Optical granulometric analysis of sedimentary deposits by color segmentation-based software: OPTGRAN-CS

The study of grain size distribution is fundamental for understanding sedimentological environments. Through these analyses, clast erosion, transport and deposition processes can be interpreted and modeled. However, grain size distribution analysis can be difficult in some outcrops due to the number and complexity of the arrangement of clasts and matrix and their physical size. Despite various technological advances, it is almost impossible to get the full grain size distribution (blocks to sand grain size) with a single method or instrument of analysis. For this reason development in this area continues to be fundamental. In recent years, various methods of particle size analysis by automatic image processing have been developed, due to their potential advantages with respect to classical ones; speed and final detailed content of information (virtually for each analyzed particle). In this framework, we have developed a novel algorithm and software for grain size distribution analysis, based on color image segmentation using an entropy-controlled quadratic Markov measure field algorithm and the Rosiwal method for counting intersections between clast and linear transects in the images. We test the novel algorithm in different sedimentary deposit types from 14 varieties of sedimentological environments. The results of the new algorithm were compared with grain counts performed manually by the same Rosiwal methods applied by experts. The new algorithm has the same accuracy as a classical manual count process, but the application of this innovative methodology is much easier and dramatically less time-consuming. The final productivity of the new software for analysis of clasts deposits after recording field outcrop images can be increased significantly.The study of grain size distribution is fundamental for understanding sedimentological environments. Through these analyses, clast erosion, transport and deposition processes can be interpreted and modeled. However, grain size distribution analysis can be difficult in some outcrops due to the number and complexity of the arrangement of clasts and matrix and their physical size. Despite various technological advances, it is almost impossible to get the full grain size distribution (blocks to sand grain size) with a single method or instrument of analysis. For this reason development in this area continues to be fundamental. In recent years, various methods of particle size analysis by automatic image processing have been developed, due to their potential advantages with respect to classical ones; speed and final detailed content of information (virtually for each analyzed particle). In this framework, we have developed a novel algorithm and software for grain size distribution analysis, based on color image segmentation using an entropy-controlled quadratic Markov measure field algorithm and the Rosiwal method for counting intersections between clast and linear transects in the images. We test the novel algorithm in different sedimentary deposit types from 14 varieties of sedimentological environments. The results of the new algorithm were compared with grain counts performed manually by the same Rosiwal methods applied by experts. The new algorithm has the same accuracy as a classical manual count process, but the application of this innovative methodology is much easier and dramatically less time-consuming. The final productivity of the new software for analysis of clasts deposits after recording field outcrop images can be increased significantly

Synthesizing Field and Experimental Observations to Investigate the Behavior of Pyroclastic Density Currents

One of the major hazards associated with volcanic eruptions are pyroclastic density currents (PDCs), which are fast-moving volcanic avalanches consisting of ash, boulders, and gas. Because of their unpredictability, studying PDCs in real time is dangerous and difficult. Therefore, we investigate the deposits produced by PDCs and use granular flow experiments to simulate PDCs in the laboratory. The experimental results allow us to understand sediment transport and erosional processes at small scales, and then we can extrapolate those results to natural PDCs. By better understanding what controls PDC behavior, we hope to ultimately improve risk assessment for these dangerous flows

Shallow-water models for volcanic granular flows: a review of strengths and weaknesses of TITAN2D and FLO2D numerical codes

