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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 289 records · Page 16

Speckle noise reduction of 1-look SAR imagery

Speckle noise is inherent to synthetic aperture radar (SAR) imagery. Since the degradation of the image due to this noise results in uncertainties in the interpretation of the scene and in a loss of apparent resolution, it is desirable to filter the image to reduce this noise. In this paper, an adaptive algorithm based on the calculation of the local statistics around a pixel is applied to 1-look SAR imagery. The filter adapts to the nonstationarity of the image statistics since the size of the blocks is very small compared to that of the image. The performance of the filter is measured in terms of the equivalent number of looks (ENL) of the filtered image and the resulting resolution degradation. The results are compared to those obtained from different techniques applied to similar data. The local adaptive filter (LAF) significantly increases the ENL of the final image. The associated loss of resolution is also lower than that for other commonly used speckle reduction techniques.

Nathan, Krishna S.↗

Variable cycle engines for advanced supersonic transports

Variable Cycle Engines being studied for advanced commercial supersonic transports show potential for significant environmental and economic improvements relative to 1st generation SST engines. The two most promising concepts are: a Variable Stream Control Engine and a Variable Cycle Engine with a rear flow-control valve. Each concept utilizes variable components and separate burners to provide independent temperature and velocity control for two coannular flow streams. Unique fuel control techniques are combined with cycle characteristics that provide low fuel consumption, similar to a turbojet engine, for supersonic operation. This is accomplished while retaining the good subsonic performance features of a turbofan engine. A two-stream coannular nozzle shows potential to reduce jet noise to below FAR Part 36 without suppressors. Advanced burner concepts have the potential for significant reductions in exhaust emissions. In total, these unique engine concepts have the potential for significant overall improvements to the environmental and economic characteristics of advanced supersonic transports.

Howlett, R. A.↗

Systems engingeering for the Kepler Mission : a search for terrestrial planets

The Kepler mission will launch in 2007 and determine the distribution of earth-size planets (0.5 to 10 earth masses) in the habitable zones (HZs) of solar-like stars. The mission will monitor > 100,000 dwarf stars simultaneously for at least 4 years. Precision differential photometry will be used to detect the periodic signals of transiting planets. Kepler will also support asteroseismology by measuring the pressure-mode (p-mode) oscillations of selected stars. Key mission elements include a spacecraft bus and 0.95 meter, wide-field, CCD-based photometer injected into an earth-trailing heliocentric orbit by a 3-stage Delta II launch vehicle as well as a distributed Ground Segment and Follow-up Observing Program. The project is currently preparing for Preliminary Design Review (October 2004) and is proceeding with detailed design and procurement of long-lead components. In order to meet the unprecedented photometric precision requirement and to ensure a statistically significant result, the Kepler mission involves technical challenges in the areas of photometric noise and systematic error reduction, stability, and false-positive rejection. Programmatic and logistical challenges include the collaborative design, modeling, integration, test, and operation of a geographically and functionally distributed project. A very rigorous systems engineering program has evolved to address these challenges. This paper provides an overview of the Kepler systems engineering program, including some examples of our processes and techniques in areas such as requirements synthesis, validation & verification, system robustness design, and end-to-end performance modeling.

systems engineering↗

Noise generation by a finite span swept airfoil

An analysis is developed for the noise generated by a convected gust interacting with a single swept airfoil. The airfoil spans a channel with infinite parallel walls which contains a uniform subsonic mean flow. High frequency gusts, for which the noise generation is concentrated at the airfoil leading edge, are considered. The solution utilizes the Wiener-Hopf technique applied to the equations in nonorthogonal coordinates. Closed form expressions for the farfield acoustic pressure are obtained. The convected gust is assumed to be a plane wave, i.e., the lowest order spanwise mode. Because of the swept leading edge, this convected gust generates acoustic modes of all orders. At high frequencies and low Mach numbers, moderate sweep angles produce substantial noise reductions. The residual acoustic energy is carried mainly by the higher modes. The airfoil sweep also modulates the basic high frequency farfield directivity, producing lobed patterns. The angular modulation of the directivity patterns is most pronounced for the lower order modes.

Kerschen, E. J.↗

Ka-band MMIC subarray technology program (Ka-Mist)

The broad objective of this program was to demonstrate a proof of concept insertion of Monolithic Microwave Integrated Circuit (MMIC) device technology into an innovative (tile architecture) active phased array antenna application supporting advanced EHF communication systems. Ka-band MMIC arrays have long been considered as having high potential for increasing the capability of space, aircraft, and land mobile communication systems in terms of scan performance, data rate, link margin, and flexibility while offering a significant reduction in size, weight, and power consumption. Insertion of MMIC technology into antenna systems, particularly at millimeter wave frequencies using low power and low noise amplifiers in close proximity to the radiating elements, offers a significant improvement in the array transmit efficiency, receive system noise figure, and overall array reliability. Application of active array technology also leads to the use of advanced beamforming techniques that can improve beam agility, diversity, and adaptivity to complex signal environments.

