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NASA NTRS2024

Short–Period Variables in TESS Full–Frame Image Light Curves Identified via Convolutional Neural Networks

The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ∼85% of the sky throughout its 2 yr primary mission, resulting in millions of TESS 30-minute-cadence light curves to analyze in the search for transiting exoplanets. To search this vast data set, we aim to provide an approach that is computationally efficient, produces accurate predictions, and minimizes the required human search effort. We present a convolutional neural network that we train to identify short-period variables. To make a prediction for a given light curve, our network requires no prior target parameters identified using other methods. Our network performs inference on a TESS 30-minute-cadence light curve in ∼5 ms on a single GPU, enabling large-scale archival searches. We present a collection of 14,156 short-period variables identified by our network. The majority of our identified variables fall into two prominent populations, one of close-orbit main-sequence binaries and another of δ Scuti stars. Our neural network model and related code are additionally provided as open-source code for public use and extension.

Convolutional neural networks↗

NASA NTRS2004

Constructing an Educational Mars Simulation

January 14th 2004, President George Bush announces his plans to catalyst the space program into a new era of space exploration and discovery. His vision encompasses a robotics program to explore our solar system, a return to the moon, the human exploration of Mars, and to promote international prosperity towards our endeavors. We at NASA now have the task of constructing this vision in a very real timeframe. I have been chosen to begin phase 1 of making this vision a reality. I will be working on creating an Educational Mars Simulation of human exploration of Mars to stimulate interest and involvement with the project from investors and the community. GRC s Computer Services Division (CSD) in collaboration with the Office of Education Programs will be designing models, constructing terrain, and programming this simulation to create a realistic portrayal of human exploration on mars. With recent and past technological breakthroughs in computing, my primary goal can be accomplished with only the aid of 3-4 software packages. Lightwave 3D is the modeling package we have selected to use for the creation of our digital objects. This includes a Mars pressurized rover, rover cockpit, landscape/terrain, and habitat. Once we have the models completed they need textured so Photoshop and Macromedia Fireworks are handy for bringing these objects to life. Before directly importing all of this data into a simulation environment, it is necessary to first render a stunning animation of the desired final product. This animation with represent what we hope to capture out of the simulation and it will include all of the accessories like ray-tracing, fog effects, shadows, anti-aliasing, particle effects, volumetric lighting, and lens flares. Adobe Premier will more than likely be used for video editing and adding ambient noises and music. Lastly, V-Tree is the real-time 3D graphics engine which will facilitate our realistic simulation. Additional information is included in the original extended abstract.

Henke, Stephen A.↗

NASA NTRS2017

The Challenges of Human-Autonomy Teaming

Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.

artificial intelligence↗

NASA NTRS2017

The Challenges of Human-Autonomy Teaming

Human-Autonomy teaming↗

NASA NTRS2011

NASA Aerosciences Activities to Support Human Space Flight

The Lyndon B. Johnson Space Center (JSC) has been a critical element of the United State's human space flight program for over 50 years. It is the home to NASA s Mission Control Center, the astronaut corps, and many major programs and projects including the Space Shuttle Program, International Space Station Program, and the Orion Project. As part of JSC's Engineering Directorate, the Applied Aeroscience and Computational Fluid Dynamics Branch is charted to provide aerosciences support to all human spacecraft designs and missions for all phases of flight, including ascent, exo-atmospheric, and entry. The presentation will review past and current aeroscience applications and how NASA works to apply a balanced philosophy that leverages ground testing, computational modeling and simulation, and flight testing, to develop and validate related products. The speaker will address associated aspects of aerodynamics, aerothermodynamics, rarefied gas dynamics, and decelerator systems, involving both spacecraft vehicle design and analysis, and operational mission support. From these examples some of NASA leading aerosciences challenges will be identified. These challenges will be used to provide foundational motivation for the development of specific advanced modeling and simulation capabilities, and will also be used to highlight how development activities are increasing becoming more aligned with flight projects. NASA s efforts to apply principles of innovation and inclusion towards improving its ability to support the myriad of vehicle design and operational challenges will also be briefly reviewed.

