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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

A function space approach to state and model error estimation for elliptic systems

An approach is advanced for the concurrent estimation of the state and of the model errors of a system described by elliptic equations. The estimates are obtained by a deterministic least-squares approach that seeks to minimize a quadratic functional of the model errors, or equivalently, to find the vector of smallest norm subject to linear constraints in a suitably defined function space. The minimum norm solution can be obtained by solving either a Fredholm integral equation of the second kind for the case with continuously distributed data or a related matrix equation for the problem with discretely located measurements. Solution of either one of these equations is obtained in a batch-processing mode in which all of the data is processed simultaneously or, in certain restricted geometries, in a spatially scanning mode in which the data is processed recursively. After the methods for computation of the optimal esimates are developed, an analysis of the second-order statistics of the estimates and of the corresponding estimation error is conducted. Based on this analysis, explicit expressions for the mean-square estimation error associated with both the state and model error estimates are then developed. While this paper focuses on theoretical developments, applications arising in the area of large structure static shape determination are contained in a closely related paper (Rodriguez and Scheid, 1982).

Rodriguez, G.↗
NASA NTRS2022

Exploration of an Adaptive Routine for Battery Modeling

The purpose of this document is to explore the use of adaptive routines in battery modeling. The adaptive routines consist of real-time state estimators combined with battery parameter model components that are adjusted in real-time as battery data becomes available. Several aspects are explored. It is shown that model parameter identification is possible for simple battery models using available input/output data measurements. The online system identification used is recursive least squares. Model identification may be combined with a state observer such as the extended Kalman filter or the unscented Kalman filter to form an adaptive model combined with state estimation. However, such a combination is found to be problematic due to uncertainty, observability and stability issues. This paper is organized as follows. Section 1 introduces adaptive routines and possible roles they play in battery modeling. In Section 2 real-time parameter identification is described with results based on battery data. Section 3 reviews various state estimators and results using a simple battery model. In Section 4 parameter identification and state estimation are combined to form an adaptive routine. Finally, in Section 5 conclusions are drawn and future work is suggested.

Adaptive↗
NASA NTRS2006

On the equivalence of the dual-wavelength and polarimetric equations for estimation of the raindrop size distribution

In writing the integral equations for the median mass diameter and particle concentration, or comparable parameters of the raindrop size distribution, it is apparent that when attenuation effects are included, the forms of the equations for polarimetric and dual wavelength radars are identical. In both sets of equations, differences in the backscattering and extinction cross sections appear: in the polarimetric equations, the differences are taken with respect polarization at a fixed frequency while for the dual wavelength equations, the differences are taken with respect to wavelength at a fixed polarization. Because the forms of the equations are the same, the ways in which they can be solved are similar as well. To avoid instabilities in the forward recursion procedure, the equations can be expressed in the form of a final-value. Solving the equations in this way traditionally has required estimates of the path attenuations to the final gate: either the attenuations at horizontal and vertical polarizations at the same frequency or attenuations at two frequencies with the same polarization. This has been done for dual-frequency (air/spaceborne case) and polarimetric radars by the respective use of the surface reference technique and the differential phase shift. An alternative to solving the constrained version of the equations is an iterative procedure recently proposed in which independent estimates of path attenuation are not required. Although the procedure has limitations, it appears to be quite useful. Simulations of the retrievals help clarify the relationship between the constrained and unconstrained approaches and their application to the polarimetric and dual-wavelength equations.

Meneghini, Robert↗
NASA NTRS1972

Star scanner attitude determination for the OSO-7 spacecraft.

Calculation of the inertial orientation of the OSO-7 spacecraft from the times at which known stars or planets transit planes fixed in the spacecraft. Both the reference planes and the timing information are provided by the star scanner instrument aboard the spacecraft, while the star identification and the statistical estimation of a set of parameters describing the spacecraft attitude are accomplished in a ground station computer facility. A recursive least-squares determination is made of a vector of first-order differential corrections to the attitude state vector. Preliminary analysis indicates the system accuracy to be 3 arc min in each attitude Euler angle.

Mackison, D. L.↗
NASA NTRS1984

A fundamental model and efficient inference for SAR ocean imagery

Employing a synthetic aperture radar (SAR) imaging model based on fundamental models of nonlinear hydrodynamics, electromagnetic scattering from a two-scale surface, and SAR imaging of a time-variant scene, the optimal (minimum mean-square error) estimates of the parameters of a sinusoidal, long gravity wave, and the short gravity wave ensemble are found in an efficient recursive form and their performance evaluated, generally by numerical simulation, in a one-dimensional stationary version. An application is made to Seasat-SAR complex imagery.

