Key predictors of structure settlement on liquefiable ground: a numerical parametric study. Issue 113 (October 2018)
- Record Type:
- Journal Article
- Title:
- Key predictors of structure settlement on liquefiable ground: a numerical parametric study. Issue 113 (October 2018)
- Main Title:
- Key predictors of structure settlement on liquefiable ground: a numerical parametric study
- Authors:
- Karimi, Zana
Dashti, Shideh
Bullock, Zach
Porter, Keith
Liel, Abbie - Abstract:
- Abstract: Excessive building settlement and tilt on liquefiable soils has led to significant damage in previous earthquakes. The state-of-practice for evaluating liquefaction-induced building settlement still primarily relies on semi-empirical free-field relationships that have repeatedly been shown as unreliable and inaccurate during field and physical model studies. This is because these methods ignore the presence of the building, soil-foundation-structure interaction, and some of the dominant mechanisms of deformation near buildings. In a comprehensive numerical parametric study, the dynamic response of the soil-foundation-structure (SFS) system was assessed with a wide range of soil, structure, and ground motion characteristics. The primary objectives were: first, to identify the key predictors of foundation settlement and study their relative importance and interdependence; and second, to provide a comprehensive and mechanistically-sound dataset for the future development of a probabilistic predictive model of building settlement. The numerical simulations involved fully-coupled, 3-dimensional, nonlinear dynamic analyses of the SFS system, previously validated using centrifuge experimental results. For the conditions considered, the key predictors of building settlement were identified as the cumulative absolute velocity (CAV) of the outcropping rock motion, the relative density of, thickness of, and depth to the liquefiable layer(s), presence of a low-permeabilityAbstract: Excessive building settlement and tilt on liquefiable soils has led to significant damage in previous earthquakes. The state-of-practice for evaluating liquefaction-induced building settlement still primarily relies on semi-empirical free-field relationships that have repeatedly been shown as unreliable and inaccurate during field and physical model studies. This is because these methods ignore the presence of the building, soil-foundation-structure interaction, and some of the dominant mechanisms of deformation near buildings. In a comprehensive numerical parametric study, the dynamic response of the soil-foundation-structure (SFS) system was assessed with a wide range of soil, structure, and ground motion characteristics. The primary objectives were: first, to identify the key predictors of foundation settlement and study their relative importance and interdependence; and second, to provide a comprehensive and mechanistically-sound dataset for the future development of a probabilistic predictive model of building settlement. The numerical simulations involved fully-coupled, 3-dimensional, nonlinear dynamic analyses of the SFS system, previously validated using centrifuge experimental results. For the conditions considered, the key predictors of building settlement were identified as the cumulative absolute velocity (CAV) of the outcropping rock motion, the relative density of, thickness of, and depth to the liquefiable layer(s), presence of a low-permeability cap, followed by foundation length-to-width ratio, embedment depth, contact area, and bearing pressure. The structure's inertial mass and height/width ratio as well as the initial fundamental period of the structure and site were comparatively less influential. The relative importance and influence of most input parameters were shown to depend on ground motion intensity (e.g., CAV) and soil relative density. Highlights: Available procedures for liquefaction-induced building settlement are not reliable. Numerical parametric study were previously validated with centrifuge experiments. The key predictors of foundation settlement were identified. Comprehensive and mechanistically-sound dataset provided for future predictive models. Knowledge of key predictors can guide future design and predictive models. … (more)
- Is Part Of:
- Soil dynamics and earthquake engineering. Issue 113(2018)
- Journal:
- Soil dynamics and earthquake engineering
- Issue:
- Issue 113(2018)
- Issue Display:
- Volume 113, Issue 113 (2018)
- Year:
- 2018
- Volume:
- 113
- Issue:
- 113
- Issue Sort Value:
- 2018-0113-0113-0000
- Page Start:
- 286
- Page End:
- 308
- Publication Date:
- 2018-10
- Subjects:
- Soil dynamics -- Periodicals
Earthquake engineering -- Periodicals
Sols -- Dynamique -- Périodiques
Génie parasismique -- Périodiques
624.176205 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02677261 ↗
http://www.sciencedirect.com/science/journal/02617277 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.soildyn.2018.03.001 ↗
- Languages:
- English
- ISSNs:
- 0267-7261
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8322.225000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17165.xml