Te Xiao

Shanghai Jiao Tong University | SJTU · Department of Civil Engineering

This paper aims to propose an auxiliary random finite element method (ARFEM) for efficient three-dimensional (3-D) slope reliability analysis and risk assessment considering spatial variability of soil properties. The ARFEM mainly consists of two steps: (1) preliminary analysis using a relatively coarse finite-element model and Subset Simulation, a...

Engineering geological characterization, subject to spatial variability of soil properties, is a three-dimensional (3D) problem in reality, although it is often simplified as one- or two-dimensional. Direct characterization of 3D spatial variability is a challenging task due to the scarcity of geotechnical data and a satisfactory characterization m...

The Yangtze River is one of the most important rivers in China due to its large basin size, the large population along the river, and the numerous large dams and reservoirs on the river. The Jinsha River, the upper reach of the Yangtze River, was dammed twice recently at Baige, Tibet, one on 10 October 2018 and the other on 3 November 2018 (UTC + 8...

Rain-induced man-made slope failures pose great threats to public safety as most man-made slopes are formed in densely populated areas. A critical step in managing landslide risks is to predict the time, locations and consequences of slope failures in future rainstorms. Based on comprehensive databases of in-service man-made slopes, rainstorms and...

Various data-driven methods, including empirical, statistical, and machine learning methods, have been developed to promptly forecast rain-induced landslides. Their abilities differ considerably in spatio-temporal landslide prediction and in handling datasets of varying qualities. A challenging issue that significantly hinders the applications of d...

Evaluating collapse susceptibility of loess is essential for the construction of transportation lines in loess regions as it provides guidance for ground treatment. For the existing methods, a large number of boreholes need to be drilled along transportation lines to collect intact samples for laboratory tests, which make them very time and cost-co...

The ISSMGE TC309/TC304/TC222 and ASCE Geo-Institute Risk Assessment Management Committee Fourth Machine Learning (ML) in Geotechnics Dialogue was held at the Okayama Convention Center on 5 December 2023. The dialogue focused on “machine learning supremacy projects”, which involve the use of novel ML techniques to analyse emerging data, potentially...

Rapid urbanization has caused numerous construction solid waste landfills. Few studies have explored the impact of multi-source waste soils with remarkable spatial variability on the reliability of landfills. This study aims to characterize the site-specific spatial variability of stockpiled waste soils and perform a probabilistic stability assessm...

Uncertainties are pervasive in geotechnical engineering. Reliability analysis provides a scientific way to characterize, model, and assess the impact of uncertainties in geotechnical engineering. Due to the increase in processing power of personal computers, the field of geotechnical reliability has experienced significant advancements since 1990s....

Due to the existence of uncertainties in geotechnical engineering, the performance of a geotechnical system can hardly be predicted deterministically. In such a case, the performance of a geotechnical system can be measured by the probability of failure, i.e., the probability that the designed performance cannot be achieved.

Uncertainties are pervasive in geotechnical engineering, such as the inherent variability of the soil, the measurement error due to imperfect testing, the statistical uncertainties due to limited amount of testings, and uncertainties due to modeling assumptions.

Although first-order reliability methods introduced in the previous chapter are efficient and easy to apply, they may not work well for problems with high dimensionality, nonlinear performance functions, and multiple failure modes (e.g., Schuëller et al. (Schuëller et al. in Probab Eng Mech 19:463–474, 2004); Song et al. (Song et al. in ASCE-ASME J...

The RSMs are a set of techniques used in the empirical study of relationships [1]. It was proposed by Box and Wilson in 1951 [2], and it is currently widely used in reliability analysis.

The uncertainty in geotechnical engineering depends on the amount of information available. When more information is available, such information can be used to reduce the uncertainty in geotechnical engineering, and hence improve decision making.

The working stress design has long been used in civil engineering (e.g., Barker et al. in Manuals for the design of bridge foundations: shallow foundations, driven piles, retaining walls and abutments, drilled shafts, estimating tolerable movements, and load factor design specifications and commentary. Transportation Research Board, Washington, DC,...

