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At least 1,513 records · Page 84

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NASA NTRS1994

Goal Directed Model Inversion: Learning Within Domain Constraints

Goal Directed Model Inversion (GDMI) is an algorithm designed to generalize supervised learning to the case where target outputs are not available to the learning system. The output of the learning system becomes the input to some external device or transformation, and only the output of this device or transformation can be compared to a desired target. The fundamental driving mechanism of GDMI is to learn from success. Given that a wrong outcome is achieved, one notes that the action that produced that outcome "would have been right if the outcome had been the desired one." The algorithm makes use of these intermediate "successes" to achieve the final goal. A unique and potentially very important feature of this algorithm is the ability to modify the output of the learning module to force upon it a desired syntactic structure. This differs from ordinary supervised learning in the following way: in supervised learning the exact desired output pattern must be provided. In GDMI instead, it is possible to require simply that the output obey certain rules, i.e., that it "make sense" in some way determined by the knowledge domain. The exact pattern that will achieve the desired outcome is then found by the system. The ability to impose rules while allowing the system to search for its own answers in the context of neural networks is potentially a major breakthrough in two ways: 1) it may allow the construction of networks that can incorporate immediately some important knowledge, i.e. would not need to learn everything from scratch as normally required at present, and 2) learning and searching would be limited to the areas where it is necessary, thus facilitating and speeding up the process. These points are illustrated with examples from robotic path planning and parametric design.

Colombano, Silvano P.↗

NASA NTRS1994

Goal Directed Model Inversion: Learning Within Domain Constraints

Goal Directed Model Inversion (GDMI) is an algorithm designed to generalize supervised learning to the case where target outputs are not available to the learning system. The output of the learning system becomes the input to some external device or transformation, and only the output of this device or transformation can be compared to a desired target. The fundamental driving mechanism of GDMI is to learn from success. Given that a wrong outcome is achieved, one notes that the action that produced that outcome "would have been right if the outcome had been the desired one." The algorithm makes use of these intermediate "successes" to achieve the final goal. A unique and potentially very important feature of this algorithm is the ability to modify the output of the learning module to force upon it a desired syntactic structure. This differs from ordinary supervised learning in the following way: in supervised learning the exact desired output pattern must be provided. In GDMI instead, it is possible to require simply that the output obey certain rules, i.e., that it "make sense" in some way determined by the knowledge domain. The exact pattern that will achieve the desired outcome is then found by the system. The ability to impose rules while allowing the system to search for its own answers in the context of neural networks is potentially a major breakthrough in two ways: (1) it may allow the construction of networks that can incorporate immediately some important knowledge, i.e., would not need to learn everything from scratch as normally required at present; and (2) learning and searching would be limited to the areas where it is necessary, thus facilitating and speeding up the process. These points are illustrated with examples from robotic path planning and parametric design.

Colombano, Silvano P.↗

NASA NTRS1975

Nonreactive mixing study of a scramjet swept-strut fuel injector

The results are presented of a cold-mixing investigation performed to supply combustor design information and to determine optimum normal fuel-injector configurations for a general scramjet swept-strut fuel injector. The experimental investigation was made with two swept struts in a closed duct at a Mach number of 4.4 and a nominal ratio of jet mass flow to air mass flow of 0.0295, with helium used to simulate hydrogen fuel. Four injector patterns were evaluated; they represented the range of hole spacing and the ratio of jet dynamic pressure to free-stream dynamic pressure. Helium concentration, pitot pressure, and static pressure in the downstream mixing region were measured to generate the contour plots needed to define the mixing-region flow field and the mixing parameters. Experimental results show that the fuel penetration from the struts was less than the predicted values based on flat-plate data; but the mixing rate was faster and produced a mixing length less than one-half that predicted.

Mcclinton, C. R.↗

NASA NTRS1975

Space shuttle orbital maneuvering engine platelet injector program

A platelet face injector for the Orbit Maneuvering Engine (OME) on the space shuttle was evaluated as a means of obtaining additional design margin and lower cost. The program was conducted in three phases. The first phase evaluated single injection elements, or unielements; it involved visual flow studies, mixing experiments using propellant simulants, and hot firings to assess combustion efficiency, chamber wall compatibility, and injector face temperatures. In the second phase, subscale units producing 600 lbf thrust were used to further evaluate the orifice patterns chosen on the basis of unielement testing. In addition to combustion efficiency, chamber and injector heat transfer, the subscale testing provided a preliminary indication of injector stability. Full scale testing of the selected patterns at 6,000 lbf thrust was performed in the third phase. Performance, heat transfer, and combustion stability were evaluated over the anticipated range of OMS operating conditions. The effects on combustion stability of acoustic cavity configuration, including cavity depth, open area, inlet contour, and other parameters, were investigated.

