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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

neural network↗
NASA NTRS2000

TERA-OPS Processing for ATR

A three-dimensional microelectronic device (3DANN-R) capable of performing general image convolution at the speed of 10***sup12*** operations/second (ops) in a volume of less than 1.5 cubic centimeter has been successfully built under the BMDO/JPL VIGILANTE program.

Automatic↗
NASA NTRS1981

Autothermal reforming of sulfur-free and sulfur-containing hydrocarbon liquids

The mechanisms by which various fuel component hydrocarbons related to both heavy petroleum and coal-derived liquids are converted to hydrogen without forming carbon were investigated. Reactive differences between paraffins and aromatics in autothermal reforming (ATR) were shown to be responsible for the observed fuel-specific carbon formation characteristics. The types of carbon formed in the reformer were identified by SEM and XRD analyses of catalyst samples and carbon deposits. From tests with both light and heavy paraffins and aromatics, it is concluded that high boiling point hydrocarbons and polynuclear aromatics enhance the propensity for carbon formation. The effects of propylene addition on the ATR performance of benzene are described. In ATR tests with mixtures of paraffins and aromatics, synergistic effects on conversion characteristics were identified. Indications that the sulfur content of the fuel may be the limiting factor for efficient ATR operation were found. The conversion and degradation effects of the sulfur additive (thiophene) were examined.

Source record↗
NASA NTRS1991

User acceptance of intelligent avionics: A study of automatic-aided target recognition

User acceptance of new support systems typically was evaluated after the systems were specified, designed, and built. The current study attempts to assess user acceptance of an Automatic-Aided Target Recognition (ATR) system using an emulation of such a proposed system. The detection accuracy and false alarm level of the ATR system were varied systematically, and subjects rated the tactical value of systems exhibiting different performance levels. Both detection accuracy and false alarm level affected the subjects' ratings. The data from two experiments suggest a cut-off point in ATR performance below which the subjects saw little tactical value in the system. An ATR system seems to have obvious tactical value only if it functions at a correct detection rate of 0.7 or better with a false alarm level of 0.167 false alarms per square degree or fewer.

Becker, Curtis A.↗
NASA NTRS2002

Projection Moire Interferometry for Rotorcraft Applications: Deformation Measurements of Active Twist Rotor Blades

Projection Moire Interferometry (PMI) has been used during wind tunnel tests to obtain azimuthally dependent blade bending and twist measurements for a 4-bladed Active Twist Rotor (ATR) system in simulated forward flight. The ATR concept offers a means to reduce rotor vibratory loads and noise by using piezoelectric active fiber composite actuators embedded in the blade structure to twist each blade as they rotate throughout the rotor azimuth. The twist imparted on the blades for blade control causes significant changes in blade loading, resulting in complex blade deformation consisting of coupled bending and twist. Measurement of this blade deformation is critical in understanding the overall behavior of the ATR system and the physical mechanisms causing the reduction in rotor loads and noise. PMI is a non-contacting, video-based optical measurement technique capable of obtaining spatially continuous structural deformation measurements over the entire object surface within the PMI system field-of-view. When applied to rotorcraft testing, PMI can be used to measure the azimuth-dependent blade bending and twist along the full span of the rotor blade. This paper presents the PMI technique as applied to rotorcraft testing, and provides results obtained during the ATR tests demonstrating the PMI system performance. PMI measurements acquired at select blade actuation conditions generating minimum and maximum rotor loads are provided to explore the interrelationship between rotor loads, blade bending, and twist.

Fleming, Gary A.↗
NASA NTRS2011

Testing of a Composite Wavelet Filter to Enhance Automated Target Recognition in SONAR

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low resolution SONAR and camera videos taken from Unmanned Underwater Vehicles (UUVs). These SONAR images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both SONAR and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this report.

