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At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Stratified Volume Diffractive Optical Elements as Low-Mass Coherent Lidar Scanners

Transmissive scanning elements for coherent laser radar systems are typically optical wedges, or prisms, which deflect the lidar beam at a specified angle and are then rotated about the instrument optical axis to produce a scan pattern. The wedge is placed in the lidar optical system subsequent to a beam-expanding telescope, implying that it has the largest diameter of any element in the system. The combination of the wedge diameter and asymmetric profile result in the element having very large mass and, consequently, relatively large power consumption required for scanning. These two parameters, mass and power consumption, are among the instrument requirements which need to be minimized when designing a lidar for a space-borne platform. Reducing the scanner contributions in these areas will have a significant effect on the overall instrument specifications, Replacing the optical wedge with a diffraction grating on the surface of a thin substrate is a straight forward approach with potential to reduce the mass of the scanning element significantly. For example, the optical wedge that will be used for the SPAce Readiness Coherent Lidar Experiment (SPARCLE) is approximately 25 cm in diameter and is made from silicon with a wedge angle designed for 30 degree deflection of a beam operating at approx. 2 micrometer wavelength. The mass of this element could be reduced by a factor of four by instead using a fused silica substrate, 1 cm thick, with a grating fabricated on one of the surfaces. For a grating to deflect a beam with a 2 micrometer wavelength by 30 degrees, a period of approximately 4 micrometers is required. This is small enough that fabrication of appropriate high efficiency blazed or multi-phase level diffractive optical gratings is prohibitively difficult. Moreover, bulk or stratified volume holographic approaches appear impractical due to materials limitations at 2 micrometers and the need to maintain adequate wavefront quality. In order to avoid the difficulties encountered in these approaches, we have developed a new type of high-efficiency grating which we call a Stratified Volume Diffractive Optical Element (SVDOE). The features of the gratings in this approach can be easily fabricated using standard photolithography and etching techniques and the materials used in the grating can be chosen specifically for a given application, In this paper we will briefly discuss the SVDOE technique and will present an example design of a lidar scanner using this approach. We will also discuss performance predictions for the example design.

Chambers, Diana M.↗
NASA NTRS2016

Characterization of Potential Springs in the Lower Colorado Desert of Southern California using Satellite Radar and Landsat Time Series Analysis

Renewable energy development in southern California is receiving increasing attention due to potential impacts on wildlife habitats and water sources. This study was designed to quantify and map, for the first time, sub-surface water sources from springs in the Lower Colorado Desert area of southern California using satellite radar data and 30 years of Landsat satellite image data. Synthetic Aperture Radar (SAR) data was used to identify sub-surface water sources not already documented as springs or seeps in the National Hydrography Database. Landsat imagery starting in 1985 was used to characterize vegetation growth patterns at these suspected spring locations detected from SAR analysis. Results showed a total of 104 potential spring locations across the Lower Colorado Desert study area, 19 of which were detected within Solar Energy Zone (SEZ) development boundaries, roughly evenly split between Riverside East and Imperial East, and 13 of which (both inside and outside SEZs) showed relatively high green vegetation index values over the period of 1985 to 2015 that would depend on non-precipitation water sources associated with active springs.

DRECP↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27509-DND

The information about composition of aerosols has a great importance for monitoring and understanding of climate and environment dynamics. Such information can be obtained using situ measurements or chemical transport models. However, in situ sampling has limited spatial and temporal coverage, while estimations have large uncertainties. The present work enables the monitoring of aerosol chemical species from space-borne observations, providing observationally-based results with spatial and temporal coverage. Following the ideas of Schuster et al.(2005, 2009, 2016), we retrieve chemical composition directly from satellite observations without intermediate retrieval of the refractive index (in contrast with Schuster's approach). This approach is expected to reduce the influence of modeling uncertainties, and to provide additional constraints in situations where remote sensing observations do not have enough spectral sensitivity to refractive index. One of principal difficulties is the identification of an adequate model for linking refractive index to chemical composition. Therefore, the initial effort of this work has focused on identifying an optimal physico-chemistry to refractive index conversion model. With that purpose, we first tested the retrieval approach using a simplified volume-weighting model and updated by the Maxwell Garnett mixing model. This concept was incorporated into the GRASP algorithm designed to retrieve an extended set of atmospheric parameters from remote sensing observations. Then a series of sensitivity tests using synthetic data of POLDER/PARASOL were conducted, and followed by inversion of real PARASOL observations over Africa. The sensitivity tests showed that these two models allow the retrieval to distinguish amongst the assumed chemical species. Results obtained from real PARASOL data demonstrated good agreement with the optical characteristics provided by AERONET. In addition, the obtained patterns of chemical component distribution agreed with known physical expectations. We also compared the chemical composition retrievals to GOCART model simulations and obtained good consistencies.

