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NASA NTRS1980

Galactic-scale civilization

Evolutionary arguments are presented in favor of the existence of civilization on a galactic scale. Patterns of physical, chemical, biological, social and cultural evolution leading to increasing levels of complexity are pointed out and explained thermodynamically in terms of the maximization of free energy dissipation in the environment of the organized system. The possibility of the evolution of a global and then a galactic human civilization is considered, and probabilities that the galaxy is presently in its colonization state and that life could have evolved to its present state on earth are discussed. Fermi's paradox of the absence of extraterrestrials in light of the probability of their existence is noted, and a variety of possible explanations is indicated. Finally, it is argued that although mankind may be the first occurrence of intelligence in the galaxy, it is unjustified to presume that this is so.

Kuiper, T. B. H.↗

NASA NTRS2000

An Approach to Experimental Design for the Computer Analysis of Complex Phenomenon

The ability to make credible system assessments, predictions and design decisions related to engineered systems and other complex phenomenon is key to a successful program for many large-scale investigations in government and industry. Recently, many of these large-scale analyses have turned to computational simulation to provide much of the required information. Addressing specific goals in the computer analysis of these complex phenomenon is often accomplished through the use of performance measures that are based on system response models. The response models are constructed using computer-generated responses together with physical test results where possible. They are often based on probabilistically defined inputs and generally require estimation of a set of response modeling parameters. As a consequence, the performance measures are themselves distributed quantities reflecting these variabilities and uncertainties. Uncertainty in the values of the performance measures leads to uncertainties in predicted performance and can cloud the decisions required of the analysis. A specific goal of this research has been to develop methodology that will reduce this uncertainty in an analysis environment where limited resources and system complexity together restrict the number of simulations that can be performed. An approach has been developed that is based on evaluation of the potential information provided for each "intelligently selected" candidate set of computer runs. Each candidate is evaluated by partitioning the performance measure uncertainty into two components - one component that could be explained through the additional computational simulation runs and a second that would remain uncertain. The portion explained is estimated using a probabilistic evaluation of likely results for the additional computational analyses based on what is currently known about the system. The set of runs indicating the largest potential reduction in uncertainty is then selected and the computational simulations are performed. Examples are provided to demonstrate this approach on small scale problems. These examples give encouraging results. Directions for further research are indicated.

Rutherford, Brian↗

NASA NTRS1994

SIGMA: A Knowledge-Based Simulation Tool Applied to Ecosystem Modeling

The need for better technology to facilitate building, sharing and reusing models is generally recognized within the ecosystem modeling community. The Scientists' Intelligent Graphical Modelling Assistant (SIGMA) creates an environment for model building, sharing and reuse which provides an alternative to more conventional approaches which too often yield poorly documented, awkwardly structured model code. The SIGMA interface presents the user a list of model quantities which can be selected for computation. Equations to calculate the model quantities may be chosen from an existing library of ecosystem modeling equations, or built using a specialized equation editor. Inputs for dim equations may be supplied by data or by calculation from other equations. Each variable and equation is expressed using ecological terminology and scientific units, and is documented with explanatory descriptions and optional literature citations. Automatic scientific unit conversion is supported and only physically-consistent equations are accepted by the system. The system uses knowledge-based semantic conditions to decide which equations in its library make sense to apply in a given situation, and supplies these to the user for selection. "Me equations and variables are graphically represented as a flow diagram which provides a complete summary of the model. Forest-BGC, a stand-level model that simulates photosynthesis and evapo-transpiration for conifer canopies, was originally implemented in Fortran and subsequenty re-implemented using SIGMA. The SIGMA version reproduces daily results and also provides a knowledge base which greatly facilitates inspection, modification and extension of Forest-BGC.