Source record↗

NASA NTRS1977

A methodology for estimating dog noise in an animal housing facility

A rectangular reverberation chamber was designed, constructed and calibrated for the experimental measurement of the sound power level (acoustic power) of a dog. Calibration of the chamber consisted of comparing the acoustic power measured for a random noise source in the chamber with that for the identical source in a free field environment. Data from dogs indicate that barking noise can be modeled as a square wave pattern with short duration and peak sound power levels in the 500 Hz octave band. A-weighted sound pressure levels of up to 114.7 dBA were absorbed, indicating a potential concern for both animals and man chronically exposed to such environments.

Sierens, S. E.↗

NASA NTRS1983

A study of pump cavitation damage

The cavitation assessment for the space shuttle main engine high pressure oxidizer turbopump is documented. A model of the flow through the pump was developed. Initially, a computational procedure was used to analyze the flow through the inlet casing including the prediction of wakes downstream of the casing vanes. From these flow calculations, cavitation patterns on the inducer blades were approximated and the damage rate estimated. The model correlates the heavy damage on the housing and over the inducer with unsteady blade surface cavitation. The unsteady blade surface cavitation is due to the large incidence changes caused by the wakes of the upstream vanes. Very high cavitation damage rates are associated with this type of cavitation. Design recommendations for reducing the unsteady cavitation include removing the set of vanes closest to the inducer and modifying the remaining vanes.

Brophy, M. C.↗

NASA NTRS1985

An analysis of pump cavitation damage

Brophy, M. C.↗

NASA NTRS1988

KAM (Knowledge Acquisition Module): A tool to simplify the knowledge acquisition process

Analysts, knowledge engineers and information specialists are faced with increasing volumes of time-sensitive data in text form, either as free text or highly structured text records. Rapid access to the relevant data in these sources is essential. However, due to the volume and organization of the contents, and limitations of human memory and association, frequently: (1) important information is not located in time; (2) reams of irrelevant data are searched; and (3) interesting or critical associations are missed due to physical or temporal gaps involved in working with large files. The Knowledge Acquisition Module (KAM) is a microcomputer-based expert system designed to assist knowledge engineers, analysts, and other specialists in extracting useful knowledge from large volumes of digitized text and text-based files. KAM formulates non-explicit, ambiguous, or vague relations, rules, and facts into a manageable and consistent formal code. A library of system rules or heuristics is maintained to control the extraction of rules, relations, assertions, and other patterns from the text. These heuristics can be added, deleted or customized by the user. The user can further control the extraction process with optional topic specifications. This allows the user to cluster extracts based on specific topics. Because KAM formalizes diverse knowledge, it can be used by a variety of expert systems and automated reasoning applications. KAM can also perform important roles in computer-assisted training and skill development. Current research efforts include the applicability of neural networks to aid in the extraction process and the conversion of these extracts into standard formats.

Gettig, Gary A.↗

NASA NTRS1992

Fault diagnosis for the Space Shuttle main engine

A conceptual design of a model-based fault detection and diagnosis system is developed for the Space Shuttle main engine. The design approach consists of process modeling, residual generation, and fault detection and diagnosis. The engine is modeled using a discrete time, quasilinear state-space representation. Model parameters are determined by identification. Residuals generated from the model are used by a neural network to detect and diagnose engine component faults. Fault diagnosis is accomplished by training the neural network to recognize the pattern of the respective fault signatures. Preliminary results for a failed valve, generated using a full, nonlinear simulation of the engine, are presented. These results indicate that the developed approach can be used for fault detection and diagnosis. The results also show that the developed model is an accurate and reliable predictor of the highly nonlinear and very complex engine.

