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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Active magnetic bearings: As applied to centrifugal pumps

Application of magnetic bearings to boiler feed pumps presents various attractive features, such as longer bearing life, lower maintenance costs, and improved operability through control of the rotordynamics. Magnetic bearings were fitted to an eight-stage, 600 hp boiler feed pump, which generates 2600 ft of heat at 680 gpm and 3560 rpm. In addition to the varied and severe operating environment in steady state operation of this pump in a power plant, it is also subjected to transient loads during frequent starts and stops. These loads can now be measured by the in-built instrumentation of the magnetic bearings. Following site installation, a follow-up bearing tune-up was performed, and pump transient response testing was conducted. The bearing response was completely satisfactory, ensuring trouble-free pump operation even in the range of reduced load. The experience gained so far through design and testing proves feasibility of magnetic bearings for boiler feed pumps, which sets the stage for application of even higher energy centrifugal pumps equipped with magnetic bearings.

Lev Nelik↗
NASA NTRS1992

IRAF and STSDAS under the new ALPHA architecture

Digital's next generation RISC architecture, known as ALPHA, presents many IRAF system portability questions and challenges to both site managers and end users. DEC promises to support the ULTRIX, VMS, and OSF/1 operating systems, which should allow IRAF to be ported to the new architecture at either the program executable level (using VEST), or at the source level, where IRAF can be tuned for greater performance. These notes highlight some of the details of porting IRAF to OpenVMS on the ALPHA architecture.

Zarate, N. R.↗
NASA NTRS2001

Advanced Technology Development for Active Acoustic Liners

Objectives include: (1) Develop electro-mechanical/acoustic models of a Helmholtz resonator possessing a compliant diaphragm coupled to a piezoelectric device; (2) Design and fabricate the energy reclamation module and active Helmholtz resonator; (3) Develop and build appropriate energy reclamation/storage circuit; (4) Develop and fabricate appropriate piezoelectric shunt circuit to tune the compliance of the active Helmholtz resonator via a variable capacitor; (5) Quantify energy reclamation module efficiency in a grazing-flow plane wave tube possessing known acoustic energy input; and (6) Quantify actively tuned Helmholtz resonator performance in grazing-flow plane wave tube for a white-noise input

Sheplak, Mark↗
NASA NTRS2006

Tunable semiconductor lasers

Tunable semiconductor lasers are disclosed requiring minimized coupling regions. Multiple laser embodiments employ ring resonators or ring resonator pairs using only a single coupling region with the gain medium are detailed. Tuning can be performed by changing the phase of the coupling coefficient between the gain medium and a ring resonator of the laser. Another embodiment provides a tunable laser including two Mach-Zehnder interferometers in series and a reflector coupled to a gain medium.

Taghavi-Larigani, Shervin↗
NASA NTRS2013

Real-Time Minimization of Tracking Error for Aircraft Systems

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Garud, Sumedha↗
NASA NTRS2018

Laboratory and On-Sky Validation of the Shaped Pupil Coronagraph's Sensitivity to Low-Order Aberrations with Active Wavefront Control