Pottenger, Warren↗

Ka-Band MMIC Subarray Technology Program (Ka-Mist)

Ka-band monolithic microwave integrated circuit (MMIC) arrays have been considered as having high potential for increasing the capability of space, aircraft, and land mobile communication systems in terms of scan performance, data rate, link margin, and flexibility while offering a significant reduction in size, weight, and power consumption. Insertion of MMIC technology into antenna systems, particularly at millimeter wave frequencies using low power and low noise amplifiers in closed proximity to the radiating elements, offers a significant improvement in the array transmit efficiency, receive system noise figure, and overall array reliability. Application of active array technology also leads to the use of advanced beamforming techniques that can improve beam agility, diversity, and adaptivity to complex signal environments. The objective of this program was to demonstrate the technical feasibility of the 'tile' array packaging architecture at EHF via the insertion of 1990 MMIC technology into a functional tile array or subarray module. The means test of this objective was to demonstrate and deliver to NASA a minimum of two 4 x 4 (16 radiating element) subarray modules operating in a transmit mode at 29.6 GHz. Available (1990) MMIC technology was chosen to focus the program effort on the novel interconnect schemes and packaging requirements rather than focusing on MMIC development. Major technical achievements of this program include the successful integration of two 4 x 4 subarray modules into a single antenna array. This 32 element array demonstrates a transmit EIRP of over 300 watts yielding an effective directive power gain in excess of 55 dB at 29.63 GHz. The array has been actively used as the transmit link in airborne/terrestrial mobile communication experiments accomplished via the ACTS satellite launched in August 1993.

Pottinger, W.↗

Spur-Reduced Digital Sinusoid Generation Using Higher-Order Phase Dithering

A higher-order phase dithering technique that reduces the complexity of digital sinusoid generation is presented and analyzed. M(sup th) order phase dithering denotes the addition of M independent, uniform variates to the sinusoid phase prior to word-length reduction. Spurious magnitudes due to quantization effects are accelerated from the usual -6 dBc per phase bit to -6(M + 1) dBc per phase bit, while the noise power increases linearly in M. For a given spurious specification, higher-order phase dithering permits the use of fewer phase bits than the non-dithered system, resulting in an exponential reduction in look-up table size, dramatically decreasing system complexity.

digital sinusoid generation higher-order phase dit↗

Origin and mitigation of wind noise on balloon-borne infrasound microbarometers

High-altitude monitoring of low-frequency acoustic waves (infrasound) on Earth has regained prominence in recent years, primarily driven by improvements in light-weight sensor technology and advances in scientific ballooning techniques. Balloon-borne infrasound monitoring is also being proposed as a remote sensing technique for planetary exploration. Contrary to ground-based infrasound monitoring, the infrasound noise background in the stratosphere as measured by a balloon remains uncharacterized and the efficacy of wind noise mitigation filters has not been investigated. In this study, an analysis of pressure data collected using infrasound microbarometers during the flight of a long-duration zero pressure balloon is presented. Here, a dramatic reduction of background noise in the stratosphere is demonstrated and it is shown that wind noise mitigation filters are not effective at reducing wind noise under these conditions. Results from this study demonstrate stratospheric balloons as a low-noise platform for infrasound monitoring and motivate the development of improved noise mitigation tools.

47 OTHER INSTRUMENTATION↗

Experimental modal analysis of the fuselage panels of an Aero Commander aircraft

The reduction of interior noise in light aircraft was investigated with emphasis the thin fuselage sidewall. The approach used is theoretical and involves modeling of the sidewall panels and stiffeners. Experimental data obtained from tests investigating the effects of mass and stiffness treatments to the sidewalls are presented. The dynamic characteristics of treated panels are contrasted with the untreated sidewall panels using experimental modal analysis techniques. The results include the natural frequencies, modal dampling, and mode shapes of selected panels. Frequency response functions, data relating to the global fuselage response, and acoustic response are also presented.