Lei Li↗
NASA NTRS2019

HelioSwarm: Swarm Mission Design in High Altitude Orbit for Heliophysics

Resolving the complex three-dimensional turbulent structures that characterize the solar wind requires contemporaneous spatially and temporally distributed measurements. HelioSwarm is a mission concept that will deploy multiple, co-orbiting satellites to use the solar wind as a natural laboratory for understanding the fundamental, universal process of plasma turbulence. The HelioSwarm transfer trajectory and science orbit use a lunar gravity assist to deliver the ESPA-class nodes attached to a large data transfer hub to a P/2 lunar resonant orbit. Once deployed in the science orbit, the free-flying, propulsive nodes use simple Cartesian relative motion patterns to establish baseline separations both along and across the solar wind flow direction.

lunar resonant orbit↗
NASA NTRS2019

HelioSwarm: Swarm Mission Design in High Altitude Orbit for Heliophysics

Resolving the complex three-dimensional turbulent structures that characterize the solar wind requires contemporaneous spatially and temporally distributed measurements. HelioSwarm is a mission concept that will deploy multiple, co-orbiting satellites to use the solar wind as a natural laboratory for understanding the fundamental, universal process of plasma turbulence. The HelioSwarm transfer trajectory and science orbit use a lunar gravity assist to deliver the ESPA-class nodes attached to a large data transfer hub to a P/2 lunar resonant orbit. Once deployed in the science orbit, the free-flying, propulsive nodes use simple Cartesian relative motion patterns to establish baseline separations both along and across the solar wind flow direction.

lunar resonant orbit↗
NASA NTRS1979

The charge injection device /CID/ as a stellar tracking sensor

A 128 x 128 element CID imager was operated in a simulated stellar trackling environment and evaluated for temporal and pattern noise and spectral response over a temperature range of -40 C to +25 C. The test devices were fabricated on long-lifetime bulk silicon material and utilized very thin upper-level polysilicon electrodes for enhanced spectral response. A standard microcomputer was used to generate all control signals and to collect and process performance data. The results of this program were used to predict the performance of a 400 x 400 CID array designed specifically for stellar-tracking.

Burke, H. K.↗
NASA NTRS1981

Effects of curved approach paths and advanced displays on pilot scan patterns

The effect on pilot scan behavior of both advanced cockpit and advanced manuevers was assessed. A series of straight-in and curved landing approaches were performed in the Terminal Configured Vehicle (TCV) simulator. Two comparisons of pilot scan behavior were made: (1) pilot scan behavior for straight-in approaches compared with scan behavior previously obtained in a conventionally equipped simulator, and (2) pilot scan behavior for straight-in approaches compared with scan behavior for curved approaches. The results indicate very similar scanning patterns during the straight-in approaches in the conventional and advanced cockpits. However, for the curved approaches pilot attention shifted to the electronic horizontal situation display (moving map), and a new eye scan path appeared between the map and the airspeed indicator. The very high dwell percentage and dwell times on the electronic displays in the TCV simulator during the final portions of the approaches suggest that the electronic attitude direction indicator was well designed for these landing approaches.

