1 / 8

Transformation models and their applications in geotechnical design

Transformation models and their applications in geotechnical design. Jianye Ching (National Taiwan University)

tkinser
Download Presentation

Transformation models and their applications in geotechnical design

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Transformation models and their applications in geotechnical design Jianye Ching (National Taiwan University) Marcos Arroyo, Jieru Chen (contributor of SAND/7/2794), Celeste Jorge, Tim Länsivaara (contributor of F-CLAY/7/216), Dianqing Li, Paul Mayne, Kok-Kwang Phoon, Widjojo Prakoso, Marco Uzielli June 5 2017 @ Geo-Risk 2017

  2. Transformation models • Models that convert test results to design parameter • Mostly based on generic/global dataset • Kulhawy & Mayne (1990) • How do these models perform? • For a region • For a specific site

  3. OCR versus su/v dataset • CLAY/10/7490 dataset • 30 regions, 250+ studies • All su converted to su(mob) • Median estimate • 95% confidence interval • Transformation uncertainty Ching, J. and Phoon, K.K. (2014). Transformations and correlations among some clay parameters – the global database, Canadian Geotechnical Journal, 51(6), 663-685.

  4. OCR versus su/v model • How does it perform for a region? • Scandinavia dataset • Courtesy of Tim Länsivaara • 22 sites, 168 data points • All su converted to su(mob) • Median estimate • Systematically biased • 95% confidence interval • Not genuine 95%

  5. OCR versus su/v model • What does it perform for specific site(s)? • Individual site can have its own local trend • Median estimate • Systematically biased • 95% confidence interval • Typically too wide • Ensemble global sites • Median estimate • Unbiased • 95% confidence interval • Genuine 95%

  6. Global transformation models Biased for a region or a specific site Wide confidence interval (conservative) Unbiased for ensemble global sites Genuine 95% confidence interval

  7. Future needs • Intermediate transformation models • Site-specific models are good, but not enough data • Large statistical uncertainty • Global models can be biased and with wide CI • Large transformation uncertainty • Is there something in between that works well? • Fusion between limited site-specific data and global data? • Accumulate soil & rock databases • Make them available to the public • Web software & Apps • Sinotech cooperation

  8. Thank you (Some useful global transformation models are at the end of Chapter 1)

More Related