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Jeff Lam, M.Eng., P.Eng.
Rocscience, Toronto, Ontario, Canada
ProbabilisticSlopeStabilityAnalysisofanEarth‐filledEmbankmentDam– CaseStudy
Geo3T2, Cary, North Carolina
April 12, 2017
Motivation
Background – Summary of Analysis Techniques
Case Study – Methodology
Case Study – Analysis Results
Outline
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•Determine the feasibility of implementing probabilistic based design with data from existing projects
•Validate results from probabilistic based design with observed performance
Motivation
Background
Deterministic Probabilistic
Traditional Standard Based
Non‐traditional probability based
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Background
Deterministic Probabilistic
Traditional Standard Based
Non‐traditional probability based
Background
Deterministic Probabilistic
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Background
Deterministic Probabilistic
Background
Deterministic Probabilistic
Traditional Standard Based
Non‐traditional probability based
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Background
Deterministic Probabilistic
Traditional Standard Based
Non‐traditional probability based
Background
Deterministic Probabilistic
Traditional Standard Based
1.2
Non‐traditional probability based
2.3
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Background
Deterministic Probabilistic
Uncertainty handled discretely through the use of “most likely scenarios”, “worst case scenarios”, etc.
Most Likely Case FoS = 1.5
Worst Case FoS = 1.2
The combined effects of various scenarios and their probability of occurrence considered holistically.
Pf = 0.5%
Background
Deterministic Probabilistic
Analytical
α
Iteration• Limit Equilibrium
Approximation• Finite element analysis• Tables and charts
Analytical
ϕ ϕ
Simulation• Monte Carlo simulation
Approximation• Tables and charts• Uncertainty propagation• Other reliability methods
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Background
Deterministic Probabilistic
Analytical
α
Iteration• Limit Equilibrium
Approximation• Finite element analysis• Tables and charts
Analytical
ϕ ϕ
Simulation• Monte Carlo simulation
Approximation• Tables and charts• Uncertainty propagation• Other reliability methods
Background
Deterministic Probabilistic
Analytical
α
Iteration• Limit Equilibrium
Approximation• Tables and charts• Finite element analysis
Analytical
ϕ ϕ
Simulation• Monte Carlo simulation
Approximation• Tables and charts• Uncertainty propagation• Other reliability methods
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Background
Background
Deterministic Probabilistic
Analytical
α
Iteration• Limit Equilibrium
Approximation• Tables and charts• Finite element analysis
Analytical
ϕ ϕ
Simulation• Monte Carlo simulation
Approximation• Tables and charts• Uncertainty propagation• Other reliability methods
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Background
Deterministic Probabilistic
Analytical
α
Iteration• Limit Equilibrium
Approximation• Finite element analysis• Tables and charts
Analytical
ϕ ϕ
Simulation• Monte Carlo simulation
Approximation• Tables and charts• Uncertainty propagation• Other reliability methods
μ= 1.00σ= 0.10Pf = 0.48
Case Study
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Methodology
Methodology
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Methodology
Methodology
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Analytical Model:Morgenstern‐Price 2D Limit Equilibrium
Reliability Analysis Method:Monte Carlo Simulation
Defining the Failure: Factor of Safety <1
Defining Material Properties: Literature review (Phoon & Kulhawy 1999), tailings data from similar mines, calculated some based on lab test data.
Analysis Tool: Slide by Rocscience
Methodology
Defining Material Properties:
Methodology
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Defining Material Properties:
Methodology
Model Calibration:
Methodology
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Model Calibration:
Methodology
μ= 1.00σ= 0.10Pf = 0.48
Model Calibration:
Methodology
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Defining Geological Model:
Methodology
10’
650’
Defining Geological Model:
Methodology
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Defining Geological Model:
Methodology GW96-1A
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10’ thick - 650' diameter
Defining Geological Model:
Methodology
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Methodology
Defining Geological Model:
Methodology
10’ – 20’
10’
650’
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Defining Geological Model:
Methodology
20’ – 30’
10’
650’
Defining Geological Model:
Methodology
30’ – 40’
10’
650’
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Results
•Risk = Probability x Consequence
•Discount cash flow valuations when valuing projects for business cases
•Justifying site investigation costs – “You pay for a site investigation program whether you have one or not.” So how many boreholes do we need?
Conclusion
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Questions?
Results
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