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E. Bruce Pitman
University at Buffalo
58Publications
18H-index
1,097Citations
Publications 58
Newest
#1Qingyuan Yang (UB: University at Buffalo)H-Index: 2
#2Marcus I. Bursik (UB: University at Buffalo)H-Index: 34
Last.E. Bruce Pitman (UB: University at Buffalo)H-Index: 18
view all 3 authors...
A new method to identify the source vent location of tephra fall deposits based on thickness or maximum clast size measurements is presented in this work. It couples a first-order gradient descent method with either one of two commonly used semi-empirical models of tephra thickness distribution. The method is applied to three tephra thickness and one maximum clast size datasets of the North Mono and Fogo A tephra deposits. Randomly selected and localized subsets of these datasets are used as inp...
Source
#1Andrea Bevilacqua (UB: University at Buffalo)H-Index: 7
#2Abani K. Patra (UB: University at Buffalo)H-Index: 26
Last.David Hyman (UB: University at Buffalo)H-Index: 2
view all 7 authors...
Abstract. We detail a new prediction-oriented procedure aimed at volcanic hazard assessment based on geophysical mass flow models constrained with heterogeneous and poorly defined data. Our method relies on an itemized application of the empirical falsification principle over an arbitrarily wide envelope of possible input conditions. We thus provide a first step towards a objective and partially automated experimental design construction. In particular, instead of fully calibrating model inputs ...
2 CitationsSource
#1Andrea Bevilacqua (UB: University at Buffalo)H-Index: 7
#2Marcus I. Bursik (UB: University at Buffalo)H-Index: 34
Last.Shannon Kobs-Nawotniak (ISU: Idaho State University)H-Index: 1
view all 7 authors...
8 CitationsSource
#1Qingyuan YangH-Index: 2
#2Marcus I. BursikH-Index: 34
Last.E. Bruce PitmanH-Index: 18
view all 3 authors...
A new method to identify the source vent location of tephra fall deposits based on thickness or maximum clast size measurements is presented in this work. It couples a first-order gradient descent method with either one of two commonly-used semi-empirical models of tephra thickness distribution. The method is successfully applied to three tephra thickness and one maximum clast size datasets of the North Mono and Fogo A tephra deposits. Randomly selected and localized subsets of these datasets ar...
#1Abani K. PatraH-Index: 26
#2Andrea BevilacquaH-Index: 7
Last.David HymanH-Index: 2
view all 6 authors...
We present a new statistically driven method for analyzing the modeling of geophysical flows. Many models have been advocated by different modelers for such flows incorporating different modeling assumptions. Limited and sparse observational data on the modeled phenomena usually does not permit a clean discrimination among models for fitness of purpose, and, heuristic choices are usually made, especially for critical predictions of behavior that has not been experienced. We advocate here a metho...
1 Citations
#1Andrea BevilacquaH-Index: 7
#2E. Bruce PitmanH-Index: 18
Last.Augusto NeriH-Index: 33
view all 4 authors...
We introduce a doubly stochastic method for performing material failure theory based forecasts of volcanic eruptions. The method enhances the well known Failure Forecast Method equation, introducing a new formulation similar to the Hull-White model. In particular, we incorporate a stochastic noise term in the original equation, and systematically characterize the uncertainty. The model is a stochastic differential equation (SDE) with a mean reverting solution, which assumes the traditional ordin...
We introduce a doubly stochastic method for performing material failure theory based forecasts of volcanic eruptions. The method enhances the well known Failure Forecast Method equation, introducing a new formulation similar to the Hull-White model in financial mathematics. In particular, we incorporate a stochastic noise term in the original equation, and systematically characterize the uncertainty. The model is a stochastic differential equation with mean reverting paths, where the traditional...
#1Edward Swinnich (UB: University at Buffalo)H-Index: 2
#2Yash Jayeshbhai Dave (UB: University at Buffalo)H-Index: 1
Last.Jung-Hun Seo (UB: University at Buffalo)H-Index: 24
view all 6 authors...
Abstract In this study, the optical band gap of β-(AlxGa1-x)2O3 versus the Al composition x is predicted using principal component regression and a Gaussian stochastic process. Properties were sourced from other mature Al-alloyed compound semiconductors to form a band gap model. It is found that the electronic band gap, the thermal conductivity, and the Al composition have the greatest influences on the optical band gap. A final relation is generated from a hybrid informatics approach combining ...
3 CitationsSource
#1Andrea BevilacquaH-Index: 7
#2Marcus I. BursikH-Index: 34
Last.Ryan TillH-Index: 1
view all 5 authors...
11 CitationsSource
#1Zhixuan Cao (UB: University at Buffalo)H-Index: 1
#2Abani K. Patra (UB: University at Buffalo)H-Index: 26
Last.Matthew D. Jones (UB: University at Buffalo)H-Index: 18
view all 5 authors...
Abstract. Plume-SPH provides the first particle-based simulation of volcanic plumes. Smoothed particle hydrodynamics (SPH) has several advantages over currently used mesh-based methods in modeling of multiphase free boundary flows like volcanic plumes. This tool will provide more accurate eruption source terms to users of volcanic ash transport and dispersion models (VATDs), greatly improving volcanic ash forecasts. The accuracy of these terms is crucial for forecasts from VATDs, and the 3-D SPH...
1 CitationsSource
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