Geisler, D.↗

Applications of data compression techniques in modal analysis for on-orbit system identification

Data compression techniques have been investigated for use with modal analysis applications. A redundancy-reduction algorithm was used to compress frequency response functions (FRFs) in order to reduce the amount of disk space necessary to store the data and/or save time in processing it. Tests were performed for both single- and multiple-degree-of-freedom (SDOF and MDOF, respectively) systems, with varying amounts of noise. Analysis was done on both the compressed and uncompressed FRFs using an SDOF Nyquist curve fit as well as the Eigensystem Realization Algorithm. Significant savings were realized with minimal errors incurred by the compression process.

Carlin, Robert A.↗

Development of an Efficient Binaural Simulation for the Analysis of Structural Acoustic Data

Applying binaural simulation techniques to structural acoustic data can be very computationally intensive as the number of discrete noise sources can be very large. Typically, Head Related Transfer Functions (HRTFs) are used to individually filter the signals from each of the sources in the acoustic field. Therefore, creating a binaural simulation implies the use of potentially hundreds of real time filters. This paper details two methods of reducing the number of real-time computations required by: (i) using the singular value decomposition (SVD) to reduce the complexity of the HRTFs by breaking them into dominant singular values and vectors and (ii) by using equivalent source reduction (ESR) to reduce the number of sources to be analyzed in real-time by replacing sources on the scale of a structural wavelength with sources on the scale of an acoustic wavelength. The ESR and SVD reduction methods can be combined to provide an estimated computation time reduction of 99.4% for the structural acoustic data tested. In addition, preliminary tests have shown that there is a 97% correlation between the results of the combined reduction methods and the results found with the current binaural simulation techniques

Johnson, Marty E.↗

Procedures for dealing with certain types of noise and systematic errors common to many Hadamard transform optical systems

Sources of noise and error correcting procedures characteristic of Hadamard transform optical systems were investigated. Reduction of spectral noise due to noise spikes in the data, the effect of random errors, the relative performance of Fourier and Hadamard transform spectrometers operated under identical detector-noise-limited conditions, and systematic means for dealing with mask defects are among the topics discussed. The distortion in Hadamard transform optical instruments caused by moving Masks, incorrect mask alignment, missing measurements, and diffraction is analyzed and techniques for reducing or eliminating this distortion are described.

Harwit, M.↗

An Eigensystem Realization Algorithm (ERA) for modal parameter identification and model reduction

A method, called the Eigensystem Realization Algorithm (ERA), is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system modes and noise modes. For illustration of the algorithm, examples are shown using simulation data and experimental data for a rectangular grid structure.

Juang, J. N.↗

An eigensystem realization algorithm for modal parameter identification and model reduction

A method called the eigensystem realization algorithm is developed for modal parameter identification and model reduction of dynamic systems from test data. A new approach is introduced in conjunction with the singular-value decomposition technique to derive the basic formulation of minimum order realization which is an extended version of the Ho-Kalman algorithm. The basic formulation is then transformed into modal space for modal parameter identification. Two accuracy indicators are developed to quantitatively identify the system and noise modes. For illustration of the algorithm, an example is shown using experimental data from the Galileo spacecraft.

Juang, J.-N.↗

Aeroservoelastic Model Validation and Test Data Analysis of the F/A-18 Active Aeroelastic Wing

Model validation and flight test data analysis require careful consideration of the effects of uncertainty, noise, and nonlinearity. Uncertainty prevails in the data analysis techniques and results in a composite model uncertainty from unmodeled dynamics, assumptions and mechanics of the estimation procedures, noise, and nonlinearity. A fundamental requirement for reliable and robust model development is an attempt to account for each of these sources of error, in particular, for model validation, robust stability prediction, and flight control system development. This paper is concerned with data processing procedures for uncertainty reduction in model validation for stability estimation and nonlinear identification. F/A-18 Active Aeroelastic Wing (AAW) aircraft data is used to demonstrate signal representation effects on uncertain model development, stability estimation, and nonlinear identification. Data is decomposed using adaptive orthonormal best-basis and wavelet-basis signal decompositions for signal denoising into linear and nonlinear identification algorithms. Nonlinear identification from a wavelet-based Volterra kernel procedure is used to extract nonlinear dynamics from aeroelastic responses, and to assist model development and uncertainty reduction for model validation and stability prediction by removing a class of nonlinearity from the uncertainty.

