An intelligent system for monitoring the microgravity environment quality on-board the International Space Station

Monitoring the Microgravity Environment Quality On-Board the International Space Station Using Soft Computing Techniques

Monitoring the Microgravity Environment Quality On-Board the International Space Station Using Soft Computing Techniques

This paper presents an artificial intelligence monitoring system developed by the NASA Glenn Principal Investigator Microgravity Services project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment in time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed...

Microgravity Induces Changes in Microsome-Associated Proteins of Arabidopsis Seedlings Grown on Board the International Space Station

The "GENARA A" experiment was designed to monitor global changes in the proteome of membranes of Arabidopsis thaliana seedlings subjected to microgravity on board the International Space Station (ISS). For this purpose, 12-day-old seedlings were grown either in space, in the European Modular Cultivation System (EMCS) under microgravity or on a 1 g centrifuge, or on the ground. Proteins associat...

Artificial Neural Networks Applications: From Aircraft Design Optimization to Orbiting Spacecraft On–Board Environment Monitoring

This paper reviews some of the recent applications of artificial neural networks taken from various works performed by the authors over the last four years at the NASA Glenn Research Center. This paper focuses mainly on two areas. 1) Artificial neural networks application in design and optimization of aircraft/engine propulsion systems to shorten the overall design cycle. Out of that specific a...

MULTICRITERION SYNTHESIS OF INTELLIGENT CONTROL SYSTEMS OF GENERATING UNIT OF NUCLEAR POWER STATION

The paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. Some mathematical vector models were obtained for control system multicriterion quality indices with due ...