image processing↗
NASA NTRS2001

Integral Twist Actuation of Helicopter Rotor Blades for Vibration Reduction

Active integral twist control for vibration reduction of helicopter rotors during forward flight is investigated. The twist deformation is obtained using embedded anisotropic piezocomposite actuators. An analytical framework is developed to examine integrally-twisted blades and their aeroelastic response during different flight conditions: frequency domain analysis for hover, and time domain analysis for forward flight. Both stem from the same three-dimensional electroelastic beam formulation with geometrical-exactness, and axe coupled with a finite-state dynamic inflow aerodynamics model. A prototype Active Twist Rotor blade was designed with this framework using Active Fiber Composites as the actuator. The ATR prototype blade was successfully tested under non-rotating conditions. Hover testing was conducted to evaluate structural integrity and dynamic response. In both conditions, a very good correlation was obtained against the analysis. Finally, a four-bladed ATR system is built and tested to demonstrate its concept in forward flight. This experiment was conducted at NASA Langley T~ansonic Dynamics Tunnel and represents the first-of-a-kind Mach-scaled fully-active-twist rotor system to undergo forward flight test. In parallel, the impact upon the fixed- and rotating-system loads is estimated by the analysis. While discrepancies are found in the amplitude of the loads under actuation, the predicted trend of load variation with respect to its control phase correlates well. It was also shown, both experimentally and numerically, that the ATR blade design has the potential for hub vibratory load reduction of up to 90% using individual blade control actuation. Using the numerical framework, system identification is performed to estimate the harmonic transfer functions. The linear time-periodic system can be represented by a linear time-invariant system under the three modes of blade actuation: collective, longitudinal cyclic, and lateral cyclic. A vibration minimizing controller is designed based on this result, which implements classical disturbance rejection algorithm with some modifications. The controller is simulated numerically, and more than 90% of the 4P hub vibratory load is eliminated. By accomplishing the experimental and analytical steps described in this thesis, the present concept is found to be a viable candidate for future generation low-vibration helicopters. Also, the analytical framework is shown to be very appropriate for exploring active blade designs, aeroelastic behavior prediction, and as simulation tool for closed-loop controllers.

Shin, SangJoon↗
NASA NTRS2006

Bench-Scale Monolith Autothermal Reformer Catalyst Screening Evaluations in a Micro-Reactor With Jet-A Fuel

Solid oxide fuel cell systems used in the aerospace or commercial aviation environment require a compact, light-weight and highly durable catalytic fuel processor. The fuel processing method considered here is an autothermal reforming (ATR) step. The ATR converts Jet-A fuel by a reaction with steam and air forming hydrogen (H2) and carbon monoxide (CO) to be used for production of electrical power in the fuel cell. This paper addresses the first phase of an experimental catalyst screening study, looking at the relative effectiveness of several monolith catalyst types when operating with untreated Jet-A fuel. Six monolith catalyst materials were selected for preliminary evaluation and experimental bench-scale screening in a small 0.05 kWe micro-reactor test apparatus. These tests were conducted to assess relative catalyst performance under atmospheric pressure ATR conditions and processing Jet-A fuel at a steam-to-carbon ratio of 3.5, a value higher than anticipated to be run in an optimized system. The average reformer efficiencies for the six catalysts tested ranged from 75 to 83 percent at a constant gas-hourly space velocity of 12,000 hr 1. The corresponding hydrocarbon conversion efficiency varied from 86 to 95 percent during experiments run at reaction temperatures between 750 to 830 C. Based on the results of the short-duration 100 hr tests reported herein, two of the highest performing catalysts were selected for further evaluation in a follow-on 1000 hr life durability study in Phase II.

Tomsik, Thomas M.↗
NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗
NASA NTRS2006

Grayscale Optical Correlator Workbench

Grayscale Optical Correlator Workbench (GOCWB) is a computer program for use in automatic target recognition (ATR). GOCWB performs ATR with an accurate simulation of a hardware grayscale optical correlator (GOC). This simulation is performed to test filters that are created in GOCWB. Thus, GOCWB can be used as a stand-alone ATR software tool or in combination with GOC hardware for building (target training), testing, and optimization of filters. The software is divided into three main parts, denoted filter, testing, and training. The training part is used for assembling training images as input to a filter. The filter part is used for combining training images into a filter and optimizing that filter. The testing part is used for testing new filters and for general simulation of GOC output. The current version of GOCWB relies on the mathematical software tools from MATLAB binaries for performing matrix operations and fast Fourier transforms. Optimization of filters is based on an algorithm, known as OT-MACH, in which variables specified by the user are parameterized and the best filter is selected on the basis of an average result for correct identification of targets in multiple test images.

Hanan, Jay↗
NASA NTRS2012

Composite Wavelet Filters for Enhanced Automated Target Recognition

Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.

automated target recognition↗
NASA NTRS2012

Intelligent Image Analysis for Image-Guided Laser Hair Removal and Skin Therapy

We present the development of advanced automatic target recognition (ATR) algorithms for the hair follicles identification in digital skin images to accurately direct the laser beam to remove the hair. The ATR system first performs a wavelet filtering to enhance the contrast of the hair features in the image. The system then extracts the unique features of the targets and sends the features to an Adaboost based classifier for training and recognition operations. The ATR system automatically classifies the hair, moles, or other skin lesion and provides the accurate coordinates of the intended hair follicle locations. The coordinates can be used to guide a scanning laser to focus energy only on the hair follicles. The intended benefit would be to protect the skin from unwanted laser exposure and to provide more effective skin therapy.

laser hair removal↗
NASA NTRS2020

Release of the NASA Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) OpenVSP Model

The Open VSP model represents the geometry of PEGASUS as is currently modeled. PEGASUS is a concept vehicle that will not be physically produced. As such, the baseline model is subject to change without notice or requirement that updates are provided external to NASA. The current baseline is derived from the outer mold line (OML) of the ATR 42-500. As such, planform areas for the wing, fuselage, vertical tail, and horizontal tail mimic those published in public ATR 42 literature. NASA Aeronautics Systems Analysis Branch (ASAB) does not contain any proprietary data on the ATR 42, thus the PEGASUS model does not contain any proprietary or sensitive information. Further, model details that are required for an actual aircraft such as airfoils, twist distributions and propeller geometries are unknown at this time, and generic stand-ins are used within the OpenVSP model. The intent is to provide this model to Georgia Tech ASDL to allow the ASDL team to model the impact of the propulsion system at the wingtip’s impact on structural characteristics. The ASDL will be using the model to generate estimated aerodynamic load and structural members for analysis.

