A Systematic Method to Determine and Test the Ignition and Growth Reactive Flow Model Parameters of a Newly Designed Polymer-Bonded Explosive

2018 ◽  
Vol 43 (9) ◽  
pp. 948-954 ◽  
Author(s):  
Xiao Li ◽  
Yi Sun ◽  
Hongda Zhao ◽  
Youcai Xiao ◽  
Xuanming Cai ◽  
...  
Keyword(s):  
Flow Model ◽  
Reactive Flow ◽  
Model Parameters ◽  
Systematic Method

A Reactive Flow Model with Coupled Reaction Kinetics for Detonation and Combustion in Non-Ideal Explosives

1995 ◽  
Vol 418 ◽  
Author(s):  
Philip J. Miller
Keyword(s):  
Reaction Kinetics ◽  
Flow Model ◽  
Reaction Model ◽  
Reactive Flow ◽  
Model Parameters ◽  
Combustion Chemistry ◽  
Metal Combustion ◽  
Dimensional Finite Element ◽  
Hydrodynamic Code ◽  
Coupled Reaction

AbstractA new reactive flow model for highly non-ideal explosives and propellants is presented. These compostions, which contain large amounts of metal, upon explosion have reaction kinetics that are characteristic of both fast detonation and slow metal combustion chemistry. A reaction model for these systems was incorporated into the two-dimensional, finite element, Lagrangian hydrodynamic code, DYNA2D. A description of how to determine the model parameters is given.

A reactive flow model of the geothermal reservoir Waiwera, New Zealand

2004 ◽  
Vol 13 (4) ◽  
pp. 606-626 ◽  
Author(s):  
Michael Kühn ◽  
Heinke Stöfen
Keyword(s):  
New Zealand ◽  
Flow Model ◽  
Geothermal Reservoir ◽  
Reactive Flow

scholarly journals Automated calibration of a two-dimensional overland flow model by estimating Manning's roughness coefficient using genetic algorithm

2017 ◽  
Vol 20 (2) ◽  
pp. 440-456
Author(s):  
J. Drisya ◽  
D. Sathish Kumar
Keyword(s):  
Genetic Algorithm ◽  
Flow Model ◽  
Overland Flow ◽  
Fitness Function ◽  
Roughness Coefficient ◽  
Model Parameters ◽  
Automatic Data ◽  
Automated Calibration ◽  
Manning’S Roughness Coefficient ◽  
Overland Flow Model

Abstract Calibration is an important phase in the hydrological modelling process. In this study, an automated calibration framework is developed for estimating Manning's roughness coefficient. The calibration process is formulated as an optimization problem and solved using a genetic algorithm (GA). A heuristic search procedure using GA is developed by including runoff simulation process and evaluating the fitness function by comparing the experimental results. The model is calibrated and validated using datasets of Watershed Experimentation System. A loosely coupled architecture is followed with an interface program to enable automatic data transfer between overland flow model and GA. Single objective GA optimization with minimizing percentage bias, root mean square error and maximizing Nash–Sutcliffe efficiency is integrated with the model scheme. Trade-offs are observed between the different objectives and no single set of the parameter is able to optimize all objectives simultaneously. Hence, multi-objective GA using pooled and balanced aggregated function statistic are used along with the model. The results indicate that the solutions on the Pareto-front are equally good with respect to one objective, but may not be suitable regarding other objectives. The present technique can be applied to calibrate the hydrological model parameters.

scholarly journals Back-calculation of the 2017 Piz Cengalo-Bondo landslide cascade with r.avaflow

2019 ◽  
Author(s):  
Martin Mergili ◽  
Michel Jaboyedoff ◽  
José Pullarello ◽  
Shiva P. Pudasaini
Keyword(s):  
Debris Flow ◽  
Flow Model ◽  
Rock Avalanche ◽  
Simulation Software ◽  
Process Models ◽  
Rock Fall ◽  
Model Parameters ◽  
Rock Slide ◽  
Glacier Ice ◽  
Initial Rock

Abstract. In the morning of 23 August 2017, around 3 million m3 of granitoid rock broke off from the east face of Piz Cengalo, SE Switzerland. The initial rock slide-rock fall entrained 0.6 million m3 of a glacier and continued as a rock(-ice) avalanche, before evolving into a channelized debris flow that reached the village of Bondo at a distance of 6.5 km after a couple of minutes. Subsequent debris flow surges followed in the next hours and days. The event resulted in eight fatalities along its path and severely damaged Bondo. The most likely candidates for the water causing the transformation of the rock avalanche into a long-runout debris flow are the entrained glacier ice and water originating from the debris beneath the rock avalanche. In the present work we try to reconstruct conceptually and numerically the cascade from the initial rock slide-rock fall to the first debris flow surge and thereby consider two scenarios in terms of qualitative conceptual process models: (i) entrainment of most of the glacier ice by the frontal part of the initial rock slide-rock fall and/or injection of water from the basal sediments due to sudden rise in pore pressure, leading to a frontal debris flow, with the rear part largely remaining dry and depositing mid-valley; and (ii) most of the entrained glacier ice remaining beneath/behind the frontal rock avalanche, and developing into an avalanching flow of ice and water, part of which overtops and partially entrains the rock avalanche deposit, resulting in a debris flow. Both scenarios can be numerically reproduced with the two-phase mass flow model implemented with the simulation software r.avaflow, based on plausible assumptions of the model parameters. However, these simulation results do not allow to conclude on which of the two scenarios is the more likely one. Future work will be directed towards the application of a three-phase flow model (rock, ice, fluid) including phase transitions, in order to better represent the melting of glacier ice, and a more appropriate consideration of deposition of debris flow material along the channel.

scholarly journals Comparison of three Models of Avalanche Dynamics

1989 ◽  
Vol 13 ◽  
pp. 82-89 ◽  
Author(s):  
H. Gubler
Keyword(s):  
Differential Equation ◽  
Granular Flow ◽  
Flow Model ◽  
Model Parameters ◽  
Field Observations ◽  
Segmentation Method ◽  
Avalanche Dynamics ◽  
Flow Speeds ◽  
Avalanche Flow ◽  
Longitudinal Profiles

Results and characteristics of three models for estimating avalanche flow speeds, flow heights, and run-out distances are compared: (1) Voellmy–Salm equation used with the traditional release, track, and run-out segmentation method; (2) Voellmy–Salm differential equation solved numerically along longitudinal profiles of avalanche paths, combined with modified assumptions for the flow in the run-out zone; (3) a granular-flow model introduced by Salm and Gubler. Within the limits of the accuracy of the field observations, all models are able to predict run-out distances correctly, at least for large avalanches, but the Voellmy–Salm type models significantly underestimate flow speeds. Modelling different flow regimes (sliding and partial fluidization) increases the range of avalanche sizes for which correct run-out modelling is possible without recalibration of model parameters.

Sign in / Sign up

Export Citation Format

Share Document