The Experts below are selected from a list of 24132 Experts worldwide ranked by ideXlab platform
Abani Patra - One of the best experts on this subject based on the ideXlab platform.
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comparative analysis of the structures and outcomes of Geophysical Flow models and modeling assumptions using uncertainty quantification
Frontiers in Earth Science, 2020Co-Authors: Marcus Bursik, Abani Patra, Ali Akhavansafaei, Andrea Bevilacqua, Bruce E Pitman, David HymanAbstract:We advocate here a methodology for characterizing models of Geophysical Flows and the modeling assumptions they represent, using a statistical approach over the full range of applicability of the models. Such a characterization may then be used to decide the appropriateness of a model and modeling assumption for use. We present our method by comparing three different models arising from different rheology assumptions, and the output data show unambiguously the performance of the models across a wide range of possible Flow regimes. This comparison is facilitated by the recent development of the new release of our TITAN2D mass Flow code that allows choice of multiple rheologies The quantitative and probabilistic analysis of contributions from different modeling assumptions in the models is particularly illustrative of the impact of the assumptions. Knowledge of which assumptions dominate, and, by how much, is illustrated in the topography on the SW slope of Volcan de Colima (MX). A simple model performance evaluation completes the presentation.
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modernizing titan2d a parallel amr Geophysical Flow code to support multiple rheologies and extendability
IEEE International Conference on High Performance Computing Data and Analytics, 2019Co-Authors: Nikolay A Simakov, Matthew D Jones, Renette Jonesivey, Ali Akhavansafaei, Hossein Aghakhani, Abani PatraAbstract:In this work, we report on strategies and results of our initial approach for modernization of Titan2D code. Titan2D is a Geophysical mass Flow simulation code designed for modeling of volcanic Flows, debris avalanches and landslides over a realistic terrain model. It solves an underlying hyperbolic system of partial differential equations using parallel adaptive mesh Godunov scheme. The following work was done during code refactoring and modernization. To facilitate user input two level python interface was developed. Such design permits large changes in C++ and Python low-level while maintaining stable high-level interface exposed to the end user. Multiple diverged forks implementing different material models were merged back together. Data storage layout was changed from a linked list of structures to a structure of arrays representation for better memory access and in preparation for further work on better utilization of vectorized instruction. Existing MPI parallelization was augmented with OpenMP parallelization. The performance of a hash table used to store mesh elements and nodes references was improved by switching from a linked list for overFlow entries to dynamic arrays allowing the implementation of the binary search algorithm. The introduction of the new data layout made possible to reduce the number of hash table look-ups by replacing them with direct use of indexes from the storage class. The modifications lead to 8–9 times performance improvement for serial execution.
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comparative analysis of the structures and outcomes of Geophysical Flow models and modeling assumptions using uncertainty quantification
arXiv: Fluid Dynamics, 2018Co-Authors: Marcus Bursik, Abani Patra, Ali Akhavansafaei, Andrea Bevilacqua, Bruce E Pitman, David HymanAbstract: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 methodology for characterizing models and the modeling assumptions they represent, using a statistical approach over the full range of applicability of the models. Such a characterization may then be used to decide the appropriateness of a model and modeling assumption for use. We present our method by comparing three different models arising from different rheology assumptions, and the data show unambiguously the performance of the models across a wide range of possible Flow regimes. This comparison is facilitated by the recent development of the new release of our TITAN2D mass Flow code that allows choice of multiple rheologies The quantitative and probabilistic analysis of contributions from different modeling assumptions in the models is particularly illustrative of the impact of the assumptions. Knowledge of which assumptions dominate, and, by how much, is illustrated in two different case studies: a small scale inclined plane with a flat runway, and the large scale topography on the SW slope of Volcan de Colima (MX). A simple model performance evaluation completes the presentation.
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digital elevation model uncertainty and hazard analysis using a Geophysical Flow model
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2012Co-Authors: E R Stefanescu, Marcus Bursik, G Cordoba, K Dalbey, Matthew D Jones, Abani Patra, D C Pieri, E B Pitman, Michael F SheridanAbstract:This paper describes a new methodology to quantify the variation in the output of a computational fluid dynamics model for block and ash Flows, when the digital elevation model (DEM) of the terrain and other inputs are given as a range of possible values with a prescribed uncertainty. Integrating these variations in the possible Flows as a function of input uncertainties provides well-defined hazard probabilities at specific locations, i.e. a hazard map. Earlier work provided a methodology for assessing hazards based on variations in Flow initiation and friction parameters. This paper extends this approach to include the effect of terrain error and uncertainty. The results are based on potential Flows at Mammoth Mountain, CA, and Galeras Volcano, Colombia. The analysis establishes the soundness of the approach and the effect of including the uncertainty in DEMs in the construction of probabilistic hazard maps.