PEGASUS↗
NASA NTRS2012

Testing Saliency Parameters for Automatic Target Recognition

A bottom-up visual attention model (the saliency model) is tested to enhance the performance of Automated Target Recognition (ATR). JPL has developed an ATR system that identifies regions of interest (ROI) using a trained OT-MACH filter, and then classifies potential targets as true- or false-positives using machine-learning techniques. In this project, saliency is used as a pre-processing step to reduce the space for performing OT-MACH filtering. Saliency parameters, such as output level and orientation weight, are tuned to detect known target features. Preliminary results are promising and future work entails a rigrous and parameter-based search to gain maximum insight about this method.

regions of interest (ROI)↗
NASA NTRS1981

Catalytic autothermal reforming increases fuel cell flexibility

Experimental results are presented for the autothermal reforming (ATR) of n-hexane, n-tetradecane, benzene and benzene solutions of naphthalene. The tests were run at atmospheric pressure and at moderately high reactant preheat temperatures in the 800-900 K range. Carbon formation lines were determined for paraffinic and aromatic liquids. Profiles were determined for axial bed temperature and composition. Space velocity efforts were assessed, and the locations and types of carbon were recorded. Significant reactive differences between hydrocarbons were identified. Carbon formation characteristics were hydrocarbon specific. The differing behavior of paraffinic and aromatic fuels with respect to their carbon formation may be important in explaining the narrow range of carbon-free operating conditions found in the ATR of number two fuel oil.

Flytzani-Stephanopoulos, M.↗
NASA NTRS1983

Autothermal reforming of aliphatic and aromatic hydrocarbon liquids

Results are presented from a study of the autothermal reforming of paraffins and aromatics over nickel catalysts. The trials were performed to examine the carbon products that appear when steam is passed over hydrocarbon liquids to form H2-rich gases, i.e., the autothermal process (ATR). Attention was given to n-hexane, n-tetradecane, benzene, and benzene solutions of naphthalene with reactant preheat to 1000-1150 F. The carbon-formation limit was sought as a function of the steam-to-carbon and oxygen to carbon molar ratios at constant pressure and the preheat temperatures. The catalyst bed was examined after each trial to identify the locations and types of carbon formed using SEM, thermal gravimetric analysis, and X ray diffraction techniques. The hydrocarbon fuels each had a separate temperature and reaction profile, as well as carbon formation characteristics. No carbon formation was observed in the upper layer of the reactor bed, while both gas phase and surface-grown deposits were present in the lower part. The results are concluded of use in the study of No. 2 fuel oil for ATR feedstock.

Flytzani-Stephanopoulos, M.↗
NASA NTRS1991

Ceramic regenerator program

The feasibility of fabricating an Air Turbo Ramjet (ATR) regenerator containing intricate hydraulic passages from a ceramic material in order to allow operation with high temperature combustion gas and to reduce weight as compared with metallic materials was demonstrated. Platelet technology, ceramic tape casting, and multilayer ceramic packaging techniques were used in this fabrication of subscale silicon nitride components. Proof-of-concept demonstrations were performed to simulate a methane cooled regenerator for an ATR engine. The regenerator vane was designed to operate at realistic service conditions, i.e., 600 psi in a 3500 R (3040 F), 500 fps combustion gas environment. A total of six regenerators were fabricated and tested. The regenerators were shown to be able to withstand internal pressurization to 1575 psi. They were subjected to testing in 500 fps, 3560 R (3100 F) air/propane combustion products and were operated satisfactorily for an excess of 100 hr and 40 thermal cycles which exceeded 2460 R (2000 F).

Franklin, Jerrold E.↗
NASA NTRS1997

Vigilante: Ultrafast Smart Sensor for Target Recognition and Precision Tracking in a Simulated CMD Scenario

VIGILANTE is an ultrafast smart sensor testbed for generic Automatic Target Recognition (ATR) applications with a series of capability demonstration focussed on cruise missile defense (CMD). VIGILANTE's sensor/processor architecture is based on next-generation UV/visible/IR sensors and a tera-operations per second sugar-cube processor, as well as supporting airborne vehicle. Excellent results of efficient ATR methodologies that use an eigenvectors/neural network combination and feature-based precision tracking have been demonstrated in the laboratory environment.

TARGET RECOGNITION↗