Harger, R. O.↗
NASA NTRS2009

Parameter Estimation for a Hybrid Adaptive Flight Controller

This paper expands on the hybrid control architecture developed at the NASA Ames Research Center by addressing issues related to indirect adaptation using the recursive least squares (RLS) algorithm. Specifically, the hybrid control architecture is an adaptive flight controller that features both direct and indirect adaptation techniques. This paper will focus almost exclusively on the modifications necessary to achieve quality indirect adaptive control. Additionally this paper will present results that, using a full non -linear aircraft model, demonstrate the effectiveness of the hybrid control architecture given drastic changes in an aircraft s dynamics. Throughout the development of this topic, a thorough discussion of the RLS algorithm as a system identification technique will be provided along with results from seven well-known modifications to the popular RLS algorithm.

Campbell, Stefan F.↗
NASA NTRS2006

Estimation of Stability and Control Derivatives of an F-15

A technique for real-time estimation of stability and control derivatives (derivatives of moment coefficients with respect to control-surface deflection angles) was used to support a flight demonstration of a concept of an indirect-adaptive intelligent flight control system (IFCS). Traditionally, parameter identification, including estimation of stability and control derivatives, is done post-flight. However, for the indirect-adaptive IFCS concept, parameter identification is required during flight so that the system can modify control laws for a damaged aircraft. The flight demonstration was carried out on a highly modified F-15 airplane (see Figure 1). The main objective was to estimate the stability and control derivatives of the airplane in nearly real time. A secondary goal was to develop a system to automatically assess the quality of the results, so as to be able to tell a learning neural network which data to use. Parameter estimation was performed by use of Fourier-transform regression (FTR) a technique developed at NASA Langley Research Center. FTR is an equation- error technique that operates in the frequency domain. Data are put into the frequency domain by use of a recursive Fourier transform for a discrete frequency set. This calculation simplifies many subsequent calculations, removes biases, and automatically filters out data beyond the chosen frequency range. FTR as applied here was tailored to work with pilot inputs, which produce correlated surface positions that prevent accurate parameter estimates, by replacing half the derivatives with predicted values. FTR was also set up to work only on a recent window of data, to accommodate changes in flight condition. A system of confidence measures was developed to identify quality-parameter estimates that a learning neural network could use. This system judged the estimates primarily on the basis of their estimated variances and of the level of aircraft response. The resulting FTR system was implemented in the Simulink software system and auto-coded in the C programming language for use on the Airborne Research Test System (ARTS II) computer installed in the F-15 airplane. The Simulink model was also used in a control room that utilizes the Ring Buffered Network Bus hardware and software, making it possible to evaluate test points during flights. In-flight parameter estimation was done for piloted and automated maneuvers, primarily at three test conditions. Figure 2 shows results for pitching moment due to symmetric stabilator actuations for a series of three pitch doublet maneuvers (in a doublet maneuver, a command to change attitude in a given direction by a given amount is followed immediately by a command to change attitude in the opposite direction by the same amount). A time window of 5 seconds was used. The portions of the curves shown in red are those that passed the confidence tests. The technique showed good convergence for most derivatives for both kinds of maneuvers - typically within a few seconds. The confidence tests were marginally successful, and it would be necessary to refine them for use in an IFCS.

Smith, Mark↗
NASA NTRS1987

Spatially random models, estimation theory, and robot arm dynamics

Spatially random models provide an alternative to the more traditional deterministic models used to describe robot arm dynamics. These alternative models can be used to establish a relationship between the methodologies of estimation theory and robot dynamics. A new class of algorithms for many of the fundamental robotics problems of inverse and forward dynamics, inverse kinematics, etc. can be developed that use computations typical in estimation theory. The algorithms make extensive use of the difference equations of Kalman filtering and Bryson-Frazier smoothing to conduct spatial recursions. The spatially random models are very easy to describe and are based on the assumption that all of the inertial (D'Alembert) forces in the system are represented by a spatially distributed white-noise model. The models can also be used to generate numerically the composite multibody system inertia matrix. This is done without resorting to the more common methods of deterministic modeling involving Lagrangian dynamics, Newton-Euler equations, etc. These methods make substantial use of human knowledge in derivation and minipulation of equations of motion for complex mechanical systems.

Rodriguez, G.↗
NASA NTRS1976

On least-squares design of recursive digital filters

Time-domain methods for the design of recursive digital filters using a squared error criterion are compared with a frequency-domain technique. Levy's method, which has been used to estimate transfer functions of continuous-time systems is modified to obtain design equations for digital filters. A special case of Levy's method is shown to be essentially equivalent to the time-domain methods.

