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NASA NTRSDate not supplied

ICME: The Design of Fit-for-Purpose Materials

With the increased emphasis on reducing the cost and time to market of new materials, ICME (Integrated Computational Materials Engineering) has become a fast growing discipline within materials science and engineering. The vision of ICME is compelling in many respects, not only for the value added in reducing time to market for new products with advanced, tailored materials, but also for enhanced efficiency and performance of these materials. Although the challenges and barriers (both technical and cultural) are formidable, substantial cost, schedule, and technical benefits can result from broad development, implementation, and validation of ICME principles. ICME is an integrated approach to the design of products, and the materials that comprise them, by linking material and structural models at multiple time and length scales. NASA’s Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) in 2016 to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review ICME, the findings of the 2040 Vision study, and discuss NASA’s TTT 2040 implementation activities: with special emphasis on recent accomplishments. The 2040 study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems by enabling the engineer to not only “design-with-the” material but also concurrently “design-the” material.

multiscale analysis↗
NASA NTRS2015

NASA's Vision for Potential Energy Reduction from Future Generations of Propulsion Technology

Through a robust partnership with the aviation industry, over the past 50 years NASA programs have helped foster advances in propulsion technology that enabled substantial reductions in fuel consumption for commercial transports. Emerging global trends and continuing environmental concerns are creating challenges that will very likely transform the face of aviation over the next 20-40 years. In recognition of this development, NASA Aeronautics has established a set of Research Thrusts that will help define the future direction of the agency's research technology efforts. Two of these thrusts, Ultra-Efficient Commercial Vehicles and Transition to Low-Carbon Propulsion, serve as cornerstones for the Advanced Air Transport Technology (AATT) project. The AATT project is exploring and developing high-payoff technologies and concepts that are key to continued improvement in energy efficiency and environmental compatibility for future generations of fixed-wing, subsonic transports. The AATT project is primarily focused on the N+3 timeframe, or 3 generations from current technology levels. As should be expected, many of the propulsion system architectures technologies envisioned for N+3 vary significantly from todays engines. The use of batteries in a hybrid-electric configuration or deploying multiple fans distributed across the airframe to enable higher bypass ratios are just two examples of potential advances that could enable substantial energy reductions over current propulsion systems.

Airbreathing Propulsion↗
NASA NTRS1984

Computer vision for real-time orbital operations. Center directors discretionary fund

Machine vision research is examined as it relates to the NASA Space Station program and its associated Orbital Maneuvering Vehicle (OMV). Initial operation of OMV for orbital assembly, docking, and servicing are manually controlled from the ground by means of an on board TV camera. These orbital operations may be accomplished autonomously by machine vision techniques which use the TV camera as a sensing device. Classical machine vision techniques are described. An alternate method is developed and described which employs a syntactic pattern recognition scheme. It has the potential for substantial reduction of computing and data storage requirements in comparison to the Two-Dimensional Fast Fourier Transform (2D FFT) image analysis. The method embodies powerful heuristic pattern recognition capability by identifying image shapes such as elongation, symmetry, number of appendages, and the relative length of appendages.

Vinz, F. L.↗
NASA NTRS1989

Implementation of an algorithm for cylindrical object identification using range data

One of the problems in 3-D object identification and localization is addressed. In robotic and navigation applications the vision system must be able to distinguish cylindrical or spherical objects as well as those of other geometric shapes. An algorithm was developed to identify cylindrical objects in an image when range data is used. The algorithm incorporates the Hough transform for line detection using edge points which emerge from a Sobel mask. Slices of the data are examined to locate arcs of circles using the normal equations of an over-determined linear system. Current efforts are devoted to testing the computer implementation of the algorithm. Refinements are expected to continue in order to accommodate cylinders in various positions. A technique is sought which is robust in the presence of noise and partial occlusions.

Bozeman, Sylvia T.↗
NASA NTRS2005

Demonstration of Four Operating Capabilities to Enable a Small Aircraft Transportation System

The Small Aircraft Transportation System (SATS) project has been a five-year effort fostering research and development that could lead to the transformation of our country s air transportation system. It has become evident that our commercial air transportation system is reaching its peak in terms of capacity, with numerous delays in the system and the demand keeps steadily increasing. The SATS vision is to increase mobility in our nation s transportation system by expanding access to more than 3400 small community airports that are currently under-utilized. The SATS project has focused its efforts on four key operating capabilities that have addressed new emerging technologies and procedures to pave the way for a new way of air travel. The four key operating capabilities are: Higher Volume Operations at Non-Towered/Non-Radar Airports, En Route Procedures and Systems for Integrated Fleet Operations, Lower Landing Minimums at Minimally Equipped Landing Facilities, and Increased Single Pilot Performance. These four capabilities are key to enabling low-cost, on-demand, point-to-point transportation of goods and passengers utilizing small aircraft operating from small airports. The focus of this paper is to discuss the technical and operational feasibility of the four operating capabilities and demonstrate how they can enable a small aircraft transportation system.

