Faster geospeedometry: A Monte Carlo approach to relaxational geospeedometry for determining cooling rates of volcanic glasses

Kenderes, Stuart M.; Whittington, A. G.

doi:10.1016/j.chemgeo.2021.120385

Cited by 4 publications

(7 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additional details of the method using the specific Tool-Narayanaswamy geospeedometer can be found in Kenderes and Whittington (2021).…”

Section: Relaxation Geospeedometrymentioning

confidence: 99%

“…Previous studies that have applied relaxation geospeedometry to natural volcanic systems using the Tool-Narayanaswamy geospeedometer have required repeat CP measurements of the same sample with controlled experimental thermal histories. Repeat measurements are used to constrain four model parameters, however, Kenderes and Whittington (2021) demonstrated that similar natural cooling rate estimates can be identified using a single CP measurement. Following this method, the five unknown parameters must be solved simultaneously using a numerical solver called CoolMonte written in MATLAB.…”

Section: Relaxation Geospeedometrymentioning

confidence: 99%

“…Relaxation geospeedometry has been used to measure natural cooling rates of natural glasses of many compositions and geologic settings, including obsidian lavas (Wilding et al, 1995;Wilding et al, 1996;Gottsmann and Dingwell, 2001a;Gottsmann and Dingwell, 2001b;Wilding et al, 2004). Kenderes and Whittington (2021) improved on previous implementations on relaxation geospeedometry by developing a…”

Section: Introductionmentioning

confidence: 99%

“…We measured the amount and speciation of volatile oxides in obsidian samples using Fourier-transform infrared spectroscopy (FTIR) and constrained the thermal history by measuring natural cooling rates using relaxation geospeedometry. We modelled cooling rates of obsidian from Banco Bonito using both the multiple CP method (Wilding et al, 1995) and the newly developed single CP method (Kenderes and Whittington, 2021). Together, FTIR and relaxation geospeedometry datasets expose the thermo-rheological evolution of the effusive eruption of Banco Bonito and the VC-1 Rhyolite.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Emplacement styles of obsidian lavas: an integrated field and laboratory study

Kenderes¹

View full text Add to dashboard Cite

Previously accepted models of emplacement dynamics of obsidian lavas have recently been called into question by observations made during the effusive eruptions of Chaiten in 2008-2009 and Cordon Caulle in 2011-2012 in Chile. The eruption of Chaiten was characterized by two distinct styles of emplacement, with the transition between the two resulting in hazardous block and ash flows and periods of dome collapse. Cordon Caulle erupted an obsidian coulee that exhibited behaviors typically associated with eruptions of more mafic lavas such as inflation and advancement via break-out lobe development. Lava emplacement styles are controlled by the physical properties of the lava which are a function of composition, temperature, and time. Banco Bonito lava, Valles caldera, NM, and Obsidian Dome, Inyo Craters, Long Valley, CA are like the lavas from Cordon Caulle and Chaiten respectively and were the subject of scientific research drilling in the 1980's, providing spatially well-constrained samples that can be used to measure residual water concentrations, thermal histories, and apparent viscosities. These three datasets are then used to infer emplacement behaviors of Banco Bonito and Obsidian Dome. Thermal histories of obsidian lavas can be constrained experimentally using relaxation geospeedometry. Previous applications of the method used up to five isobaric heat capacity measurements per quantitative cooling rate, requiring multiple days of laboratory work. We present a Monte Carlo inspired numerical solver capable of identifying comparable natural cooling rates using a single experimental measurement.

show abstract

“…Additional details of the method using the specific Tool-Narayanaswamy geospeedometer can be found in Kenderes and Whittington (2021).…”

Section: Relaxation Geospeedometrymentioning

confidence: 99%

Section: Relaxation Geospeedometrymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Emplacement styles of obsidian lavas: an integrated field and laboratory study

Kenderes¹

View full text Add to dashboard Cite

show abstract

“…Afterwards, two empirical parameters (β and ξ) ranging between 0 and 1 are fitted by tweaking them to minimize the root square mean error to derive T f and thereby the unknown cooling rate (q c ). Kenderes and Whittington (2021) have recently provided a Matlab code to derive the four kinetic parameters without the need to perform multiple heat capacity measurements. However, the TNM approach cannot model the broad exothermic enthalpy relaxation upon DSC upscan before the glass transition interval typical of hyperquenched glasses (Yue et al 2002;Potuzak et al 2008;Nichols et al 2009;Zheng et al 2019).…”

Section: Theoretical Background and Experimental Challengesmentioning

confidence: 99%

Determination of cooling rates of glasses over four orders of magnitude

Scarani

Vona

Genova

et al. 2022

Contrib Mineral Petrol

View full text Add to dashboard Cite

Volcanic materials can experience up to eleven orders of magnitude of cooling rate (qc) starting from 10–5 K s−1. The glassy component of volcanic material is routinely measured via differential scanning calorimeter (DSC) to obtain qc through the determination of the glass fictive temperature (Tf). Conventional DSC (C-DSC), which has been employed for decades, can only access a relatively small range of qc (from ~ 10–2 to ~ 1 K s−1). Therefore, extrapolations up to six orders of magnitude of C-DSC data are necessary to derive qc of glasses quenched both at extremely low and high qc. Here, we test the reliability of such extrapolations by combining C-DSC with the recently introduced flash calorimetry (F-DSC). F-DSC enables to extend the qc exploration up to 104 K s−1. We use three synthetic glasses as analogs of volcanic melts. We first apply a normalization procedure of heat flow data for both C-DSC and F-DSC to derive Tf as a function of experimental qc, following the “unified area-matching” approach. The obtained Tf–qc relationship shows that Arrhenius models, widely adopted in previous studies, are only valid for qc determination within the calibration range. In contrast, a non-Arrhenius model better captures qc values, especially when a significant extrapolation is required. We, therefore, present a practical “how-to” protocol for estimating qc using DSC.

show abstract