Search NASA⌕ Search

SEARCH · Search NASA

Results for “linear estimation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sound Speed as a Candidate for Internal Temperature Monitoring During Solid Phase Processing of Materials

Internal temperature is an important parameter for understanding the solid phase processing (SPP) of materials and improving feedback control of these processes. Friction stir processes, shear assisted processing and extrusion (ShAPE ™ ), and ultrahigh velocity (UHV) cold spray are examples of such processes. Simple thermal models based on temperatures measured at the boundary of the deforming body cannot capture the dynamic nature of temperature generation within the deforming solid. One possibly way of understanding internal temperature is by measuring sound speed, which varies as a function of temperature for materials and directing ultrasonic wave propagation through selected material volumes of interest. In this project, longitudinal wave speed is estimated for aluminum 6061. Piezoelectric materials bonded to a specimen provided data from which longitudinal wave speed was estimated. A discussion evaluated the linear relationship of wave speed versus temperature and postulated how wave speed measurements could be used to estimate the internal temperature of selected material volumes for feedback during SPP of materials. Instrumentation, data and analysis, and a discussion are reviewed.

36 MATERIALS SCIENCE↗
NASA NTRS2009

Estimating Volume, Biomass, and Carbon in Hedmark County, Norway Using a Profiling LiDAR

A profiling airborne LiDAR is used to estimate the forest resources of Hedmark County, Norway, a 27390 square kilometer area in southeastern Norway on the Swedish border. One hundred five profiling flight lines totaling 9166 km were flown over the entire county; east-west. The lines, spaced 3 km apart north-south, duplicate the systematic pattern of the Norwegian Forest Inventory (NFI) ground plot arrangement, enabling the profiler to transit 1290 circular, 250 square meter fixed-area NFI ground plots while collecting the systematic LiDAR sample. Seven hundred sixty-three plots of the 1290 plots were overflown within 17.8 m of plot center. Laser measurements of canopy height and crown density are extracted along fixed-length, 17.8 m segments closest to the center of the ground plot and related to basal area, timber volume and above- and belowground dry biomass. Linear, nonstratified equations that estimate ground-measured total aboveground dry biomass report an R(sup 2) = 0.63, with an regression RMSE = 35.2 t/ha. Nonstratified model results for the other biomass components, volume, and basal area are similar, with R(sup 2) values for all models ranging from 0.58 (belowground biomass, RMSE = 8.6 t/ha) to 0.63. Consistently, the most useful single profiling LiDAR variable is quadratic mean canopy height, h (sup bar)(sub qa). Two-variable models typically include h (sup bar)(sub qa) or mean canopy height, h(sup bar)(sub a), with a canopy density or a canopy height standard deviation measure. Stratification by productivity class did not improve the nonstratified models, nor did stratification by pine/spruce/hardwood. County-wide profiling LiDAR estimates are reported, by land cover type, and compared to NFI estimates.

Nelson, Ross↗
NASA NTRS2012

Anomaly Detection in Test Equipment via Sliding Mode Observers

Nonlinear observers were originally developed based on the ideas of variable structure control, and for the purpose of detecting disturbances in complex systems. In this anomaly detection application, these observers were designed for estimating the distributed state of fluid flow in a pipe described by a class of advection equations. The observer algorithm uses collected data in a piping system to estimate the distributed system state (pressure and velocity along a pipe containing liquid gas propellant flow) using only boundary measurements. These estimates are then used to further estimate and localize possible anomalies such as leaks or foreign objects, and instrumentation metering problems such as incorrect flow meter orifice plate size. The observer algorithm has the following parts: a mathematical model of the fluid flow, observer control algorithm, and an anomaly identification algorithm. The main functional operation of the algorithm is in creating the sliding mode in the observer system implemented as software. Once the sliding mode starts in the system, the equivalent value of the discontinuous function in sliding mode can be obtained by filtering out the high-frequency chattering component. In control theory, "observers" are dynamic algorithms for the online estimation of the current state of a dynamic system by measurements of an output of the system. Classical linear observers can provide optimal estimates of a system state in case of uncertainty modeled by white noise. For nonlinear cases, the theory of nonlinear observers has been developed and its success is mainly due to the sliding mode approach. Using the mathematical theory of variable structure systems with sliding modes, the observer algorithm is designed in such a way that it steers the output of the model to the output of the system obtained via a variety of sensors, in spite of possible mismatches between the assumed model and actual system. The unique properties of sliding mode control allow not only control of the model internal states to the states of the real-life system, but also identification of the disturbance or anomaly that may occur.