The behaviour of dry and wet volcanic granular flows is one of the main research topics in present day geophysics and volcanology. It involves various disciplines (e.g. sedimentology, geophysics, fluid dynamics) and investigation techniques (e.g. field studies, laboratory experiments, computational fluid dynamics). The vast interest is justified by the complex nature of these flows and their very dangerous nature that threaten millions of people around the world. In the last decade, computational fluid dynamics has become one of the main instruments used to reproduce past events of volcanic granular flows or to predict their behaviour and potential hazard. In this study, we tested two of the most used codes for simulating volcanic granular flows, TITAN2D and FLO2D, against well studied natural cases (the 1998 wet granular flows in the Sarno area and the 2005 block and ash flows at Colima volcano) and large-scale experiments on granular flows. Comparison between simulated parameters and real ones were carried out in order to evaluate strengths and weaknesses of the two numerical codes. TITAN2D results showed how the basal friction angle is fundamental to control numerical simulations and its dependence on the topographic complexities, DEM resolution and slope-angle ratio. Simulation of large scale experiments offered a good relationship between slope angle ratio at break in slope and basal friction angle, which is useful for application to small drainage basins with not complex channel morphology. FLO2D suffers the lack of rheometric parameters for volcaniclastic material, but is less sensitive of DEM resolution with respect to TITAN2D

Construcción de perfiles granulométricos de depósitos piroclásticos por métodos ópticos

El análisis granulométrico de los depósitos piroclásticos proporciona información muy importante sobre los mecanismos de transporte y sedimentación de los flujos que los emplazaron. En este trabajo se presenta el método alternativo de las intersecciones de Rosiwal para el estudio de esta clase de depósitos. El método consiste en tomar fotografías de la pared del depósito desde una posición conocida. Por medio de un programa de análisis de imágenes, las fotografías se calibran dimensionalmente, procesándolas digitalmente para obtener un mejor detalle y se les sobreponen líneas horizontales paralelas a diferentes alturas. A lo largo de estas líneas se miden sus intersecciones con los clastos y, utilizando el método de Rosiwal, se obtienen las distribuciones granulométricas en los diferentes niveles del depósito. Comparando este método con el de conteo de puntos (análisis modal), que es ampliamente utilizado y ha sido ya comprobado, el resultado revela que el método de Rosiwal es aún más preciso. Debido a que el análisis granulométrico óptico de un afloramiento puede ser alterado por la deformación debida a la perspectiva de la fotografía, se propone un método empírico, sencillo y riguroso para corregir los datos obtenidos. El método fue aplicado a dos afloramientos de un depósito de flujo de bloques y ceniza del volcán de Colima, el cual, aparentemente, se emplazó a partir de un flujo piroclástico. El análisis de las variaciones verticales de la granulometría con el método aquí propuesto, evidencia estructuras que no son apreciables a simple vista. Los resultados indican que el depósito está compuesto por dos unidades, las cuales probablemente representan dos flujos diferentes o dos pulsaciones del mismo flujo piroclástico. La técnica es muy útil para estudiar depósitos piroclásticos; sin embargo, los resultados obtenidos sugieren que podría aplicarse a otro tipo de depósitos granulares, ya sean de origen volcánico o no

El análisis de imágenes como instrumento diagnóstico del estado de conservación: aplicación a la pintura con soporte lapídeo de la Virgen de Analco, Puebla

Por mucho tiempo, han sido los expertos quienes determinan el estado de conservación de una obra de arte de manera cualitativa, con resultados generalmente subjetivos. Un método rápido, práctico y semicuantitativo para efectuar este estudio utiliza el análisis de imágenes: éstas se subdividen en áreas caracterizadas por el mismo Grado de Alteración (GA), determinado por un restaurador en forma semi-manual, y analizadas automáticamente por un software. Esta metodología ha sido aplicada a una obra pictórica poblana que representa a la Inmaculada Concepción, pintada sobre basalto con una técnica única en su género. Los resultados obtenidos ofrecen un marco semicuantitativo del estado de conservación de la obra y evidencian las zonas más afectadas por los procesos de intemperismo y envejecimiento. El método puede ser una herramienta útil para el estudio del grado de conservación de obras pictóricas sobre diferentes soportes

Reconstrucción del evento eruptivo asociado al emplazamiento del flujo piroclástico El Refugio hace 13 ka, volcán Nevado de Toluca (México)

