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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Future possibilities in objective analysis and data assimilation for atmospheric dynamics

The role that dynamics plays in estimating the state of the atmosphere from incomplete and noisy data is reviewed. Objective analysis represents an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and related sciences, namely, mesoscale meteorology, long range forecasting, and upper ocean dynamics. Possibilities offered by judicious data assimilation in understanding barotropic adjustment, a phenomenon that appears to play a crucial role in atmospheric behavior on the scale of weeks to months, and hence in long range forecasting are addressed.

Ghil, M.↗
NASA NTRS1986

Sequential estimation and satellite data assimilation in meteorology and oceanography

The central theme of this review article is the role that dynamics plays in estimating the state of the atmosphere and of the ocean from incomplete and noisy data. Objective analysis and inverse methods represent an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Four-dimensional data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric or oceanic model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and oceanic sciences, namely, mesoscale meteorology, medium and long-range forecasting, and upper-ocean dynamics.

Ghil, M.↗
NASA NTRS1989

An optimal recursive filter for the attitude determination of the Spacelab instrument pointing subsystem

The instrument pointing subsystem (IPS) is a three-axis stabilized platform developed to point various astronomical observation instruments aboard NASA's Shuttle. In order to compensate for system drifts and attitude errors, the IPS utilizes a linearized Kalman filter (LKF) with precomputed gains. Since the a priori gains are generated for an expected system configuration, any system variations result in a suboptimal estimation process. The performance of two real-time estimation filters is compared with that of the current LKF implementation. It is shown that a real-time estimation filter that reduces sensitivity to system variations and preflight computations is feasible.

West, Mark E.↗
NASA NTRS1985

Optimal frequency domain textural edge detection filter

An optimal frequency domain textural edge detection filter is developed and its performance evaluated. For the given model and filter bandwidth, the filter maximizes the amount of output image energy placed within a specified resolution interval centered on the textural edge. Filter derivation is based on relating textural edge detection to tonal edge detection via the complex low-pass equivalent representation of narrowband bandpass signals and systems. The filter is specified in terms of the prolate spheroidal wave functions translated in frequency. Performance is evaluated using the asymptotic approximation version of the filter. This evaluation demonstrates satisfactory filter performance for ideal and nonideal textures. In addition, the filter can be adjusted to detect textural edges in noisy images at the expense of edge resolution.

Townsend, J. K.↗
NASA NTRS1989

The soft x ray telescope for Solar-A

The Solar-A satellite being prepared by the Institute for Sapce and Astronautical Sciences (ISAS) in Japan is dedicated to high energy observations of solar flares. The Soft X Ray Telescope (SXT) is being prepared to provide filtered images in the 2 to 60 A interval. The flight model is now undergoing tests in the 1000 foot tunnel at MSFC. Launch will be in September 1991. Earlier resolution and efficiency tests on the grazing incidence mirror have established its performance in soft x rays. The one-piece, two mirror grazing incidence telescope is supported in a strain free mount separated from the focal plane assembly by a carbon-epoxy metering tube whose windings and filler are chosen to minimize thermal and hygroscopic effects. The CCD detector images both the x ray and the concentric visible light aspect telescope. Optical filters provide images at 4308 and 4700 A. The SXT will be capable of producing over 8000 of the smallest partial frame images per day, or fewer but larger images, up to 1024 x 1024 pixel images. Image sequence with two or more of the five x ray analysis filters, with automatic exposure compensation to optimize the charge collection by the CCD detector, will be used to provide plasma diagnostics. Calculations using a differential emission measure code were used to optimize filter selection over the range of emission measure variations and to avoid redundancy, but the filters were chosen primarily to give ratios that are monotonic in plasma temperature.

Brown, W. A.↗
NASA NTRS1984

Instrument failure detection and isolation in a system with variable plant parameters

This paper considers the problem of detecting instrument failures in a system in which there are plant parameter variations. The method described is based on the use of Kalman filters to provide a detection comparison in a manner similar to Clark's dedicated observer method. To improve the sensitivity to sensor variation and reduce the sensitivity to plant parameter variation the Kalman filters are designed to be sub-optimal. A procedure is described to design the sub-optimal filters so as to improve a measure of the ratio of sensor to plant sensitivity.

