstrator at the NASA Dryden Flight Research Center (Edwards, California). An input design technique that uses mutually orthogonal square wave inputs for de-correlation of control surfaces is proposed. Flight-test results are compared with prior flight-test results for a different maneuver style.

Taylor, Brian R.↗

DOE OSTI2021

Mathematical modeling and parameter estimation of MFI membranes for para/ortho‐xylene separation

Abstract A mathematical model of a membrane with a thin, oriented, and selective MFI layer, which also includes contributions from defects, pore blockages, support layer, and external mass transfer, was formulated based on the Maxwell‐Stefan equations. It was validated using reported (Kim et al., Angew Chemie Int Ed, 2018, 57:480–485; Jeon et al., Nature, 2017, 543:690–694) para/ortho‐xylene separation data from five MFI membranes. The diffusivities of the xylenes were considered to be the same for all membranes, while the thickness and the density of defects and pore blockage were treated as unique properties of each membrane, and their contributions were estimated by fitting the model to the corresponding separation data. The effects of these properties and the role of permeate pressure on the separation performance were subsequently analyzed. The proposed modeling, parameter estimation, and analysis framework allow one to quantitatively interpret the variation of separation performance, to understand separation bottlenecks, and to provide guidance for designing membranes with desired performance.

Liu, Jingjun↗

NASA NTRS1983

The application of parameter estimation to flight measurements to obtain lateral-directional stability derivatives of an augmented jet-flap STOL airplane

Flight experiments with an augmented jet flap STOL aircraft provided data from which the lateral directional stability and control derivatives were calculated by applying a linear regression parameter estimation procedure. The tests, which were conducted with the jet flaps set at a 65 deg deflection, covered a large range of angles of attack and engine power settings. The effect of changing the angle of the jet thrust vector was also investigated. Test results are compared with stability derivatives that had been predicted. The roll damping derived from the tests was significantly larger than had been predicted, whereas the other derivatives were generally in agreement with the predictions. Results obtained using a maximum likelihood estimation procedure are compared with those from the linear regression solutions.

Stephenson, J. D.↗

NASA NTRS2015

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

gravitational wave↗

NASA NTRS2007

Mechanical Analog Approach to Parameter Estimation of Lateral Spacecraft Fuel Slosh

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. Even with modern computing systems, CFD type simulations are not fast enough to allow for large scale Monte Carlo analyses of spacecraft and launch vehicle dynamic behavior with slosh included. Simplified mechanical analogs for the slosh are preferred during the initial stages of design to reduce computational time and effort to evaluate the Nutation Time Constant (NTC). Analytic determination of the slosh analog parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices such as elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks, these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the hand-derived equations of motion for the mechanical analog are evaluated and their results compared with the experimental results. Of particular interest is the effect of diaphragms and bladders on the slosh dynamics and how best to model these devices. An experimental set-up is designed and built to include a diaphragm in the simulated spacecraft fuel tank subjected to lateral slosh. This research paper focuses on the parameter estimation of a SimMechanics model of the simulated spacecraft propellant tank with and without diaphragms using lateral fuel slosh experiments. Automating the parameter identification process will save time and thus allow earlier identification of potential vehicle problems.

Chatman, Yadira↗

NASA NTRS1982

Comparison of laser anemometer measurements and theory in an annular turbine cascade with experimental accuracy determined by parameter estimation

Experimental measurements of the velocity components in the blade to blade (axial tangential) plane were obtained with an axial flow turbine stator passage and were compared with calculations from three turbomachinery computer programs. The theoretical results were calculated from a quasi three dimensional inviscid code, a three dimensional inviscid code, and a three dimensional viscous code. Parameter estimation techniques and a particle dynamics calculation were used to assess the accuracy of the laser measurements, which allow a rational basis for comparison of the experimenal and theoretical results. The general agreement of the experimental data with the results from the two inviscid computer codes indicates the usefulness of these calculation procedures for turbomachinery blading. The comparison with the viscous code, while generally reasonable, was not as good as for the inviscid codes.

Goldman, L. J.↗

NASA NTRS1975

Transfer-function-parameter estimation from frequency response data: A FORTRAN program

A FORTRAN computer program designed to fit a linear transfer function model to given frequency response magnitude and phase data is presented. A conjugate gradient search is used that minimizes the integral of the absolute value of the error squared between the model and the data. The search is constrained to insure model stability. A scaling of the model parameters by their own magnitude aids search convergence. Efficient computer algorithms result in a small and fast program suitable for a minicomputer. A sample problem with different model structures and parameter estimates is reported.

Seidel, R. C.↗

NASA NTRS1979

A parameter-estimation subroutine package

Estimation subroutine package comprises fast, efficient, and simple least-squares data-processing algorithms for use in orbit determination and related analyses. Very reliable and general algorithms have been documented. Package contains collection of streamlined subroutines that can be used to solve large variety of parameter-estimation and filtering problems. Special routines are included for problems with colored process noise and covariance (factor) mapping.

Bierman, G.↗

NASA NTRS1994

Parameter estimation of the vibrational model for the SCOLE experimental facility

The objective of this study is to experimentally determine an empirical model of the vibrational dynamics of the Spacecraft COntrol Laboratory Experiment (SCOLE) facility. The first two flexible modes of this test article are identified using a linear least-square identification procedure and the data utilized for this procedure are obtained by exciting the structure from a quiescent state with torque wheels. The time history data of rate gyro sensors and accelerometers due to excitation and after excitation in terms of free-decay are used in the parameter estimation of the vibrational model. The free-decay portion of the data is analyzed using the Discrete Fourier transform to determine the optimal model order to use in modelling the response. Linear least-square analysis is then used to select the parameters that best fit the output of an Autoregressive (AR) model to the data. The control effectiveness of the torque wheels is then determined using the excitation portion of the test data, again using linear least squares.

Crotts, B. D.↗

DOE OSTI2021

Multiscale Reduced Order Modeling and Parameter Estimation for Climate Sciences

Several problems in earth system modeling are dependent on highly multiscale phenomena, such as turbulence, where computational modeling is challenging and expensive. This issue is exacerbated in atmospheric and oceanic domains, due to inherent high-dimensionality of the problem. One approach to this problem has been reduced order modeling (ROM); which aims to represent the key physics of the phenomena as a low-dimensional system. AI methods have huge potential in building accurate, stable ROMs and parameter estimation for these ROMs, as it requires extracting nonlinearities and patterns from simulation and/or observational data. Developing physics-based AI approaches specialized for the complexities of multiscale data, along with strategies to account for uncertainties, will revolutionize rapid modeling, analysis and decision making for earth system problems of practical interest.

58 GEOSCIENCES↗

NASA NTRS1989

Statistical precipitation cell parameter estimation using passive 118-GHz O2 observations

This paper investigates the statistical retrieval of cell top altitude using high-resolution passive 118-GHz multichannel precipitation cell imagery. The observations were made using the millimeter-wave temperature sounder scanning spectrometer aboard the NASA ER-2 high-altitude research aircraft, during the Genesis of Atlantic Lows Experiment and the Cooperative Huntsville Meteorological Experiment, 1986. Results obtained using a nonlinear statistical 118-GHz cell top altitude retrieval technique are presented, illustrating a systematic method for parameter estimation from noisy nonlinearly dependent observations.

Gasiewski, A. J.↗

NASA NTRS1997

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.↗