Dungan, Jennifer L.↗

NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Reinforcement Learning

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. The goal of reinforcement learning is for an agent to learn a policy (task strategy) through interactions with an environment. When the agent performs an action, a change occurs in environment state and a numerical reward is received which informs the agent whether the action performed was good or not. Since reinforcement learning algorithms learn through trial-and-error, a simulation is a desirable first environment for development and learning. We developed two simulations, the first is a 2D excavation simulation developed to facilitate parameter selection, and a 3D simulation developed using a game physics engine, to simulate simplified soil interactions and increase the fidelity of the dynamic models of the robotic agents. The development of this 3D simulation has enabled the training of additional sensing capabilities and research both at the granular mechanics and operations levels. We experimented with various virtual sensor payloads to identify a combination that enabled efficient excavation operation and learning. Our reward function is based on how much material is excavated per step. A penalty is also received for leaving the dig site and to smooth the acceleration of the drum arms. We implemented pseudo time-of-flight sensors to report distance from each drum to ground and the height above ground which was found to be more efficient than existing solutions. Our findings suggest that reinforcement learning for autonomous operations has learned viable trenching strategies within 3000 training episodes in our simplified 2D environment and helped identify desirable sensing capabilities, arrangements, and considerations such as the positioning of time-of-flight sensors. Future work includes expanding our simulation to more complex environments and scenarios, and transfer learning from simulation to RASSOR 2.0 hardware for deployment in the Regolith Test Bin at NASA's Kennedy Space Center.

rassor↗

NASA NTRS1989

Computer simulation of the mathematical modeling involved in constitutive equation development: Via symbolic computations

Development of new material models for describing the high temperature constitutive behavior of real materials represents an important area of research in engineering disciplines. Derivation of mathematical expressions (constitutive equations) which describe this high temperature material behavior can be quite time consuming, involved and error prone; thus intelligent application of symbolic systems to facilitate this tedious process can be of significant benefit. A computerized procedure (SDICE) capable of efficiently deriving potential based constitutive models, in analytical form is presented. This package, running under MACSYMA, has the following features: partial differentiation, tensor computations, automatic grouping and labeling of common factors, expression substitution and simplification, back substitution of invariant and tensorial relations and a relational data base. Also limited aspects of invariant theory were incorporated into SDICE due to the utilization of potentials as a starting point and the desire for these potentials to be frame invariant (objective). Finally not only calculation of flow and/or evolutionary laws were accomplished but also the determination of history independent nonphysical coefficients in terms of physically measurable parameters, e.g., Young's modulus, was achieved. The uniqueness of SDICE resides in its ability to manipulate expressions in a general yet predefined order and simplify expressions so as to limit expression growth. Results are displayed when applicable utilizing index notation.

Arnold, S. M.↗

NASA NTRS2008

Spaceborne Processor Array

A Spaceborne Processor Array in Multifunctional Structure (SPAMS) can lower the total mass of the electronic and structural overhead of spacecraft, resulting in reduced launch costs, while increasing the science return through dynamic onboard computing. SPAMS integrates the multifunctional structure (MFS) and the Gilgamesh Memory, Intelligence, and Network Device (MIND) multi-core in-memory computer architecture into a single-system super-architecture. This transforms every inch of a spacecraft into a sharable, interconnected, smart computing element to increase computing performance while simultaneously reducing mass. The MIND in-memory architecture provides a foundation for high-performance, low-power, and fault-tolerant computing. The MIND chip has an internal structure that includes memory, processing, and communication functionality. The Gilgamesh is a scalable system comprising multiple MIND chips interconnected to operate as a single, tightly coupled, parallel computer. The array of MIND components shares a global, virtual name space for program variables and tasks that are allocated at run time to the distributed physical memory and processing resources. Individual processor- memory nodes can be activated or powered down at run time to provide active power management and to configure around faults. A SPAMS system is comprised of a distributed Gilgamesh array built into MFS, interfaces into instrument and communication subsystems, a mass storage interface, and a radiation-hardened flight computer.

