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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

A Comparison of Filter-based Approaches for Model-based Prognostics

Model-based prognostics approaches use domain knowledge about a system and its failure modes through the use of physics-based models. Model-based prognosis is generally divided into two sequential problems: a joint state-parameter estimation problem, in which, using the model, the health of a system or component is determined based on the observations; and a prediction problem, in which, using the model, the stateparameter distribution is simulated forward in time to compute end of life and remaining useful life. The first problem is typically solved through the use of a state observer, or filter. The choice of filter depends on the assumptions that may be made about the system, and on the desired algorithm performance. In this paper, we review three separate filters for the solution to the first problem: the Daum filter, an exact nonlinear filter; the unscented Kalman filter, which approximates nonlinearities through the use of a deterministic sampling method known as the unscented transform; and the particle filter, which approximates the state distribution using a finite set of discrete, weighted samples, called particles. Using a centrifugal pump as a case study, we conduct a number of simulation-based experiments investigating the performance of the different algorithms as applied to prognostics.

prognostics↗
NASA NTRS1990

Attitude determination error analysis - General model and specific application

This paper presents a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The discussion includes models for both batch least-squares and sequential estimators, a specific dynamic model for attitude determination error analysis of a three-axis stabilized spacecraft equipped with strapdown gyros, and the incorporation of general attitude sensor observations. An analyst using this approach to perform an error analysis chooses a subset of the spacecraft parameters to be 'solve-for' parameters, which are to be estimated, and another subset to be 'consider' parameters, which are assumed to have errors but not to be estimated. The result of the error analysis is an indication of overall uncertainties in the 'solve-for' parameters, as well as the contributions of the various error sources to these uncertainties, including those of errors in the a priori 'solve-for' estimates, of measurement noise, of dynamic noise (also known as process noise or plant noise), and of 'consider' parameter uncertainties. The analysis of attitude, star tracker alignment, and gyro bias uncertainties for the Gamma Ray Observatory spacecraft provide a specific example of the use of a general-purpose software package incorporating these models.

Markley, F. Landis↗
NASA NTRS1999

High Temperature Superconductor/Semiconductor Hybrid Microwave Devices and Circuits

Contents include following: film deposition technique; laser ablation; magnetron sputtering; sequential evaporation; microwave substrates; film characterization at microwave frequencies; complex conductivity; magnetic penetration depth; surface impedance; planar single-mode filters; small antennas; antenna arrays phase noise; tunable oscillations; hybrid superconductor/semiconductor receiver front ends; and noise modeling.

Romanofsky, Robert R.↗
NASA NTRS2013

Assessing the Temperature Dependence of Narrow-Band Raman Water Vapor Lidar Measurements: A Practical Approach

Narrow-band detection of the Raman water vapor spectrum using the lidar technique introduces a concern over the temperature dependence of the Raman spectrum. Various groups have addressed this issue either by trying to minimize the temperature dependence to the point where it can be ignored or by correcting for whatever degree of temperature dependence exists. The traditional technique for performing either of these entails accurately measuring both the laser output wavelength and the water vapor spectral passband with combined uncertainty of approximately 0.01 nm. However, uncertainty in interference filter center wavelengths and laser output wavelengths can be this large or larger. These combined uncertainties translate into uncertainties in the magnitude of the temperature dependence of the Raman lidar water vapor measurement of 3% or more. We present here an alternate approach for accurately determining the temperature dependence of the Raman lidar water vapor measurement. This alternate approach entails acquiring sequential atmospheric profiles using the lidar while scanning the channel passband across portions of the Raman water vapor Q-branch. This scanning is accomplished either by tilt-tuning an interference filter or by scanning the output of a spectrometer. Through this process a peak in the transmitted intensity can be discerned in a manner that defines the spectral location of the channel passband with respect to the laser output wavelength to much higher accuracy than that achieved with standard laboratory techniques. Given the peak of the water vapor signal intensity curve, determined using the techniques described here, and an approximate knowledge of atmospheric temperature, the temperature dependence of a given Raman lidar profile can be determined with accuracy of 0.5% or better. A Mathematica notebook that demonstrates the calculations used here is available from the lead author.