Duyar, Ahmet↗

NASA NTRS1993

Development of generalized 3-D braiding machines for composite preforms

The operating principles of two prototype braiding machines for the production of generalized braid patterns are described. Both processes afford previously unachievable control of the interlacing of fibers within a textile structure that make them especially amenable to the fabrication of textile preforms for composite materials. They enable independent control of the motion of the individual fibers being woven, thereby enabling the greatest possible freedom in controlling fiber orientation within a structure. This freedom enables the designer to prescribe local fiber orientation to better optimize material performance. The processes have been implemented on a very small scale but at a level that demonstrates their practicality and the soundness of the principles governing their operation.

Huey, Cecil O., Jr.↗

NASA NTRS1998

Current and Future Critical Issues in Rocket Propulsion Systems

The objective of this research was to tackle several problems that are currently of great importance to NASA. In a liquid rocket engine several complex processes take place that are not thoroughly understood. Droplet evaporation, turbulence, finite rate chemistry, instability, and injection/atomization phenomena are some of the critical issues being encountered in a liquid rocket engine environment. Pulse Detonation Engines (PDE) performance, combustion chamber instability analysis, 60K motor flowfield pattern from hydrocarbon fuel combustion, and 3D flowfield analysis for the Combined Cycle engine were of special interest to NASA. During the summer of 1997, we made an attempt to generate computational results for all of the above problems and shed some light on understanding some of the complex physical phenomena. For this purpose, the Liquid Thrust Chamber Performance (LTCP) code, mainly designed for liquid rocket engine applications, was utilized. The following test cases were considered: (1) Characterization of a detonation wave in a Pulse Detonation Tube; (2) 60K Motor wall temperature studies; (3) Propagation of a pressure pulse in a combustion chamber (under single and two-phase flow conditions); (4) Transonic region flowfield analysis affected by viscous effects; (5) Exploring the viscous differences between a smooth and a corrugated wall; and (6) 3D thrust chamber flowfield analysis of the Combined Cycle engine. It was shown that the LTCP-2D and LTCP-3D codes are capable of solving complex and stiff conservation equations for gaseous and droplet phases in a very robust and efficient manner. These codes can be run on a workstation and personal computers (PC's).

Navaz, Homayun K.↗

NASA NTRS1999

CFD Predictions of Sonic-Boom Characteristics for Unmodified and Modified SR-71 Configurations

Shaped sonic-boom signatures refer to signatures that look something other than the typical N-waves. Shaped sonic-boom signatures such as "flat-top," "ramp-type," or "hybrid-type" waveforms have been shown to reduce the subjective loudness without requiring reductions in overpressure peaks. The shaping of sonic-boom signatures requires increasing the shock rise time and changes in frequency spectra. So far, a flat-top waveform was shown to be achievable in wind tunnels; however, the influence of long propagation distance and real atmosphere on shaped signatures should be addressed using flight tests. Two different approaches have been proposed for sonic-boom minimization flight tests. The first approach, proposed by Eagle Aerospace, is for a flight test using a modified BQM-34 "FIREBEE" remotely piloted vehicle. The 30-foot long FIREBEE has a steady state flight condition at the Mach number and altitude of interest, and it can be recovered by helicopter from the water. As an alternative approach, a modified SR-71 vehicle has been proposed by the McDonnell Douglas Corporation. Benefits of the SR-71 include its variable geometry supersonic inlets, small cockpit bulge, higher Mach number capabilities, slender design, and longer length (105 foot). The present investigation addresses the sonic-boom analysis for the second vehicle.The objective of the current investigation is to assess the feasibility of a modified SR-71 configuration, with McDonnell Douglas-designed fuselage modifications, intended to produce shaped sonic-boom signatures on the ground. The present study describes the use of a higher-order computational fluid dynamics (CFD) method to predict the sonic-boom characteristics for both unmodified and modified SR-71 configurations. An Euler unstructured grid methodology is used to predict the near-field, three-dimensional pressure patterns generated by both SR-71 models. The computed near-field pressure signatures are extrapolated to specified distances below the aircraft down to impingement on the ground using the code MDBOOM. Comparisons of the near-field pressure signatures with available flight-test data are presented in the current paper.