Due to the complex geologic, environmental, and physical–chemical processes, geotechnical properties vary spatially even in the same geological unit, referred to as spatial variability.

Prompt prediction of landslide occurrence and movement in a future rainstorm is one of the most effective manners to cope with the increasing landslide risk in a changing climate. Despite the rapid development of many machine learning algorithms, most studies stay on landslide susceptibility mapping because of the challenging time-unknown and terra...

Real-time information on flooding extent, severity, and duration is necessary for effective metropolitan flood emergency management. Existing pluvial flood analysis methods are unable to simulate real-time regional flooding processes under spatiotemporally varying rainstorms. This paper presents a deep learning-enabled super-resolution hydrodynamic...

Deep cement mixing (DCM) is an effective technique for ground improvement by injecting dry cement or cement slurry into the ground with continuous mixing and finally forming cemented soils with improved mechanical properties. A large-scale spatial distribution model is established in this study to investigate the characteristics of spatial variatio...

An extreme rainstorm can cause thousands of landslides and kill hundreds of people. In the changing climate, fatal rainstorms become more frequent and intense. The current landslide emergency management evaluates hazard intensities but lacks key information on likely consequences. This study presents a novel prompt quantitative risk assessment meth...

Landslide volume is critical in landslide risk management due to its close association with the landslide mobility and damage to elements at risk. Limited by accessibility, site conditions and availability of equipment, directly measuring the landslide volume on site is challenging. Instead, many empirical area-volume power-law models have been dev...

Slope failures or landslides are a major geo-hazard worldwide. Quantitative slope risk assessment and control have been used as an effective method for mitigating landslide hazards. A key task of quantitative slope risk assessment is to evaluate probability and consequences of slope failure, which relies on the understanding of site conditions, slo...

Understanding marine geological conditions is a primary task for land reclamation, and a three-dimensional (3-D) marine geological model is a straightforward and visualized tool for this purpose. Considering the different advantages of boreholes and geophysical surveys in terms of accuracy and scale, this study proposes a Bayesian framework to inte...

With the rapid development of deep learning algorithms and easier access to remote sensing images, deep learning-based landslide identification using remote sensing images becomes possible. Pan-sharpening techniques are often adopted to fuse low-resolution multispectral images and high-resolution panchromatic images. This paper combines the deep le...

Regional liquefaction potential assessment usually requires spatial interpolation based on probabilistic models (e.g., conditional random field, CRF). Accuracy of spatial interpolation relies highly on the number of testing data and stochastic model parameters. Since testing data is often insufficient, statistical uncertainty on model parameters is...

Assessing the spatial variability of the liquefaction-induced settlement at a site often involves spatial interpolation based on some stochastic models (e.g., random fields). Accuracy of the spatial interpolation results highly depends on the number of testing data and statistical model parameters. Statistical uncertainty in model parameters is ine...

Landslide debris will travel certain distances and threaten people and properties along its runout path, highlighting the importance of runout path prediction in landslide risk management. Conventional landslide runout models, either statistical or machine learning-based, only consider the geographic characteristics at the source without fitting th...

In October and November of 2018, the upper reach of the Yangtze River was blocked twice by landslide dams. A large landslide dam on a major river can impound a huge amount of water and trigger catastrophic flooding once it fails, imposing great risk to the downstream communities. Considering the chain of large dams and densely populated cities alon...

A three-dimensional (3-D) geological model has been established for Hong Kong using existing borehole data in order to facilitate detailed site investigations for future engineering projects. This study aims to digitalise ground investigation data in Hong Kong, develop easy-to-use tools for 3-D borehole management and visualisation, and eventually...

On 10 October and 3 November 2018, two large landslides occurred at Baige on the Qinghai-Tibet Plateau, and completely blocked the Jinsha River. Accordingly two landslide dams formed and breached sequentially, with the breaching of the 3 Nov. dam generating a flood larger than the 10,000-year return period flood over a river reach of approximately...

Integrating borehole and piezocone penetration test (CPTU) data in site characterization helps to achieve a more comprehensive understanding of ground conditions. However, soil types at CPTU and nearby borehole locations may not always be consistent. The presence of noisy data or thin layers will mislead the interpretation of CPTU data in soil type...

