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2024 Terzaghi Lecture - Coggle Diagram
2024 Terzaghi Lecture
Introduction
Historical
Mohr-Coulomb, Drucker-Prager
Emphasis on simplicity
Motivation
complexity of geotechnical structures
Demand for realistic stress–strain and time-dependent modeling
Integration with finite element (FE) and finite difference analyses
Challenges
Scale effects (lab → field)
Incomplete material characterization
Computational limits
Objective
three advanced MIT models (E3, S1, SR)
Demonstrate their predictive capabilities
Discuss lessons from real-world case histories
Concluding Remarks
Value of Constitutive Modeling
Enhances predictive capability in design.
Reduces uncertainty in risk assessment.
Bridging Laboratory & Field
Advanced models calibrated from lab data → reliable field-scale performance.
Need for Simplicity vs. Complexity
Complex models should serve design efficiency, not hinder it.
Balance between accuracy and practicality.
Future Directions
Coupled hydro-mechanical modeling.
Multi-scale soil characterization (particle to structure).
AI/data-driven calibration of soil parameters.
Lessons Learned from Applications for Clays
Deep Excavations & Retaining Structures
Accurate simulation of wall deflections and ground movements.
Importance of anisotropy in stiffness and strength.
Time-dependent behavior critical for long-term stability.
Soft Clay Consolidation
MIT-SR predicts settlement rates and creep accurately.
Captures secondary compression → critical for embankments and land reclamation.
Pile & Foundation Behavior
Model explains setup phenomenon (increase in capacity over time).
Captures reconsolidation and aging effects after installation.
Lessons Learned from Applications for Sands
Liquefaction & Instability
Captures pre-failure strain accumulation.
Predicts pore pressure generation and post-liquefaction strength.
Explains cyclic mobility behavior under repeated loading.
Embankment & Slope Stability
Accounts for state parameter and dilatancy angle.
Predicts different failure modes depending on density and confinement.
Foundations & Offshore Structures
Accurately reproduces load–displacement behavior in dense and loose sands.
Useful for offshore monopiles and footings.
1D Soil Compression Behavior and Three Generalized Soil
Models
1D Compression Behavior
Soils display non-linear stress–strain and irreversible plastic deformation.
Parameters
Void ratio (e), mean stress (p), plastic strain (εp)
Phases
Elastic Region → Yield → Plastic Compression → Creep
Generalized Models
E3 for Clays
anisotropy and rotation of yield surface.
Accounts for overconsolidation and fabric effects.
Based on critical state and bounding surface theory.
S1 for sands
Introduces state parameter (ψ = e - ec) linking void ratio to strength.
Predicts both contractive and dilative responses.
Models liquefaction and post-liquefaction behavior.
SR for creep & rate effects
Combines elasticity, plasticity, and viscoplasticity.
Captures time-dependent settlements (secondary compression).
Useful for long-term prediction of soft clay consolidation.