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effect of digital elevation model on mohr coulomb Geophysical Flow model output
Natural Hazards, 2012Co-Authors: E R Stefanescu, Marcus Bursik, Abani PatraAbstract:Digital elevation models (DEMs) used in geospatial analysis like the simulation of Geophysical Flows, such as floods, landslides, and block and ash Flows, differ in resolution, acquisition time and generation methodology, which results in varied representation of topographic features. This study investigates the effects of DEMs on the output of a granular Flow model, TITAN2D by comparing the output using different DEMs to that obtained with a “true” representation of the terrain, which is considered to be that obtained by using TOPSAR 5 m data. Seven DEMs at four resolutions from four sources were used for Mammoth Mountain, California, a cumulodome volcano. TITAN2D was run for seven different locations of an eruption of a potential dome and two different collapse volumes. The resulting outputs were subsequently compared with TOPSAR 5 m output, and qualitative and statistical inferences were drawn. DEMs with different resolutions and sources generated different outputs that led to different Flow maps. For moderate and smaller scale Flows ( $$\mathcal{O}(10^4)$$ m3 – $$\mathcal{O}(10^5) \,\text{m}^3$$ ), different representations can affect the computation of accurate footprint of the Flow and fine DEM resolution is critical for correct characterization of these Flows.
Matthew D Jones - One of the best experts on this subject based on the ideXlab platform.
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modernizing titan2d a parallel amr Geophysical Flow code to support multiple rheologies and extendability
IEEE International Conference on High Performance Computing Data and Analytics, 2019Co-Authors: Nikolay A Simakov, Matthew D Jones, Renette Jonesivey, Ali Akhavansafaei, Hossein Aghakhani, Abani PatraAbstract:In this work, we report on strategies and results of our initial approach for modernization of Titan2D code. Titan2D is a Geophysical mass Flow simulation code designed for modeling of volcanic Flows, debris avalanches and landslides over a realistic terrain model. It solves an underlying hyperbolic system of partial differential equations using parallel adaptive mesh Godunov scheme. The following work was done during code refactoring and modernization. To facilitate user input two level python interface was developed. Such design permits large changes in C++ and Python low-level while maintaining stable high-level interface exposed to the end user. Multiple diverged forks implementing different material models were merged back together. Data storage layout was changed from a linked list of structures to a structure of arrays representation for better memory access and in preparation for further work on better utilization of vectorized instruction. Existing MPI parallelization was augmented with OpenMP parallelization. The performance of a hash table used to store mesh elements and nodes references was improved by switching from a linked list for overFlow entries to dynamic arrays allowing the implementation of the binary search algorithm. The introduction of the new data layout made possible to reduce the number of hash table look-ups by replacing them with direct use of indexes from the storage class. The modifications lead to 8–9 times performance improvement for serial execution.
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digital elevation model uncertainty and hazard analysis using a Geophysical Flow model
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2012Co-Authors: E R Stefanescu, Marcus Bursik, G Cordoba, K Dalbey, Matthew D Jones, Abani Patra, D C Pieri, E B Pitman, Michael F SheridanAbstract:This paper describes a new methodology to quantify the variation in the output of a computational fluid dynamics model for block and ash Flows, when the digital elevation model (DEM) of the terrain and other inputs are given as a range of possible values with a prescribed uncertainty. Integrating these variations in the possible Flows as a function of input uncertainties provides well-defined hazard probabilities at specific locations, i.e. a hazard map. Earlier work provided a methodology for assessing hazards based on variations in Flow initiation and friction parameters. This paper extends this approach to include the effect of terrain error and uncertainty. The results are based on potential Flows at Mammoth Mountain, CA, and Galeras Volcano, Colombia. The analysis establishes the soundness of the approach and the effect of including the uncertainty in DEMs in the construction of probabilistic hazard maps.
Michael F Sheridan - One of the best experts on this subject based on the ideXlab platform.
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digital elevation model uncertainty and hazard analysis using a Geophysical Flow model
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2012Co-Authors: E R Stefanescu, Marcus Bursik, G Cordoba, K Dalbey, Matthew D Jones, Abani Patra, D C Pieri, E B Pitman, Michael F SheridanAbstract:This paper describes a new methodology to quantify the variation in the output of a computational fluid dynamics model for block and ash Flows, when the digital elevation model (DEM) of the terrain and other inputs are given as a range of possible values with a prescribed uncertainty. Integrating these variations in the possible Flows as a function of input uncertainties provides well-defined hazard probabilities at specific locations, i.e. a hazard map. Earlier work provided a methodology for assessing hazards based on variations in Flow initiation and friction parameters. This paper extends this approach to include the effect of terrain error and uncertainty. The results are based on potential Flows at Mammoth Mountain, CA, and Galeras Volcano, Colombia. The analysis establishes the soundness of the approach and the effect of including the uncertainty in DEMs in the construction of probabilistic hazard maps.
Konstantin V. Koshel - One of the best experts on this subject based on the ideXlab platform.
