Results for “Data Analysis: Parameter Estimation” — Page 5

DOE OSTI2026

Poisson-response Tensor-on-Tensor Regression and Applications

We introduce Poisson-response tensor-on-tensor regression (PToTR), a novel regression framework designed to handle tensor responses composed element-wise of random Poisson-distributed counts. Tensors, or multi-dimensional arrays, composed of counts are common data in fields such as inter national relations, social networks, epidemiology, and medical imaging, where events occur across multiple dimensions like time, location, and dyads. PToTR accommodates such tensor responses alongside tensor covariates, providing a versatile tool for multi dimensional data analysis. We propose algorithms for maximum likelihood estimation under a canonical polyadic (CP) structure on the regression coefficient tensor that satisfy the positivity of Poisson parameters and then provide an initial theoretical error analysis for PToTR estimators. We also demonstrate the utility of PToTR through three concrete applications: longitudinal data analysis of the Integrated Crisis Early Warning System database, positron emission tomography (PET) image reconstruction, and change-point detection of communication patterns in longitudinal dyadic data. These applications highlight the versatility of PToTR in addressing complex, structured count data across various domains.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1982

Variational methods in simultaneous optimum interpolation and initialization

The duality between optimum interpolation and variational objective analysis, is reviewed. This duality is used to set up a variational approach to objective analysis which uses prior information concerning the atmospheric spectral energy distribution, in the variational problem. In the wind analysis example, the wind field is partitioned into divergent and nondivergent parts, and a control parameter governing the relative energy in the two parts is estimated from the observational data being analyzed by generalized cross validation, along with a bandwidth parameter. A variational approach to combining objective analysis and initialization in a single step is proposed. In a simple example of this approach, data, forecast, and prior information concerning atmospheric energy distribution is combined into a single variational problem. This problem has (at least) one bandwidth parameter, one partitioning parameter governing the relative energy in fast slow modes, and one parameter governing the relative weight to be given to observational and forecast data.

Wahba, G.↗

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 NTRSDate not supplied

Launch Vehicle Loads Analysis Using Pressure-Sensitive Paint

Pressure transducers have been the instrumentation of choice for measuring unsteady flow phenomena. With recent advances in high-speed cameras, high-powered LEDs, and fast-response, pressure-sensitive paint, the unsteady pressure-sensitive paint (uPSP) technique has become a valuable alternative for production wind tunnel facilities, enabling time-resolved measurements of unsteady pressure fluctuations over a dense spatial grid on a wind tunnel model. Launch vehicle ground tests have proven to be a particularly well-matched application for uPSP due to the high signal level relative to tunnel background acoustics, relatively simple camera optical access, and rigidity of the model in wind-on test conditions. This presentation will highlight recent advances in data reduction of uPSP measurement data from recent launch vehicle wind tunnel tests at the NASA Ames Unitary Plan Wind Tunnel Complex (UPWT). The system can provide both localized surface pressure spectra as well as regional or zonal estimates of turbulence correlation model parameters. In addition, integrated vehicle-scale loads can be provided for buffet analysis. Data is reduced at the on-premise NASA Advanced Supercomputer (NAS) Division for just-in-time delivery of results during an ongoing wind tunnel test.

Pressure-Sensitive Paint↗

NASA NTRSDate not supplied

Launch Vehicle Loads Analysis Using Pressure-Sensitive Paint

Pressure transducers have been the instrumentation of choice for measuring unsteady flow phenomena. With recent advances in high-speed cameras, high-powered LEDs, and fast-response, pressure-sensitive paint, the unsteady pressure-sensitive paint (uPSP) technique has become a valuable alternative for production wind tunnel facilities, enabling time-resolved measurements of unsteady pressure fluctuations over a dense spatial grid on a wind tunnel model. Launch vehicle ground tests have proven to be a particularly well-matched application for uPSP due to the high signal level relative to tunnel background acoustics, relatively simple camera optical access, and rigidity of the model in wind-on test conditions. This presentation will highlight recent advances in data reduction of uPSP measurement data from recent launch vehicle wind tunnel tests at the NASA Ames Unitary Plan Wind Tunnel Complex (UPWT). The system can provide both localized surface pressure spectra as well as regional or zonal estimates of turbulence correlation model parameters. In addition, integrated vehicle-scale loads can be provided for buffet analysis. Data is reduced at the on-premise NASA Advanced Supercomputer (NAS) Division for just-in-time delivery of results during an ongoing wind tunnel test.