Harris, R. L., Sr.↗
NASA NTRS1986

Incipient fault detection study for advanced spacecraft systems

A feasibility study to investigate the application of vibration monitoring to the rotating machinery of planned NASA advanced spacecraft components is described. Factors investigated include: (1) special problems associated with small, high RPM machines; (2) application across multiple component types; (3) microgravity; (4) multiple fault types; (5) eight different analysis techniques including signature analysis, high frequency demodulation, cepstrum, clustering, amplitude analysis, and pattern recognition are compared; and (6) small sample statistical analysis is used to compare performance by computation of probability of detection and false alarm for an ensemble of repeated baseline and faulted tests. Both detection and classification performance are quantified. Vibration monitoring is shown to be an effective means of detecting the most important problem types for small, high RPM fans and pumps typical of those planned for the advanced spacecraft. A preliminary monitoring system design and implementation plan is presented.

Milner, G. Martin↗
NASA NTRS1993

The importance of properties in modeling

Casting and welding of superalloys, stainless steel and titanium alloys are processes which can be improved through modeling of heat flow, fluid flow, residual stress development, and microstructural evolution. These simulations require inputs of thermophysical data, some of which involves the partially or totally liquid state. In particular, these processes involve melting, flow in the liquid, and solidification. Modeling of such processes can lead to an improved understanding of defects such as shrinkage, inclusions, cracks, incomplete filling (or penetration), macrosegregation, improper grain structure, and deviations from dimensional specifications. Effective modeling can shorten process development time and improve quality. An approach to these problems is to develop efficient models; validate through correlations with thermal, distortion, and microstructural data; run parametric studies; extract knowledge based rules; and apply to adaptive closed loop control systems. With the appropriate pre- and post-processing, such analyses can be made 'user friendly'. This would include graphical user interfaces as well as realistic images and color maps. In such form, these models can be used for sensitivity analyses, which are useful in defining appropriate sensors and in the development of control strategies. Such modeling can be done at several levels, e.g., the MARO level, modeling large scale phenomena such as heat and fluid flow or material deformation; the MICRO level, modeling the development of dendrites, grains or precipitates; or at the NANO level, modeling point defects, dislocations, stacking faults, etc. There are many computational issues associated with these simulations, e.g. computational efficiency and accuracy. In addition, there are many materials issues, not the least of which is the availability of accurate high temperature thermophysical data for complex alloys. This would include latent heat of fusion, temperature dependent heat capacity and thermal conductivity (for liquid and solid), viscosity, surface tension, thermal expansion, mechanical properties, etc. Preliminary data is frequently gathered from the literature; however, this is often not available for modern alloys. If additional data are required, measurements can be used; however, these are costly, time consuming and can be erroneous due to a lack of testing standards or impure materials. Microstructural predictors can be extracted from thermal information, e.g. cooling rate and thermal gradient; the prediction of microstructure is dependent on solidus and liquidus temperature, mushy zone permeability, the solidification curve, volume changes, phase transformations, alloying effects (such as surface tension or viscosity), mold/metal reactions, metal/environment reactions, etc. Defect maps may be needed to predict the onset of shrinkage, hot cracking or 'freckling'. Constants may be needed for stress relaxation, dendrite coarsening, vaporization, etc. Visualization was used as a tool to better comprehend complex data sets associated with the analysis of directional solidification (including crystal growth) and welding. Examples include not only isotherms, but also cooling rate, growth rate and thermal gradient. The latter two are not single valued scalars, but rather time and space dependent vector fields. Efficient models were developed for both casting and welding to predict heat flow and the relationship to dendrite and grain growth. These codes include many of the non-linear effects, e.g. radiation, which dominate these processes. The home-built FDM code(s) were designed to be useful not only to the scientist, but also to the process engineer. Special output can be requested to compare directly to experimental data. Visualization procedures were developed to visualize critical results, e.g. fusion zone width at the surface opposite that where the arc is applied ('penetration'). Both elaborate and simplified distortion analyses were carried out. It is clear that extensive mechanical property data are critical in order to accurately predict residual stress patterns. A scheme is currently being developed to integrate these modeling tools into a set of control algorithms; however, the success of this approach is critically dependent on the availability of accurate high temperature thermophysical data.