Chow, Edward T.↗

NASA NTRS2004

Three-Dimensional High-Resolution Optical/X-Ray Stereoscopic Tracking Velocimetry

Measurement of three-dimensional (3-D) three-component velocity fields is of great importance in a variety of research and industrial applications for understanding materials processing, fluid physics, and strain/displacement measurements. The 3-D experiments in these fields most likely inhibit the use of conventional techniques, which are based only on planar and optically-transparent-field observation. Here, we briefly review the current status of 3-D diagnostics for motion/velocity detection, for both optical and x-ray systems. As an initial step for providing 3-D capabilities, we nave developed stereoscopic tracking velocimetry (STV) to measure 3-D flow/deformation through optical observation. The STV is advantageous in system simplicity, for continually observing 3- D phenomena in near real-time. In an effort to enhance the data processing through automation and to avoid the confusion in tracking numerous markers or particles, artificial neural networks are employed to incorporate human intelligence. Our initial optical investigations have proven the STV to be a very viable candidate for reliably measuring 3-D flow motions. With previous activities are focused on improving the processing efficiency, overall accuracy, and automation based on the optical system, the current efforts is directed to the concurrent expansion to the x-ray system for broader experimental applications.

Cha, Soyoung S.↗

NASA NTRS2005

Three-Dimensional High-Resolution Optical/X-Ray Stereoscopic Tracking Velocimetry

Measurement of three-dimensional (3-D) three-component velocity fields is of great importance in a variety of research and industrial applications for understanding materials processing, fluid physics, and strain/displacement measurements. The 3-D experiments in these fields most likely inhibit the use of conventional techniques, which are based only on planar and optically-transparent-field observation. Here, we briefly review the current status of 3-D diagnostics for motion/velocity detection, for both optical and x-ray systems. As an initial step for providing 3-D capabilities, we have developed stereoscopic tracking velocimetry (STV) to measure 3-D flow/deformation through optical observation. The STV is advantageous in system simplicity, for continually observing 3-D phenomena in near real-time. In an effort to enhance the data processing through automation and to avoid the confusion in tracking numerous markers or particles, artificial neural networks are employed to incorporate human intelligence. Our initial optical investigations have proven the STV to be a very viable candidate for reliably measuring 3-D flow motions. With previous activities focused on improving the processing efficiency, overall accuracy, and automation based on the optical system, the current efforts is directed to the concurrent expansion to the x-ray system for broader experimental applications.

Cha, Soyoung S.↗

NASA NTRS1993

An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence

This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation.

Lindley, Craig A.↗

NASA NTRS2012

A Model-Based Approach to Engineering Behavior of Complex Aerospace Systems

One of the most challenging yet poorly defined aspects of engineering a complex aerospace system is behavior engineering, including definition, specification, design, implementation, and verification and validation of the system's behaviors. This is especially true for behaviors of highly autonomous and intelligent systems. Behavior engineering is more of an art than a science. As a process it is generally ad-hoc, poorly specified, and inconsistently applied from one project to the next. It uses largely informal representations, and results in system behavior being documented in a wide variety of disparate documents. To address this problem, JPL has undertaken a pilot project to apply its institutional capabilities in Model-Based Systems Engineering to the challenge of specifying complex spacecraft system behavior. This paper describes the results of the work in progress on this project. In particular, we discuss our approach to modeling spacecraft behavior including 1) requirements and design flowdown from system-level to subsystem-level, 2) patterns for behavior decomposition, 3) allocation of behaviors to physical elements in the system, and 4) patterns for capturing V&V activities associated with behavioral requirements. We provide examples of interesting behavior specification patterns, and discuss findings from the pilot project.

SysML↗

NASA NTRS2000

Internet Technologies for Space-based Communications: State of the Art and Challenges

The Internet is rapidly changing the ways we communicate information around the globe today. The desire to provide Internet-based services to anyone, anywhere, anytime has brought satellite communications to the forefront to become an integral part of the Internet. In spite of the distances involved, satellite links are proving to be capable of providing Internet services based on Internet protocol (TCP/IP) stack. This development has led to the question particularly at NASA; can satellites and other space platforms become an Internet-node in space? This will allow the direct transfer of information directly from space to the users on Earth and even be able to control the spacecraft and its instruments. NASA even wants to extend the near earth space Internet to deep space applications where scientists and the public here on Earth may view space exploration in real time via the Internet. NASA's future solar system exploration will involve intensive in situ investigations of planets, moons, asteroids, and comets. While past missions typically involved a single fly-by or orbiting science spacecraft, future missions will begin to use fleets of small, highly intelligent robotic vehicles to carry out collaborative investigations. The resulting multi-spacecraft topologies will effectively create a wide area network spanning the solar system. However, this will require significant development in Internet technologies for space use. This paper provides the status'of the Internet for near earth applications and the potential extension of the Internet for use in deep space planetary exploration. The paper will discuss the overall challenges of implementing the space Internet and how the space Internet will integrate into the complex terrestrial systems those forms the Internet of today in a hybrid set of networks. Internet. We envision extending to the deep space environment such Internet concepts as a well-designed layered architecture. This effort will require an ability to develop and infuse new physical layer technology to increase network bandwidth at very low-bit error rates. In addition, we identify network technologies such as routers and switches needed to maintain standard application layer interfaces, while providing low-cost, efficient, modular networking solutions. We will describe the overall architectural approach to extending the concept of the Internet to space and highlight the important technological challenges and initiatives that will make it a reality.