El Nevado de Toluca es un volcán activo en estado de quietud, localizado en el sector central del Cinturón Volcánico Transmexicano, 80 km al suroeste de Ciudad de México. Su formación ha sido caracterizada por una etapa efusiva inicial (entre 2.6 y 1.15 Ma), de composición andesítico-dacítica y una etapa explosiva más reciente (desde los 42 ka) que se manifestó con la alternancia de cinco erupciones plinianas (42, 36, 21.7, 12.1 y 10.5 ka) y de por lo menos cinco destrucciones de domos (37, 32, 28, 26 y 13 ka) asociados al emplazamiento de fl ujos de bloques y ceniza alrededor del volcán. Hace aproximadamente 13 ka ocurrió el evento más reciente de destrucción de domo, con el emplazamiento en el sector N-NE de un fl ujo piroclástico, aquí denominado fl ujo El Refugio, con un volumen de 0.11 km3. El depósito está constituido por dos facies de fl ujo: facies central, hasta 10 m de espesor, que consiste de hasta cinco unidades de fl ujo con clastos de varios decímetros de diámetro en una matriz arenosa; facies lateral, hasta 4 m de espesor, que consiste de una unidad masiva de material arenoso. En la base de la secuencia afl ora un depósito de oleada piroclástica de hasta 30 cm de espesor. Fragmentos de dacita representan el componente principal del depósito, con distinto grado de vesicularidad y con una asociación mineralógica de Pl-Hbl-Opx. Con base en las características estratigráfi cas, petrográfi cas y de la textura de los componentes juveniles, se pudo determinar que la extrusión del domo fue un proceso muy rápido y que su destrucción fue acompañada por una componente explosiva. El proceso magmático que dio inicio a la actividad fue debido a un sobrecalentamiento de la cámara magmática que promovió un proceso de 'self-mixing' con movimientos convectivos que llevaron a la cristalización y sobrepresión del reservorio. Finalmente, poder determinar una componente explosiva asociada a la destrucción de domos somitales en el Nevado de Toluca, pone en evidencia el alto peligro que este tipo de actividad podría representar en un futuro para las poblaciones aledañas

Fabric Analysis of Unconsolidated Pyroclastic Density Current Deposits

Pyroclastic density currents (PDCs) are gravity-driven mixtures of hot volcanic material and gas often produced during explosive volcanic eruptions. PDCs are extremely hazardous and difficult to analyze in real time. Therefore, we use their deposits to better understand PDC flow dynamics. Previous work proves that particle orientation and deposit fabric can provide information about flow direction and internal flow processes. We collected 19 samples of unconsolidated PDC deposits generated in the 1980 Mount St. Helens eruption and lithified these samples using a sodium silicate vacuum impregnation technique. Once solidified, the samples were cut in three planes: horizontal (map view), parallel to flow, and perpendicular to flow. These faces were analyzed using FabricS, a software that automatically measures particle orientation and statistically determines fabric strength. Analyses of the horizontal plane show mean particle orientations that correlate well with previous estimates of Mount St. Helens PDC flow directions. This study demonstrates that these techniques can constrain flow direction in outcrops without contextual information. Future analyses will provide information on particle transport mechanisms and further insights into flow rheology. Understanding PDC flow dynamics will allow for more accurate numerical modeling, and thus better hazard assessment, of these dangerous volcanic flows

Computational fluid dynamic simulations of granular flows: Insights on the flow-wall interaction dynamics

Dry volcanic granular flows are gravity-driven currents composed of solid particles where particle-particle interactions dominate the motion. The interaction with topography is a relevant factor controlling the propagation of such flows. In this paper we investigate the dynamics of channelised volcanic granular flows by comparing large-scale experiments with multiphase computational fluid dynamic simulations using the Two-Fluid Model approach, with an emphasis on the dynamics regulating the flow-wall interactions. We use the software MFIX to carry out sensitivity analysis of the boundary conditions for the solid phase implemented in the numerical code. The sensitivity analysis shows how the choice of the boundary condition and of the relevant parameters controlling the boundary conditions highly affect the dynamics of the whole flow. Finally, a preliminary benchmark of the MFIX boundary conditions with one large-scale experiment is presented, showing good agreement between the simulated and experimental flow front velocities