Giamei, A. F.↗
NASA NTRS1997

Precision Casting via Advanced Simulation and Manufacturing

A two-year program was conducted to develop and commercially implement selected casting manufacturing technologies to enable significant reductions in the costs of castings, increase the complexity and dimensional accuracy of castings, and reduce the development times for delivery of high quality castings. The industry-led R&D project was cost shared with NASA's Aerospace Industry Technology Program (AITP). The Rocketdyne Division of Boeing North American, Inc. served as the team lead with participation from Lockheed Martin, Ford Motor Company, Howmet Corporation, PCC Airfoils, General Electric, UES, Inc., University of Alabama, Auburn University, Robinson, Inc., Aracor, and NASA-LeRC. The technical effort was organized into four distinct tasks. The accomplishments reported herein. Task 1.0 developed advanced simulation technology for core molding. Ford headed up this task. On this program, a specialized core machine was designed and built. Task 2.0 focused on intelligent process control for precision core molding. Howmet led this effort. The primary focus of these experimental efforts was to characterize the process parameters that have a strong impact on dimensional control issues of injection molded cores during their fabrication. Task 3.0 developed and applied rapid prototyping to produce near net shape castings. Rocketdyne was responsible for this task. CAD files were generated using reverse engineering, rapid prototype patterns were fabricated using SLS and SLA, and castings produced and evaluated. Task 4.0 was aimed at developing technology transfer. Rocketdyne coordinated this task. Casting related technology, explored and evaluated in the first three tasks of this program, was implemented into manufacturing processes.

Source record↗
NASA NTRSDate not supplied

Exploring Requirements for Software that Learns: A Research Preview

Context & motivation: The development of software that learns has revolutionized how many systems perform. For the most part, these systems are neither safety- nor mission-critical. However, as technology and aspirations advance, there is an increased desire and need for Machine Learning (ML) software in safety- and mission-critical systems, e.g., driverless cars or autonomous space robotics. Problem: In these domains, reliability is crucial and systems have to undergo much scrutiny in terms of both the developed artefacts and the adopted development process. Central to the development of such systems is the elicitation and definition of software requirements that are used to guide the design and verification process. The addition of software components that learn, and the associated capability for unforeseen behavior, makes defining detailed software requirements especially difficult. Principal ideas/results: In this paper, we identify unique characteristics of software requirements that are specific to ML components. To this end, we collect and examine requirements from both academic and industrial sources. Contribution: To the best of our knowledge, this is the first work that presents real-life, industrial patterns of requirements for ML components. Furthermore, this paper identifies key characteristics and provides a foundation for developing a taxonomy of requirements for software that learns.

Probabilistic requirements↗
NASA NTRS1972

On the elastic properties of fiber composite laminates with statistically dispersed ply orientations

Structural application of advanced composite filamentary materials requires lamination of the basic orthotropic plies into angle-ply laminates. The resulting elastic and strength properties depend on the pattern of orientation and are influenced by inevitable errors and inaccuracy in placement of the angle plies. Reviewed is the effect on elastic properties of orientation dispersion. The conventional constitutive relations are recast in a homologous form to account for orientation dispersion by addition of a single parameter. Graphical results are presented to show the behavior of the most important advanced composite materials. The results are directly useful for estimating effects of manufacturing inaccuracy and for design of partially oriented reinforced structures.

Robinson, E. Y.↗
NASA NTRS1985

Human factors studies of control configurations for advanced transport aircraft

This research investigated the threshold levels of display luminance contrast which were required to interpret static, achromatic, integrated displays of primary flight information. A four-factor within-subjects design was used to investigate the influences of type of flight variable information, the level of ambient illumination, the type of control input, and the size of the display symbology on the setting of these interpretability thresholds. A three-alternative forced choice paradigm was used in conjunction with the method of adjustments to obtain a measure of the upper limen of display luminance contrast needed to interpret a complex display of primary flight information. The pattern of results and the absolute magnitudes of the luminance contrast settings were found to be in good agreement with previously reported data from psychophysical investigations of display luminance contrast requirements.

