Withdraw
Loading…
Next generation triaxial apparatus using combined computational-experimental testing framework
Asmar, Randa Khaleel
Loading…
Permalink
https://hdl.handle.net/2142/97439
Description
- Title
- Next generation triaxial apparatus using combined computational-experimental testing framework
- Author(s)
- Asmar, Randa Khaleel
- Issue Date
- 2017-04-21
- Director of Research (if dissertation) or Advisor (if thesis)
- Hashash, Youssef M. A.
- Doctoral Committee Chair(s)
- Hashash, Youssef M. A.
- Committee Member(s)
- Ghaboussi, Jamshid
- Olson, Scott M.
- Rutherford, Cassandra J.
- Department of Study
- Civil & Environmental Eng
- Discipline
- Civil Engineering
- Degree Granting Institution
- University of Illinois at Urbana-Champaign
- Degree Name
- Ph.D.
- Degree Level
- Dissertation
- Keyword(s)
- Modified triaxial device
- Digital photogrammetry
- Image processing
- 3D deformations
- Inverse analysis
- Deep learning
- Abstract
- Solving complex boundary value problems in geotechnical engineering requires a soil constitutive model that reliably captures the soil behavior under general loading conditions. However, soil behavior is commonly characterized based on laboratory tests with imposed or assumed uniform stress and strain distribution within the soil specimen for convenient data reduction. This uniformity assumption limits each test to a single stress–strain path, and therefore extensive laboratory testing is required to represent real soil behavior such as small strain nonlinearity and anisotropy. The process of development of material constitutive models remains lengthy and requires numerous tests to cover a broad range of loading paths. This limited information generally results in a constitutive model that may not be justifiable to represent loading conditions that differ substantially from the ones in laboratory tests. This study presents the development of a modified triaxial device that can generate multiple stress paths in a single test which can be extracted using Self-learning simulations (SelfSim) inverse analysis – an advanced deep learning computational engine. The new device inherits all features of a conventional triaxial test, and adds lateral restraint clamps, to increase non-uniformity in specimen deformation, combined with a digital photogrammetry system to measure the 3-D deformed shapes of the specimen. Using two high resolution digital cameras mounted in front of the cell, the system is able to capture the specimen’s deformed shape synchronously with measurements of loads, axial displacement, and pore pressures/volume change during the shearing process. The design of the restraint clamps was optimized using numerical simulations which showed that the sheared specimen includes shear modes that cannot currently be mobilized with available testing devices. Evaluation of the proposed device was done by testing soil specimens of Ottawa sand using both conventional and modified triaxial devices. The photogrammetry system was able to successfully capture the specimen deformations and these deformations are highly non-uniform in the new apparatus compared with those using a conventional triaxial device. SelfSim is employed to interpret Ottawa sand shear behavior. The tested sand specimens cover three different relative densities, and were tested under three different confining pressures. A soil-specific material constitutive model can be generated from this information. The constitutive model can then be directly used within a numerical analysis (e.g., finite element (FE) method) of a geotechnical problem.
- Graduation Semester
- 2017-05
- Type of Resource
- text
- Permalink
- http://hdl.handle.net/2142/97439
- Copyright and License Information
- Copyright 2017 Randa Asmar
Owning Collections
Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at IllinoisManage Files
Loading…
Edit Collection Membership
Loading…
Edit Metadata
Loading…
Edit Properties
Loading…
Embargoes
Loading…