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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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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source

Radar signal processing applications frequently require an estimate of the Doppler centroid of a received signal. The Doppler centroid estimate is required for synthetic aperture radar (SAR) processing. It is also required for some applications involving target motion estimation and antenna pointing direction estimation. In some cases, the Doppler centroid can be accurately estimated based on available information regarding the terrain topography, the relative motion between the sensor and the terrain, and the antenna pointing direction. Often, the accuracy of the Doppler centroid estimate can be improved by analyzing the characteristics of the received SAR signal. This kind of signal processing is also referred to as clutterlock processing. A Doppler centroid estimation (DCE) algorithm is described which contains a linear estimator optimized for the type of terrain surface that can be modeled by a quasi-homogeneous source (QHS). Information on the following topics is presented: (1) an introduction to the theory of Doppler centroid estimation; (2) analysis of the performance characteristics of previously reported DCE algorithms; (3) comparison of these analysis results with experimental results; (4) a description and performance analysis of a Doppler centroid estimator which is optimized for a QHS; and (5) comparison of the performance of the optimal QHS Doppler centroid estimator with that of previously reported methods.

Jin, Michael Y.↗
NASA NTRS2001

Optimal firing rate estimation

We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.

NASA Discipline Neuroscience↗
NASA NTRS1994

MME-based attitude dynamics identification and estimation for SAMPEX

A method is described for obtaining optimal attitude estimation algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. Problems arise since typical attitude estimation is accomplished by filtering measurements of both attitude and attitude rates. Rates are nearly always sampled much more densely than are attitudes. Thus, the absence/loss of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is increased need for accurate models of the rotational dynamics. The proposed approach is based on the minimum model error (MME) optimal estimation strategy, which has been successfully applied to estimation of poorly modeled dynamic systems which are relatively sparsely and/or noisily measured. The MME estimates may be used to construct accurate models of the system dynamics (i.e. perform system model identification). Thus, an MME-based approach directly addresses the problems created by absence of attitude rate measurements.

Depena, Juan↗
NASA NTRS1980

Linear stochastic optimal control and estimation problem

Problem involves design of controls for linear time-invariant system disturbed by white noise. Solution is Kalman filter coupled through set of optimal regulator gains to produce desired control signal. Key to solution is solving matrix Riccati differential equation. LSOCE effectively solves problem for wide range of practical applications. Program is written in FORTRAN IV for batch execution and has been implemented on IBM 360.

Geyser, L. C.↗
NASA NTRS2005

Automatic Aircraft Structural Topology Generation for Multidisciplinary Optimization and Weight Estimation

An approach is proposed for the application of rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process. This should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. A demonstration of this process is shown for two sample aircraft wing designs.

Sensmeier, Mark D.↗
NASA NTRS2006

Rapid Assessment of Aircraft Structural Topologies for Multidisciplinary Optimization and Weight Estimation

Algorithms for rapid generation of moderate-fidelity structural finite element models of air vehicle structures to allow more accurate weight estimation earlier in the vehicle design process have been developed. Application of these algorithms should help to rapidly assess many structural layouts before the start of the preliminary design phase and eliminate weight penalties imposed when actual structure weights exceed those estimated during conceptual design. By defining the structural topology in a fully parametric manner, the structure can be mapped to arbitrary vehicle configurations being considered during conceptual design optimization. Recent enhancements to this approach include the porting of the algorithms to a platform-independent software language Python, and modifications to specifically consider morphing aircraft-type configurations. Two sample cases which illustrate these recent developments are presented.

Samareh, Jamshid A.↗
NASA NTRS1986

Optimal Doppler centroid estimation for SAR data from a quasi-homogeneous source

This correspondence briefly describes two Doppler centroid estimation (DCE) algorithms, provides a performance summary for these algorithms, and presents the experimental results. These algorithms include that of Li et al. (1985) and a newly developed one that is optimized for quasi-homogeneous sources. The performance enhancement achieved by the optimal DCE algorithm is clearly demonstrated by the experimental results.

Jin, M. Y.↗
NASA NTRS1992

Runway exit designs for capacity improvement demonstrations. Phase 2: Computer model development

The development is described of a computer simulation/optimization model to: (1) estimate the optimal locations of existing and proposed runway turnoffs; and (2) estimate the geometric design requirements associated with newly developed high speed turnoffs. The model described, named REDIM 2.0, represents a stand alone application to be used by airport planners, designers, and researchers alike to estimate optimal turnoff locations. The main procedures are described in detail which are implemented in the software package and possible applications are illustrated when using 6 major runway scenarios. The main output of the computer program is the estimation of the weighted average runway occupancy time for a user defined aircraft population. Also, the location and geometric characteristics of each turnoff are provided to the user.

