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Mitigating power and memory constraints on a Venusian seismometer

Yuan Tian, Robert R. Herrick, Michael E. West and Tibor Kremic
Mitigating power and memory constraints on a Venusian seismometer
Seismological Research Letters (October 2022) 94 (1): 159-171

Abstract

The nearest term pathway to the deployment of a seismometer on Venus is an instrument that can operate under ambient surface conditions on battery power. We conduct a series of studies on combined hardware and software approaches to maximize the quality of data returned under the likely restrictions of minimal on-board data storage and only being able to transmit in real time during a small fraction of a multimonth deployment. We assess likely Venus seismicity by examining different terrestrial analog settings; we find that likely Venus analog settings all fall within about an order of magnitude of mean Earth in terms of seismicity level. We use the seismic record from a station in central Alaska as a Venus surrogate for algorithm development. We tested various transmission triggers and developed a simple low-memory algorithm that mimics the common terrestrial long-term average/short-term average trigger. If the seismometer can operate in coordination with an orbiter that can remotely turn off data transmission, then the frequency content of a few seconds of data can be used to distinguish small, nearby earthquakes from large, distal ones, and total data transmission can be tuned to favor the latter. If an orbiter can also turn on transmission for other nearby seismometers, it would further enhance the ability to distinguish small- and large-magnitude earthquakes autonomously and increase the chances of capturing the initial onset of significant events.


ISSN: 0895-0695
EISSN: 1938-2057
Serial Title: Seismological Research Letters
Serial Volume: 94
Serial Issue: 1
Title: Mitigating power and memory constraints on a Venusian seismometer
Affiliation: University of Alaska Fairbanks, Geophysical Institute, Fairbanks, AK, United States
Pages: 159-171
Published: 20221011
Text Language: English
Publisher: Seismological Society of America, El Cerrito, CA, United States
References: 45
Accession Number: 2022-058754
Categories: Extraterrestrial geologySeismology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 1 table
Secondary Affiliation: National Aeronautics and Space Administration, Glenn Research Center, USA, United States
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2023, American Geosciences Institute. Abstract, Copyright, Seismological Society of America. Reference includes data from GeoScienceWorld, Alexandria, VA, United States
Update Code: 202244

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