We present early laboratory simulations and extensive on-sky tests validating of the performance of a shaped pupil coronagraph (SPC) behind an extreme-AO (Adaptive Optics) corrected beam of the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system. In tests with the SCExAO internal source/wavefront error simulator, the normalized intensity profile for the SPC degrades more slowly than for the Lyot coronagraph as low-order aberrations reduce the Strehl ratio (S.R.) from extremely high values (S.R. approximately 0.93-0.99) to those characteristic of current ground-based extreme AO systems (S.R. approximately 0.74-0.93) and then slightly lower values down to S.R. approximately 0.57. On-sky SCExAO data taken with the SPC and other coronagraphs for brown dwarf/planet-hosting stars HD 1160 and HR 8799 provide further evidence for the SPC's robustness to low-order aberrations. From H-band Strehl ratios of 80 percent to 70 percent, the Lyot coronagraph's performance versus that of the SPC may degrade even faster on sky than is seen in our internal source simulations. The 5-sigma contrast also degrades faster (by a factor of two) for the Lyot than the SPC. The SPC we use was designed as a technology demonstrator only, with a contrast floor, throughput, and outer working angle poorly matched for SCExAO's current AO performance and poorly tuned for imaging the HR 8799 planets. Nevertheless, we detect HR 8799 cde with SCExAO/CHARIS using the SPC in broadband mode, where the signal-to-noise ratio for planet e is within 30 percent of that obtained using the vortex coronagraph. The shaped-pupil coronagraph is a promising design demonstrated to be robust in the presence of low-order aberrations and may be well-suited for future ground and space-based direct imaging observations, especially those focused on follow-up exoplanet characterization and technology demonstration of deep contrast within well-defined regions of the image plane.

Currie, Thayne↗
NASA NTRS2022

Characterization of Aerogel Scattering Filters for Astronomical Telescopes

We have developed a suite of novel infrared-blocking filters made by embedding scattering particles in a polymer aerogel substrate. Our developments allow us to tune the spectral performance of the filters based on both the composition of the base aerogel material and the properties of the scattering particles. Our filters are targeted for use in a variety of applications, from ground-based CMB experiments to planetary science probes. We summarize the formulations we have fabricated and tested to date, including several polyimide base aerogel formulations incorporating a range of size distributions of diamond scattering particles. We also describe the spectral characterization techniques used to measure the filters’ optical properties, including the development o fa mm-wave Fourier transform spectrometer testbed.

aerogel, filter, blocking, scattering, Fourier Tra↗
NASA NTRSDate not supplied

Revolutionizing Earth Science with Generalized AI Models

Foundation Models (FM) are generalized Artificial Intelligence (AI) models that are designed to replace a task or an application-specific model and can be used for many downstream applications. These FM can be built on any sequence data and are trained utilizing self-supervised approaches. The obstacle of creating a sizable labeled dataset for training is removed by using self-supervised learning. Most FM employ transformer design that takes advantage of the idea of self-attention, allowing the network to represent the impact of distant data points on one another in space and time. The FM models show emergent qualities that are induced from the data. FM can become a valuable tool for Earth science researchers. Due to the size of these models, downstream applications built fine-tuning these FM perform better and exhibit greater accuracy than models created from scratch. FM significantly lowers the entry barrier in terms of both the time and effort required to develop various downstream applications. For some scientific datasets, such as optical remote sensing data, FM can speed up processes like classification, object detection and prediction. By eliminating the training data bottleneck and maximizing the usage of science data, FM can make it simpler to integrate AI into scientific research. Initial results for three different FMs will be presented.

Rahul Ramachandran↗
NASA NTRSDate not supplied

Study of Martian Polar Caps with GISS ROCKE-3D GCM

Martian polar caps consist of both H 2 O and CO 2 ice. While H 2 O ice is mainly passive on modern Mars, it may have not been the case in recent Martian history, when its obliquity was higher, or when it was changing rapidly. The distribution of ice species in the snowpack affects its physical and thermodynamic properties. In the upper layers, it determines its albedo and thermal emissivity. Thus understanding the mutual effect between these ices and their interaction with the atmosphere is crucial for understanding the evolution of Martian polar regions. In this study, we employ a newly-developed Exotic Ices snow model coupled to the NASA Goddard Institute for Space Studies (GISS) ROCKE-3D planetary General Circulation Model (GCM) [1] to study the behavior of Martian polar caps. ROCKE-3D is a planetary GCM developed at NASA GISS as an extension of its Earth climate model, modelE [2]. It has been extensively used to simulate climate of various planets, including Mars (e.g. [3,4]). The Exotic Ices snow model was specially developed for planetary applications which involve more than one condensable in the atmosphere, in which case snow can contain multiple species of ice (CO2 and H 2 O in the Mars case). For each species of ice, the model uses their proper physical properties and phase diagram, but otherwise it treats all species of ice on an equal footing. The combined effects on albedo, thermal inertia and mutual insulation are treated accordingly. The snowpack interacts with the atmospheric dust cycle, and can accumulate a prognostic amount of dust, though the effect of dust on snow properties is not currently treated explicitly, and is prescribed. In this study, we first validate our model against the modern Martial climate, for which we use mission results from Mars Climate Sounder (atmospheric temperature and dust optical depth), SPICAM on Mars Express (atmospheric water), and Viking 2 (surface pressure). We investigate the effect of snow radiative properties on CO 2 and water cycles and the ability of our model to accurately reproduce those with minimal model tuning. We then perform simulations for several obliquities from a recent Martian past, and investigate the behavior of the Martian polar caps in such conditions.

