Probabilistic Analysis for Seismic Stability of Beach Earth Embankment

The current safety factor method for evaluating earth embankment stability is not very rational since the assessment of slope stability is really an uncertainty problem. In order to consider the random property of this problem, the probabilistic analysis is introduced herein. Finally, the stability of a real beach earth embankment is analysed by means of the suggested probabilitic approach. It may be seen that the results of analysis can represent the numerical assessment of the degree of seismic stability.

Fuzzy Probabilistic Analysis of Seismic Stability of Coastal Embankment

The stability of slope is affected by a number of factors, some of which have not only random property but also fuzzy characteristic. Therefore, the analysis of slope stability is really an uncertain problem. The customary safety factor does not in reality reflect stability scientifically, quantitatively and practically. In order to obtain more practical results, the slope stability is treated as a fuzzy random event for the evaluation of its fuzzy probability. Finally, the seismic stability of an existing coastal embankment is analyzed by means of the suggested fuzzy probabilistic method. It may be seen that the results of analysis can more fully represent the numerical assessment of the degree of slope seismic stability.

Field test and probabilistic analysis of irregular steel debris casualty risks from a person-borne improvised explosive device

Person-borne improvised explosive devices(PBIEDs)are often used in terrorist attacks in Western countries.This study aims to predict the trajectories of PBIED fragments and the subsequent safety risks for people exposed to this hazard.An explosive field test with a typical PBIED composed of a plastic explosive charge and steel nut enhancements was performed to record initial fragment behaviour,including positions,velocity,and trajectory angles.These data were used to predict the full trajectory of PBIED fragments using a probabilistic analysis.In the probabilistic analyses a probability of fatality or serious injury was computed.Based on the results presented,many practical conclusions can be drawn,for instance,regarding safe evacuation distances if a person were exposed to a suspected PBIED.

Probabilistic Analysis on Connectivity for Sensor Grids with Unreliable Nodes

This paper mainly investigates the connectivity of the unreliable sensor grid network. We consider an unreliable sensor grid network with mn nodes placed in a certain planar area A, and we assume that each node has independent failure probability p and has the same transmission range R. This paper presents a new method for calculating the connectivity probability of the network, which uses thorough mathematical methods to derive the relationship among the network connectivity probability, the probability that a node is ＂failed＂ （not active）, the numbers of node, and the node＇s transmission range in unreliable sensor networks. Our approach is more useful and efficient for given problem and conditions. Such as the numerical calculating results indicate that, for a 100×100 size sensot network, if node failure probability is bounded 0.5%, even if the transmission range is small （such as R = 10）, we can still maintain very high connectivity probability （reach 95.8%）. On the other hand, the simulation results show that building high connectivity probability is entirely possible on unreliable sensor grid networks.

Earthquake-induced landslide displacement attenuation models and application in probabilistic seismic landslide displacement analysis

A landslide displacement (DLL) attenuation model has been developed using spectral intensity and a ratio of critical acceleration coefficient to ground acceleration coefficient. In the development of the model,a New Zealand earthquake record data set with magnitudes ranging from 5.0 to 7.2 within a source distance of 175 km is used. The model can be used to carry out deterministic landslide displacement analysis,and readily extended to carry out probabilistic seismic landslide displacement analysis. DLL attenuation models have also been developed by using earthquake source terms,such as magnitude and source distance,that account for the effects of earthquake faulttype,source type,and site conditions. Sensitivity analyses show that the predicted DLL values from the new models are close to those from the Romeo model that was developed from an Italian earthquake record data set. The proposed models are also applied to an analysis of landslide displacements in the Wenchuan earthquake,and a comparison between the predicted and the observed results shows that the proposed models are reliable,and can be confidently used in mapping landslide potential.

Probabilistic analysis of secant piles with random geometric imperfections

The failure to achieve minimum design overlap between secant piles compromises the ability of a structure to perform as designed,resulting in water leakage or even ground collapse.To establish a more realistic simulation and provide guidelines for designing a safe and cost-effective secant-pile wall,a three-dimensional model of a secant pile,considering the geometric imperfections of the diameter and direction of the borehole,is introduced.An ultrasonic cross-hole test was performed during the construction of secant piles in a launching shaft in Beijing,China.Based on the test results,the statistical characteristics of the pile diameters and orientation parameters were obtained.By taking the pile diameter D,inclination angleβ,and azimuth angleαas random variables,Monte Carlo simulations were performed to discuss the influence of different design parameters on the probability density functions of the overlap of secant piles.The obtained results show that the randomness of the inclination angle and pile diameter can be well described by a normal distribution,whereas the azimuth angle is more consistent with a uniform distribution.The integrity of the secant-pile wall can be overestimated without considering the uncertainty of geometric imperfections.The failure of the secant-pile wall increases substantially with increasing spatial variability in drilling inclination and diameter.A design flowchart for pile spacing under the target safety level is proposed to help engineers design a safe and economical pile wall.