Alexandro, F. J., Jr.↗
DOE OSTI2023

SPLENDAQ: A Detector-Agnostic Data Acquisition System for Small-Scale Physics Experiments

Many scientific applications from rare-event searches to condensed matter system characterization to high-rate nuclear experiments require time-domain triggering on a raw stream of data, where the triggering is generally threshold-based or randomly acquired. When carrying out detector R &D, there is a need for a general data acquisition (DAQ) system to quickly and efficiently process such data. In the SPLENDOR collaboration, we are developing the Python-based SPLENDAQ package for this exact purpose—it offers two main features for offline analysis of continuous data: a threshold triggering algorithm based on the time-domain optimal filter formalism and an algorithm for randomly choosing nonoverlapping segments for noise measurements. Further, combined with the commercially available Moku platform, developed by Liquid Instruments, we have a full pipeline of event building off raw data with minimal setup. Here, we review the underlying principles of this detector-agnostic DAQ package and give concrete examples of its utility in various applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2014

Optimal Energy Measurement in Nonlinear Systems: An Application of Differential Geometry

Design of TES microcalorimeters requires a tradeoff between resolution and dynamic range. Often, experimenters will require linearity for the highest energy signals, which requires additional heat capacity be added to the detector. This results in a reduction of low energy resolution in the detector. We derive and demonstrate an algorithm that allows operation far into the nonlinear regime with little loss in spectral resolution. We use a least squares optimal filter that varies with photon energy to accommodate the nonlinearity of the detector and the non-stationarity of the noise. The fitting process we use can be seen as an application of differential geometry. This recognition provides a set of well-developed tools to extend our work to more complex situations. The proper calibration of a nonlinear microcalorimeter requires a source with densely spaced narrow lines. A pulsed laser multi-photon source is used here, and is seen to be a powerful tool for allowing us to develop practical systems with significant detector nonlinearity. The combination of our analysis techniques and the multi-photon laser source create a powerful tool for increasing the performance of future TES microcalorimeters.

Nonlinear response↗
NASA NTRS1999

Developing a Fundamental Model for an Integrated GPS/INS State Estimation System with Kalman Filtering

This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.

Canfield, Stephen↗
NASA NTRS1977

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

It is demonstrated that use of the square root information filter (SRIF) can reduce the storage and computation required for estimation of certain classes of large-scale interconnected systems. The SRIF uses an information array that is related to the Kalman filter covariance and estimate. The SRIF algorithm, which is optimal, is a direct application of matrix partitioning to some optimal filtering algorithms described in the literature. The SRIF algorithm is able to reduce the storage requirements of a 40-subsystem 10-state problem by a full order of magnitude.

Bierman, G. J.↗
DOE OSTI2020

Knowing our Sun: data fusion for optimizing space weather forecasts

Outline: Space weather: model for predicting solar wind & polarity; Particle filtering: optimization with Monte Carlo; Simulation & observation: twin tests and real data; Back to Earth: independent work in inertial confinement fusion (ICF)

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Maximized gust loads for a nonlinear airplane using matched filter theory and constrained optimization

Two matched filter theory based schemes are described and illustrated for obtaining maximized and time correlated gust loads for a nonlinear aircraft. The first scheme is computationally fast because it uses a simple 1-D search procedure to obtain its answers. The second scheme is computationally slow because it uses a more complex multi-dimensional search procedure to obtain its answers, but it consistently provides slightly higher maximum loads than the first scheme. Both schemes are illustrated with numerical examples involving a nonlinear control system.

Scott, Robert C.↗
DOE OSTI2025

Enhancing the Cherenkov over scintillation ratio using dichroic filters in BGO and TlCl for TOF-PET

Abstract The Cherenkov emission in inorganic crystal scintillators has been shown to dramatically improve time resolution for time-of-flight positron emission tomography (TOF-PET) for in slow scintillators with a high refractive index such as bismuth germanium oxide (BGO). This is due to the faster nature of the Cherenkov emission (tens of picoseconds) with respect to scintillation (nanosecond). However, the presence of slower scintillation light and the inability of existing detectors to distinguish between Cherenkov and scintillation make it difficult for BGO to achieve a good CTR for all the detected coincidence events. In this paper, we exploit the difference between the Cherenkov and scintillation emission spectra and use dichroic filters to enhance the Cherenkov over scintillation ratio. Dichroic filters transmit or reflect photons based on their wavelength, with a photon attenuation lower than 10%. We investigate several shortpass and longpass dichroic filters in a single-photon configuration with BGO and find the optimal filter that maximizes the Cherenkov over scintillation ratio. We demonstrate that we can enhance the ratio of Cherenkov to scintillation photons by a factor of 2.17 ± 0.38 by employing a shortpass dichroic filter with a cut-off wavelength of 450 nm for BGO, and by a factor of 2.87 ± 0.40 using a longpass dichroic filter with a cut-on wavelength of 550 nm for iodine/beryllium-doped thallium chloride.

Science & Technology - Other Topics↗
NASA NTRS1987

Control-System Design Program

Control-theory design package, Optimal Regulator Algorithms for Control of Linear Systems (ORACLS), developed to aid in design of controllers and optimal filters for systems modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, Linear-Quadratic-Gaussian (LQG) problem, most widely accepted method of determining optimal control policy. Provides for solution to time-in-variant continuous or discrete LQG problems. Attractive to control-system designer providing rigorous tool for dealing with multi-input and multi-output dynamic systems in continuous and discrete form. CDO version written in FORTRAN IV. VAX version written in FORTRAN 77.

Frisch, Harold P.↗