Solano, Wanda M.↗
NASA NTRS1999

Integration of a Decentralized Linear-Quadratic-Gaussian Control into GSFC's Universal 3-D Autonomous Formation Flying Algorithm

A decentralized control is investigated for applicability to the autonomous formation flying control algorithm developed by GSFC for the New Millenium Program Earth Observer-1 (EO-1) mission. This decentralized framework has the following characteristics: The approach is non-hierarchical, and coordination by a central supervisor is not required; Detected failures degrade the system performance gracefully; Each node in the decentralized network processes only its own measurement data, in parallel with the other nodes; Although the total computational burden over the entire network is greater than it would be for a single, centralized controller, fewer computations are required locally at each node; Requirements for data transmission between nodes are limited to only the dimension of the control vector, at the cost of maintaining a local additional data vector. The data vector compresses all past measurement history from all the nodes into a single vector of the dimension of the state; and The approach is optimal with respect to standard cost functions. The current approach is valid for linear time-invariant systems only. Similar to the GSFC formation flying algorithm, the extension to linear LQG time-varying systems requires that each node propagate its filter covariance forward (navigation) and controller Riccati matrix backward (guidance) at each time step. Extension of the GSFC algorithm to non-linear systems can also be accomplished via linearization about a reference trajectory in the standard fashion, or linearization about the current state estimate as with the extended Kalman filter. To investigate the feasibility of the decentralized integration with the GSFC algorithm, an existing centralized LQG design for a single spacecraft orbit control problem is adapted to the decentralized framework while using the GSFC algorithm's state transition matrices and framework. The existing GSFC design uses both reference trajectories of each spacecraft in formation and by appropriate choice of coordinates and simplified measurement modeling is formulated as a linear time-invariant system. Results for improvements to the GSFC algorithm and a multiple satellite formation will be addressed. The goal of this investigation is to progressively relax the assumptions that result in linear time-invariance, ultimately to the point of linearization of the non-linear dynamics about the current state estimate as in the extended Kalman filter. An assessment will then be made about the feasibility of the decentralized approach to the realistic formation flying application of the EO-1/Landsat 7 formation flying experiment.

Folta, David C.↗
DOE OSTI2026

LandCast Mosaic: Reconstructing Global Population Distributions, 1975-2025

LandCast Mosaic (LCM) provides a global, high-resolution gridded population dataset spanning 1975–2025, representing annual, scenario-consistent estimates of daytime, nighttime, and ambient population distributions. LCM builds on the 2025 LandScan Mosaic (LSM) population data by backcasting to earlier years using historical changes in built-surface area derived from the Global Human Settlement Layer (GHSL) and authoritative population counts from international datasets. The workflow scales 2025 building-informed gridded population estimates according to observed changes in built surface, applies linear interpolation for intermediate years, and normalizes estimates to match administrative- and country-level totals. The resulting dataset offers consistent, globally gridded population estimates over fifty years, suitable for temporal analyses of population dynamics, disaster risk modeling, and urban planning applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Intrinsic frequency spectra of short gravity-capillary waves obtained from temporal measurements of wave height on a lake

Intrinsic frequency spectra of water waves in the range of 6-17 Hz were obtained as a function of both wind speed and wind stress from point measurements of wave height. In a lake with a limited fetch, there are two types of surface motions causing Doppler shift in the frequencies of short waves: orbital velocity of long waves and surface wind drift. The former was estimated from long-wave amplitude by using a linear wave theory. The error in this estimate is of the order of the long-wave slope, and for this work it is typically 10 percent. The latter was approximated by the friction velocity. The friction velocity could be either taken as 3 percent of the mean wind speed measured at a height of 10 m or obtained from direct measurements of the wind stress. The surface drift velocities obtained by these two approaches were found to be in close agreement. Doppler frequency shift can be corrected in either the frequency or the equivalent spatial domain. The two techniques were found to produce comparable results. Experimental results showed that the spectral energy of short waves rapidly increased in response to increasing winds and jumped up by an order of magnitude when wave breaking occurred.

Atakturk, S. S.↗
NASA NTRS1983

The use of linear feature detection to investigate thematic mapper data performance and processing

The geometric and radiometric characteristics of thematic mapper data through analysis of linear features in the data are investigated. The particular aspects considered are: (1) thematic mapper ground IFOV; (2) radiometric contrast between linear features and background; (3) precision of system geometric correction; (4) band-to-band registration; and (5) potential utility of TM data for linear feature detection especially as compared to MSS data. It is shown that TM data may be used to estimate TM pixel size and to illustrate band-band mis-registration. Further, the geometry and radiometry of the data are sufficiently precise to allow accurate estimation of the widths of linear features. In optimum conditions features one quarter of a pixel in width may be accurately measured. These results have considerable potential for applications for hydrological and topographic mapping.