Raman lidar↗
NASA NTRS1990

An approach for targeting landers and penetrators using orbital optical navigation

Onboard orbital optical navigation data is analyzed with the purpose of generating topographic maps for selecting a landing site. It is suggested that a near-real time orbit-determination process be used for solving a large set of parameters including the spacecraft orbit and primary-body gravity field, the rotational properties of the planetary body, the coordinates of surface features, and the camera-pointing and orientation angles of each picture. A batch-sequential formulation of the standard least-squares problem is employed, along with backward smoothing and a square-root formation filter. An experiment in which over 100 images of Phobos are processed to estimate about 2000 parameters is presented, with emphasis on coordinate systems, transforming points on the reference surface to images in the picture, parameter estimation, and cartographic accuracy.

Wang, Tseng-Chan↗
NASA NTRS2006

Nonlinear consider covariance analysis using a sigma-point filter formulation

The research reported here extends the mathematical formulation of nonlinear, sigma-point estimators to enable consider covariance analysis for dynamical systems. This paper presents a novel sigma-point consider filter algorithm, for consider-parameterized nonlinear estimation, following the unscented Kalman filter (UKF) variation on the sigma-point filter formulation, which requires no partial derivatives of dynamics models or measurement models with respect to the parameter list. It is shown that, consistent with the attributes of sigma-point estimators, a consider-parameterized sigma-point estimator can be developed entirely without requiring the derivation of any partial-derivative matrices related to the dynamical system, the measurements, or the considered parameters, which appears to be an advantage over the formulation of a linear-theory sequential consider estimator. It is also demonstrated that a consider covariance analysis performed with this 'partial-derivative-free' formulation yields equivalent results to the linear-theory consider filter, for purely linear problems.

covariance↗
DOE OSTI2026

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗
NASA NTRS1978

Shuttle GPS R/PA evaluation analysis and performance tradeoff study

Primary responsibility was understanding and analyzing the various GPS receiver functions as they relate to the shuttle environment. These receiver functions included acquisition properties of the sequential detector, acquisition and tracking properties of the various receiver phase locked loops, and the techniques of sequential receiver operation. In addition to these areas, support was provided in the areas of oscillator stability requirements, antenna management, and navigation filter requirements, including preposition aiding.

Booth, R. W. D.↗
NASA NTRS1973

Lidar Observations of Raman Scattering from S02 in a Power Plant Stack Plume

LIDAR techniques have been successfully applied to the detection of the Raman backscatter from S02 in the plume of a 200 megawatt coal-burning electrical- generating plant from a distance of 210 meters. The LIDAR system used consists of a 61-centimeter-diameter, f /4 Newtonian telescope and a 1.0-1.5-joules per pulse, 1-pulse-per-second ruby laser. Narrow band interference filters are used to select the 7546-angstrom v (sub 1) vibrational line of S02. The signal from a photomultiplier tube was sequentially applied to each 254-nanosecond-wide channel of a 15-cihannel photon counting system, resulting in a direct correlation between channel number and range increment. Photon counts were accumulated from the backscatter of a number of laser pulses (typically 50 or 100), and the accumulated counts per channel printed on paper tape. One sequence of measurements was made during a two-hour period while the plant electrical output was being reduced by approximately 50 percent. Although the Raman system had not been quantitatively calibrated, the LIDAR data correlated well with the varying plant electrical output. N2 scattering observations were also made and an approximate quantitative S02 concentration obtained by ratioing the S02 data to N2 data. This ratio compared well to the in-situ measurements made during the same period by Environmental Protection Agency sampling instruments.