Shenoi, K.↗
NASA NTRS1996

REQUEST: A Recursive QUEST Algorithm for Sequential Attitude Determination

In order to find the attitude of a spacecraft with respect to a reference coordinate system, vector measurements are taken. The vectors are pairs of measurements of the same generalized vector, taken in the spacecraft body coordinates, as well as in the reference coordinate system. We are interested in finding the best estimate of the transformation between these coordinate system.s The algorithm called QUEST yields that estimate where attitude is expressed by a quarternion. Quest is an efficient algorithm which provides a least squares fit of the quaternion of rotation to the vector measurements. Quest however, is a single time point (single frame) batch algorithm, thus measurements that were taken at previous time points are discarded. The algorithm presented in this work provides a recursive routine which considers all past measurements. The algorithm is based on on the fact that the, so called, K matrix, one of whose eigenvectors is the sought quaternion, is linerly related to the measured pairs, and on the ability to propagate K. The extraction of the appropriate eigenvector is done according to the classical QUEST algorithm. This stage, however, can be eliminated, and the computation simplified, if a standard eigenvalue-eigenvector solver algorithm is used. The development of the recursive algorithm is presented and illustrated via a numerical example.

Bar-Itzhack, Itzhack Y.↗
NASA NTRS1985

Real-time flutter identification

The techniques and a FORTRAN 77 MOdal Parameter IDentification (MOPID) computer program developed for identification of the frequencies and damping ratios of multiple flutter modes in real time are documented. Physically meaningful model parameterization was combined with state of the art recursive identification techniques and applied to the problem of real time flutter mode monitoring. The performance of the algorithm in terms of convergence speed and parameter estimation error is demonstrated for several simulated data cases, and the results of actual flight data analysis from two different vehicles are presented. It is indicated that the algorithm is capable of real time monitoring of aircraft flutter characteristics with a high degree of reliability.

Roy, R.↗
NASA NTRS1987

Real time identification of large space structures

Identification of frequencies, damping ratios, and mode shapes of large space structures (LSSs) are examined in real time. Real time processing allows for quick updates of model processing after a reconfiguration of structural failure. Recursive lattice least squares (RLLS) was selected as the baseline algorithm for the identification. Simulation results on a one dimensional LSS demonstrated that it provides good estimates, was not ill-conditioned in the presence of under-excited modes, allowed activity by a supervisory control system which prevented damage to the LSS or excessive drift, and was capable of real-time processing for typical LSS models. A suboptimal version of RLLS, which is equivalent to simulated parallel processing, was derived. A NASTRAN model of the dual keel U.S. space station was used to demonstrate the input/identification algorithm package in a more realistic simulation. Because the first eight flexible modes were very close together, the identification was much more difficult than in the simple examples. Even so, the model was accurately identified in real time.

Voss, Janice E.↗
NASA NTRS1987

Differential sampling for fast frequency acquisition via adaptive extended least squares algorithm

This paper presents a differential signal model along with appropriate sampling techinques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in mesurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can made small.

Kumar, Rajendra↗
NASA NTRS1995

Parallel CFD Algorithms for Aerodynamical Flow Solvers on Unstructured Meshes

The Advisory Group for Aerospace Research and Development (AGARD) has requested my participation in the lecture series entitled Parallel Computing in Computational Fluid Dynamics to be held at the von Karman Institute in Brussels, Belgium on May 15-19, 1995. In addition, a request has been made from the US Coordinator for AGARD at the Pentagon for NASA Ames to hold a repetition of the lecture series on October 16-20, 1995. I have been asked to be a local coordinator for the Ames event. All AGARD lecture series events have attendance limited to NATO allied countries. A brief of the lecture series is provided in the attached enclosure. Specifically, I have been asked to give two lectures of approximately 75 minutes each on the subject of parallel solution techniques for the fluid flow equations on unstructured meshes. The title of my lectures is "Parallel CFD Algorithms for Aerodynamical Flow Solvers on Unstructured Meshes" (Parts I-II). The contents of these lectures will be largely review in nature and will draw upon previously published work in this area. Topics of my lectures will include: (1) Mesh partitioning algorithms. Recursive techniques based on coordinate bisection, Cuthill-McKee level structures, and spectral bisection. (2) Newton's method for large scale CFD problems. Size and complexity estimates for Newton's method, modifications for insuring global convergence. (3) Techniques for constructing the Jacobian matrix. Analytic and numerical techniques for Jacobian matrix-vector products, constructing the transposed matrix, extensions to optimization and homotopy theories. (4) Iterative solution algorithms. Practical experience with GIVIRES and BICG-STAB matrix solvers. (5) Parallel matrix preconditioning. Incomplete Lower-Upper (ILU) factorization, domain-decomposed ILU, approximate Schur complement strategies.