Study region Hong Kong, China. Study focus This paper aims to develop a flood analysis model to integrate the effects of multiple flooding triggers (i.e. rainfall, high sea levels and wave overtopping) during powerful tropical cyclones and investigate coastal flood hazards in an urban area at the street scale. The process of wave overtopping is pr...

Response surface methods are widely used in slope reliability analysis due to the high efficiency. However, they are often criticized of the curse of high dimensionality, problem-dependent accuracy, and mechanism-free interpretation. To address these issues, this study proposes a response surface-guided adaptive slope reliability analysis method fo...

Many coastal cities face growing flood risks due to interactions of multiple triggers related to the changing climate such as intense rainstorms, rising sea level, severe storm surges, etc. The complex urban morphology and infrastructural systems have profound effects on flow routing and need to be properly considered in flood modelling. In particu...

Real-world geotechnical reliability analysis is limited in practice partially because of computationally time-consuming complex deterministic models involved. Auxiliary random finite element method (ARFEM) is a representative reliability method that fully utilizes the correlation between simple and complex models to achieve efficient and consistent...

This paper presents the methodology and outcome of a novel quantitative risk assessment implemented in a 10-year reconstruction project of two mountain highways in the epicenter area of the 2008 Wenchuan earthquake. Routed in deep valleys, the highways were severely damaged during and on multiple counts after the earthquake, making highway reconstr...

Landslide susceptibility analysis is an essential part of landslide risk assessment and hazard mitigation. A high-resolution digital terrain model (DTM) and its derivatives can precisely capture and characterize the ground features of historical landslide locations. Also, machine learning has been proven to be a promising tool in landslide suscepti...

The break of large landslide dam will trigger catastrophic flood hazard to the downstream area. To manage the flood risk, multiple mitigation measures are required, such as evacuation and removal of obstacles in the river channel. Design of these mitigation measures relies on the estimation of critical flood parameters, namely, peak discharges and...

Two landslide dams were formed on the upper reach of the Jinsha River on 10 October 2018 and 3 November 2018, respectively. Considering the great threats to the lives and properties in downstream areas, it is important to rapidly simulate the dam breaching and the flood routing for risk management. This paper focuses on the second landslide dam tha...

A stochastic rainfall generator is required to provide rainfall inputs for the analysis and mitigation of such hydrological or geologic hazards as floods and rain-induced landslides. This paper presents a new spatial-temporal rainstorm generator for generating simultaneous rainfall processes at numerous locations considering the spatial correlation...

Ice-soil mixture landslide dams formed frequently in the Tibetan Plateau in response to global warming, which pose great threats to both upstream and downstream areas due to inundation and lake bursting. On 17 October 2018, a large landslide, induced by an ice-avalanche at the Sedongpu Basin of the Yarlung Tsangpo, blocked the main course of the ri...

Rainfall is a major cause of slope failures. As rainstorms become more frequent and intense over time due to climate change, the reliability of a large number of existing engineered slopes under extreme rainstorms is of great concern to the public. This study develops a weighted bilinear correlation between the failure frequency of engineered slope...

Spatial variability in geomaterials in three-dimensions affects the failure mechanism and reliability of geotechnical structures, and can be modeled rigorously as a 3-D random field. To address the computational difficulties in simulating large-scale 3-D random fields, an algorithmically simple and computationally economical 3-D random field simula...

The Guangdong-Hong Kong-Macao Bay Area, located in the southeast of China, suffers typhoon-related storms and floods. This paper presents a spatial-temporal rainfall generation model for regional flood response analysis, with its parameters easily obtainable from historical point observations. The model generates point rainfall event series at diff...

The 3-D spatial variability of soils has significant impacts on the failure mechanism and reliability of geotechnical structures and deserves a quantitative characterization through site investigation. This study develops a probabilistic approach for characterizing the 3-D spatial variability of soils within the framework of maximum likelihood esti...

