Chemistry: Space resources for teachers including suggestions for classroom activities and laboratory experiments

Curriculum supplement to assist general chemistry teachers in updating instruction materials with aerospace development

Winona Daily News

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A state machine architecture for aerospace vehicle fault protection

Because of their complexity and the unforgiving environment in which they operate, aerospace vehicles are vulnerable to mission-critical failures. In order to prevent these failures, aerospace vehicles often employ Fault Detection, Isolation, and Recovery (FDIR) systems to sense, identify the source of, and recover from faults. Typically, aerospace systems use a rule-based paradigm for FDIR where telemetry values are monitored against specific logical statements such as static upper and lower limits. The model-based paradigm allows more complex decision logic to be used for FDIR. State machines are a particular tool for model-based FDIR that have been explored by industry but not yet widely adopted. This study develops a generic and modular state machine FDIR architecture that is portable to flight software. The study will focus on FDIR for the Guidance, Navigation, & Control subsystem, but it will be presented in a manner that is applicable to all vehicle subsystems. The state machine formulation is applied for on-board model-based fault diagnosis. Two specific case studies are employed to demonstrate the architecture. The first is a terrestrial application of unmanned aerial vehicles for 3D scanning and mapping, which is validated through flight testing. The second is a space-based application of automated close approach and capture for a Mars sample return mission, which is validated through software-in-the-loop testing with flight-like software components.Ph.D

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so