Brenner, Martin J.↗

Integration of Propulsion-Airframe-Aeroacoustic Technologies and Design Concepts for a Quiet Blended-Wing-Body Transport

This paper summarizes the results of studies undertaken to investigate revolutionary propulsion-airframe configurations that have the potential to achieve significant noise reductions over present-day commercial transport aircraft. Using a 300 passenger Blended-Wing-Body (BWB) as a baseline, several alternative low-noise propulsion-airframe-aeroacoustic (PAA) technologies and design concepts were investigated both for their potential to reduce the overall BWB noise levels, and for their impact on the weight, performance, and cost of the vehicle. Two evaluation frameworks were implemented for the assessments. The first was a Multi-Attribute Decision Making (MADM) process that used a Pugh Evaluation Matrix coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This process provided a qualitative evaluation of the PAA technologies and design concepts and ranked them based on how well they satisfied chosen design requirements. From the results of the evaluation, it was observed that almost all of the PAA concepts gave the BWB a noise benefit, but degraded its performance. The second evaluation framework involved both deterministic and probabilistic systems analyses that were performed on a down-selected number of BWB propulsion configurations incorporating the PAA technologies and design concepts. These configurations included embedded engines with Boundary Layer Ingesting Inlets, Distributed Exhaust Nozzles installed on podded engines, a High Aspect Ratio Rectangular Nozzle, Distributed Propulsion, and a fixed and retractable aft airframe extension. The systems analyses focused on the BWB performance impacts of each concept using the mission range as a measure of merit. Noise effects were also investigated when enough information was available for a tractable analysis. Some tentative conclusions were drawn from the results. One was that the Boundary Layer Ingesting Inlets provided improvements to the BWB's mission range, by increasing the propulsive efficiency at cruise, and therefore offered a means to offset performance penalties imposed by some of the advanced PAA configurations. It was also found that the podded Distributed Exhaust Nozzle configuration imposed high penalties on the mission range and the need for substantial synergistic performance enhancements from an advanced integration scheme was identified. The High Aspect Ratio Nozzle showed inconclusive noise results and posed significant integration difficulties. Distributed Propulsion, in general, imposed performance penalties but may offer some promise for noise reduction from jet-to-jet shielding effects. Finally, a retractable aft airframe extension provided excellent noise reduction for a modest decrease in range.

Hill, G. A.↗

Automated quantum error mitigation based on probabilistic error reduction

Current quantum computers suffer from a level of noise that prohibits extracting useful results directly from longer computations. The figure of merit in many near-term quantum algorithms is an expectation value measured at the end of the computation, which experiences a bias in the presence of hardware noise. A systematic way to remove such bias is probabilistic error cancellation (PEC). PEC requires a full characterization of the noise and introduces a sampling overhead that increases exponentially with circuit depth, prohibiting high-depth circuits at realistic noise levels. Probabilistic error reduction (PER) is a related quantum error mitigation method that systematically reduces the sampling overhead at the cost of reintroducing bias. In combination with zero-noise extrapolation, PER can yield expectation values with an accuracy comparable to PEC.Noise reduction through PER is broadly applicable to near-term algorithms, and the automated implementation of PER is thus desirable for facilitating its widespread use. To this end, we present an automated quantum error mitigation software framework that includes noise tomography and application of PER to user-specified circuits. We provide a multi-platform Python package that implements a recently developed Pauli noise tomography (PNT) technique for learning a sparse Pauli noise model and exploits a Pauli noise scaling method to carry out PER.We also provide software tools that leverage a previously developed toolchain, employing PyGSTi for gate set tomography and providing a functionality to use the software Mitiq for PER and zero-noise extrapolation to obtain error-mitigated expectation values on a user-defined circuit.

McDonough, Benjamin↗

An integrated manifold learning approach for high-dimensional data feature extractions and its applications to online process monitoring of additive manufacturing

As an effective dimension reduction and feature extraction technique, manifold learning has been successfully applied to high-dimensional data analysis. With the rapid development of sensor technology, a large amount of high-dimensional data such as image streams can be easily available. Thus, a promising application of manifold learning is in the field of sensor signal analysis, particular for the applications of online process monitoring and control using high-dimensional data. The objective of this study is to develop a manifold learning-based feature extraction method for process monitoring of Additive Manufacturing (AM) using online sensor data. Due to the non-parametric nature of most existing manifold learning methods, their performance in terms of computational efficiency, as well as noise resistance has yet to be improved. To address this issue, this study proposes an integrated manifold learning approach termed multi-kernel metric learning embedded isometric feature mapping (MKML-ISOMAP) for dimension reduction and feature extraction of online high-dimensional sensor data such as images. Based on the extracted features with the utilization of supervised classification and regression methods, an online process monitoring methodology for AM is implemented to identify the actual process quality status. Finally, in the numerical simulation and real-world case studies, the proposed method demonstrates excellent performance in both prediction accuracy and computational efficiency.

36 MATERIALS SCIENCE↗