Chaofeng Wang

CPT-Based Evaluation of Liquefaction Potential Accounting for Soil Spatial Variability at Multiple Scales

AbstractUnderstanding and assessing the spatial extent of liquefaction requires that the spatial dependence of soil properties to be taken into account. In this work, a cone penetration test (CPT)-based approach for the evaluation of liquefaction potential is presented where the soil spatial variability is explicitly considered through internally-consistent probabilistic models developed at multiple scales. The novelty of the proposed work comes from the integration of the classical empirically-developed liquefaction criteria with tools in geostatistics and novel multiscale random-field models. A unique feature of the proposed work is its ability to refine and obtain higher resolution random fields for soil properties in critical areas, such as those adjacent to important infrastructure or in areas with detailed small-scale field data. An illustrative example assessing the liquefaction potential at various shaking levels in the Marina District of San Francisco is used to demonstrate the capability of the ...

Random field-based regional liquefaction hazard mapping — data inference and model verification using a synthetic digital soil field

Geostatistical tools and random field models have been increasingly used in recent liquefaction mapping studies. However, a systematic verification and assessment of random field models has yet to be taken, and implications of various random field-based mapping approaches are unknown. In this paper, an extremely detailed three-dimensional synthetic digital soil field is artificially generated and used as a basis for assessing and verifying various random field-based models for liquefaction mapping. Liquefaction hazard is quantified in terms of the liquefaction potential index (LPI), which is mapped over the studied field. A classical CPT-based liquefaction model is adopted to assess liquefaction potential of a soil layer. Different virtual field investigation plans are designed to assess the dependency of data inference and model performance upon the level of availability of sampling data. Model performances are assessed using three information theory-based measures. Results show that when sampling data is sufficient, all random field-based models examined capture fairly well the benchmark liquefaction potentials in the studied field. As the size of the sampling data decreases, the accuracy of predictions decreases for all models but to different degrees; the three-dimensional random field model gives the best result in this scenario. All random field-based models examined in this paper yield a slightly more conservative prediction of liquefaction potential over the studied field.

Probabilistic Assessment and Mapping of Liquefaction Hazard: From Site-Specific Analysis to Regional Mapping

Probabilistic methods have been increasingly used in liquefaction hazard assessments for purposes of considering the substantial uncertainties in both the liquefaction case histories and the model development process, and for the risk assessment and performance-based earthquake engineering. In this paper, a review on the probabilistic methods of site-specific liquefaction assessment, including logistic regression, the Bayesian method and various performance-based methods, is first undertaken. Another important topic in the liquefaction hazard assessment is to understand its spatial extent, leading to mapping of liquefaction hazard over a region. The regional liquefaction hazard maps are being employed as planning tools and provide guidance to assess the need for site-specific evaluations. The second focus of this paper details a review of methods for regional liquefaction hazard mapping, including geology-based, geotechnical data-driven and geostatistical methods as well as multiscale methods. The review of the site-specific probabilistic methods and regional mapping methods involves a discussion of their formulations, key assumptions, advantages and applications in liquefaction assessment. The challenges and the need for further research in these areas are also mentioned.

Multiscale Regional Liquefaction Hazard Mapping Accounting for Heterogeneous Data Sources

In this work, a multiscale random field-based method is presented to integrate heterogeneous data sources, i.e., geologic data at the regional scale and geotechnical data at the site-specific scale, for regional liquefaction hazard mapping. The multiscale random field model accounts for spatial variability of soil parameters over multiple length scales. Uncertainties and spatial variability of soil parameters are appropriately accounted for in the process. The proposed method is then applied to an earthquake-prone region for liquefaction hazard mapping. It is found that the spatial correlation structure of the calculated liquefaction potential index (LPI) is prominent in the study region. The influence of geologic data on the generated liquefaction hazard map is significant. As the weight of the geologic data increases, the geologic boundaries become more distinguishable in the generated map. With an appropriately selected or calibrated Markov-Bayes coefficient, the geotechnical and geologic data could be properly accounted in the mapping process.