Viken, Sally A.↗
NASA NTRS2019

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗
NASA NTRS1991

Energy functions for regularization algorithms

Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.

Delingette, H.↗
NASA NTRS1993

Infrared sensors and systems for enhanced vision/autonomous landing applications

There exists a large body of data spanning more than two decades, regarding the ability of infrared imagers to 'see' through fog, i.e., in Category III weather conditions. Much of this data is anecdotal, highly specialized, and/or proprietary. In order to determine the efficacy and cost effectiveness of these sensors under a variety of climatic/weather conditions, there is a need for systematic data spanning a significant range of slant-path scenarios. These data should include simultaneous video recordings at visible, midwave (3-5 microns), and longwave (8-12 microns) wavelengths, with airborne weather pods that include the capability of determining the fog droplet size distributions. Existing data tend to show that infrared is more effective than would be expected from analysis and modeling. It is particularly more effective for inland (radiation) fog as compared to coastal (advection) fog, although both of these archetypes are oversimplifications. In addition, as would be expected from droplet size vs wavelength considerations, longwave outperforms midwave, in many cases by very substantial margins. Longwave also benefits from the higher level of available thermal energy at ambient temperatures. The principal attraction of midwave sensors is that staring focal plane technology is available at attractive cost-performance levels. However, longwave technology such as that developed at FLIR Systems, Inc. (FSI), has achieved high performance in small, economical, reliable imagers utilizing serial-parallel scanning techniques. In addition, FSI has developed dual-waveband systems particularly suited for enhanced vision flight testing. These systems include a substantial, embedded processing capability which can perform video-rate image enhancement and multisensor fusion. This is achieved with proprietary algorithms and includes such operations as real-time histograms, convolutions, and fast Fourier transforms.

Kerr, J. Richard↗
NASA NTRS2012

Quantifying Pilot Visual Attention in Low Visibility Terminal Operations

Quantifying pilot visual behavior allows researchers to determine not only where a pilot is looking and when, but holds implications for specific behavioral tracking when these data are coupled with flight technical performance. Remote eye tracking systems have been integrated into simulators at NASA Langley with effectively no impact on the pilot environment. This paper discusses the installation and use of a remote eye tracking system. The data collection techniques from a complex human-in-the-loop (HITL) research experiment are discussed; especially, the data reduction algorithms and logic to transform raw eye tracking data into quantified visual behavior metrics, and analysis methods to interpret visual behavior. The findings suggest superior performance for Head-Up Display (HUD) and improved attentional behavior for Head-Down Display (HDD) implementations of Synthetic Vision System (SVS) technologies for low visibility terminal area operations. Keywords: eye tracking, flight deck, NextGen, human machine interface, aviation