pressure-sensitive paint↗

NASA NTRS2011

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Murphy, Patrick C.↗

NASA NTRS2020

Multibody Based Digital Astronaut Dynamics Simulation

BACKGROUND: This study provides the Software, Robotics, & Simulation Division at the NASA Johnson Space Center with a verification tool for multibody dynamics simulation requiring human motion. The motivation stems from current studies of several Vibration Isolation & Stabilization(VIS)system designs that attenuate the moments and forces which would be transmitted to a spacecraft during an exercise. A multibody dynamics model for a proposed VIS was available previously[1], therefore modeling of the VIS was not needed for this work. The interest here is in creating the multibody dynamics model of an astronaut in motion which may be utilized independently or while attached to a mechanism. An existing simulation [2] that utilizes OpenSim [3,4] and an in-house multibody dynamics package (MBDyn) [5] is used in order to verify the astronaut model. The main advantage this model will have over the existing simulation is that everything will be processed in one tool. METHODS AND RESULTS: Creating the simulation required; estimation of Body Segment Inertial Parameters (BSIP),a multibody model of the human-VIS system, joint acceleration profiles, and input files for MBDyn, which is used for this analysis. The scaling factors provided by Dumas et al. [6] are utilized in estimating the BSIP. Anthropometric data are used for estimating these parameters, the Anthropometric Survey of US Army Personnel (ANSUR II) [7] was the source. The astronaut model consists of 15 bodies, 14 joints and 32 degrees of freedom, with the dynamics topology generated using the center of mass locations and anthropometric data. MBDyn has an option for prescribed joint motion (PJM), which requires joint acceleration data as input. The joint angle data is first obtained from a motion capture system and then processed through code that has been created to generate approximate joint acceleration profiles. The topology tree for the astronaut model begins at the right foot up to the pelvis where there is one branch for going down the left leg and another for the torso. The torso branch leads to branches for the arms and a leaf body for the head/neck segment. For attachment to the VIS, the heel of the right foot is connected to the VIS platform through a fixed joint, resembling a foot restraint. The left foot does not attach to the platform in order to prevent a system with a closed loop. Topology and symmetry of the astronaut model were verified through kinematic analysis. Further verification of the forces and moments transmitted to the VIS were verified against the existing simulation. There was a satisfactory level of agreement when testing a simple motion, for example, rocking back and forth. Full exercise motions are to be tested soon. The main outcome has been a novel application of MBDyn for biomechanics modeling that is now available for dynamic simulations involving human motion. The estimation of BSIP was another useful result of this study, requiring only 15 inputs for generating mass properties of a theoretical astronaut model. Expansion on this work is possible by going through an alternative route in obtaining the joint motion data. Instead of high-tech and often expensive motion capture systems, an individual may watch videos with high focus and at a slow motion for each individual segment in order to determine the initial and final time and angle for that specific degree of freedom. Synthetic trajectories may also be created if there is no video reference available.

F N Matari↗

NASA NTRS2017

Mars 2020 Entry, Descent, and Landing Instrumentation 2 (MEDLI2) Sensor Suite

The Mars 2020 Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite seeks to address the aerodynamic, aerothermodynamic, and thermal protection system (TPS) performance issues during atmospheric entry, descent, and landing of the Mars 2020 mission. Based on the highly successful instrumentation suite that flew on Mars Science Laboratory (MEDLI), the new sensor suite expands on the types of measurements and also seeks to answer questions not fully addressed by the previous mission. Sensor Package: MEDLI2 consists of 7 pressure transducers, 17 thermal plugs, 2 heat flux sensors, and one radiometer. The sensors are distributed across both the heatshield and backshell, unlike MEDLI (the first sensor suite), which was located solely on the heat-shield. The sensors will measure supersonic pressure on the forebody, a pressure measurement on the aftbody, near-surface and in-depth temperatures in the heatshield and backshell TPS materials, direct total heat flux on the aftbody, and direct radiative heating on the aftbody. Instrument Development: The supersonic pressure transducers, the direct heat flux sensors, and the radiometer all were tested during the development phase. The status of these sensors, including the piezo-resistive pressure sensors, will be presented. The current plans for qualification and calibration for all of the sensors will also be discussed. Post-Flight Data Analysis: Similar to MEDLI, the estimated flight trajectory will be reconstructed from the data. The aerodynamic parameters that will be reconstructed will be the axial force coefficient, freestream Mach number, base pressure, atmospheric density, and winds. The aerothermal quantities that will be determined are the heatshield and backshell aero-heating, turbulence transition across the heatshield, and TPS in-depth performance of PICA. By directly measuring the radiative and total heat fluxes on the back-shell, the convective portion of the heat flux will be estimated. The status of the current tools to perform the post-flight data analysis will be presented, along with plans for model improvements.

