Venus, with a surface temperature of 450°C and an atmospheric pressure 90 times higher than that of the Earth, is a difficult target for exploration. However, high-temperature electronics and power systems now being developed make it possible that future missions may be able to operate in the Venus environment. Powering such a rover within the scope of a Discovery class mission will be difficult, but harnessing Venus' surface winds provides a possible way to keep a powered rover small and light. This project scopes out the feasibility of a wind-powered rover for Venus surface missions. Two rover concepts, a landsailing rover and a wind-turbine-powered rover, were considered. The turbine-powered rover design is selected as being a low-risk and low-cost strategy. Turbine detailed analysis and design shows that the turbine can meet mission requirements across the desired range of wind speeds by utilizing three constant voltage generators at fixed gear ratios.

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Traditional probabilistic risk assessment approaches often require failure scenarios to be explicitly defined through event sequences that are then quantified as part of the integrated analysis. This approach becomes difficult when failure propagation paths change as a function of the system operation. Additionally, if the propagation paths represent interactions among even a modest number of components, the scenario count becomes combinatorially intractable. This paper presents an alternate approach for quantifying the probability of failure propagation in such a case. Rather than explicitly defining scenario sequences, simple physical models are created for each of the components. In this way, only the physical states and rules of component interactions must be defined, rather than event sequences for each individual scenario. Initiating failures are introducted into the system, either randomly or as defined by relative likelihood, and the failures cascade through the system via the interaction rules. This process is repeated using Monte Carlo methods and, as a result, the most probable scenarios "self-evolve" in terms of both sequence path and frequency.This approach was applied to failures occurring in the engine compartment of a space launch vehicle with four liquid rocket engines and four high-pressure helium tanks. Each engine was modeled with key components, such as turbomachinery, combustion chamber, propellant lines, and additional support systems. Three test cases were conducted with different high-energy engine failures. End results of interest included an additional engine-out failure and tank burst, which represent the loss-of-mission (LOM) and loss-ofcrew (LOC) failure environments, respectively. Observations show that almost every scenario outcome is unique and that many scenarios involve complex chain reactions that are difficult to predict. This validates the usefulness of the modeling approach in assessing the overall risks to the crew during a launch vehicle abort.

This paper presents a method to promote STEM (Science, Technology, Engineering, and Mathematics) education through participation in a reduced gravity program with NASA (National Aeronautics and Space Administration). Microgravity programs with NASA provide students with a unique opportunity to conduct scientific research with innovative and creative solutions through hands-on experimental design and testing in reduced gravity conditions. A group of undergraduate students from California State Polytechnic University, Pomona, participated in the NASA's SEED (Systems Engineering Educational Discovery) Reduced Gravity Program, which focuses on addressing systems engineering challenges in microgravity. The team worked with a NASA Principal Investigator on a project to build and fly a prototype test article to demonstrate emergency atmospheric reentry with single-axis control. Through this experience, the team was able to gain hands-on experience with spacecraft instrumentation and learn valuable lessons in teamwork and systems engineering that can be applied to real-world situations. As part of the SEED program, the team shared its experience with local high schools in order to spark interest in STEM-related fields in the next generation of scientists and engineers.