Engineering topics

Scarl, Ethan A.

Publications and source records attributed to Scarl, Ethan A..

4 records

NASA NTRS1999

Space Station Reboost with Electrodynamic Tethers

This paper presents the results of a study of an electrodynamic tether system to reboost the International Space Station (ISS). One recommendation is to use a partially bare tether for electron collection. Locations are suggested as to where the tether system is to be attached at the space station. The effects of the tether system on the microgravity environment may actually be beneficial, because the system can neutralize aerodrag during quiescent periods and, if deployed from a movable boom, can permit optimization of laboratory positioning with respect to acceleration contours. Alternative approaches to tether deployment and retrieval are discussed. It is shown that a relatively short tether system, 7 km long, operating at a power level of 5 kW could provide cumulative savings or over a billion dollars during a 10-year period ending in 2012. This savings is the direct result of a reduction in the number or nights that would otherwise be required to deliver propellant for reboost, with larger cost savings for higher tether usage. In addition to economic considerations, an electrodynamic tether promises a practical backup system that could ensure ISS survival in the event of an (otherwise) catastrophic delay in propellant delivery.

Vas, Irwin E.↗

NASA NTRS1989

Diagnostic tolerance for missing sensor data

For practical automated diagnostic systems to continue functioning after failure, they must not only be able to diagnose sensor failures but also be able to tolerate the absence of data from the faulty sensors. It is shown that conventional (associational) diagnostic methods will have combinatoric problems when trying to isolate faulty sensors, even if they adequately diagnose other components. Moreover, attempts to extend the operation of diagnostic capability past sensor failure will necessarily compound those difficulties. Model-based reasoning offers a structured alternative that has no special problems diagnosing faulty sensors and can operate gracefully when sensor data is missing.

Scarl, Ethan A.↗

NASA NTRS1987

Sensor-based diagnosis using knowledge of structure and function

A system for fault detection and isolation called LES, developed at the Kennedy Space Center for the Space Shuttle's Launch Processing System, is a well-developed diagnostic system that is simultaneously model-based and sensor-based. This experiment has led to a surprising result: the failure of a sensor can not only be handled in precisely the same way as the failure of any other object, but may present an especially easy case. Classical rule-based diagnostic systems need to find out whether or not their sensors are telling them the truth before they can safely draw inferences from them. By contrast, while LES does treat sensors as a special case, it does so only because there may exist a short cut that allows them to be handled more simply than other objects. LES uses both structural and functional knowledge, and has found cases in which the structural knowledge can be economically replaced by the judicious use of functional relationships; LES' functional relationships are stored in exactly one place, so they must be inverted to determine hypothetical values for possibly faulty objects. The inversion process has been extended to include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗

NASA NTRS1987

Diagnosis and sensor validation through knowledge of structure and function

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