NASA Scientific and Technical Aerospace Reports

A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical
Decision Generator (TDG) for Within Visual Range (WVR) air combat engagements is discussed. The application of AI
programming and problem solving methods in the development and implementation of the Computerized Logic For Air-to-Air
Warfare Simulations (CLAWS), a second generation TDG, is presented. The Knowledge-Based Systems used by CLAWS to
aid in the tactical decision-making process are outlined in detail, and the results of tests to evaluate the performance of
CLAWS versus a baseline TDG developed in FORTRAN to run in real-time in the Langley Differential Maneuvering
Simulator (DMS), are presented. To date, these test results have shown significant performance gains with respect to the TDG
baseline in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify
and maintain than the baseline FORTRAN TDG programs. Alternate computing environments and programming approaches,
including the use of parallel algorithms and heterogeneous computer networks are discussed, and the design and performance
of a prototype concurrent TDG system are presented.
Author
Artificial Intelligence; Expert Systems; Flight Simulators; Applications Programs (Computers)
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NUMERICAL ANALYSIS
Includes iteration, differential and difference equations, and numerical approximation.
20040111033 Rice Univ., Houston, TX, USA
Assimilative Forecasting of the Energetic Particle Environment
Naehr, S.; Toffoletto, F.; 8th Spacecraft Charging Technology Conference; March 2004; 14 pp.; In English; See also
20040111031; No Copyright; Avail: CASI; A03, Hardcopy
We present a computational approach to specifying and forecasting the outer radiation belt particle distribution, by
incorporating data from space-based measurements. In this approach, a Kalman-Bucy filter is designed to assimilate particle
flux data from a spacecraft spanning a broad range of particle drift paths. A spatial analysis algorithm is used to incorporate
this data into the framework of a physics-based forecast model, using the statistical error structures of the model and data to
produce an optimal estimate. The assimilation algorithm is validated in a set of experiments simulating a magnetic storm,
using artificial magnetic field and particle flux data fabricated by an independent model. The simulated data is compared to
the model over the entire modeling region at each time step, providing a global assessment of the model s accuracy over the
course of dynamically active period.
Author
Outer Radiation Belt; Forecasting; Kalman Filters; Flux (Rate); Algorithms; Assimilation
20040111047 Osaka Univ., Toyonaka, Japan
Ground Experiment and Numerical Simulation of Spacecraft Arcing in Ambient Plasma Environments
Masuyama, Takahisa; Nagata, Masato; Onishi, Tatsuo; Tahara, Hirokazu; Yoshikawa, Takao; 8th Spacecraft Charging
Technology Conference; March 2004; 15 pp.; In English; See also 20040111031; No Copyright; Avail: CASI; A03, Hardcopy
In the future, LEO spacecraft will be larger and higher powered. Because of the balance of leakage currents through
ambient space plasma, their main conductive body will have a higher negative potential without plasma contactor operation.
When spacecraft operate with a higher voltage, more intensive arcing is suspected to occur on the surface. In this study,
ground-based experiment and Direct-Simulation-Monte-Carlo Particle-In-Cell plasma simulation were carried out to
understand the arcing phenomenon and to examine influences of ambient space plasma on the arcing process. Simulating
plasmas were generated by electron cyclotron resonance discharge. When arcing occurred on negatively-biased anodized
aluminum sample (AAS) plates in the plasma environment, the time variations in arc current and bias voltage were measured.
Arc spot diameter was also measured. The experimental results showed that both the peak arc current and the total charge
emitted by arcing increased with initial charging voltage and neutral particle number density. The diameter of arc spots
increased with initial charging voltage although it was almost constant regardless of neutral particle density. The calculated
results showed that neutral particles in addition to charged particles around spacecraft played an important role in expansion
of arc plasma causing the arcing characteristics. Accordingly, high voltage operation of LEO spacecraft might bring drastic
degradation of AAS by arcing depending on ambient plasma conditions.
Author
Space Plasmas; Spacecraft Environments; Simulation; Neutral Particles; High Voltages; Monte Carlo Method; Electron
Cyclotron Resonance
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