Reliability-based serviceability limit state design of spread foundations under uplift loading in cohesionless soils

IF 6.5 3区工程技术 Q1 ENGINEERING, GEOLOGICAL

Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards Pub Date : 2023-01-09 DOI:10.1080/17499518.2023.2164900

Jayne M. Han, Kyo-Young Gu, Kyeong-Sun Kim, Kyung-Won Ham, Sung-Ryul Kim

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引用次数: 0

Abstract

ABSTRACT The design of foundations is often governed by the serviceability limit state (SLS) requirements of the supported structure, particularly for large spread foundations. This paper aims to develop a reliability-based SLS design method for spread foundations under uplift loading in cohesionless soils. A probabilistic framework was adopted for the empirical characterisation of the compiled load-displacement curves and the quantification of the associated uncertainties. By using the obtained statistics of the curves, reliability analysis was carried out with Monte-Carlo simulations to calibrate the resistance factors within the load and resistance factor design (LRFD) framework. The calibration results showed that the embedment ratio of the foundation and the fitting errors of the empirical model, which were previously unaddressed in the literature, had notable effects on the calibrated SLS resistance factors. The relationship of the SLS with the ultimate limit state was assessed, including the governing limit state at each allowable displacement level, and the probability of ultimate failure of the foundation at the SLS condition. By considering the relationship between the limit states, the procedures for determining the design resistance factor and foundation capacity were proposed.

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基于可靠性的无粘性土中扬载作用下扩展基础的正常使用极限状态设计

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来源期刊

Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards Multiple-

CiteScore

8.70

自引率

10.40%

发文量

期刊介绍： Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.