Snyder, Harry L.↗
NASA NTRS1991

The effect of a type 3 and type 4 shock/shock interaction on heat transfer in the stagnation region

One of the major engineering challenges in designing the National Aerospace Plane, NASP, is to overcome augmented heating on the intake cowl lip from shock/shock interactions. The shock/shock interaction arises when the bow shock from the craft's nose interferes with the bow shock from the cowl lip. Considering only the region immediately around the cowl lip, the problem geometry may be simplified as that of an oblique shock impinging on a bow shock from a circular cylinder. Edney classified six different interference patterns resulting from an oblique-shock/curved bow-shock interaction. Of these six types, type 3 and 4 are most significant in that augmented surface heat transfer may be ten to thirty times greater than the case without the shock/shock interaction. The objective was to begin to develop a mathematical model which is capable of predicting the effect of a type 3 and 4 shock/shock interaction in the stagnation region of an arbitrary 2-D body. This model must be capable of predicting the maximum surface heat flux and the surface stagnation point pressure once the outer (effectively inviscid) flowfield is given. Therefore, it must capture the unsteady physics of the impinging shear layer.

Wilson, Dennis↗
NASA NTRS1992

The cognitive bases for the design of a new class of fuzzy logic controllers: The clearness transformation fuzzy logic controller

This paper analyses the internal operation of fuzzy logic controllers as referenced to the human cognitive tasks of control and decision making. Two goals are targeted. The first goal focuses on the cognitive interpretation of the mechanisms employed in the current design of fuzzy logic controllers. This analysis helps to create a ground to explore the potential of enhancing the functional intelligence of fuzzy controllers. The second goal is to outline the features of a new class of fuzzy controllers, the Clearness Transformation Fuzzy Logic Controller (CT-FLC), whereby some new concepts are advanced to qualify fuzzy controllers as 'cognitive devices' rather than 'expert system devices'. The operation of the CT-FLC, as a fuzzy pattern processing controller, is explored, simulated, and evaluated.

Sultan, Labib↗
NASA NTRS1997

Emulating the Visual Receptive Field Properties of MST Neurons with a Template Model of Heading Estimation

We have previously proposed a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. The model detectors were designed to extract self-translation (heading), self-rotation, as well as the scene layout (relative distances) ahead of a moving observer, and are arranged in cortical-like heading maps to perform this function. Heading estimation from optic flow has been postulated by some to be implemented within the medial superior temporal (MST) area. Others have questioned whether MST neurons can fulfill this role because some of their receptive-field properties appear inconsistent with a role in heading estimation. To resolve this issue, we systematically compared MST single-unit responses with the outputs of model detectors under matched stimulus conditions. We found that the basic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support heading estimation and that the template model provides an explicit set of testable hypotheses which can guide future exploration of MST and adjacent areas within the primate superior temporal sulcus.

Perrone, John A.↗
NASA NTRS2010

Development of Testing Station for Prototype Rover Thermal Subsystem

In order to successfully and efficiently explore the moon or other planets, a vehicle must be built to assist astronauts as they travel across the surface. One concept created to meet this need is NASA's Space Exploration Vehicle (SEV). The SEV, a small pressurized cabin integrated onto a 12-wheeled chassis, can support two astronauts up to 14 days. Engineers are currently developing the second generation of the SEV, with the goal of being faster, more robust, and able to carry a heavier payload. In order to function properly, the rover must dissipate heat produced during operation and maintain an appropriate temperature profile inside the rover. If these activities do not occur, components of the rover will start to break down, eventually leading to the failure of the rover. On the rover, these requirements are the responsibility of the thermal subsystem. My project for the summer was to design and build a testing station to facilitate the design and testing of the new thermal subsystem. As the rover develops, initial low fidelity parts can be interchanged for the high fidelity parts used on the rover. Based on a schematic of the proposed thermal system, I sized and selected parts for each of the components in the thermal subsystem. For the components in the system that produced heat but had not yet been finalized or fabricated, I used power resistors to model their load patterns. I also selected all of the fittings to put the system together and a mounting platform to support the testing station. Finally, I implemented sensors at various points in the system to measure the temperature, pressure, and flow rate, and a data acquisition system to collect this information. In the future, the information from these sensors will be used to study the behavior of the subsystem under different conditions and select the best part for the rover.

Burlingame, Kaitlin↗
NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