Accession Number : ADA304692

Title :   Probabilistic Structural Analysis of Deep Tunnels.

Descriptive Note : Technical rept. 9 Jan 90-30 Jun 95,

Corporate Author : SOUTHWEST RESEARCH INST SAN ANTONIO TX

Personal Author(s) : Thacker, Ben H. ; Riha, David S. ; Wu, Y. T.

PDF Url : ADA304692

Report Date : FEB 1996

Pagination or Media Count : 91

Abstract : Accurate and efficient methods for performing probabilistic structural analysis are developed and demonstrated using highly detailed numerical tunnel models. Typical result from the probabilistic analysis include probability of failure, cumulative distribution functions, and probabilistic sensitivities with respect to all input statistical parameters. The results are useful for survivability/vulnerability assessments, strategic planning, tunnel design, and test planning. The report describes a program comprising development and application of several advanced probabilistic analysis methods, verification and validation of deterministic numerical models, and application of probabilistic analysis methods to several different tunnel problems. Statistical properties measured in laboratory testing are used directly in the calculations. A novel probabilistic cap constitutive model is developed that allows the model parameters to be treated as non-normal dependent random variables. The probabilistic methods used are based on a class of methods known as Fast Probability Integration (FPI). For probabilistic finite element analysis, the Advanced Mean Value (AMV) method is generally recommended. The methods are verified using Latin hypercube, adaptive importance sampling, and Monte Carlo Simulation. (MM)

Descriptors :   *PROBABILITY, *TUNNELS, *ELASTOPLASTICITY, MATHEMATICAL MODELS, UNCERTAINTY, CLOSURES, SURVIVABILITY, PROBABILITY DISTRIBUTION FUNCTIONS, RANDOM VARIABLES, FINITE ELEMENT ANALYSIS, STRUCTURAL ANALYSIS, DAMAGE ASSESSMENT, VULNERABILITY, MODULUS OF ELASTICITY, MONTE CARLO METHOD, STRAIN RATE, LIMESTONE, MEAN, FAILURE(MECHANICS), HARDENING, DETERMINANTS(MATHEMATICS), STATIC TESTS, DEEP DEPTH.

Subject Categories : Statistics and Probability
      Civil Engineering

Distribution Statement : APPROVED FOR PUBLIC RELEASE