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NASA NTRS1952

Theoretical Investigation of the Effects of the Artificial-Feel System on the Maneuvering Characteristics of the F-89 Airplane

The possibility of overshooting the anticipated normal acceleration as a result of the artificial-feel characteristics of the F-89C airplane at a condition of minimum static stability was investigated analytically by means of an electronic simulator. Several methods of improving the stick-force characteristics were studied. It is shown that, due to the lag in build-up of the portion of the stick force introduced by the bobweight, it would be possible for excessive overshoots of normal acceleration to occur in abrupt maneuvers with reasonable assumed control movements. The addition of a transient stick force proportional to pitching acceleration (which leads the normal acceleration) to prevent this occurring would not be practical due to the introduction of an oscillatory mode to the stick-position response. A device to introduce a viscous damping force would Improve the stick-force characteristics so that normal acceleration overshoots would not be likely, and the variation of the maximum stick force in rapid pulse-type maneuvers with duration of the maneuver then would have a favorable trend.

Abramovitz, Marvin↗

NASA NTRS2010

Micromachined Artificial Haircell

A micromachined artificial sensor comprises a support coupled to and movable with respect to a substrate. A polymer, high-aspect ratio cilia-like structure is disposed on and extends out-of-plane from the support. A strain detector is disposed with respect to the support to detect movement of the support.

Liu, Chang↗

NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗

NASA NTRS2010

Study - Radiation Shielding Effectiveness of the Prototyped High Temperature Superconductivity (HTS) 'Artificial' Magnetosphere for Deep Space Missions

The high temperature superconductor (HTS) is being used to develop the magnets for the Variable Specific Impulse Magneto-plasma Rocket (VASIMR ) propulsion system and may provide lightweight magnetic radiation shielding to protect spacecraft crews from radiation caused by GCR and SPEs on missions to Mars. A study is being planned to assess the radiation shielding effectiveness of the artificial magnetosphere produced by the HTS magnet. VASIMR is an advanced technology propulsion engine which is being touted as enabling one way transit to Mars in 90 days or less. This is extremely important to NASA. This technology would enable a significant reduction in the number of days in transit to and from Mars and significantly reduce the astronauts exposure to a major threat - high energy particles from solar storms and GCR during long term deep space missions. This paper summarizes the plans for the study and the subsequent testing of the VASIMR technology onboard the ISS slated for 2013.

Denkins, Pamela↗

NASA NTRS2005

Artificial Immune System for Recognizing Patterns

A method of recognizing or classifying patterns is based on an artificial immune system (AIS), which includes an algorithm and a computational model of nonlinear dynamics inspired by the behavior of a biological immune system. The method has been proposed as the theoretical basis of the computational portion of a star-tracking system aboard a spacecraft. In that system, a newly acquired star image would be treated as an antigen that would be matched by an appropriate antibody (an entry in a star catalog). The method would enable rapid convergence, would afford robustness in the face of noise in the star sensors, would enable recognition of star images acquired in any sensor or spacecraft orientation, and would not make an excessive demand on the computational resources of a typical spacecraft. Going beyond the star-tracking application, the AIS-based pattern-recognition method is potentially applicable to pattern- recognition and -classification processes for diverse purposes -- for example, reconnaissance, detecting intruders, and mining data.

Huntsberger, Terrance↗

NASA NTRS2005

Artificial Intelligence for Controlling Robotic Aircraft

A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

Krishnakumar, Kalmanje↗

NASA NTRS2012

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Roberts, J. Brent↗

NASA NTRS2012

Implementing Artificial Intelligence Behaviors in a Virtual World

In this paper, we will present a look at the current state of the art in human-computer interface technologies, including intelligent interactive agents, natural speech interaction and gestural based interfaces. We describe our use of these technologies to implement a cost effective, immersive experience on a public region in Second Life. We provision our Artificial Agents as a German Shepherd Dog avatar with an external rules engine controlling the behavior and movement. To interact with the avatar, we implemented a natural language and gesture system allowing the human avatars to use speech and physical gestures rather than interacting via a keyboard and mouse. The result is a system that allows multiple humans to interact naturally with AI avatars by playing games such as fetch with a flying disk and even practicing obedience exercises using voice and gesture, a natural seeming day in the park.

Krisler, Brian↗

NASA NTRS2013

Characterizing the In-Phase Reflection Bandwidth Theoretical Limit of Artificial Magnetic Conductors With a Transmission Line Model

We validate through simulation and experiment that artificial magnetic conductors (AMC s) can be well characterized by a transmission line model. The theoretical bandwidth limit of the in-phase reflection can be expressed in terms of the effective RLC parameters from the surface patch and the properties of the substrate. It is found that the existence of effective inductive components will reduce the in-phase reflection bandwidth of the AMC. Furthermore, we propose design strategies to optimize AMC structures with an in-phase reflection bandwidth closer to the theoretical limit.

Xie, Yunsong↗

NASA NTRS2014

Artificial Gravity Research Plan

This document describes the forward working plan to identify what countermeasure resources are needed for a vehicle with an artificial gravity module (intermittent centrifugation) and what Countermeasure Resources are needed for a rotating transit vehicle (continuous centrifugation) to minimize the effects of microgravity to Mars Exploration crewmembers.