Bhasin, K.↗

NASA NTRS2003

A Real-Time Rover Executive based On Model-Based Reactive Planning

This paper reports on the experimental verification of the ability of IDEA (Intelligent Distributed Execution Architecture) effectively operate at multiple levels of abstraction in an autonomous control system. The basic hypothesis of IDEA is that a large control system can be structured as a collection of interacting control agents, each organized around the same fundamental structure. Two IDEA agents, a system-level agent and a mission-level agent, are designed and implemented to autonomously control the K9 rover in real-time. The system is evaluated in the scenario where the rover must acquire images from a specified set of locations. The IDEA agents are responsible for enabling the rover to achieve its goals while monitoring the execution and safety of the rover and recovering from dangerous states when necessary. Experiments carried out both in simulation and on the physical rover, produced highly promising results.

Bias, M. Bernardine↗

NASA NTRS2018

An Evolutionary Computation System Design Concept for Developing Controlled Closed Ecosystems: An Intelligent Systems Approach to Foster Gravitational Ecosystem Research for Developing Sustainable Communities in Space and on Earth

An adjustably-autonomous intelligent systems approach for developing Closed Ecosystems (CESs) is presented, which includes a design concept and preliminary design details for the Controlled Closed-Ecosystem Development System (CCEDS) and the Orbiting Modular Artificial-Gravity Spacecraft (OMAGS). The paper is divided into three sections: CESs, the CCEDS Design Concept, and Orbiting Fractional-Gravity Closed Ecosystems OMAGS design concept. The first section briefly describes Closed EcoSystems (CESs), complex adaptive systems, biomes, microbial microbiomes, and their relevance for the study of astrobiology. This section also discusses initial efforts in the development of Closed Environment Life Support Systems (CELSSs) for sustainable communities in space and on Earth. This section concludes with a discussion of the bioregenerative life support system challenge of and the corresponding consequences due to the inverse relationship of the very small human biomass/non-human biomass ratio overall on the Earth with respect to the extremely large human biomass/non-human-biomass ratio found in cities and the International Space Station. The second section describes the CCEDS design concept, which consists of a population of controlled colonies of CES Modules (CESMs), each an integrated CES, continually generating data for an intelligent system that operates the CESs and their CESMs. A variety of CESM types and their use are briefly described. The CCEDS intelligent system uses an evolutionary computation algorithm described in this section to develop and optimize these CESs to increase their viability duration and the size of the animals they support with the ultimate goal to support populations of humans, both on Earth and in space. The CCEDS architecture, its five control subsystems, and its five evolutionary computation levels are also discussed. The section concludes with a discussion of several CCEDS design strategies. The third section summarizes the OMAGS design concept for a spacecraft with a payload consisting of CESs in an orbiting spacecraft centrifuge that operates for at least 5 years. The spacecraft concept is described including its 150cm-radius centrifuge with a 2 ton & 3,000 liter bioscience payload capacity for 24 CESMs. The centrifuge design has four physical levels for its CESMs, each level subject to a different fractional gravity level. This section presents the spacecraft benefits of being designed and operated such that the spacecraft and payload centrifuge wheel counter-rotate resulting in net zero angular momentum and zero gyroscopic forces. Artificial-gravity generation by centripetal acceleration is also discussed. This section concludes by showing the external specifications of the CESMs and their layout in the centrifuge, followed by discussing the multi-payload module rationale. In tandem, the CCEDS and OMAGS systems can be used to foster gravitational ecosystem research for developing sustainable communities in space and on Earth.

