• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content

Loading…

Flash Player 9 (or above) is needed to view presentations.
We have detected that you do not have it on your computer. To install it, go here.

Like this presentation? Why not share!

A Practical Reliability-Based Method for Assessing Soil Liquefaction Potential

on

  • 1,477 views

Lecture Topic: A Practical Reliability-Based Method for Assessing Soil Liquefaction Potential

Lecture Topic: A Practical Reliability-Based Method for Assessing Soil Liquefaction Potential

By Prof. Jin-Hung Hwang of National Central University, Taiwan.

Statistics

Views

Total Views
1,477
Views on SlideShare
1,080
Embed Views
397

Actions

Likes
0
Downloads
26
Comments
0

4 Embeds 397

http://cesnitsilchar.wordpress.com 394
http://cesnitsilchar.org 1
http://www.cesnitsilchar.org 1
url_unknown 1

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    A Practical Reliability-Based Method for Assessing Soil Liquefaction Potential A Practical Reliability-Based Method for Assessing Soil Liquefaction Potential Presentation Transcript

    • U.S.-Taiwan Workshop on Soil Liquefaction A Practical Reliability-Based Method for Assessing Soil Liquefaction Potential Jin-Hung Hwang National Central University, Taiwan
    • DATE:10th Nov, 2010 CET Hall
    • www.cesnitsilchar.wordpress.com Fanpage MISSION 2015::NIT Silchar www.twitter.com/cesnitsilchar
    • Outline
      • Previous studies
      • Reliability model
      • Probability density function of CSR
      • Probability density function of CRR
      • Liquefaction probability and safety factor
      • Summary and discussion
    • Previous Studies
      • Haldar and Tang (1975),
      • Fardis and Veneziano (1982),
      • Chameau and Clough (1983),
      • Liao et al . (1988),
      • Youd and Nobel (1997),
      • Toprak et al . (1999) ,
      • Juang et al . (2000a,2000b)
      • Some comments
        • Soil parameters and data should be updated.
        • Probabilistic cyclic strength curves without the statistics.
        • Juang’s work is a notable advancement, however ANN is a little unfamiliar to engineers.
    • Reliability Model
      • Based on Seed’85 method
      • Assume CSR and CRR are normal distribution
    • Fig.1 Probability density distribution for the liquefaction performance function.
      • Assume CSR and CRR are log-normal distributions
      • Flow chart of calculation
      • Information required
        • Mean values and variance coefficients of
        • CSR and CRR
      Table 2 Mean values and variance coefficients of CSR and CRR Mean value Variance coefficient CSR 0.581 CRR 0.604
    • PDF of CSR Fig.2 Calculated probability density function of a soil at a depth of 10 m.
    • PDF of CRR Table 1 Parameters in the logistic model Fig.3 Probabilistic cyclic resistance curves regressed by the logistic model. Parameter β 0 β 1 β 2 β 3 Regressed result 10.4 -0.2283 -0.001927 3.8
    • PDF of CRR Fig.4 Probability density function of the soil cyclic resistance ratio.
    • PDF of CRR Fig.5 Mean and median curves compared with the probabilistic curve of P L =0.6.
    • Liquefaction Probability and Safety Factor Fig.7 Relations of liquefaction probability with the safety factor for different variance coefficients.
      • Compared with the safety factor defined by the Seed’85 method
      Fig.8 Comparison of the probabilistic CRR curves with the empirical curve proposed by Seed’85 method.
      • Compared with Juang’s result
      Fig.9 Relation of liquefaction probability with the safety factor calculated by Seed’85 method.
    • Parameter Study
      • Influences of and the ground water table on the liquefaction probability
      Fig.10(a) Variation of liquefaction probability with (N 1 ) 60 .
    • Parameter Study
      • Influences of and the ground water table on the liquefaction probability
      Fig.10(b) Influence of fines content on liquefaction probability.
    • Parameter Study
      • Influences of and the ground water table on the liquefaction probability
      Fig.10(c) Influence of ground water table on liquefaction probability.
    • Application Example
      • Active Hsinhwa fault (12km rupture)
      • 1946 Tainan earthquake
      • Caused extensive liquefaction
      • Design earthquake
      • Result of liquefaction analysis
    • Application Example Table 3 Result of liquefaction analysis for the site near the Hsinhwa fault depth ( m ) Unit weight ( t / m 3 ) SPT- N FC (%) Soil classification F.S. (Seed) P L (%) 1.3 1.97 3 73 CL-ML - - 2.8 2.02 6 69 CL-ML - - 4.3 2.00 7 75 CL-ML - - 5.8 1.89 15 82 ML - - 7.3 1.93 6 99 ML - - 8.8 2.01 6 91 CL-ML - - 10.3 1.98 17 33 SM 1.2 35% 11.8 1.95 23 29 SM 1.4 19% 13.3 1.87 18 33 SM 1.2 35% 14.8 1.96 13 14 SM 0.8 62% 16.3 1.95 9 99 CL - - 18.8 2.04 33 25 SM 2.0 6% 19.3 2.19 33 20 SM 1.9 9%
    • Application Example Fig.11 Result of liquefaction analysis for the site near the Hsinhwa fault.
    • Summary and Discussion
      • A simple and practical reliability method for liquefaction analysis was proposed
      • The liquefaction probability is just a probability under a given earthquake event
      • It needs to combine the probability of earthquake occurrence