PROBABILISTIC METHODOLOGY OF LOW CYCLE FATIGUE ANALYSIS

The cyclic stress-strain responses (CSSR), Neuber's rule (NR) and cyclic strain-life relation (CSLR) are treated as probabilistic curves in local stress and strain method of low cycle fatigue analysis. The randomness of loading and the theory of fatigue damage accumulation (TOFDA) are considered. The probabilistic analysis of local stress, local strain and fatigue life are constructed based on the first-order Taylor's series expansions. Through this method proposed fatigue reliability analysis can be accomplished.

PROBABILISTIC ANALYSIS OF GALERKIN-LIKE METHODS FOR THE FREDHOLM EQUATION OF THE SECOND KIND

This paper deals with the approximate solution of the Fredholm equation u TKu = f of the second kind from a probabilistic point of view. With Wiener typemeasures on the set of kernels and free terms we determine statistical features of the approximation process, i.e., the most likely rate of convergence and the dominating individual behavior. The analysis carried out for a kind of Galerkin-like method.

Probabilistic Study of Landslide Susceptibility in the Sagrado River Watershed,Brazil

In this paper,we present a probabilistic study of landslide susceptibility at the Sagrado River Watershed in Morretes,Brazil.The area is characterized by slopes higher than 20%in a large part of the relief,variable soil depths,and by strong rainfall intensities due to orographic rains.Taken together,these factors promote the occurrence of translational landslides.Anthropic occupation is distributed along the lowlands and on the less inclined slopes of the Serra do Mar.The infinite slope method was used to determine the distribution of susceptibility to landslides.Input parameters of the model consisted of geotechnical soil parameters,soil layer thickness,slope of the hillside,and matric suction,and the analysis implemented a Monte Carlo probabilistic method.As such,this method allows the quantification of uncertainties due to the variability in geotechnical parameters,which enables the determination of a probability of rupture.The elaboration of susceptibility maps to landslides for unsaturated soil conditions represents a useful tool to support the identification of critical events occurrences in this location.

Probabilistic fragility analysis:A tool for assessing design rules of RC buildings

In this work, fragility analysis is performed to assess two groups of reinforced concrete structures. The first group of structures is composed of buildings that implement three common design practices; namely, fully infilled, weak ground story and short columns. The three design practices are applied during the design process of a reinforced concrete building. The structures of the second group vary according to the value of the behavioral factors used to define the seismic forces as specified in design procedures. Most seismic design codes belong to the class of prescriptive procedures where if certain constraints are fulfilled, the structure is considered safe. Prescriptive design procedures express the ability of the structure to absorb energy through inelastic deformation using the behavior factor. The basic objective of this work is to assess both groups of structures with reference to the limit-state probability of exceedance. Thus, four limit state fragility curves are developed on the basis of nonlinear static analysis for both groups of structures. Moreover, the 95% confidence intervals of the fragility curves are also calculated, taking into account two types of random variables that influence structural capacity and seismic demand.

Semi-supervised learning based probabilistic latent semantic analysis for automatic image annotation

In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.

Potential rupture surface model and its ap-plication on probabilistic seismic hazard analysis

Potential sources are simplified as point sources or linear sources in current probabilistic seismic hazard analysis （PSHA） methods. Focus size of large earthquakes is considerable, and fault rupture attitudes may have great influence upon the seismic hazard of a site which is near the source. Under this circumstance, it is unreasonable to use the simplified potential source models in the PSHA, so a potential rupture surface model is proposed in this paper. Adopting this model, we analyze the seismic hazard near the Chelungpu fault that generated the Chi-Chi （Jiji） earthquake with magnitude 7.6 and the following conclusions are reached. （1） This model is reasonable on the base of focal mechanism, especially for sites near potential earthquakes with large magnitude; （2） The attitudes of potential rupture surfaces have great influence on the results of probabilistic seismic hazard analysis and seismic zoning.