Gurney, C. M.↗
DOE OSTI2020

Application of Generalized Standard Addition Method and Ultraviolet Spectroscopy to Quantify Electrolytic Depolymerization of Lignin

Industrial lignin waste is an important byproduct of bio-refineries and the paper industry. Depolymerization of this industrial lignin could generate useful aromatic compounds. This group has focused on electrolytic decomposition of biorefinery lignin. To quantify electrolytic decomposition of the lignin in a highly caustic solution, ultraviolet (UV) spectroscopy provides a useful probe. The conversion of the neat lignin to the oxidized products achieved by the electrolytic reactor may be measured by quantifying the amount of unreacted neat lignin that remains in the effluent. Because the properties of electrolytic decomposition products are largely unknown, a useful approach to quantify decomposition of the neat lignin is to use a multivariate calibration method referred to as the generalized standard addition method (GSAM). In this approach, the electrolytic decomposition products represent a background interference and the neat lignin that remains can be quantified. Furthermore, this approach allows the conversion of the neat lignin to be calculated in a solution that is a complex mixture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

An optical-input Maximum Likelihood Estimation feedback system demonstrated on tokamak horizontal equilibrium control

A readily parallelized Maximum Likelihood Estimation (MLE) algorithm with linear computational complexity is demonstrated in real time using only measurements from an extreme ultraviolet (EUV) diagnostic to control the horizontal position of a tokamak plasma. A set of trial emissivity profiles are parameterized by the control quantity of interest (R m ), and the MLE is identified from the profile which minimizes the signal reconstruction residual. The algorithm depends on an empirically determined likelihood function with exponential form. EUV emission (λ ≈ 15eV-1keV) is captured in a poloidal plane by four 16-channel AXUV diodes mounted at different poloidal angles with radial and angular resolution sufficient to discern plasma equilibrium evolution in HBT-EP. Calculations of the plasma major radius by the system are consistent within diagnostic uncertainty for the majority of the discharge with those of: a weighted average of vertical soft X-ray or EUV chords, magnetic sensors, and an equilibrium reconstruction. The feedback system corrects for a horizontal displacement of the major radius equal to 20% of the plasma minor radius by adjusting the vertical field produced from 40 in-vessel control coils in real time. The MLE calculation is performed on a GPU in a 15 μs cycle, with similar performance in this application to a simple weighted average of vertical chords. Finally, results demonstrate horizontal position control using magnetic actuators and an optical observer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Techno-economic analysis and life cycle assessment for the catalytic hydrogenolysis and hydrocracking of polyethylene

Catalytic hydrogenolysis and hydrocracking are promising technologies for the conversion of polyolefin waste into hydrocarbons. Here, to explore the economic and environmental viability of these approaches, we conducted techno-economic analysis and life cycle assessment of polyethylene hydrogenolysis and hydrocracking processes that produce fuel-range products or olefins, respectively. Relative to primary production, the minimum selling price (MSP) of alkanes for linear-chain naphtha was estimated to be 1.8-fold higher, whereas branched-chain naphtha and propylene were shown to be cost competitive. Environmental impacts showed similar trends across scenarios, with propylene production by hydrocracking exhibiting greenhouse gas emissions comparable with conventional propylene due to relatively low hydrogen demand and high yield. Together, these results suggest that innovations in catalysis and reaction engineering will be required to make viable products that are scale matched with today's plastics, such as light olefins for closed-loop recycling.

09 BIOMASS FUELS↗
DOE OSTI2023

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13 C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Scaling of Transition State Vibrational Frequencies and Application of d -Band Theory to the Brønsted–Evans–Polanyi Relationship on Surfaces

Semiempirical energy relations provide a means of estimating thermodynamic properties. Specifically, linear scaling relationships (LSRs) and Brønsted–Evans–Polanyi (BEP) relationships correlate adsorption energies between adsorbates across surfaces and reaction energies with activation barriers, respectively. Although vibrational scaling relations (VSRs) exist between adsorbates at identical sites, scaling between vibrational frequencies of adsorbed local minima and transition states is lacking. Here, we present density functional theory calculations for AH X (A = C, N, O) diffusions on transition metal surfaces and reveal linear scaling between frequencies of local minima and the transition state between those minima. Using d-band theory and linear muffin tin orbital theory (LMTO), we derive the slopes of these transition state vibrational scaling relations (TSVSRs) and, in so doing, provide a rigorous theory extending the original BEP relations developed for solution chemistry to surface chemistry. Furthermore, with a single reference DFT calculation, we predict the slopes and quantify uncertainty in the predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Measuring neutrino mass imprinted on the anisotropic galaxy clustering