The spatial variability of geomaterials affects the failure mechanism and reliability of geotechnical structures significantly, and can be modeled rigorously as a three-dimensional (3-D) random field. However, the simulation of multivariate, large-scale and high-resolution 3-D random fields is a challenging task due to extraordinary demands in comp...

Data-driven methodologies emerge recently in geotechnics. This paper proposes a method for learning failure modes of soil slopes using deformation monitoring information. First, a finite number of representative failure modes are identified based on their contributions to the overall reliability of the slope. Then, a random field model is developed...

A novel physically-based method for updating landslide susceptibility is presented in this paper, considering both spatial and cross correlations. First, a Bayesian network relating landslide susceptibility to spatially and cross correlated soil parameters is constructed for susceptibility assessment. Then, the correlations among the grid cells and...

Site characterization is usually carried out based on geotechnical data from site investigation. However, the existence of outliers in geotechnical data might lead to an incorrect characterization result, which necessitate the outlier detection. Site-specific geotechnical data is usually multivariate, sparse and might has a certain trend. This stud...

Buried water mains, sewers and storm water pipes are critical infrastructures in the urban environment. In Hong Kong, a great number of pipes are buried in slopes, and catastrophic consequences due to landslides may happen upon pipe leakage. This study aims to investigate the infiltration process of leakage water with respect to the current Hong Ko...

Natural soils often exhibit an anisotropic fabric pattern as a result of soil deposition, weathering or filling. This study aims to investigate the effects of spatially variable anisotropic soil fabric in a slope on its safety factor and failure mechanisms, and to identify the critical fabric orientation that is most unfavorable to the slope stabil...

Abstract Mohr-Coulomb shear strength parameters (i.e. cohesion c and friction angle ϕ) have been widely applied to analyses and designs of rock engineering (such as tunnels, underground caverns, and rock slopes), and they are statistically correlated. Such a correlation plays a vital role in the reliability and risk assessment of rock engineering,...

Many high engineered slopes are stabilized using anchors, which may corrode over time. Proper maintenance is essential to recover the system performance and upkeep slope functions. This paper presents a resilience model for maintenance decision by analysing the degradation of an anchor-stabilized slope due to corrosion and evaluating the recovery o...

Stratification in geologic profiles is one of the most significant uncertainties in geotechnical site characterization. In this paper, a three-level probabilistic framework is proposed for geotechnical stratification modeling considering stratigraphic uncertainty. The framework consists of model parameter identification, conditional simulation, and...

Spatial variability of soil properties is one of the major uncertainties in geotechnical properties that significantly affect slope reliability and risk. To account for the effect of three-dimensional (3-D) spatial variability, an efficient random finite element method (RFEM), named auxiliary RFEM (ARFEM), is proposed for 3-D slope reliability anal...

A simplified reliability analysis method is proposed for efficient full probabilistic design of soil slopes in spatially variable soils. The soil slope is viewed as a series system comprised of numerous potential slip surfaces and the spatial variability of soil properties is modelled by the spatial averaging technique along potential slip surfaces...

A tutorial for in-house reliability analysis software, NIGPA

Limit equilibrium methods (LEMs) and finite element methods (FEMs) of slope stability analysis can be used in computer-based probabilistic simulation approaches (e.g., direct Monte Carlo Simulation (MCS) and Subset Simulation (SS)) to evaluate the slope failure probability (Pf). For a given slope problem, the computational effort for the LEM is gen...

Random finite element method (RFEM) provides a rigorous tool to incorporate spatial variability of soil properties into reliability analysis and risk assessment of slope stability. However, it suffers from a common criticism of requiring extensive computational efforts and a lack of efficiency, particularly at small probability levels (e.g., slope...

Stochastic finite element method and random finite element method can provide rigorous tools for slope reliability analysis incorporating spatial variability of soil properties. However, both of them are difficult to be applied into practice due to the modification of finite-element codes and the low efficiency, respectively. To address these probl...

Spatial variability is one of the most significant uncertainties in soil properties that affect the reliability of slope stability. It can be incorporated into slope reliability analysis and risk assessment through random finite element method (RFEM) in a rigorous manner. The great potential of RFEM in reliability analysis and risk assessment of so...