Hwang, Helen H.↗

NASA NTRS2017

Mars 2020 Entry, Descent, and Landing Instrumentation 2 (MEDLI2) Sensor Suite

The Mars 2020 Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite seeks to address the aerodynamic, aerothermodynamic, and thermal protection system (TPS) performance issues during atmospheric entry, descent, and landing of the Mars 2020 mission. Based on the highly successful instrumentation suite that flew on Mars Science Laboratory (MEDLI), the new sensor suite expands on the types of measurements and also seeks to answer questions not fully addressed by the previous mission. Sensor Package: MEDLI2 consists of 7 pressure transducers, 17 thermal plugs, 2 heat flux sensors, and one radiometer. The sensors are distributed across both the heatshield and backshell, unlike MEDLI (the first sensor suite), which was located solely on the heat-shield. The sensors will measure supersonic pressure on the forebody, a pressure measurement on the aftbody, near-surface and in-depth temperatures in the heatshield and backshell TPS materials, direct total heat flux on the aftbody, and direct radiative heating on the aftbody. Instrument Development: The supersonic pressure transducers, the direct heat flux sensors, and the radiometer all were tested during the development phase. The status of these sensors, including the piezo-resistive pressure sensors, will be presented. The current plans for qualification and calibration for all of the sensors will also be discussed. Post-Flight Data Analysis: Similar to MEDLI, the estimated flight trajectory will be reconstructed from the data. The aerodynamic parameters that will be reconstructed will be the axial force coefficient, freestream Mach number, base pressure, atmospheric density, and winds. The aerothermal quantities that will be determined are the heatshield and backshell aero-heating, turbulence transition across the heatshield, and TPS in-depth performance of PICA. By directly measuring the radiative and total heat fluxes on the back-shell, the convective portion of the heat flux will be estimated. The status of the current tools to perform the post-flight data analysis will be presented, along with plans for model improvements.

Hwang, Helen↗

NASA NTRS1984

Methodology for predictive testing of fuel cells

A perturbation testing method has been developed and tested for predictive testing of fuel cells. This method involves application of small changes to the operating conditions of the cell in a predetermined sequence. The resultant response of the cell is then measured and statistically correlated with the corresponding test conditions. This method has been applied to the phosphoric acid fuel cell, and the effect of operating and cell-component variables on cell-performance degradation has been studied. A strong effect of the cell temperature and cathode potential on fuel-cell-performance degradation has been observed. A cell-performance degradation model has been formulated, and the unknown parameters in the model have been estimated by a regression analysis of the experimental data. A reasonable agreement between the fuel cell performance predicted by this model (derived from the perturbation experiments) and the unperturbed test data supports fthe applicability of the perturbation method.

Patel, D. N.↗

NASA NTRSDate not supplied

From Formal Errors Towards Realistic Uncertainties

Evaluation of uncertainties of geodetic parameter estimates is the problem that is not yet solved in a satisfactory way. A direct evaluation of the uncertainties derived from a least square solution is labeled "formal" and is usually biased, sometimes up to an order of magnitude. Customary, the use of formal errors for scientific analysis is discouraged. We claim that the root of the problem is neglecting off-diagonal elements in the variance-covariance matrix of the noise in the data. A careful reconstruction of the full variance-covariance matrix, including the off-diagonal terms greatly improves realism of uncertainty estimates derived from least squares. We processed the dataset of VLBI group delays and built a prior variance-covariance of the atmosphere-driven noise based on analysis of the output of NASA high-resolution numerical weather models. We found that the uncertainties of parameter estimates derived from this least square solution that uses such variance-covariance matrices become much closer to realistic errors. We consider approaches for implementation of this method in routine data analysis of space geodesy data.