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Interaction of a monopole vortex with an isolated topographic feature in a three-layer Geophysical Flow
Nonlinear Processes in Geophysics, 2013Co-Authors: E. A. Ryzhov, Konstantin V. KoshelAbstract:In the frame of a three-layer quasi-geostrophic analytical model of a $f$-plane Geophysical Flow, Lagrangian advection being induced by the interaction of a monopole vortex with an isolated topographic feature is addressed. Two different cases when the monopole locates either within the upper or the middle layer are of our interest. In the bottom layer, there is a delta function topographic feature, which generates a closed recirculation region in its vicinity due to the background Flow. This recirculation region extends to the middle and upper layers, and it plays the role of a topographic vortex. The interaction between the monopole and the topographic vortex causes complex, including chaotic, advection of fluid particles. We show that the model's parameters, namely, the monopole and topographic vortices' strengths and initial positions, the layers' depths and densities are responsible for the diverse advection patterns. While the patterns are rather complicated, however, one can single out two major processes, which mostly govern fluid particle advection. The first one is the variation in time of the system's phase space structure, so that within the closed region of the topographic vortex, there appear periodically unclosed particle pathways by which the particles leave the topographic vortex. The second one is chaotic advection that arises from the nonstationarity of the monopole-topography interaction.
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interaction of a monopole vortex with an isolated topographic feature in a three layer Geophysical Flow
Nonlinear Processes in Geophysics, 2013Co-Authors: E. A. Ryzhov, Konstantin V. KoshelAbstract:Abstract. In the frame of a three-layer, quasi-geostrophic analytical model of an f-plane Geophysical Flow, the Lagrangian advection induced by the interaction of a monopole vortex with an isolated topographic feature is addressed. Two different cases when the monopole is located either within the upper or the middle layer are of our interest. In the bottom layer, there is a delta-function topographic feature, which generates a closed recirculation region in its vicinity due to the background Flow. This recirculation region extends to the middle and upper layers, and it plays the role of a topographic vortex. The interaction between the monopole and the topographic vortex causes a complex, including chaotic, advection of fluid particles. We show that the model's parameters, namely the monopole and topographic vortices' strengths and initial positions, and the layers' depths and densities, are responsible for the diverse advection patterns. While the patterns are rather complicated, one can single out two major processes, which mostly govern the fluid particle advection. The first one is the variation in time of the system's phase space structure, so that within the closed region of the topographic vortex, there appear periodically unclosed particle pathways by which the particles leave the topographic vortex. The second one is chaotic advection that arises from the nonstationarity of the monopole–topography interaction.
E R Stefanescu - One of the best experts on this subject based on the ideXlab platform.
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digital elevation model uncertainty and hazard analysis using a Geophysical Flow model
Proceedings of The Royal Society A: Mathematical Physical and Engineering Sciences, 2012Co-Authors: E R Stefanescu, Marcus Bursik, G Cordoba, K Dalbey, Matthew D Jones, Abani Patra, D C Pieri, E B Pitman, Michael F SheridanAbstract:This paper describes a new methodology to quantify the variation in the output of a computational fluid dynamics model for block and ash Flows, when the digital elevation model (DEM) of the terrain and other inputs are given as a range of possible values with a prescribed uncertainty. Integrating these variations in the possible Flows as a function of input uncertainties provides well-defined hazard probabilities at specific locations, i.e. a hazard map. Earlier work provided a methodology for assessing hazards based on variations in Flow initiation and friction parameters. This paper extends this approach to include the effect of terrain error and uncertainty. The results are based on potential Flows at Mammoth Mountain, CA, and Galeras Volcano, Colombia. The analysis establishes the soundness of the approach and the effect of including the uncertainty in DEMs in the construction of probabilistic hazard maps.
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effect of digital elevation model on mohr coulomb Geophysical Flow model output
Natural Hazards, 2012Co-Authors: E R Stefanescu, Marcus Bursik, Abani PatraAbstract:Digital elevation models (DEMs) used in geospatial analysis like the simulation of Geophysical Flows, such as floods, landslides, and block and ash Flows, differ in resolution, acquisition time and generation methodology, which results in varied representation of topographic features. This study investigates the effects of DEMs on the output of a granular Flow model, TITAN2D by comparing the output using different DEMs to that obtained with a “true” representation of the terrain, which is considered to be that obtained by using TOPSAR 5 m data. Seven DEMs at four resolutions from four sources were used for Mammoth Mountain, California, a cumulodome volcano. TITAN2D was run for seven different locations of an eruption of a potential dome and two different collapse volumes. The resulting outputs were subsequently compared with TOPSAR 5 m output, and qualitative and statistical inferences were drawn. DEMs with different resolutions and sources generated different outputs that led to different Flow maps. For moderate and smaller scale Flows ( $$\mathcal{O}(10^4)$$ m3 – $$\mathcal{O}(10^5) \,\text{m}^3$$ ), different representations can affect the computation of accurate footprint of the Flow and fine DEM resolution is critical for correct characterization of these Flows.