The anisotropic galaxy clustering of large scale structure observed by the Baryon Oscillation Spectroscopic Survey Data Release 11 is analyzed to probe the sum of neutrino masses in the small m {sub ν} ∼< 1 eV limit in which the early broadband shape determined before the last scattering surface is immune from the variation of m {sub ν}. The signature of m {sub ν} is imprinted on the altered shape of the power spectrum at later epoch, which provides an opportunity to access the non-trivial m {sub ν} through the measured anisotropic correlation function in redshift space (hereafter RSD instead of Redshift Space Distortion). The non-linear RSD corrections with massive neutrinos in the quasi linear regime are approximately estimated using one-loop order terms. We suggest an approach to probe m {sub ν} simultaneously with all other distance measures and coherent growth functions, exploiting this deformation of the early broadband shape of the spectrum at later epoch. If the origin of cosmic acceleration is unknown, m {sub ν} is poorly determined after marginalizing over all other observables. However, we find that the measured distances and coherent growth functions are minimally affected by the presence of mild neutrino mass. Although the standard model of cosmic acceleration is assumed to be the cosmological constant, the constraint on m {sub ν} is little improved. Interestingly, the measured Cosmic Microwave Background (hereafter CMB) distance to the last scattering surface sharply slices the degeneracy between the matter content and m {sub ν}, and the m {sub ν} is observed to be m {sub ν} = 0.19{sup +0.28}{sub −0.17} eV which is different from massless neutrino at 68% confidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Eddy Current Loss Model Unifying the Effects of Reaction Field and Non-Homogeneous 3-D Magnetic Field

In this article, a new analytical method is proposed to estimate eddy currents inside linear conductive materials. The novel closed-form formulation takes into account the effects of both conductor reaction field that dominates at high frequencies as well as the spatially non-homogeneous nature of the magnetic field penetrating the material. Although the model is suitable for most kinds of permanent magnet machines, it is particularly useful for Surface-mounted Permanent Magnet (SPM) machines where both of these phenomena are prominent. The numerical implementation of the proposed model, which consists of a combination of the method of images and 4-D Fourier transform, is presented. The model is then validated against 2-D and 3-D finite element models (FEMs) for a simple magnetic circuit, showing good agreement. Finally, the eddy current magnet loss in an SPM synchronous machine is evaluated and results are discussed.

Sahu, Raj↗
DOE OSTI2018

A Fast Scalable Quasi-Static Time Series Analysis Method for PV Impact Studies Using Linear Sensitivity Model

Understanding the impact of distributed photovoltaic (PV) resources on various elements of the distribution feeder is imperative for their cost effective integration. A year-long quasi-static time series (QSTS) simulation at 1-second granularity is often necessary to fully study these impacts. However, the significant computational burden associated with running QSTS simulations is a major challenge to their adoption. In this paper, we propose a fast scalable QSTS simulation algorithm that is based on a linear sensitivity model for estimating voltage-related PV impact metrics of a three-phase unbalanced, nonradial distribution system with various discrete step control elements including tap changing transformers and capacitor banks. Here, the algorithm relies on computing voltage sensitivities while taking into account all the effects of discrete controllable elements in the circuit. Consequently, the proposed sensitivity model can accurately estimate the state of controllers at each time step and the number of control actions throughout the year. For the test case of a real distribution feeder with 2969 buses (5469 nodes), 6 load/PV time series power profiles, and 9 voltage regulating elements including controller delays, the proposed algorithm demonstrates a dramatic time reduction, more than 180 times faster than traditional QSTS techniques.

14 SOLAR ENERGY↗
DOE OSTI2026

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗
DOE OSTI2020

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) [SWR-20-115]

GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) can be used to estimate behind the meter (BTM) solar generation from limited datasets. Using distributed sets of diverse solar sites, but with close spatial proximity, and/or limited historical PV generation information can be used to generate of solar profiles. This is useful for applications where partial solar generation data is available, and on-site irradiance data is not available. GET-Solar calculates PV technical data parameters and calculates output by modeling shading and cloud cover impacts. Clear sky irradiance profiles are used to calculate base generation profiles on which the local shading and cloud cover layers are added. In order to arrive at clear sky generation data, PV mounting information like panel tilt and and angle is needed. For cases where PV mounting information is missing, panel tilt and azimuth angle can be estimated using a non-linear optimization algorithm. GET-Solar can also be used for forecasting applications where historical PV data is available to estimate local shading at various solar positions. This overall framework can be used for estimation of solar parameters, and assisting in analyzing and modeling diverse sets of DER where solar generation is also present in utility meter data. GET-Solar has been developed in Python and uses the Pyomo optimization language.

Abraham, Sherin Ann↗