Ellis, Kyle K.↗
NASA NTRS2020

UAM Vision Concept of Operations (ConOps) UAM Maturity Level (UML) 4

This Vision ConOps is intended as a foundation to engage members of the UAM community and provide a consensus on the future vision of UAM operations. It provides a concept for more detailed discussion and a basis for the exploration of ideas using a common framework to inform the continued development and integration of UAM as part of the broader transportation system. Advanced Air Mobility (AAM) encompasses a range of innovative aviation technologies (small drones, electric aircraft, automated air traffic management, etc.) that are transforming aviation’s role in everyday life, including the movement of goods and people. Urban Air Mobility (UAM) represents one of the most exciting and complex AAM concepts with highly automated aircraft, providing commercial services to the public over densely populated cities. This concept has generated tremendous interest and industry investment. UAM envisages a future in which advanced technologies and new operational procedures enable practical, cost-effective air travel as an integral mode of transportation in metropolitan areas. It represents one of the most exciting and complex AAM concepts with highly automated aircraft providing commercial services to the public over densely populated cities. For this reason, the National Aeronautics and Space Administration (NASA) selected UAM as the initial goal of its AAM efforts and the focus of this Vision Concept of Operations (ConOps) document. UAM Community Vision ConOps: This Vision ConOps effort was led by experts from NASA’s Aeronautics Research Mission Directorate (ARMD) in collaboration with the Federal Aviation Administration (FAA) and Deloitte’s Ecosystem Advisory Group (a cohort of advisers with aviation, aerospace, and regulatory expertise). To develop this Vision ConOps, NASA, FAA, and Deloitte built upon the current body of aeronautical research and consulted with more than 100 stakeholder organizations. This UAM community includes entities ranging from legacy aviation leaders to innovators and new market entrants. Stakeholders consulted included the federal government, state and local government, aerospace original equipment manufacturers (OEMs), local transportation organizations, prospective UAM operators, academia, industry standards-setting bodies, airports, service suppliers, and others (as described in Appendix G). This input was captured through the following methods: • A series of more than two dozen interviews with industry experts, federal regulators, state and local governments, and industry trade groups provided insight into the challenges of UAM integration into the National Airspace System (NAS), as well as technology developments and a variety of perspectives as to how UAM systems will integrate. • A series of two-day community workshops enabling active, detailed engagement of nearly 100 industry, academic, federal, and state stakeholder individuals. These workshops, hosted by NASA and Deloitte, explored UAM concepts in detail, and stakeholders were invited to collaboratively analyze and propose solutions to some of the greatest conceptual challenges behind UAM at an intermediate state. • A review of more than 160 sources of UAM literature from across government, industry, and academia, which are listed in Appendix H. • The public sharing of workshop input and document drafts for review and input across the UAM community. Feedback in the form of more than 1,000 comments and inputs on the document was received from industry groups, individual companies, academia, and government (federal, state, and local), among others. Although effort was made to incorporate inputs from across the UAM stakeholder group, not all comments could ultimately be incorporated in this version. The team resolved conflicting comments or ideas while maintaining consistency with the known direction of regulators and ensuring the document was coherent and consistent. It is recognized that this is a rapidly evolving area and that concepts will likely change over time; as such, this Vision ConOps is a living document and is expected to evolve as concepts mature. The ConOps does, however, provide a vision of UAM concepts and solutions based on the broad insights from across the UAM stakeholder community at the time of its publication and is intended to serve as a UAM North Star for continued research and development of UAM. As a broad Vision ConOps, is not a detailed engineering document; rather, it focuses primarily on outlining a broad, high-level vision across all aspects of a UAM transportation system.

Urban Air Mobility↗
NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

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 feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗
NASA NTRS2008

The Stellar Imager (SI) Vision Mission and the Benefits of an Ares V Launch

The Stellar Imager (SI) is a UV/Optical, Space-Based Interferometer designed to enable 0.1 milli-arcsecond (mas) spectral imaging of stellar surfaces and, via asteroseismology, stellar interiors and of the Universe in general. The ultra-sharp images of the Stellar Imager will revolutionize our view of many dynamic astrophysical processes by transforming point sources into extended sources, and snapshots into evolving views. SI's science focuses on the role of magnetism in the Universe, particularly on magnetic activity on the surfaces of stars like the Sun. SI's prime goal is to enable long-term forecasting of solar activity and the space weather that it drives. SI will also revolutionize our understanding of the formation of planetary systems, of the habitability and climatology of distant planets, and of many magneto-hydrodynamically controlled processes in the Universe. SI is a "Flagship and Landmark Discovery Mission" in the 2005 Heliophysics Roadmap and a potential implementation of the UVOI in the 2006 Science Program for NASA's Astronomy and Physics Division. In this paper we briefly discuss the science goals, technology needs, and baseline design of the SI Mission, and then describe the benefits to the mission that a launch on an Ares V, with its larger payload shroud, would produce. Additional information on SI can be found at: http://hires.gsfc.nasa.gov/si/.

Carpenter, Kenneth F.↗
NASA NTRS2006

Direct Imaging of Stellar Surfaces: Results from the Stellar Imager (SI) Vision Mission Study