Brumfield, M. L.↗
NASA NTRS2009

Estimating Relative Positions of Outer-Space Structures

A computer program estimates the relative position and orientation of two structures from measurements, made by use of electronic cameras and laser range finders on one structure, of distances and angular positions of fiducial objects on the other structure. The program was written specifically for use in determining errors in the alignment of large structures deployed in outer space from a space shuttle. The program is based partly on equations for transformations among the various coordinate systems involved in the measurements and on equations that account for errors in the transformation operators. It computes a least-squares estimate of the relative position and orientation. Sequential least-squares estimates, acquired at a measurement rate of 4 Hz, are averaged by passing them through a fourth-order Butterworth filter. The program is executed in a computer aboard the space shuttle, and its position and orientation estimates are displayed to astronauts on a graphical user interface.

Balian, Harry↗
NASA NTRS1988

Rapid code acquisition algorithms employing PN matched filters

The performance of four algorithms using pseudonoise matched filters (PNMFs), for direct-sequence spread-spectrum systems, is analyzed. They are: parallel search with fix dwell detector (PL-FDD), parallel search with sequential detector (PL-SD), parallel-serial search with fix dwell detector (PS-FDD), and parallel-serial search with sequential detector (PS-SD). The operation characteristic for each detector and the mean acquisition time for each algorithm are derived. All the algorithms are studied in conjunction with the noncoherent integration technique, which enables the system to operate in the presence of data modulation. Several previous proposals using PNMF are seen as special cases of the present algorithms.

Su, Yu T.↗
NASA NTRS1983

The function and response of an improved stratospheric condensation nucleus counter

An improved condensation nucleus counter (CNC) for use in the stratosphere is described. The University of Minnesota CNC (UMCNC) has a sequential saturator and condenser and uses n-butyl alcohol as the working fluid. The use of a coaxial saturator flow, with aerosol in the center and filtered, alcohol-laden air around it, speeds the response of this instrument and improves its stability as pressure changes. The counting efficiency has been studied as a function of particle size and pressure. The UMCNC provides an accurate measure of submicron aerosol concentration as long as the number distribution is not dominated by sub-0.02 micron diameter aerosol. The response of the UMCNC is compared with that of other stratospheric condensation nucleus counters, and the results of a (near) comparison with a balloon-borne condensation nucleus counter are presented. The UMCNC has operated 14 times on a NASA U-2 aircraft at altitudes from 8 to 21.5 km.

Wilson, J. C.↗
NASA NTRS1991

Progress toward a 30 percent-efficient, monolithic, three-junction, two-terminal concentrator solar cell for space applications

Component efficiencies of 0.2/sq cm cells at approximately 100x AMO light concentration and 80 C temperatures are not at 15.3 percent for a 1.9 eV AlGaAs top cell, 9.9 percent for a 1.4 eV GaAs middle cell under a 1.9 eV AlGaAs filter, and 2.4 percent for a bottom 1.0 eV InGaAs cell under a GaAs substrate. The goal is to continue improvement in these performance levels and to sequentially grow these devices on a single substrate to give 30 percent efficient, monolithic, two-terminal, three-junction space concentrator cells. The broad objective is a 30 percent efficient monolithic two-terminal cell that can operate under 25 to 100x AMO light concentrations and at 75 to 100 C cell temperatures. Detailed modeling predicts that this requires three junctions. Two options are being pursued, and both use a 1.9 eV AlGaAs top junction and a 1.4 eV GaAs middle junction grown by a 1 atm OMVPE on a lattice matched substrate. Option 1 uses a low-doped GaAs substrate with a lattice mismatched 1.0 eV InGaAs cell formed on the back of the substrate. Option 2 uses a Ge substrate to which the AlGaAs and GaAs top junctions are lattice matched, with a bottom 0.7 eV Ge junction formed near the substrate interface with the GaAs growth. The projected efficiency contributions are near 16, 11, and 3 percent, respectively, from the top, middle, and bottom junctions.