Mars↗
NASA NTRS1998

A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers

This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.

Woodard, Stanley E.↗
NASA NTRS1993

Application of genetic algorithms to tuning fuzzy control systems

Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

Espy, Todd↗
NASA NTRS1999

A Self-Tuning Kalman Filter for Autonomous Navigation Using the Global Positioning System (GPS)

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman filter and GPS (Global Positioning Systems) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. These systems, however, still rely on manual tuning from analysts. A sophisticated neuro-fuzzy component fully integrated with the flight navigation system can perform the self-tuning capability for the Kalman filter and help the navigation system recover from estimation errors in real time.

Truong, Son H.↗
NASA NTRS1999

A Self-Tuning Kalman Filter for Autonomous Navigation using the Global Positioning System (GPS)

Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman filter and GPS data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. These systems, however, still rely on manual tuning from analysts. A sophisticated neuro-fuzzy component fully integrated with the flight navigation system can perform the self-tuning capability for the Kalman filter and help the navigation system recover from estimation errors in real time.

Truong, S. H.↗
NASA NTRS2011

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Simon, Donald L.↗
NASA NTRS1998

On-Orbit Model Refinement for Controller Redesign

High performance control design for a flexible space structure is challenging since high fidelity plant models are difficult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. A new procedure for refining a multivariable open loop plant model based on closed-loop response data is presented. Using a minimal representation of the state space dynamics, a least squares prediction error method is employed to estimate the plant parameters. This control-relevant system identification procedure stresses the joint nature of the system identification and control design problem by seeking to obtain a model that minimizes the difference between the predicted and actual closed-loop performance. This paper presents an algorithm for iterative closed-loop system identification and controller redesign along with illustrative examples.

Whorton, Mark S.↗
NASA NTRS2004

Closed Loop System Identification with Genetic Algorithms

High performance control design for a flexible space structure is challenging since high fidelity plant models are di.cult to obtain a priori. Uncertainty in the control design models typically require a very robust, low performance control design which must be tuned on-orbit to achieve the required performance. Closed loop system identi.cation is often required to obtain a multivariable open loop plant model based on closed-loop response data. In order to provide an accurate initial plant model to guarantee convergence for standard local optimization methods, this paper presents a global parameter optimization method using genetic algorithms. A minimal representation of the state space dynamics is employed to mitigate the non-uniqueness and over-parameterization of general state space realizations. This control-relevant system identi.cation procedure stresses the joint nature of the system identi.cation and control design problem by seeking to obtain a model that minimizes the di.erence between the predicted and actual closed-loop performance.

Whorton, Mark S.↗
NASA NTRS1977

The 5K70SK automatically tuned, high power, S-band klystron

Primary objectives include delivery of 44 5K70SK klystron amplifier tubes and 26 remote tuner assemblies with spare parts kits. Results of a reliability demonstration on a klystron test cavity are discussed, along with reliability tests performed on a remote tuning unit. Production problems and one design modification are reported and discussed. Results of PAT and DVT are included.

Goldfinger, A.↗
NASA NTRS2010

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Simon, Donald L.↗