Cromwell, Ronita↗

NASA NTRS2014

Artificial Gravity Research Plan

Gilbert, Charlene↗

NASA NTRS2014

Training Knowledge Bots for Physics-Based Simulations Using Artificial Neural Networks

Millions of complex physics-based simulations are required for design of an aerospace vehicle. These simulations are usually performed by highly trained and skilled analysts, who execute, monitor, and steer each simulation. Analysts rely heavily on their broad experience that may have taken 20-30 years to accumulate. In addition, the simulation software is complex in nature, requiring significant computational resources. Simulations of system of systems become even more complex and are beyond human capacity to effectively learn their behavior. IBM has developed machines that can learn and compete successfully with a chess grandmaster and most successful jeopardy contestants. These machines are capable of learning some complex problems much faster than humans can learn. In this paper, we propose using artificial neural network to train knowledge bots to identify the idiosyncrasies of simulation software and recognize patterns that can lead to successful simulations. We examine the use of knowledge bots for applications of computational fluid dynamics (CFD), trajectory analysis, commercial finite-element analysis software, and slosh propellant dynamics. We will show that machine learning algorithms can be used to learn the idiosyncrasies of computational simulations and identify regions of instability without including any additional information about their mathematical form or applied discretization approaches.

Samareh, Jamshid A.↗

NASA NTRS2014

Analysis of Dual Rotating Rake Data from the NASA Glenn Advanced Noise Control Fan Duct with Artificial Sources

The Rotating Rake mode measurement system was designed to measure acoustic duct modes generated by a fan stage. Initially, the mode amplitudes and phases were quantified from a single rake measurement at one axial location. To directly measure the modes propagating in both directions within a duct, a second rake was mounted to the rotating system with an offset in both the axial and the azimuthal directions. The rotating rake data analysis technique was then extended to include the data measured by the second rake. The analysis resulted in a set of circumferential mode levels at each of the two rake microphone locations. Radial basis functions were then least-squares fit to this data to obtain the radial mode amplitudes for the modes propagating in both directions within the duct. Validation experiments have been conducted using artificial acoustic sources. Results are shown for the measurement of the standing waves in the duct from sound generated by one and two acoustic sources that are separated into the component modes propagating in both directions within the duct. Measured reflection coefficients from the open end of the duct are compared to analytical predictions.

Noise↗

NASA NTRS2015

Human Research Program Human Health Countermeasures Element: Evidence Report - Artificial Gravity

The most serious risks of long-duration flight involve radiation, behavioral stresses, and physiological deconditioning. Artificial gravity (AG), by substituting for the missing gravitational cues and loading in space, has the potential to mitigate the last of these risks by preventing the adaptive responses from occurring. The rotation of a Mars-bound spacecraft or an embarked human centrifuge offers significant promise as an effective, efficient multi-system countermeasure against the physiological deconditioning associated with prolonged weightlessness. Virtually all of the identified risks associated with bone loss, muscle weakening, cardiovascular deconditioning, and sensorimotor disturbances might be alleviated by the appropriate application of AG. However, experience with AG in space has been limited and a human-rated centrifuge is currently not available on board the ISS. A complete R&D program aimed at determining the requirements for gravity level, gravity gradient, rotation rate, frequency, and duration of AG exposure is warranted before making a decision for implementing AG in a human spacecraft.

Clement, Gilles↗

NASA NTRS1960

The Influence of the Solar Radiation Pressure on the Motion of an Artificial Satellite

This article reports an investigation of the effect of solar radiation pressure on the motion of an artificial satellite. The theory has been applied to the orbit of the Vanguard I satellite, and is found to produce significant perturbations in the perigee height of that satellite. In the case of a satellite with a large ratio of area to mass the major terms introduced by solar radiation pressure can reduce the perigee distance at the rate of 1 to 2 km per day, so that the lifetime of the satellite will become considerably shorter than it would be without this effect.

Musen, Peter↗

NASA NTRS1961

The Theory of Artificial Satellites in Terms of the Orbital True Longitude

The author's previous theory of the artificial satellite is derived in terms of the. disturbed eccentric anomaly. The present development, in terms of the orbital true longitude, is a substantial improvement over the earlier work in that it leads to the faster convergence for large eccentricities and to a smaller number of terms in the series representing the perturbations. Moreover, each approximation of the radius vector and of the parameters determining the position of the orbit plane is obtained not in the form of a truncated infinite series but in the form of trigonometric polynomials in two arguments. These arguments are the mean true anomaly and the mean argument of the latitude. The present theory, like the previous one, permits the computation of perturbations of any desired order. Thus, any future information about earth's gravitational field can easily be included.

Musen, Peter↗

NASA NTRS2016

An Artificial-Gravity Space-Settlement Ground-Analogue Design Concept

The design concept of a modular and extensible hypergravity facility is presented. Several benefits of this facility are described including that the facility is suitable as a full-scale artificial-gravity space-settlement ground analogue for humans, animals, and plants for indefinite durations. The design is applicable as an analogue for on-orbit settlements as well as those on moons, asteroids, and Mars. The design creates an extremely long-arm centrifuge using a multi-car hypergravity vehicle travelling on one or more concentric circular tracks. This design supports the simultaneous generation of multiple-gravity levels to explore the feasibility and value of and requirements for such space-settlement designs. The design synergizes a variety of existing technologies including centrifuges, tilting trains, roller coasters, and optionally magnetic levitation. The design can be incrementally implemented such that the facility can be operational for a small fraction of the cost and time required for a full implementation. Brief concept of operation examples are also presented.

Space Settlement↗

NASA NTRS2017

Enabling Autonomous Space Mission Operations with Artificial Intelligence

For over 50 years, NASA's crewed missions have been confined to the Earth-Moon system, where speed-of-light communications delays between crew and ground are practically nonexistent. This ground-centered mode of operations, with a large, ground-based support team, is not sustainable for NASAs future human exploration missions to Mars. Future astronauts will need smarter tools employing Artificial Intelligence (AI) techniques make decisions without inefficient communication back and forth with ground-based mission control. In this talk we will describe several demonstrations of astronaut decision support tools using AI techniques as a foundation. These demonstrations show that astronauts tasks ranging from living and working to piloting can benefit from AI technology development.

Frank, Jeremy↗