Trani, A. A.↗
DOE OSTI2023

Optimizing cloud motion estimation on the edge with phase correlation and optical flow

Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In this study, we investigate the performance and the stability of the blockwise PC method by changing the block size, the frame interval, and combinations of red, green, and blue (RGB) channels from the total sky imager (TSI) at the United States Atmospheric Radiation Measurement user facility's Southern Great Plains site. We find that shorter frame intervals, followed by larger block sizes, are responsible for stable estimates of the CMV, as suggested by the higher autocorrelations. The choice of RGB channels has a limited effect on the quality of CMVs, and the red and the grayscale images are marginally more reliable than the other combinations during rapidly evolving low-level clouds. The stability of CMVs was tested at different image resolutions with an implementation of the optimized algorithm on the Sage cyberinfrastructure test bed. We find that doubling the frame rate outperforms quadrupling the image resolution in achieving CMV stability. The correlations of CMVs with the wind data are significant in the range of 0.38–0.59 with a 95 % confidence interval, despite the uncertainties and limitations of both datasets. A comparison of the PC method with constructed data and the optical flow method suggests that the post-processing of the vector field has a significant effect on the quality of the CMV. The raindrop-contaminated images can be identified by the rotation of the TSI mirror in the motion field. The results of this study are critical to optimizing algorithms for edge-computing sensor systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Mars Optimal Aerobrake Maneuver Estimation

Mars science satellites often perform orbit changes to obtain different measurements, ground tracks or relay operations. Large reductions in semi-major axis and eccentricity can be done efficiently using the atmospheric drag, a.k.a aerobrake. Aerobraking is one of the most challenging planetary orbit maneuvers in terms of planning and operations. The most important consideration for aerobraking is maintaining the spacecraft's periapsis within an allocated atmospheric density corridor, which is accomplished by raising or lowering periapsis through one or a series of very small and short maneuvers. These maneuvers must be performed as efficiently as possible due to propellant constraints. Work herein details a fast and accurate method to calculate the required impulsive velocity changes in the orbit to guarantee that the spacecraft remains in a prescribed density corridor. The method makes use of the orbit's state transition matrix to map the solution space around the reference orbit. It evaluates the most efficient maneuver epochs to target a given periapsis change with a linear optimal control for single or multiple maneuvers. A fast calculation of the maneuver allows for a more comprehensive evaluation of the trade space, and the selected maneuver may be re-targeted later with a higher- fidelity model. Comparisons against fully propagated models and direct method optimizations demonstrate the new method's performance.

Sarli, Bruno V.↗
DOE OSTI2022

Optimized Quantum Phase Estimation for Simulating Electronic States in Various Energy Regimes

While quantum algorithms for simulation exhibit better asymptotic scaling than their classical counterparts, they currently cannot be implemented on real-world devices. Instead, chemists and computer scientists rely on costly classical simulations of these quantum algorithms. In particular, the quantum phase estimation (QPE) algorithm is among several approaches that have attracted much attention in recent years for its genuine quantum character. However, it is memory-intensive to simulate and intractable for moderate system sizes. Herein, this paper discusses the performance and applicability of QPESIM, a new simulation of the QPE algorithm designed to take advantage of modest computational resources. In particular, we demonstrate the versatility of QPESIM in simulating various electronic states by examining the ground and core-level states of H 2 O. For these states, we also discuss the effect of the active-space size on the quality of the calculated energies. For the high-energy core-level states, we demonstrate that new QPE simulations for active spaces defined by 15 active orbitals significantly reduce the errors in core-level excitation energies compared to earlier QPE simulations using smaller active spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Foreground-Immune Cosmic Microwave Background Lensing with Shear-Only Reconstruction

