Backgroun

Instability and strength loss from soil liquefaction are significant causes of damage to critical facilities during earthquakes. Recent earthquakes in Japan and New Zealand caused damage to government, industrial, commercial, and residential property that contributed to substantial loss of commerce and disruption of lives. Many regions within the United States are susceptible to earthquake-induced liquefaction, including California, Alaska, the Pacific Northwest, the central Mississippi region (New Madrid), and Charleston, South Carolina. Unfortunately, the sets of data supporting existing liquefaction models currently used in many engineering analyses are small and inconsistent, and do not include important case histories from many significant earthquakes that have occurred over the past two decades. In addition, many of the currently available models are effectively deterministic, in that aleatory variability in model outcomes is often unquantified, and no framework exists by which to quantify epistemic uncertainties related to limited knowledge. As a result of these and other problems, the current state of knowledge does not facilitate consensus-based risk assessments of infrastructure performance in response to liquefaction-related demands.

Objective and Scope

The Next Generation Liquefaction (NGL) Project is advancing the state of the art in liquefaction research and working toward providing end users with a consensus approach to assess liquefaction potential within a probabilistic and risk-informed framework. Specifically, NGL’s goal is to first collect and organize liquefaction information in a common and comprehensive database to provide all researchers with a substantially larger, more consistent, and more reliable source of liquefaction data than existed previously. Based on this database, we will create probabilistic models that provide hazard- and risk-consistent bases for assessing liquefaction susceptibility, the potential for liquefaction to be triggered in susceptible soils, and the likely consequences. NGL is committed to an open and objective evaluation and integration of data, models and methods, as recommended in a 2016 National Academies report. The evaluation and integration of the data into new models and methods will be clear and transparent. Following these principles will ensure that the resulting liquefaction susceptibility, triggering, and consequence models are reliable, robust and vetted by the scientific community, providing a solid foundation for designing, constructing and overseeing critical infrastructure projects.