LeBeau, Gerald J.↗

NASA NTRS1997

Verifying Stability of Dynamic Soft-Computing Systems

Soft computing is a general term for algorithms that learn from human knowledge and mimic human skills. Example of such algorithms are fuzzy inference systems and neural networks. Many applications, especially in control engineering, have demonstrated their appropriateness in building intelligent systems that are flexible and robust. Although recent research have shown that certain class of neuro-fuzzy controllers can be proven bounded and stable, they are implementation dependent and difficult to apply to the design and validation process. Many practitioners adopt the trial and error approach for system validation or resort to exhaustive testing using prototypes. In this paper, we describe our on-going research towards establishing necessary theoretic foundation as well as building practical tools for the verification and validation of soft-computing systems. A unified model for general neuro-fuzzy system is adopted. Classic non-linear system control theory and recent results of its applications to neuro-fuzzy systems are incorporated and applied to the unified model. It is hoped that general tools can be developed to help the designer to visualize and manipulate the regions of stability and boundedness, much the same way Bode plots and Root locus plots have helped conventional control design and validation.

Wen, Wu↗

NASA NTRS1990

A New Continent of Ideas

While a new technology called 'virtual reality' is still at the 'ground floor' level, one of its basic components, 3D computer graphics is already in wide commercial use and expanding. Other components that permit a human operator to 'virtually' explore an artificial environment and to interact with it are being demonstrated routinely at Ames and elsewhere. Virtual reality might be defined as an environment capable of being virtually entered - telepresence, it is called - or interacted with by a human. The Virtual Interface Environment Workstation (VIEW) is a head-mounted stereoscopic display system in which the display may be an artificial computer-generated environment or a real environment relayed from remote video cameras. Operator can 'step into' this environment and interact with it. The DataGlove has a series of fiber optic cables and sensors that detect any movement of the wearer's fingers and transmit the information to a host computer; a computer generated image of the hand will move exactly as the operator is moving his gloved hand. With appropriate software, the operator can use the glove to interact with the computer scene by grasping an object. The DataSuit is a sensor equipped full body garment that greatly increases the sphere of performance for virtual reality simulations.

Source record↗

NASA NTRS2004

NASA Johnson Space Center Usability Testing and Analysis Facility (UTAF) Overview

The Usability Testing and Analysis Facility (UTAF) is part of the Space Human Factors Laboratory at the NASA Johnson Space Center in Houston, Texas. The facility provides support to the Office of Biological and Physical Research, the Space Shuttle Program, the International Space Station Program, and other NASA organizations. In addition, there are ongoing collaborative research efforts with external businesses and universities. The UTAF provides human factors analysis, evaluation, and usability testing of crew interfaces for space applications. This includes computer displays and controls, workstation systems, and work environments. The UTAF has a unique mix of capabilities, with a staff experienced in both cognitive human factors and ergonomics. The current areas of focus are: human factors applications in emergency medical care and informatics; control and display technologies for electronic procedures and instructions; voice recognition in noisy environments; crew restraint design for unique microgravity workstations; and refinement of human factors processes. This presentation will provide an overview of ongoing activities, and will address how the projects will evolve to meet new space initiatives.

Whitmore, M.↗

NASA NTRS2004

NASA Johnson Space Center Usability Testing and Analysis Facility (WAF) Overview

Whitmore, M.↗

NASA NTRS2005

NASA Johnson Space Center Usability Testing and Analysis facility (UTAF) Overview

The Usability Testing and Analysis Facility (UTAF) is part of the Space Human Factors Laboratory at the NASA Johnson Space Center in Houston, Texas. The facility performs research for NASA's HumanSystems Integration Program, under the HumanSystems Research and Technology Division. Specifically, the UTAF provides human factors support for space vehicles, including the International Space Station, the Space Shuttle, and the forthcoming Crew Exploration Vehicle. In addition, there are ongoing collaborative research efforts with external corporations and universities. The UTAF provides human factors analysis, evaluation, and usability testing of crew interfaces for space applications. This includes computer displays and controls, workstation systems, and work environments. The UTAF has a unique mix of capabilities, with a staff experienced in both cognitive human factors and ergonomics. The current areas of focus are: human factors applications in emergency medical care and informatics; control and display technologies for electronic procedures and instructions; voice recognition in noisy environments; crew restraint design for unique microgravity workstations; and refinement of human factors processes and requirements. This presentation will provide an overview of ongoing activities, and will address how the UTAF projects will evolve to meet new space initiatives.

