Optimization of the Carbon Dioxide Removal Assembly (CDRA-4EU) in Support of the International Space System and Advanced Exploration Systems

The Life Support Systems Project (LSSP) under the Advanced Exploration Systems (AES) program builds upon the work performed under the AES Atmosphere Resource Recovery and Environmental Monitoring (ARREM) project focusing on the numerous technology development areas. The Carbon Dioxide (CO2) removal and associated air drying development efforts are focused on improving the current state-of-the-art system on the International Space Station (ISS) utilizing fixed beds of sorbent pellets by seeking more robust pelletized sorbents, evaluating structured sorbents, and examining alternate bed configurations to improve system efficiency and reliability. A component of the CO2 removal effort utilizes a virtual Carbon Dioxide Removal Assembly, revision 4 (CDRA-4) test bed to test a large number of potential operational configurations with independent variations in flow rate, cycle time, heater ramp rate, and set point. Initial ground testing will provide prerequisite source data and provide baseline data in support of the virtual CDRA. Once the configurations with the highest performance and lowest power requirements are determined by the virtual CDRA, the results will be confirmed by testing these configurations with the CDRA-4EU ground test hardware. This paper describes the initial ground testing of select configurations. The development of the virtual CDRA under the AES-LSS Project will be discussed in a companion paper

Time-Space Efficient Regression Testing for Configurable Systems

Configurable systems are those that can be adapted from a set of options. They are prevalent and testing them is important and challenging. Existing approaches for testing configurable systems are either unsound (i.e., they can miss fault-revealing configurations) or do not scale. This paper proposes EvoSPLat, a regression testing technique for configurable systems. EvoSPLat builds on our previously-developed technique, SPLat, which explores all dynamically reachable configurations from a test. EvoSPLat is tuned for two scenarios of use in regression testing: Regression Configuration Selection (RCS) and Regression Test Selection (RTS). EvoSPLat for RCS prunes configurations (not tests) that are not impacted by changes whereas EvoSPLat for RTS prunes tests (not configurations) which are not impacted by changes. Handling both scenarios in the context of evolution is important. Experimental results show that EvoSPLat is promising. We observed a substantial reduction in time (22%) and in the number of configurations (45%) for configurable Java programs. In a case study on a large real-world configurable system (GCC), EvoSPLat reduced 35% of the running time. Comparing EvoSPLat with sampling techniques, 2-wise was the most efficient technique, but it missed two bugs whereas EvoSPLat detected all bugs four times faster than 6-wise, on average.Comment: 14 page

Closing probabilities in the Kauffman model: an annealed computation

We define a probabilistic scheme to compute the distributions of periods, transients and weigths of attraction basins in Kauffman networks. These quantities are obtained in the framework of the annealed approximation, first introduced by Derrida and Pomeau. Numerical results are in good agreement with the computed values of the exponents of average periods, but show also some interesting features which can not be explained whithin the annealed approximation.Comment: latex, 36 pages, figures added in uufiles format,error in epsffile nam