Cosmic microwave background (CMB) lensing from current and upcoming wide-field CMB experiments such as AdvACT, SPT-3G and Simons Observatory relies heavily on temperature (versus polarization). In this regime, foreground contamination to the temperature map produces significant lensing biases, which cannot be fully controlled by multifrequency component separation, masking, or bias hardening. Here in this Letter, we split the standard CMB lensing quadratic estimator into a new set of optimal “multipole” estimators. On large scales, these multipole estimators reduce to the known magnification and shear estimators, and a new shear B-mode estimator. We leverage the different symmetries of the lensed CMB and extragalactic foregrounds to argue that the shear-only estimator should be approximately immune to extragalactic foregrounds. We build a new method to compute, separately and without noise, the primary, secondary, and trispectrum biases to CMB lensing from foreground simulations. Using this method, we demonstrate that the shear estimator is, indeed, insensitive to extragalactic foregrounds, even when applied to a single-frequency temperature map contaminated with cosmic infrared background, thermal Sunyaev-Zel’dovich, kinematic Sunyaev-Zel’dovich, and radio point sources. This dramatic reduction in foreground biases allows us to include higher temperature multipoles than with the standard quadratic estimator, thus, increasing the total lensing signal-to-noise ratio beyond the quadratic estimator. In addition, magnification-only and shear B-mode estimators provide useful diagnostics for potential residuals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Optimal Methods for Estimating Cactus Pear Biomass Using Cladode Dimensions of Morphologically Diverse Accessions

Current allometric methods for photosynthetic-stem (cladode) plants, such as cactus pear (Opuntia spp.), require refinement to be used in field settings in which diverse accessions are grown. We analysed cladode dimensional data using 14 accessions representing four species and two hybrids to quantify statistically significant morphological differences among accessions and derived cross-accession models to approximate cladode fresh weight. A Box model using cladode dimensions (e.g., length, width, thickness and diameter) and factorial combinations of these measures (e.g., length*width*thickness*diameter vs. fresh weight) resulted in the highest coefficient of determination (R 2 = 0.95 general fit) across all accessions for estimating fresh weight along with parsimony estimates using the Schwarz–Bayes Criterion (SBC), which assesses the most consistent performance on individual accessions. A Fitting-box modelling approach used the measured cladode area captured using ImageJ (R 2 = 0.93 general fit). Lastly, an Elliptical model used an elliptical approximation for the measured area and performed well over all accessions (R 2 = 0.94 general fit) while avoiding extensive manual measurements. These models meet or exceed the performance of previously published approaches when applied across morphologically diverse accessions, providing efficient tools for nondestructive estimation of cactus pear biomass under the conditions tested.

Opuntia↗
DOE OSTI2025

EVI-EnSitePy (Electric Vehicle Infrastructure – Energy Estimation and Site Optimization Tool in Python) [EVI-X Modeling Suite] [SWR-25-07]

EVI-EnSitePy is a comprehensive agent-based tool designed for the analysis and design of high-power charging sites, encompassing a wide array of site agents including Electric Vehicles (EVs), chargers, energy storage units (ESS), renewable energy resources (DER), and loads. This versatile tool offers diverse functionalities and a modular modeling approach, allowing detailed configuration of agents based on power ratings, port numbers, energy capacities, demand requirements, charger interfaces, and flexibility to customize the tool for project specific goals. By simulating agent interactions and employing various metrics, EVI-EnSitePy enables the assessment of site performance, exploration of energy management systems (EMS), and implementation of innovative EV charging policies. Utilizing EV charge schedules and arrival states, the tool performs thorough charging site simulations, with outputs consisting of agent and site-level power profiles and statistical metrics. Employing a tree graph structure, EVI-EnSitePy supports nested site structures and power distribution modeling. The tool's ability to generate charging schedules deterministically or via stochastic analysis further enhances its versatility. Through its features and capabilities, EVI-EnSitePy offers a powerful platform for informed decision-making in the realm of high-power charging site design and operation.

Jackson, Derek [National Renewable Energy Laborato↗
DOE OSTI2025

Optimal intrinsic alignment estimators in the presence of redshift-space distortions

We present estimators for quantifying intrinsic alignments in large spectroscopic surveys that efficiently capture line-of-sight (LOS) information while being relatively insensitive to redshift-space distortions (RSD). We demonstrate that changing the LOS integration range, pimax, as a function of transverse separation outperforms the conventional choice of a single pimax value. This is further improved by replacing the flat pimax cut with a LOS weighting based on shape projection and RSD. Although these estimators incorporate additional LOS information, they are projected correlations that exhibit signal-to-noise ratios comparable to 3D correlation functions, such as the IA quadrupole. Using simulations from Abacus Summit, we evaluate these estimators and provide recommended pimax values and weights for projected separations of 1 - 100 Mpc/h. These will improve measurements of intrinsic alignments in large cosmological surveys and the constraints they provide for both weak lensing and direct cosmological applications.

cosmology↗
NASA NTRS1974

Model optimization using statistical estimation

Program revises initial or prior estimate of stiffness and mass parameters to parameters yielding frequency and mode characteristics in agreement with test data. Variances are also calculated and consequently define uncertainties of final estimates.

Collins, J. D.↗