Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development

Low frequency seismo-volcanic signals are generated by the internal motion of fluids like magma, gases and water. They commonly occur before or together with erupting activity. Therefore, there study is fundamental for monitoring volcanic activity and assessment of volcanic risk. Nevertheless, becau...

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Main Authors: Cornejo-Suárez, Guillermo, van-der-Laat, Leonardo, Meneses, Esteban, Mora, Mauricio M., Pacheco, Javier Fco
Format: Artículo
Language: Español
Published: Editorial Tecnológica de Costa Rica (entidad editora) 2019
Subjects:
Online Access: https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4168
https://hdl.handle.net/2238/11879
id RepoTEC11879
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spelling RepoTEC118792020-09-25T23:12:18Z Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development Localizando señales sismo- volcánicas del volcán Turrialba (Costa Rica) usando Python y Computación Avanzada: Un caso de colaboración multidisciplinar para el desarrollo científico Cornejo-Suárez, Guillermo van-der-Laat, Leonardo Meneses, Esteban Mora, Mauricio M. Pacheco, Javier Fco Tremores volcánicos computación avanzada localización de tremores Python Volcán Turrialba Volcanic tremors tremor location advanced computing Python Turrialba Volcano Low frequency seismo-volcanic signals are generated by the internal motion of fluids like magma, gases and water. They commonly occur before or together with erupting activity. Therefore, there study is fundamental for monitoring volcanic activity and assessment of volcanic risk. Nevertheless, because of their source complexity, it’s not possible to use the classical procedures for seismic location, which were developed for locating the more common tectonic earthquakes. Moreover, the volcanic edifice heterogeneity modifies the waveform of seimo- volcanic signals, making the process of finding its location more challenging. Hence, signals must be processed using other methods that, because of their computational complexity, require advanced computing platforms (supercomputers), specially if real-time processing is required. However, seismic observatories of volcano monitoring in Central America have limited resources and may not afford in-house professional software developers. The present work analyzes a study case about a collaborative experience between specialists in volcano seismology and in advanced computing. We developed a computational platform to locate seismo-volcanic signals in Turrialba Volcano. Our principal conclusion is that the creation of multidisciplinary collaboration networks allow resource maximization to tackle and overcome many limitations common in our context (lack of human resource, technology, low budget, among others). Las señales sismo-volcánicas de baja frecuencia son generadas por el movimiento interno de magma, gases, agua, entre otros. Suelen preceder o acompañar la actividad eruptiva. Por lo tanto, estudiarlos resulta fundamental para el monitoreo de la actividad volcánica y una apropiada estimación de la amenaza. Sin embargo, la complejidad del mecanismo de la fuente hace que los procedimientos clásicos de localización de sismos generados por procesos tectónicos, que son los más comunes, no puedan ser utilizados para los volcánicos. A esto se suma la heterogeneidad de los edificios volcánicos que modifican en gran medida las formas de onda de las señales sismo-volcánicas, lo que también dificulta su procesamiento. Es por ello que se requiere aplicar otro tipo de métodos de tratamiento de señal los cuales, por su complejidad computacional, requieren de plataformas de computación avanzada (supercomputadoras), sobretodo cuando se precisa de resultados en tiempo real. No obstante, los observatorios o entes encargados de la auscultación y monitoreo volcánico en la región centroamericana tienen recursos limitados y no pueden mantener un departamento completo de desarrollo de software especializado. La presente ponencia analiza un caso de estudio, en el cual se desarrolló un trabajo colaborativo entre especialistas en sismología volcánica y en computación avanzada, quienes implementaron una plataforma computacional para la localización de señales sismo- volcánicas en el Volcán Turrialba, Costa Rica. Nuestra principal conclusión es que la creación de redes de colaboración multidisciplinaria es una opción que permite maximizar recursos para abordar y superar muchas de las limitaciones que existen para el desarrollo de la investigación en nuestro contexto (falta de recursos humano, tecnología, presupuesto, entre otros). 2019-03-12 2020-09-25T23:12:18Z 2020-09-25T23:12:18Z info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4168 10.18845/tm.v32i5.4168 https://hdl.handle.net/2238/11879 spa https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4168/3764 application/pdf Editorial Tecnológica de Costa Rica (entidad editora) Tecnología en marcha Journal; 2019: Vol. 32 Núm. Especial. Bienal Centroamericano y del Caribe de investigación y postgrado; Pág 18-26 Revista Tecnología en Marcha; 2019: Vol. 32 Núm. Especial. Bienal Centroamericano y del Caribe de investigación y postgrado; Pág 18-26 2215-3241 0379-3982
institution Tecnológico de Costa Rica
collection Repositorio TEC
language Español
topic Tremores volcánicos
computación avanzada
localización de tremores
Python
Volcán Turrialba
Volcanic tremors
tremor location
advanced computing
Python
Turrialba Volcano
spellingShingle Tremores volcánicos
computación avanzada
localización de tremores
Python
Volcán Turrialba
Volcanic tremors
tremor location
advanced computing
Python
Turrialba Volcano
Cornejo-Suárez, Guillermo
van-der-Laat, Leonardo
Meneses, Esteban
Mora, Mauricio M.
Pacheco, Javier Fco
Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development
description Low frequency seismo-volcanic signals are generated by the internal motion of fluids like magma, gases and water. They commonly occur before or together with erupting activity. Therefore, there study is fundamental for monitoring volcanic activity and assessment of volcanic risk. Nevertheless, because of their source complexity, it’s not possible to use the classical procedures for seismic location, which were developed for locating the more common tectonic earthquakes. Moreover, the volcanic edifice heterogeneity modifies the waveform of seimo- volcanic signals, making the process of finding its location more challenging. Hence, signals must be processed using other methods that, because of their computational complexity, require advanced computing platforms (supercomputers), specially if real-time processing is required. However, seismic observatories of volcano monitoring in Central America have limited resources and may not afford in-house professional software developers. The present work analyzes a study case about a collaborative experience between specialists in volcano seismology and in advanced computing. We developed a computational platform to locate seismo-volcanic signals in Turrialba Volcano. Our principal conclusion is that the creation of multidisciplinary collaboration networks allow resource maximization to tackle and overcome many limitations common in our context (lack of human resource, technology, low budget, among others).
format Artículo
author Cornejo-Suárez, Guillermo
van-der-Laat, Leonardo
Meneses, Esteban
Mora, Mauricio M.
Pacheco, Javier Fco
author_sort Cornejo-Suárez, Guillermo
title Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development
title_short Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development
title_full Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development
title_fullStr Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development
title_full_unstemmed Locating seismo-volcanic signals in Turrialba Volcano (Costa Rica) using Python and Advanced Computing: a case of multidisciplinary collaboration for scientific development
title_sort locating seismo-volcanic signals in turrialba volcano (costa rica) using python and advanced computing: a case of multidisciplinary collaboration for scientific development
publisher Editorial Tecnológica de Costa Rica (entidad editora)
publishDate 2019
url https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4168
https://hdl.handle.net/2238/11879
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score 11.996861