Dorais, Gregory A.↗

NASA NTRSDate not supplied

Development of Physics-Based Transition Models for Unstructured-Mesh CFD Codes Using Deep Learning Models

Predicting transition locations over a vehicle surface is of fundamental importance for many engineering applications. With the transition information, the Reynolds-averaged Navier-Stokes (RANS) computations can turn on the turbulence model at the right locations so that drag, lift and other aerodynamic quantities can be accurately predicted. In contrast to the popularity of RANS-based transition modeling in which transition onset is governed by the turbulence equations, physics-based transition models that account for instability waves within the boundary layer, thus more compliant to flow physics, only gained more attention in recent years. This paper describes the development of a new physics-based transition model based on either the linear stability theory (LST) or parabolized stability equations (PSE). The model is designed to communicate with a structured or unstructured-mesh RANS solver back and forth in order to more accurately compute transition fronts over a three-dimensional body. In the developed model, the Python suite of interface codes in conjunction with the LASTRAC software can be executed autonomously to produce transition onset locations for a given laminar or RANS-computed transitional state. In addition, as a proof of concept, the tool set consists of a deep learning neural network model that has been designed and trained to predict instability wave evolutions inside the boundary layer for various instability wave mechanisms across a selected speed range. A machine-learned intelligent profile interpolation model has also been devised to enable reliable instability-wave spectra predictions with just a few points in the mean flow profiles.

Transition Modeling↗

NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗

NASA NTRS2018

A Study of Shape Memory Polymer Based Slat-Cove Filler

Aircraft noise reduction is an application of current intense interest for which smart materials show significant potential. Specifically, the aeroacoustic noise produced by the unsteady aerodynamic flow about the leading-edge high-lift device, such as leading-edge slat, of typical transport-aircraft wings is of particular interest. Concepts with the most promise to mitigate this noise source, most notably the slat-cove filler concept, have focused on highly reconfigurable structures that change shape between different phases of the flight envelope. These shape changes often involve large deformation, which has stimulated the consideration of shape memory materials. In recent years, shape memory materials (SMMs) have drawn greater interest for applications such as smart fabrics, intelligent medical devices, self-deployable space structures, morphing structures and packaging. Compared to other shape memory materials, like shape memory alloys (SMAs) or shape memory ceramics (SMCs), shape memory polymers (SMPs) have desirable advantages such as high elastic deformation to enable large shape change, broad tailorability of mechanical properties, potential biocompatibility and biodegradability, ductility, light weight and ease of processing. However, SMPs still have some critical disadvantages such as insufficient mechanical and thermal characteristics for structural applications, low recovery stress, and long response time. The new LaRC shape memory thermosetting polymer composite (LaRC-SMPC) discussed herein was synthesized with nontoxic monomers and conductive/magnetic fillers to yield enhanced thermal/mechanical characteristics and faster response times. LaRC-SMPCs with a variety of fiber reinforcements [Kevlar®, carbon fiber (standard and thin-ply), and carbon-nanotube (CNT) sheet] were fabricated to tailor the physical properties and test for suitability as a slat-cove filler (SCF). The performance of SCF prototypes fabricated with the developed LaRC-SMPCs was evaluated using a bench-top test apparatus. The SCFs made of Kevlar® fiber fabric or carbon fiber fabric infused shape memory polymer composite (SMPC) exhibited kinking during simulated deployment and stowage, which can be problematic during operation. The SCF made of CNT sheet/SMP composite did not exhibit kinking, but the deployment was sluggish compared to carbon fiber fabric/SMP composite. This report documents the evolution of designing SMPCs as slat-cove fillers for aircraft noise reduction. In the course of the investigation, several 2 approaches were investigated to address shortcomings in material characteristics based on performance requirements of operational slat-cove fillers.

Kang, Jin Ho↗

NASA NTRS2017

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Signal Recognition↗

NASA NTRS2017

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

Signal Classification↗