Barth, Timothy J.↗
NASA NTRS1978

Application of semianalytical satellite theories to precision orbit determination

Those factors which limit the usefulness of current implementations of the semianalytical approach are discussed. Numerical and analytical enhancements to the semianalytical approach are considered. A simple mathematical model is provided to estimate the computational speed of a semianalytical theory employing the suggested enhancements. The model can factor in current experience with semianalytical theories (integration stepsizes, quadrature orders, speed of recursive formulations, etc.) and the characteristics of the particular output requirement (observation span (or orbit determination interval), observation rate, observation model, etc.). Comparisons with numerical integration are suggested.

Cefola, P. J.↗
NASA NTRS1999

Cone-Probe Rake Design and Calibration for Supersonic Wind Tunnel Models

A series of experimental investigations were conducted at the NASA Langley Unitary Plan Wind Tunnel (UPWT) to calibrate cone-probe rakes designed to measure the flow field on 1-2% scale, high-speed wind tunnel models from Mach 2.15 to 2.4. The rakes were developed from a previous design that exhibited unfavorable measurement characteristics caused by a high probe spatial density and flow blockage from the rake body. Calibration parameters included Mach number, total pressure recovery, and flow angularity. Reference conditions were determined from a localized UPWT test section flow survey using a 10deg supersonic wedge probe. Test section Mach number and total pressure were determined using a novel iterative technique that accounted for boundary layer effects on the wedge surface. Cone-probe measurements were correlated to the surveyed flow conditions using analytical functions and recursive algorithms that resolved Mach number, pressure recovery, and flow angle to within +/-0.01, +/-1% and +/-0.1deg , respectively, for angles of attack and sideslip between +/-8deg. Uncertainty estimates indicated the overall cone-probe calibration accuracy was strongly influenced by the propagation of measurement error into the calculated results.

Won, Mark J.↗
DOE OSTI2025

Predicting Initial Trans-Membrane Pressure for Optimized Operations in UF Unit Using Random Forest

With the growing scarcity of freshwater, innovative process design mechanisms like Reverse Osmosis (RO) are increasingly gaining attention among water treatment utilities to address the rising demand. Ensuring reliable water production necessitates efficient resource utilization, minimizing downtime in (ultra-filtration) UF systems. Recent advancements in machine learning (ML) have enabled the development of accurate data-driven models for Model Predictive Control (MPC), often requiring minimal prior knowledge of underlying physical processes. In this study, we present predictive regression models based on Random Forest (RF) and Auto-Regressive (AR) approaches to forecast the initial Trans-Membrane Pressure (TMP) for each filtration cycle in data generated by Direct Potable Reuse (DPR) systems. The proposed RF-based model demonstrates superior performance compared to baseline methods, including historical mean, Last Observation Carried Forward (LOCF), and naïve AR models, across various forecasting horizons in terms of root mean square error (RMSE) metric. To evaluate how different classes of process variables contribute to TMP dynamics over time, we examine the feature importance of independent covariates across multiple forecast horizons. This analysis provides insight into the temporal relevance of operational and sensor-derived features, guiding control and monitoring strategies. Additionally, the impact of hyperparameter tuning on TMP prediction performance is studied for both direct and recursive RF modelling approaches across increasing forecast horizons. Accurate prediction of initial TMP is critical for optimizing RO operations, as it enables the development of robust modelling frameworks by accurately estimating membrane fouling trends, thereby enhancing process efficiency and long-term reliability. The demonstrated efficacy of the RF-based approach highlights its potential as a tool for real-time decision-making in water treatment systems, paving the way for advanced process optimization and sustainable water resource management.

Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
NASA NTRS1991

A potential method for the estimation of drop size distribution from a dual-wavelength airborne radar

In order to investigate the role of the drop size distribution (DSD) from a dual-wavelength airborne radar and to recover profiled rain rates, a procedure is described for the purpose of estimating the DSD. The method differs from previous approaches in that it provides 2n + 1 parameters of the profiled DSD (where n is the number of range gates) and it uses a recursive procedure beginning at the range gate near the surface progressing backwards toward the storm top. The method is argued to be useful both as a diagnostic tool and as a means by which more detailed information on the vertical structure of the precipitation can be obtained.

Meneghini, R.↗