StarPlan: A model-based diagnostic system for spacecraft

The Sunnyvale Division of Ford Aerospace created a model-based reasoning capability for diagnosing faults in space systems. The approach employs reasoning about a model of the domain (as it is designed to operate) to explain differences between expected and actual telemetry; i.e., to identify the root cause of the discrepancy (at an appropriate level of detail) and determine necessary corrective action. A development environment, named Paragon, was implemented to support both model-building and reasoning. The major benefit of the model-based approach is the capability for the intelligent system to handle faults that were not anticipated by a human expert. The feasibility of this approach for diagnosing problems in a spacecraft was demonstrated in a prototype system, named StarPlan. Reasoning modules within StarPlan detect anomalous telemetry, establish goals for returning the telemetry to nominal values, and create a command plan for attaining the goals. Before commands are implemented, their effects are simulated to assure convergence toward the goal. After the commands are issued, the telemetry is monitored to assure that the plan is successful. These features of StarPlan, along with associated concerns, issues and future directions, are discussed

Temporal and contextual knowledge in model-based expert systems

A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware

BioSentinel: Mission Summary and Lessons Learned From the First Deep Space Biology CubeSat Mission

Launched on Artemis I, BioSentinel carries a biology experiment into deep space for the first time in 50 years. A 6U CubeSat form factor was utilized for the spacecraft, which included technologies newly developed or adapted for operations beyond Earth orbit. The spacecraft carries onboard budding yeast, Saccharomyces cerevisiae, as an analog to human cells to test the biological response to deep space radiation. This was the maiden deep-space voyage for many of the subsystems, and the first time to evaluate their performance in flight operation. Flying a CubeSat beyond LEO comes with unique challenges with respect to trajectory uncertainty and mission operations planning. The nominal plan was a lunar fly-by, followed by an insertion into heliocentric orbit. However, some possible scenarios included lunar eclipses that could have severely impacted the power budget during that phase of the mission, while others could have resulted in a “retrograde” hyperbola at swing-by resulting in the spacecraft traveling inward toward Earth or even towards a collision with the lunar surface. The commissioning phase of the mission was successful and completed a week ahead of schedule. It did not come without its exciting moments and challenges. First contact with the spacecraft uncovered that the vehicle was unexpectedly tumbling after deployment, a situation that needed to be corrected urgently. The mission operations team executed a contingency plan to stabilize the spacecraft, with just moments to spare before the battery ran out of power. The BioSensor payload onboard the spacecraft is a complex instrument that includes microfluidics, optical systems, sensor control electronics, as well as the living yeast cells. BioSentinel also includes a TimePix radiation sensor implemented by JSC’s RadWorks group. Total dose and Linear Energy Transfer (LET) spectrum data are compared to the rate of cell growth and metabolic activity measured in the S. cerevisiae cells. BioSentinel mature nanosatellite technologies included: deep space communications and navigation, autonomous attitude control and momentum management, and micro-propulsion systems, to provide an adaptable nanosatellite platform for deep space uses. This paper discusses the performance of the BioSentinel spacecraft through the mission phase, and includes lessons learned from challenges and anomalies. BioSentinel had many successes and will be a pathfinder for future deep space CubeSats and biology missions

Effectiveness of an Expert System for Astronaut Assistance on a Sleep Experiment

Principal Investigator-in-a-Box ([PI]) is an expert system designed to train and assist astronauts with the performance of an experiment outside their field of expertise, particularly when contact with the Principal Investigators on the ground is limited or impossible. In the current case, [PI] was designed to assist with the calibration and troubleshooting procedures of the Neurolab Sleep and Respiration Experiment during the pre-sleep period of no ground contact. It displays physiological signals in real time during the pre-sleep instrumentation period, and alerts the astronauts when a poor signal quality is detected. Results of the first study indicated a beneficial effect of [PI] and training in reducing anomaly detection time and the number of undetected anomalies. For the in-flight performance, excluding the saturated signals, the expert system had an 84.2% detection accuracy, and the questionnaires filled out by the astronauts showed positive crew reactions to the expert system

Mimicking exercise in three-dimensional bioengineered skeletal muscle to investigate cellular and molecular mechanisms of physiological adaptation

This is the peer reviewed version of the following article: KASPER, A.M. ... et al, 2017. Mimicking exercise in three-dimensional bioengineered skeletal muscle to investigate cellular and molecular mechanisms of physiological adaptation. Journal of Cellular Physiology, 233 (3), pp. 1985–1998, which has been published in final form at http://dx.doi.org/10.1002/jcp.25840. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Bioengineering of skeletal muscle in-vitro in order to produce highly aligned myofibres in relevant three dimensional (3D) matrices have allowed scientists to model the in-vivo skeletal muscle niche. This review discusses essential experimental considerations for developing bioengineered muscle in order to investigate exercise mimicking stimuli. We identify current knowledge in the use of electrical stimulation and co-culture with motor neurons to enhance skeletal muscle maturation and contractile function in bioengineered systems in-vitro. Importantly, we provide a current opinion on the use of acute and chronic exercise mimicking stimuli (electrical stimulation and mechanical overload) and the subsequent mechanisms underlying physiological adaptation in 3D bioengineered muscle. We also identify that future studies using the latest bioreactor technology, providing simultaneous electrical and mechanical loading and flow perfusion in-vitro, may provide the basis for advancing knowledge in the future. We also envisage, that more studies using genetic, pharmacological and hormonal modifications applied in human 3D bioengineered skeletal muscle may allow for an enhanced discovery of the in-depth mechanisms underlying the response to exercise in relevant human testing systems. Finally, 3D bioengineered skeletal muscle may provide an opportunity to be used as a pre-clinical in-vitro test-bed to investigate the mechanisms underlying catabolic disease, whilst modelling disease itself via the use of cells derived from human patients without exposing animals or humans (in phase I trials) to the side effects of potential therapies