TY - JOUR
T1 - Investigating lava flow rheology using video analysis and numerical flow models
AU - Lev, Einat
AU - Spiegelman, Marc
AU - Wysocki, Robert J.
AU - Karson, Jeffery A.
N1 - Funding Information:
Initial funding for the Syracuse Lava Project has been provided by the Chancellor, Vice Chancellor, VP for Research and Deans of the Visual and Performing Arts and College of Arts and Sciences of Syracuse University (to RW ad JK) and the Jessie Page Heroy Endowment (to JK). Funding for the filming equipment was provided by the LDEO Advisory Board's Innovation Fund (to EL). EL was supported during this work by the Lamont-Doherty Postdoctoral Fellowship , by a grant from the Brinson Foundation , and by NSF grant EAR-1118943 . We thank Phillip Evans, Noah Hausknecht, Matt Kissane and Michael Vicki for their assistance with lava pours. This paper benefited from discussions with Katherine Cashman, Michael Ramsey, Chris Zappa, Chris Small, and Terry Plank.
PY - 2012/12
Y1 - 2012/12
N2 - Lava rheology is a major control on lava flow behavior and a critical parameter in flow simulations, but is very difficult to measure at field conditions or correctly extrapolate from the lab scale. We present a new methodology for investigating lava rheology through a combination of controlled experiments, image analysis and numerical forward modeling. Our experimental setup, part of the Syracuse University Lava Project (http://lavaproject.syr.edu) includes a large furnace capable of melting up to 450. kg of basalt, at temperatures well above the basalt liquidus. The lava is poured onto either a tilted bed of sand or a steel channel to produce meter-long flows. This experimental setup is probably the only facility that allows such large scale controlled lava flows made of natural basaltic material.We document the motion of the lava using a high-resolution video camera placed directly above the flows, and the temperature using infrared probes and cameras. After collecting the footage, we analyze the images for lava deformation and compare with numerical forward-models to constrain the rheological parameters and laws which best describe the flowing lava. For the video analysis, we employ the technique of Differential Optical Flow, which uses the time-variations of the spatial gradients of the image intensity to estimate velocity between consecutive frames. An important benefit for using optical flow, compared with other velocimetry methods, is that it outputs a spatially coherent flow field rather than point measurements. We demonstrate that the optical flow results agree with other measures of the flow velocity, and estimate the error due to noise and time-variability to be under 30% of the measured velocity.Our forward-models are calculated by solving the Stokes flow equations on an unstructured finite-element mesh defined using the geometry of the observed flow itself. We explore a range of rheological parameters, including the lava's apparent viscosity, the power-law exponent m and the thermal activation energy. Our measurements of apparent viscosity agree well with predictions of the composition-based Shaw (1972) and GRD model (Giordano, Russell and Dingwell, 2008). We find that for the high-temperature portion of the flow a weakly shear-thinning or Newtonian rheology (m> 0.7) with an effective activation energy of B= 5500. J gives the best fit to the data.Our methodology is the first time that high-resolution optical flow analysis of flowing lava is combined with numerical flow models to constrain rheology. The methodology we present here can be used in field conditions to obtain in-situ information on lava rheology, without physical interaction with the flow and without being limited to point-wise, low strain-rate, local measurements currently available through the use of rotational viscometers in the field.
AB - Lava rheology is a major control on lava flow behavior and a critical parameter in flow simulations, but is very difficult to measure at field conditions or correctly extrapolate from the lab scale. We present a new methodology for investigating lava rheology through a combination of controlled experiments, image analysis and numerical forward modeling. Our experimental setup, part of the Syracuse University Lava Project (http://lavaproject.syr.edu) includes a large furnace capable of melting up to 450. kg of basalt, at temperatures well above the basalt liquidus. The lava is poured onto either a tilted bed of sand or a steel channel to produce meter-long flows. This experimental setup is probably the only facility that allows such large scale controlled lava flows made of natural basaltic material.We document the motion of the lava using a high-resolution video camera placed directly above the flows, and the temperature using infrared probes and cameras. After collecting the footage, we analyze the images for lava deformation and compare with numerical forward-models to constrain the rheological parameters and laws which best describe the flowing lava. For the video analysis, we employ the technique of Differential Optical Flow, which uses the time-variations of the spatial gradients of the image intensity to estimate velocity between consecutive frames. An important benefit for using optical flow, compared with other velocimetry methods, is that it outputs a spatially coherent flow field rather than point measurements. We demonstrate that the optical flow results agree with other measures of the flow velocity, and estimate the error due to noise and time-variability to be under 30% of the measured velocity.Our forward-models are calculated by solving the Stokes flow equations on an unstructured finite-element mesh defined using the geometry of the observed flow itself. We explore a range of rheological parameters, including the lava's apparent viscosity, the power-law exponent m and the thermal activation energy. Our measurements of apparent viscosity agree well with predictions of the composition-based Shaw (1972) and GRD model (Giordano, Russell and Dingwell, 2008). We find that for the high-temperature portion of the flow a weakly shear-thinning or Newtonian rheology (m> 0.7) with an effective activation energy of B= 5500. J gives the best fit to the data.Our methodology is the first time that high-resolution optical flow analysis of flowing lava is combined with numerical flow models to constrain rheology. The methodology we present here can be used in field conditions to obtain in-situ information on lava rheology, without physical interaction with the flow and without being limited to point-wise, low strain-rate, local measurements currently available through the use of rotational viscometers in the field.
KW - Experimental volcanology
KW - Lava flows
KW - Numerical modeling
KW - Optical flow
KW - Rheology
KW - Velocimetry
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U2 - 10.1016/j.jvolgeores.2012.08.002
DO - 10.1016/j.jvolgeores.2012.08.002
M3 - Article
AN - SCOPUS:84865612732
SN - 0377-0273
VL - 247-248
SP - 62
EP - 73
JO - Journal of Volcanology and Geothermal Research
JF - Journal of Volcanology and Geothermal Research
ER -