Partain, L. D.↗
NASA NTRS2017

Comparison of EKF and UKF for Robotic Missions to Mars

The batched Kalman lter works well for a wide variety of orbit determination scenarios but requires linearized approximations to the underlying dynamical system. Furthermore, implementation depends on the computation of partial derivatives for all measurements and parameters used in the lter, a non-trivial task even when analytical derivations are possible. To address these limitations, many extensions and modi - cations to the linear Kalman lter have been proposed over the years since Kalman's initial publication. Our investigation examines two popular variants of the Kalman lter, namely the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF), within the context of spacecraft missions to Mars. The EKF relies on the same mathematical basis as the classic version of the lter, however it sequentially updates the linearization as the ltering process is conducted. In contrast, the UKF is built upon the unscented transform which samples the nearby solution space and numerically propagates perturbed trajectories as part of the update / estimation process. We assess the performance of the ltering algorithms under a variety of mission scenarios with the goal of establishing decision criteria for which implementation to use under di ering circumstances.

Ely, Todd↗
DOE OSTI2026

An Integrated Framework for Memory-Centric Analysis: From Trace Collection to Co-Design

The memory wall phenomenon—where advances in processor performance significantly outpace those in memory subsystems—poses a fundamental challenge for contemporary computing systems. In memory-bound applications, memory subsystem behavior dominates performance, yet existing analysis approaches present significant limitations: detailed microarchitectural simulators require days to weeks to simulate modest workloads; hardware performance counters provide only aggregate statistics that obscure temporal and spatial access patterns; and scaled simulation approaches face challenges in capturing certain behaviors that emerge at larger scales. These limitations reflect a processor-centric design philosophy increasingly misaligned with memory-bound workloads where detailed understanding of memory access patterns, cache hierarchy interactions, and contention is critical for effective optimization. This paper presents an integrated framework for memory-centric analysis that enables effective hardware-software co-design. We describe practical trace collection techniques, including hardware-assisted processor tracing with minimal overhead and portable software-based instrumentation with statistical sampling. We present multi-perspective analysis methods that examine memory behavior from temporal, sequential, spatial, and relational viewpoints, revealing distinct optimization opportunities invisible in aggregate metrics. We detail an architectural modeling framework that uses sampled traces with temporal interpolation and confidence-based filtering to evaluate cache and memory configurations. Evaluation on representative benchmarks demonstrates that this framework achieves practical accuracy (L2 cache errors of 2.64\%, confidence-filtered L3 errors of 9.92\%, bandwidth errors of 7.33\%) while providing substantial speedup (26.8×) over cycle-accurate simulation, enabling rapid design space exploration. We demonstrate how this integrated framework enables systematic identification of both hardware optimizations (memory controller tuning, bank partitioning, NUMA configuration) and software optimizations (data layout restructuring, prefetching strategies, memory-aware scheduling). Through this comprehensive treatment of the memory-centric analysis pipeline—from trace collection through architectural modeling to co-design application—we provide researchers and practitioners with practical techniques for addressing memory bottlenecks in contemporary computing systems.

Gajaria, Dhruv Mayur↗
NASA NTRS1978

An application of the square-root information filter to large scale linear interconnected systems

The paper considers the use of numerically stable square-root information filter (SRIF) algorithms to reduce the computation and storage requirements of a certain class of large-scale linear interconnected systems (multistation satellite tracking is examined as an example). The reductions are in comparison with conventional sequential covariance type formulations. To illustrate the SRIF algorithm: a 40 subsystem, 10 state problem, for example, has its storage requirements reduced by a full order of magnitude (from 84255 to 8100).

Bierman, G. J.↗
NASA NTRS1972

Spectral factorization in periodically time-varying systems and application to navigation problems.

Spectral factorization has been used previously to derive the steady-state solution of Kalman filtering equations without iteration for constant coefficient systems. The present work extends the spectral factorization algorithm to time-varying systems having periodic coefficient matrices for cases of both discrete and continuous systems. Time-consuming, expensive iterations of sequential covariance equations are not required to reach the final solution since this is an algebraic algorithm employing existing eigenvalue, eigenvector subroutines. The computer program incorporating the algorithm is suitable for sensitivity studies in formulating navigation and guidance strategies of low-thrust interplanetary missions. The determination of an optimum tracking pattern from an earth station is examined as an example.

Nishimura, T.↗