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Research papers, The University of Auckland Library

During the recent devastating earthquakes in Christchurch, many residential houses were damaged due to widespread liquefaction of the ground. In-situ testing is widely used as a convenient method for evaluating liquefaction potential of soils. Cone penetration test (CPT) and standard penetration test (SPT) are the two popular in situ tests which are widely used in New Zealand for site characterization. The Screw Driving Sounding (SDS) method is a relatively new operating system developed in Japan consisting of a machine that drills a rod into the ground by applying torque at seven steps of axial loading. This machine can continuously measure the required torque, load, speed of penetration and rod friction during the test, and therefore can give a clear overview of the soil profile along the depth of penetration. In this paper, based on a number of SDS tests conducted in Christchurch, a correlation was developed between tip resistance of CPT test and SDS parameters for layers consisting of different fines contents. Moreover, using the obtained correlation, a chart was proposed which relates the cyclic resistance ratio to the appropriate SDS parameter. Using the proposed chart, liquefaction potential of soil can be estimated directly using SDS data. As SDS method is simpler, faster and more economical test than CPT and SPT, it can be a reliable alternative in-situ test for soil characterization, especially in residential house constructions.

Research papers, University of Canterbury Library

Semi-empirical models based on in-situ geotechnical tests have become the standard of practice for predicting soil liquefaction. Since the inception of the “simplified” cyclic-stress model in 1971, variants based on various in-situ tests have been developed, including the Cone Penetration Test (CPT). More recently, prediction models based soley on remotely-sensed data were developed. Similar to systems that provide automated content on earthquake impacts, these “geospatial” models aim to predict liquefaction for rapid response and loss estimation using readily-available data. This data includes (i) common ground-motion intensity measures (e.g., PGA), which can either be provided in near-real-time following an earthquake, or predicted for a future event; and (ii) geospatial parameters derived from digital elevation models, which are used to infer characteristics of the subsurface relevent to liquefaction. However, the predictive capabilities of geospatial and geotechnical models have not been directly compared, which could elucidate techniques for improving the geospatial models, and which would provide a baseline for measuring improvements. Accordingly, this study assesses the realtive efficacy of liquefaction models based on geospatial vs. CPT data using 9,908 case-studies from the 2010-2016 Canterbury earthquakes. While the top-performing models are CPT-based, the geospatial models perform relatively well given their simplicity and low cost. Although further research is needed (e.g., to improve upon the performance of current models), the findings of this study suggest that geospatial models have the potential to provide valuable first-order predictions of liquefaction occurence and consequence. Towards this end, performance assessments of geospatial vs. geotechnical models are ongoing for more than 20 additional global earthquakes.