Investigation on Erosion and Deposition Behavior of Debris Flow Transport Process with Numerical Simulation and Deep Learning Based Experimental Analysis Method(3/3)

Project Details

Description

In recent years, global warming causes many large scale geophysical granular flows that occur in nature such as hazardous natural events that include lahars, debris flows, snow avalanches and dense pyroclastic flows. An increase in the internal pore water pressure by extremely heavy rain cause the shear strength inside the rock to decrease, causing extremely granular avalanche behavior. At the same time, the rapid population growth will cause the utilization rate of the flat land become saturated. Human’s over-exploitation of hillsides will eventually accelerate the occurrence of landsides, rock-fall, debris flow, etc. It also poses a great loss of national economy and threat to the life. Therefore, the research on the formation of debris flow and its dynamic properties is necessary and urgency to the prevention of granular avalanche disasters. The study of erosion and deposition of granular transport is a topic that many researcher concern in the hydraulic engineering and environmental engineering field. This aims of the three years MOST project is to investigate the dynamics of granular avalanche, the erosion rate and the deposition behavior in different region of the development process of debris flow. In the first year, we performed experiments to examine the effect of the granular volume ratio and aspect ratio of accumulation of granules on collapse rate, falling time, volume fraction, erosion and deposition behavior. Using image processing technology and the particle tracking method, we also measured the dynamic average velocities, fluctuation velocities, granular temperature and diffusion coefficient. Discrete element method will also be studied and compared with experiment results in this study. Deflecting obstacles are often built to divert hazardous flows away from residential areas that are in the way of harm. Therefore, in the second and third year, we will focus on observe the change and effect of the obstacle in the granular avalanche flow. The second year project, we use chutes with four different inclined angles combined with different obstacles position and shape to investigate the overall flow behavior. The normal and shear stresses will also be measured for determining the effective viscosity. The third year project, the flow field of solid-fluid two-phase flow in the deposition area will be discussed. The purpose was to quantify the effect of fluid flow rate on the granular bed and obstacles in the rectangular sink. In addition, we will develop a deep learning based experimental analysis method for the granular flow field. It will be used to the measurement of related physical quantities in the debris flow field in this project.
StatusActive
Effective start/end date1/08/2231/07/23

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action
  • SDG 17 - Partnerships for the Goals

Keywords

  • deep learning
  • debris flow
  • dam break flow
  • granular avalanche
  • erosion rate
  • deposition

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