Leonid Petrov↗

NASA NTRS1984

Remote sensing of weather and climate parameters from HIRS2/MSU on Tiros-N

At the Goddard Laboratory for Atmospheric Sciences (GLAS) a physically based satellite temperature sounding retrieval system, involving the simultaneous analysis of HIRS2 and MSU sounding data, has been developed for determining atmospheric and surface conditions which are consistent with the observed radiances. In addition to determining accurate atmospheric temperature profiles even in the presence of cloud contamination, the system provides global estimates of day and night sea or land surface temperatures, snow and ice cover, and parameters related to cloud cover. The inverse radiative transfer equation approach to the multi-spectral analysis of the data, and details of its implementation, are described. Ice, snow, and cloud fields derived for January 1979 are consistent with other measures of similar parameters obtained from AVHRR and SMMR. Monthly mean sea-surface temperature fields agree with those derived from ship and buoy measurements to 0.5 C.

Susskind, J.↗

NASA NTRS2000

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses, and the validation of the results.

Schieldge, John↗

NASA NTRS1993

Room-Temperature Determination of Two-Dimensional Electron Gas Concentration and Mobility in Heterostructures

A technique for determination of room-temperature two-dimensional electron gas (2DEG) concentration and mobility in heterostructures is presented. Using simultaneous fits of the longitudinal and transverse voltages as a function of applied magnetic field, we were able to separate the parameters associated with the 2DEG from those of the parallel layer. Comparison with the Shubnikov-de Haas data derived from measurements at liquid helium temperatures proves that the analysis of the room-temperature data provides an excellent estimate of the 2DEG concentration. In addition we were able to obtain for the first time the room-temperature mobility of the 2DEG, an important parameter to device application. Both results are significantly different from those derived from conventional Hall analysis.

Schacham, S. E.↗

DOE OSTI2025

ASCR Workshop Position Paper: Challenges and Opportunities in High Energy Physics

High energy particle physics and cosmology concern themselves with estimating fundamental parameters of nature, such as the masses and interactions of fundamental particles like the Higgs boson and the rate of expansion of the universe. In doing so, they analyze exabyte-scale datasets, some of the largest in all of science, and face many challenges in subsequent data analysis. These challenges are shared between the two disciplines, but we focus on particle physics to highlight one specific domain. In particle physics, the standard method for estimating parameters involves performing Monte Carlo (MC) integration as a function of both parameters of interest and nuisance parameters using an expensive simulator, counting the number of observed collision events (i.i.d. samples) from an experiment in the corresponding integration domains, and forming a Poisson likelihood function. This likelihood function is then used in a Frequentist manner to construct a maximum likelihood point estimate (MLE) and confidence set for the parameters. To sufficiently populate the high-dimensional integration domains, simulators consume billions of CPU-hours annually and produce hundreds of petabytes of intermediate output data. Several techniques have been developed to: optimize definitions of the integration domains so as to be maximally sensitive to a particular subset of parameters, efficiently estimate the integrals, and build robust surrogate models by interpolating between integral evaluations at different parameter points. One can view this whole endeavor as classical Simulation-Based Inference (SBI).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1964

Estimation in mixtures of two poisson distributions

Estimating parameters of mixed distribution consisting of two Poisson components for statistical analysis of atmospheric data

ATMOSPHERE↗

NASA NTRS1994

Earth Rotation Parameters from DSN VLBI: 1994

In this report, Earth Rotation Parameter (ERP) estimates ahve been obtained from an analysis of Deep Space Network (DSN) VLBI data that directly aligns its celestial and terrestrial reference frames with those of the International Earth Rotation Service (IERS).

Earth rotation TEMPO↗

NASA NTRS1995

On the deficit problem of mass and energy of solar coronal mass ejections connected with interplanetary shocks

Mean values of a number of parameters of the most powerful coronal mass ejections (CMEs) and interplanetary shocks generated by these ejections are estimated using an analysis of data obtained by the cosmic coronagraphs and spacecrafts, and geomagnetic storm measurements. It was payed attention that the shock mass and mechanical energy, averaging 5 x 10(exp 16) grm and 2 x 10(exp 32) erg respectively, are nearly 10 times larger than corresponding parameters of the ejections. So, the CME energy deficit problem seems to exist really. To solve this problem one can make an assumption that the process of the mass and energy growth of CMEs during their propagation out of the Sun observed in the solar corona is continued in supercorona too up to distances of 10-30 solar radii. This assumption is confirmed by the data analysis of five events observed using zodiacal light photometers of the HELIOS- I and HELIOS-2 spacecrafts. The mass growth rate is estimated to be equal to (1-7) x 10(exp 11) grm/sec. It is concluded that the CME contribution to mass and energy flows in the solar winds probably, is larger enough than the value of 3-5% adopted usually.

Ivanchuk, V. I.↗