The Stellar Imager (SI) is a UV-Optical, Space-Based Interferometer designed to enable 0.1 milli-arcsecond (mas) spectral imaging of stellar surfaces and stellar interiors (via asteroseismology) and of the Universe in general. SI is identified as a "Flagship and Landmark Discovery Mission'' in the 2005 Sun Solar System Connection (SSSC) Roadmap and as a candidate for a "Pathways to Life Observatory'' in the Exploration of the Universe Division (EUD) Roadmap (May, 2005). The ultra-sharp images of the Stellar Imager will revolutionize our view of many dynamic astrophysical processes: The 0.1 mas resolution of this deep-space telescope will transform point sources into extended sources, and snapshots into evolving views. SI's science focuses on the role of magnetism in the Universe, particularly on magnetic activity on the surfaces of stars like the Sun. SI's prime goal is to enable long-term forecasting of solar activity and the space weather that it drives in support of the Living With a Star program in the Exploration Era. SI will also revolutionize our understanding of the formation of planetary systems, of the habitability and climatology of distant planets, and of many magneto-hydrodynamically controlled processes in the Universe. In this paper we will discuss the results of the SI Vision Mission Study, elaborating on the science goals of the SI Mission and a mission architecture that could meet those goals.

Carpenter, Kenneth↗
NASA NTRS2015

SLS Launched Missions Concept Studies for LUVOIR Mission

NASA's "Enduring Quests Daring Visions" report calls for an 8- to 16-meter Large UV-Optical-IR (LUVOIR) Surveyor mission to enable ultra-high-contrast spectroscopy and coronagraphy. AURA's "From Cosmic Birth to Living Earth" report calls for a 12-meter class High-Definition Space Telescope to pursue transformational scientific discoveries. The multi-center ATLAST Team is working to meet these needs. The MSFC Team is examining potential concepts that leverage the advantages of the SLS (Space Launch System). A key challenge is how to affordably get a large telescope into space. The JWST design was severely constrained by the mass and volume capacities of its launch vehicle. This problem is solved by using an SLS Block II-B rocket with its 10-m diameter x 30-m tall fairing and 45 mt payload to SE-L2. Previously, two development study cycles produced a detailed concept called ATLAST-8. Using ATLAST-8 as a point of departure, this paper reports on a new ATLAST-12 concept. ATLAST-12 is a 12-meter class segmented aperture LUVOIR with an 8-m class center segment. Thus, ATLAST-8 is now a de-scope option.

Mirror↗
NASA NTRS2016

Potential Large Decadal Missions Enabled by Nasas Space Launch System

Large space telescope missions have always been limited by their launch vehicle's mass and volume capacities. The Hubble Space Telescope (HST) was specifically designed to fit inside the Space Shuttle and the James Webb Space Telescope (JWST) is specifically designed to fit inside an Ariane 5. Astrophysicists desire even larger space telescopes. NASA's "Enduring Quests Daring Visions" report calls for an 8- to 16-m Large UV-Optical-IR (LUVOIR) Surveyor mission to enable ultra-high-contrast spectroscopy and coronagraphy. AURA's "From Cosmic Birth to Living Earth" report calls for a 12-m class High-Definition Space Telescope to pursue transformational scientific discoveries. NASA's "Planning for the 2020 Decadal Survey" calls for a Habitable Exoplanet Imaging (HabEx) and a LUVOIR as well as Far-IR and an X-Ray Surveyor missions. Packaging larger space telescopes into existing launch vehicles is a significant engineering complexity challenge that drives cost and risk. NASA's planned Space Launch System (SLS), with its 8 or 10-m diameter fairings and ability to deliver 35 to 45-mt of payload to Sun-Earth-Lagrange-2, mitigates this challenge by fundamentally changing the design paradigm for large space telescopes. This paper reviews the mass and volume capacities of the planned SLS, discusses potential implications of these capacities for designing large space telescope missions, and gives three specific mission concept implementation examples: a 4-m monolithic off-axis telescope, an 8-m monolithic on-axis telescope and a 12-m segmented on-axis telescope.

Technology↗
NASA NTRS1989

Applications of algebraic image operators to model-based vision

A highly structured and compact algebraic representation of grey-level images is expanded. Addition and multiplication are defined for the set of all grey-level images, which can then be described as polynomials of two variables. Utilizing this new algebraic structure, an innovative, efficient edge-detection scheme is devised. A robust method for linear feature extraction is developed by combining the techniques of a Hough transform and a line follower with this new edge detection scheme. The major advantage of this feature extractor is its general, object-independent nature. Target attributes, such as line segment lengths, intersections, angles of intersection, and endpoints are derived by the feature extraction algorithm and employed during model matching. The feature extractor and model matcher are being incorporated into a distributed robot-control system.

Lerner, Bao-Ting↗
NASA NTRS2006

Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System

Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion

Hines, Glenn D.↗
NASA NTRS2011

Image Segmentation, Registration, Compression, and Matching

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

Yadegar, Jacob↗