Whitmore, Mihriban↗

NASA NTRS2018

Tropical Cyclone Intensity Estimation Using Deep Convolutional Neural Networks

Estimating tropical cyclone intensity by just using satellite image is a challenging problem. With successful application of the Dvorak technique for more than 30 years along with some modifications and improvements, it is still used worldwide for tropical cyclone intensity estimation. A number of semi-automated techniques have been derived using the original Dvorak technique. However, these techniques suffer from subjective bias as evident from the most recent estimations on October 10, 2017 at 1500 UTC for Tropical Storm Ophelia: The Dvorak intensity estimates ranged from T2.3/33 kt (Tropical Cyclone Number 2.3/33 knots) from UW-CIMSS (University of Wisconsin-Madison - Cooperative Institute for Meteorological Satellite Studies) to T3.0/45 kt from TAFB (the National Hurricane Center's Tropical Analysis and Forecast Branch) to T4.0/65 kt from SAB (NOAA/NESDIS Satellite Analysis Branch). In this particular case, two human experts at TAFB and SAB differed by 20 knots in their Dvorak analyses, and the automated version at the University of Wisconsin was 12 knots lower than either of them. The National Hurricane Center (NHC) estimates about 10-20 percent uncertainty in its post analysis when only satellite based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to tropical cyclone intensity. This study aims to utilize deep learning, the current state of the art in pattern recognition and image recognition, to address the need for an automated and objective tropical cyclone intensity estimation. Deep learning is a multi-layer neural network consisting of several layers of simple computational units. It learns discriminative features without relying on a human expert to identify which features are important. Our study mainly focuses on convolutional neural network (CNN), a deep learning algorithm, to develop an objective tropical cyclone intensity estimation. CNN is a supervised learning algorithm requiring a large number of training data. Since the archives of intensity data and tropical cyclone centric satellite images is openly available for use, the training data is easily created by combining the two. Results, case studies, prototypes, and advantages of this approach will be discussed.

tropical cyclone intensity↗

NASA NTRS2026

Development of the METMAN Thermal Desktop Human Model for System Integration

Human thermal analysis and model development inform NASA’s space suit development, vehicle/habitat design, and survivability studies. Historically, human thermal models such as the 41-node metabolic man (METMAN) and the Wissler model have been standalone software tools developed with FORTRAN, a programming language known for its high performance in computationally intensive applications. Though efficient, these standalone programs pose challenges to coupled human-system analysis with detailed life support and thermal control subsystem models in other commercial software. This paper describes the conversion of the METMAN human thermal model from a standalone FORTRAN program to a model in Thermal Desktop (Ansys), a commonly used CAD-based simulation software for engineering that specializes in heat transfer, thermal radiation, and fluid flow analysis. This format was chosen to best facilitate model sharing and compatibility, enabling the direct integration of METMAN human thermal analysis with subsystem models across NASA programs and commercial partners.

Elizabeth Thurston↗

NASA NTRSDate not supplied

Experiments for Securing Air Traffic Against Cyber-Physical System Attacks

This presentation describes experiments conducted with single board computers to investigate methods for creating trust for enabling the development of cyber-resilient air transportation systems. Methods included secure communication to prevent unauthorized access to data, consistency of data obtained via sensors and by processing, and built-in safeguards to prevent mission failure. The motivation for this work are the following. The future air transportation system needs to ensure availability, integrity, confidentiality and safety of operations. Safety of vehicles and operations is paramount for successful integration of Urban Air Mobility (UAM), Unmanned Aerial Systems (UAS), supersonic aircraft and launch vehicles with conventional aviation operations in the National Airspace System. Security is becoming critical because the sensors, networks and computers are far more vulnerable to bad actors than their mechanical or human predecessors. The goal therefore is to design and develop cyber-resilient systems that continue to function even in degraded states. The main findings are (1) off-the-shelf hardware can support development of cyber-resilient onboard flight computers and (2) trust in system design and implementation can be accomplished by integrating layers in depth (detail) and in breadth (scope).