Fouladi, Kamran↗

NASA NTRS2003

Low Thermal Conductivity Thermal Barrier Coatings Developed

Thermal barrier coatings (TBCs) are used extensively in modern gas turbine engines to thermally insulate air-cooled metallic components from the hot gases in the engine. These coatings typically consist of a zirconia-yttria ceramic that has been applied by either plasma spraying or physical vapor deposition. Future engines will rely even more heavily on TBCs and will require materials that have even higher temperature capability with improved insulation (i.e., lower thermal conductivity even after many hours at high temperature). This report discusses new TBCs that have been developed with these future requirements in mind. The Ultra-Efficient Engine Technology Program at the NASA Glenn Research Center is funding this effort, which has been conducted primarily at Glenn with contractor support (GE and Howmet) for physical vapor deposition. As stated, the new TBC not only had to be more insulating but the insulation had to persist even after many hours of exposure-that is, the new TBC had to have both lower conductivity and improved sintering resistance. A new type of test rig was developed for this task. This new test approach used a laser to deliver a known high heat flux in an essentially uniform pattern to the surface of the coating, thereby establishing a realistic thermal gradient across its thickness. This gradient was determined from surface and backside pyrometry; and since the heat flux and coating thickness are known, this permitted continuous monitoring of thermal conductivity. Thus, this laser rig allowed very efficient screening of candidate low-conductivity, sinter-resistant TBCs. The coating-design approach selected for these new low-conductivity TBCs was to identify oxide dopants that had the potential to promote the formation of relatively large and stable groupings of defects known as defect clusters. This approach was used because it was felt that such clusters would reduce conductivity while enhancing stability. The approach proved to be successful: low-conductivity TBCs having improved sintering resistance were developed.

Zhu, Dongming↗

NASA NTRS2009

Microfluidic Mixing Technology for a Universal Health Sensor

A highly efficient means of microfluidic mixing has been created for use with the rHEALTH sensor an elliptical mixer and passive curvilinear mixing patterns. The rHEALTH sensor provides rapid, handheld, complete blood count, cell differential counts, electrolyte measurements, and other lab tests based on a reusable, flow-based microfluidic platform. These geometries allow for cleaning in a reusable manner, and also allow for complete mixing of fluid streams. The microfluidic mixing is performed by flowing two streams of fluid into an elliptical or curvilinear design that allows the combination of the flows into one channel. The mixing is accomplished by either chaotic advection around micro - fluidic loops. All components of the microfluidic chip are flow-through, meaning that cleaning solution can be introduced into the chip to flush out cells, plasma proteins, and dye. Tests were performed on multiple chip geometries to show that cleaning is efficient in any flowthrough design. The conclusion from these experiments is that the chip can indeed be flushed out with microliter volumes of solution and biological samples are cleaned readily from the chip with minimal effort. The technology can be applied in real-time health monitoring at patient s bedside or in a doctor s office, and real-time clinical intervention in acute situations. It also can be used for daily measurement of hematocrit for patients on anticoagulant drugs, or to detect acute myocardial damage outside a hospital.

Chan, Eugene Y.↗

NASA NTRS2009

Resilient Flexible Pressure-Activated Seal

A resilient, flexible, pressure-activated, high-temperature seal is adapted to be interposed between high and low pressure regions to provide sealing between opposing surfaces of adjacent relatively movable structures. The seal comprises at least one C-shaped sheet element. The C-shaped element design enables the seal to be pressure-activated to provide a radially outward biasing force, responsive to a seal-activating pressure differential acting across the seal thereby increasing resiliency. A centrally-located, resilient core structure provides load bearing and insulating properties. In an exemplary embodiment where at least two seal elements are used, each layer has a cutout slot pattern and the remaining strip material pattern. The slots provide flexibility to the seal, enabling the seal to be manually contoured to seal around corners and curves. The strip material of each layer covers the slots in each adjacent layer to minimize leakage through the slots. Attached barrier strips can block interface leakage between the seal and the opposing surfaces.

