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The Space Shuttle Orbiter Atmospheric Revitalization Pressure Control System (ARPCS) and the Fuel Cell System (FCS) use a hot wire anemometer type of gas mass flow sensor for flow measurement. In the ARPCS oxygen and nitrogen mass flows are measured and in the FCS oxygen and hydrogen mass flows are measured. The existing flow sensors suffer from certain accuracy limitations and potential failure modes. A new type of commercially developed solid state micro-machined silicon gas mass flow sensor developed by Honeywell was adapted to allow the technology to be assessed for the application. A demonstration test program has been conducted to evaluate the performance characteristics of the new sensor for space system applications and environments. The testing was sponsored by the National Aeronautics and Space Administration (NASA) at the Johnson Space Center (JSC).

The early external active thermal control system (EEATCS) is designed to cool the U.S. Laboratory (USL), during early assembly stages of the International Space Station (ISS), to support assured early research (AER). The ISS is assembled on orbit over a period of about 5 years and over 40 stages. During later stages, about half way through the assembly, the USL is cooled by the external active thermal control system (EATCS), but that system is not available during early stages. To assure research, during early stages, the USL is cooled by the EEATCS; at a later stage, the USL cooling is switched to EATCS. During early stages, electric power is provided by the integrated truss segment (ITS) P6, which consists of photovoltaic (PV) arrays to convert sunlight into direct current power, an integrated equipment assembly (IEA) to support hardware required to store and condition electric power, and a long spacer to provide spacing between outboard power modules.

This paper presents classical control algorithms design for the solar array pointing system of the Space Station Freedom (SSF). This development is based on continuous, rigid body model of the solar array beta gimbal assembly (BGA) containing both linear and nonlinear dynamics due to various friction components. Optimum sets of controller parameters were obtained based on integral performance criteria through EASY5 simulations in the time domain. Classical sensitivity studies conducted in EASY5 indicated that the worst potential problem (possible system instability) is due to the variations in the electric motor dead-zone characteristics. After incorporation of an alternate static friction model, a Taguchi based tolerance design sensitivity study was conducted. Results indicated that the voltage variance, torque sensitivity constant and the motor resistance are the most important tolerances investigated with respect to integral square error (ISE).

The Dynamic Isotope Power System (DIPS) Demonstration Program is currently focused on the development of a standardized 2.5-kWe portable generator for multiple applications on the lunar or Martian surface. An optimum system configuration has been developed for the 2.5-kWe DIPS module that provides a system with a radiator area which is small and manageable without significantly impacting the system mass, efficiency, and technological risk. The 2.5-kWe DIPS module configuration was developed based on a systematic series of studies. Initially, technology breakpoints in the DIPS component and subsystem designs were identified. Based on the technology assessments, the maximum design temperature for the system was selected and various system and subsystem configurations were evaluated. Finally, the subsystem and system designs for the selected configuration were optimized using a detailed system design optimization computer code.

An extensive study of liquid propellant rocket engine test and flight history data has produced methods for advanced health monitoring currently under development for application to the Advanced Shuttle, National Aero-Space Plane, and other future propulsion systems. Advanced Health Monitoring is a systematic approach to instrumentation design and development, signal processing, and knowledge-based strategies to infer the operating status of any engine component or system. Properly implemented, Advanced Health Monitoring increases safety and the probability of mission success, significantly reduces turnaround time and maintenance cost, prolongs component life and reduces life-cycle cost.