Development of a High Strain-Rate Constitutive Model for Sands and its Application in Finite Element Analysis of Tunnels Subjected to Blast
Bibliographic record
Abstract
This thesis describes the development of a constitutive model for simulating the high strain-rate behavior of sands and demonstrates the use of the model by analyzing underground tunnels subjected to blast. The constitutive model is based on the concepts of the critical state soil mechanics and bounding surface plasticity theory. The model captures the behavior of sand under multi-axial loading conditions and predicts both drained and undrained behavior at small and large strains. Perzyna’s overstress theory is incorporated in the model to simulate the viscoplastic behavior of sand under high strain rate. The model follows a nonassociated flow rule.\nThe model parameters are determined for Ottawa and Fontainebleau sands from the available experimental data of rate-independent triaxial compression test and split Hopkinson pressure bar test. The model is implemented in the finite element software Abaqus through user defined material subroutines. Finite element simulations of the split Hopkinson pressure bar experiments on Ottawa and Fontainebleau sands are performed in which the maximum axial strain rate was 2000/sec. These simulations demonstrate the model’s ability to capture the high strain-rate behavior of sands.\nSubsequently, finite element analyses of tunnels embedded in sandy soils and subjected to internal blast loading are performed using Abaqus in which the developed constitutive model is used. Blast induced pressure loading, simulated with the JWL explosive material model, is applied on the internal tunnel boundary. The effects of soil type, depth of tunnel and quantity of explosive on the blast induced stresses, strains and deformations in the soil surrounding the tunnel are investigated. These analyses demonstrate the use of the constitutive model in the study of soil-structure interaction problems under blast induced dynamic loading.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".