Steinetz, Bruce M.↗

NASA NTRS2006

Instruments for Reading Direct-Marked Data-Matrix Symbols

Improved optoelectronic instruments (specially configured digital cameras) for reading direct-marked data-matrix symbols on the surfaces of optically reflective objects (including specularly reflective ones) are undergoing development. Data-matrix symbols are two-dimensional binary patterns that are used, like common bar codes, for automated identification of objects. The first data-matrix symbols were checkerboard-like patterns of black-and-white rectangles, typically existing in the forms of paint, ink, or detachable labels. The major advantage of direct marking (the marks are more durable than are painted or printed symbols or detachable labels) is offset by a major disadvantage (the marks generated by some marking methods do not provide sufficient contrast to be readable by optoelectronic instruments designed to read black-and-white data-matrix symbols). Heretofore, elaborate lighting, lensing, and software schemes have been tried in efforts to solve the contrast problem in direct-mark matrix- symbol readers. In comparison with prior readers based on those schemes, the readers now undergoing development are expected to be more effective while costing less. All of the prior direct-mark matrix-symbol readers are designed to be aimed perpendicularly to marked target surfaces, and they tolerate very little angular offset. However, the reader now undergoing development not only tolerates angular offset but depends on angular offset as a means of obtaining the needed contrast, as described below. The prototype reader (see Figure 1) includes an electronic camera in the form of a charge-coupled-device (CCD) image detector equipped with a telecentric lens. It also includes a source of collimated visible light and a source of collimated infrared light for illuminating a target. The visible and infrared illumination complement each other: the visible illumination is more useful for aiming the reader toward a target, while the infrared illumination is more useful for reading symbols on highly reflective surfaces. By use of beam splitters, the visible and infrared collimated lights are introduced along the optical path of the telecentric lens, so that the target is illuminated and viewed from the same direction.

Schramm, Harry F.↗

NASA NTRS2010

Optical Mass Gauging System for Measuring Liquid Levels in a Reduced Gravity Environment

A compact and rugged fiber-coupled liquid volume sensor designed for flight on a sounding rocket platform is presented. The sensor consists of a Mach-Zehnder interferometer capable of measuring the amount of liquid contained in a tank under any gravitational conditions, including a microgravity environment, by detecting small changes in the index of refraction of the gas contained within a sensing region. By monitoring changes in the interference fringe pattern as the system undergoes a small compression provided by a piston, the ullage volume of a tank can be directly measured allowing for a determination of the liquid volume. To demonstrate the technique, data are acquired using two tanks containing different volumes of liquid, which are representative of the levels of liquid in a tank at different time periods during a mission. The two tanks are independently exposed to the measurement apparatus, allowing for a determination of the liquid level in each. In a controlled, laboratory test of the unit, the system demonstrated a capability of measuring a liquid level in an individual tank of 10.53 mL with a 2% error. The overall random uncertainty for the flight system is higher than that one test, at +/- 1.5 mL.

Sullenberger, Ryan M.↗

NASA NTRS2021

Hybrid phenology matching model for robust crop phenological retrieval

Crop phenology regulates seasonal agroecosystem carbon, water, and energy exchanges, and is a key component in empirical and process-based crop models for simulating biogeochemical cycles of farmlands, assessing gross and net primary production, and forecasting the crop yield. The advances in phenology matching models provide a feasible means to monitor crop phenological progress using remote sensing observations, with a priori information of reference shapes and reference phenological transition dates. Yet the underlying geometrical scaling assumption of models, together with the challenge in defining phenological references, hinders the applicability of phenology matching in crop phenological studies. The objective of this study is to develop a novel hybrid phenology matching model to robustly retrieve a diverse spectrum of crop phenological stages using satellite time series. The devised hybrid model leverages the complementary strengths of phenometric extraction methods and phenology matching models. It relaxes the geometrical scaling assumption and can characterize key phenological stages of crop cycles, ranging from farming practice-relevant stages (e.g., planted and harvested) to crop development stages (e.g., emerged and mature). To systematically evaluate the influence of phenological references on phenology matching, four representative phenological reference scenarios under varying levels of phenological calibrations in terms of time and space are further designed with publicly accessible phenological information. The results indicate that the hybrid phenology matching model can achieve high accuracies for estimating corn and soybean phenological growth stages in Illinois, particularly with the year- and region-adjusted phenological reference (R-squared higher than 0.9 and RMSE less than 5 days for most phenological stages). The inter-annual and regional phenological patterns characterized by the hybrid model correspond well with those in the crop progress reports (CPRs) from the USDA National Agricultural Statistics Service (NASS). Compared to the benchmark phenology matching model, the hybrid model is more robust to the decreasing levels of phenological reference calibrations, and is particularly advantageous in retrieving crop early phenological stages (e.g., planted and emerged stages) when the phenological reference information is limited. This innovative hybrid phenology matching model, together with CPR-enabled phenological reference calibrations, holds 3 considerable promise in revealing spatio-temporal patterns of crop phenology over extended geographical regions.

Phenology↗