cyber-resilient autonomy, trust, secure communicat↗

NASA NTRSDate not supplied

The Ocean’s Breath: How Autonomous Robotic Vehicles at Sea and Super Computers are Helping us Understand the Carbon Cycle in the Ocean

Carbon dioxide due to human activities such as fossil fuel burning has well-known and concerning implications for global temperatures as well as terrestrial and marine ecosystems. Hence, an important objective of NASA Earth science is to observe and understand the variations in the global carbon cycle and the associated climate and ecosystem impacts in the context of past and projected anthropogenic emissions. In my presentation, I will tell the story of how some of my collaborators and I are using autonomous robotic vehicles and super computers to try to untangle the mysteries of the carbon cycle in the ocean, which depends in fascinating ways on atmospheric and ocean physics, marine ecosystem dynamics, as well as the chemistry of the seawater.

Ocean's breath↗

NASA NTRS1993

Modelling decision-making by pilots

Our scientific goal is to understand the process of human decision-making. Specifically, a model of human decision-making in piloting modern commercial aircraft which prescribes optimal behavior, and against which we can measure human sub-optimality is sought. This model should help us understand such diverse aspects of piloting as strategic decision-making, and the implicit decisions involved in attention allocation. Our engineering goal is to provide design specifications for (1) better computer-based decision-aids, and (2) better training programs for the human pilot (or human decision-maker, DM).

Patrick, Nicholas J. M.↗

NASA NTRS2000

Intelligence Applied to Air Vehicles

The exponential growth in information technology has provided the potential for air vehicle capabilities that were previously unavailable to mission and vehicle designers. The increasing capabilities of computer hardware and software, including new developments such as neural networks, provide a new balance of work between humans and machines. This paper will describe several NASA projects, and review results and conclusions from ground and flight investigations where vehicle intelligence was developed and applied to aeronautical and space systems. In the first example, flight results from a neural network flight control demonstration will be reviewed. Using, a highly-modified F-15 aircraft, a NASA/Dryden experimental flight test program has demonstrated how the neural network software can correctly identify and respond to changes in aircraft stability and control characteristics. Using its on-line learning capability, the neural net software would identify that something in the vehicle has changed, then reconfigure the flight control computer system to adapt to those changes. The results of the Remote Agent software project will be presented. This capability will reduce the cost of future spacecraft operations as computers become "thinking" partners along with humans. In addition, the paper will describe the objectives and plans for the autonomous airplane program and the autonomous rotorcraft project. Technologies will also be developed.

Rosen, Robert↗

NASA NTRS1993

The coming technological singularity: How to survive in the post-human era

The acceleration of technological progress has been the central feature of this century. I argue in this paper that we are on the edge of change comparable to the rise of human life on Earth. The precise cause of this change is the imminent creation by technology of entities with greater than human intelligence. There are several means by which science may achieve this breakthrough (and this is another reason for having confidence that the event will occur): (1) the development of computers that are 'awake' and superhumanly intelligent (to date, most controversy in the area of AI relates to whether we can create human equivalence in a machine. But if the answer is 'yes, we can', then there is little doubt that beings more intelligent can be constructed shortly thereafter); (2) large computer networks (and their associated users) may 'wake up' as a superhumanly intelligent entity; (3) computer/human interfaces may become so intimate that users may reasonably be considered superhumanly intelligent; and (4) biological science may find ways to improve upon the natural human intellect. The first three possibilities depend in large part on improvements in computer hardware. Progress in computer hardware has followed an amazingly steady curve in the last few decades. Based largely on this trend, I believe that the creation of greater than human intelligence will occur during the next thirty years.

Vinge, Vernor↗

NASA NTRS2011

Human Factors Operability Timeline Analysis to Improve the Processing Flow of the Orion Spacecraft

This slide presentation reviews the use of Human factors and timeline analysis to have a more efficient and effective processing flow. The solution involved developing a written timeline of events that included each activity within each functional flow block. Each activity had computer animation videos and pictures of the people involved and the hardware. The Human Factors Engineering Analysis Tool (HFEAT) was improved by modifying it to include the timeline of events. The HFEAT was used to define the human factors requirements and design solutions were developed for these requirements. An example of a functional flow block diagram is shown, and a view from one of the animations (i.e., short stack pallet) is shown and explained.

Stambolian, Damon B.↗