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Digging deep: A data-driven approach to model reduction in a granular bulldozing scenario
Umeå University, Faculty of Science and Technology, Department of Physics.
2018 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The current simulation method for granular dynamics used by the physics engine AGX Dynamics is a nonsmooth variant of the popular Discrete Element Method (DEM). While powerful, there is a need for close to real time simulations of a higher spatial resolution than currently possible. In this thesis a data-driven model reduction approach using machine learning was considered. A data-driven simulation pipeline was presented and partially implemented. The method consists of sampling the velocity and density field of the granular particles and teaching a machine learning algorithm to predict the particles' interaction with a bulldozer blade as well as predicting the time evolution of its velocity field. A procedure for producing training scenarios and training data for the machine learning algorithm was implemented as well as several machine learning algorithms; a linear regressor, a multilayer perceptron and a convolutional neural network. The results showed that the method is promising, however further work will need to show whether or not the pipeline is feasible to implement in a simulation.

Place, publisher, year, edition, pages
2018. , p. 44
Keywords [en]
Machine learning, granular dynamics, deep learning, discrete element method, earthmoving, neural network
National Category
Physical Sciences Computer and Information Sciences
Identifiers
URN: urn:nbn:se:umu:diva-152498OAI: oai:DiVA.org:umu-152498DiVA, id: diva2:1254164
External cooperation
Algoryx Simulation AB
Subject / course
Examensarbete i teknisk fysik
Educational program
Master of Science Programme in Engineering Physics
Presentation
2018-06-08, NA340, Naturvetarhuset, Naturvetarhuset, Universitetsvägen, Umeå, 09:00 (English)
Supervisors
Examiners
Available from: 2018-10-08 Created: 2018-10-08 Last updated: 2018-10-08Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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