Probabilistic Safety Analysis of High Speed and Conventional Lines Using Bayesian Networks

A Bayesian network approach is presented for probabilistic safety analysis(PSA)of railway lines.The idea consists of identifying and reproducing all the elements that the train encounters when circulating along a railway line,such as light and speed limit signals,tunnel or viaduct entries or exits,cuttings and embankments,acoustic sounds received in the cabin,curves,etc.In addition,since the human error is very relevant for safety evaluation,the automatic train protection(ATP)systems and the driver behaviour and its time evolution are modelled and taken into account to determine the probabilities of human errors.The nodes of the Bayesian network,their links and the associated probability tables are automatically constructed based on the line data that need to be carefully given.The conditional probability tables are reproduced by closed formulas,which facilitate the modelling and the sensitivity analysis.A sorted list of the most dangerous elements in the line is obtained,which permits making decisions about the line safety and programming maintenance operations in order to optimize them and reduce the maintenance costs substantially.The proposed methodology is illustrated by its application to several cases that include real lines such as the Palencia-Santander and the Dublin-Belfast lines.

Integrated hazard assessment of rockfall incidents in the Cap Aokas Cliff Region

Rock fall accidents in mountainous cliff areas have significant consequences for human life and transportation.This study aimed to evaluate the rockfall hazard in the Cap Aokas cliff region located along the northeast coast of Algeria by identifying the key factors contributing to rockfall occurrence.We employed a combination of kinematic analysis,Matterocking method,and 3D trajectory simulations to determine zones that are susceptible to rockfall mobilization.By using a probabilistic and structural approach in conjunction with photogrammetry,we identified the controlling factors.The kinematic analysis revealed the presence of five discontinuity families,which indicated both plane and wedge failure modes.The 3D trajectory simulations demonstrated that the falling blocks followed the stream direction.We then validated the susceptibility maps generated from the analysis using aerial photos and historical rockfall events.The findings of this study enhance our understanding of rockfall phenomena and provide valuable insights for the development of effective strategies to mitigate rockfall hazards.

A two-dimensional limit equilibrium computer code for analysis of complex toppling slope failures

Evaluation of blocky or layered rock slopes against toppling failures has remained of great concern for engineers in various rock mechanics projects.Several step-by-step analytical solutions have been developed for analyzing these types of slope failures.However,manual application of these analytical solutions for real case studies can be time-consuming,complicated,and in certain cases even impossible.This study will first examine existing methods for toppling failure analyses that are reviewed,modified and generalized to consider the effects of a wide range of external and dead loads on slope stability.Next,based on the generalized presented formulae,a Windows form computer code is programmed using Visual C#for analysis of common types of toppling failures.Input parameters,including slope geometry,joint sets parameters,rock and soil properties,ground water level,dynamic loads,support anchor loads as well as magnitudes and forms of external forces,are first loaded into the code.The input data are then saved and used to graphically draw the slope model.This is followed by automatic identification of the toppling failure mode and a deterministic analysis of the slope stability against this failure mode.The results are presented using a graphical approach.The developed code allows probabilistic introduction of the input parameters via probability distribution functions(PDFs)and thus a probabilistic analysis of the toppling failure modes using Monte-Carlo simulation technique.This allows calculation of the probability of slope failure.Finally,several published case studies and typical examples are analyzed with the developed code.The outcomes are compared with those of the main references to assess the performance and robustness of the developed computer code.The comparisons demonstrate good agreement between the results.

Probabilistic seismic landslide hazard assessment: a case study in Tianshui, Northwest China

Probabilistic analysis in the field of seismic landslide hazard assessment is often based on an estimate of uncertainties of geological, geotechnical,geomorphological and seismological parameters.However, real situations are very complex and thus uncertainties of some parameters such as water content conditions and critical displacement are difficult to describe with accurate mathematical models. In this study, we present a probabilistic methodology based on the probabilistic seismic hazard analysis method and the Newmark’s displacement model. The Tianshui seismic zone(105°00′-106°00′ E, 34°20′-34°40′ N) in the northeastern Tibetan Plateau were used as an example. Arias intensity with three standard probabilities of exceedance(63%, 10%, and 2% in 50 years) in accordance with building design provisions were used to compute Newmark displacements by incorporating the effects of topographic amplification.Probable scenarios of water content condition were considered and three water content conditions(dry,wet and saturated) were adopted to simulate the effect of pore-water on slope. The influence of 5 cm and 10 cm critical displacements were investigated in order to analyze the sensitivity of critical displacement to the probabilities of earthquake-induced landslide occurrence. The results show that water content in particular, have a great influence on the distribution of high seismic landslide hazard areas. Generally, the dry coverage analysis represents a lower bound for susceptibility and hazard assessment, and the saturated coverage analysis represents an upper bound to some extent. Moreover, high seismic landslide hazard areas are also influenced by the critical displacements. The slope failure probabilities during future earthquakes with critical displacements of 5 cm can increase by a factor of 1.2 to 2.3 as compared to that of 10 cm. It suggests that more efforts are required in order to obtain reasonable threshold values for slope failure. Considering the probable scenarios of water content condition which is varied with seasons, seismic landslide hazard assessments are carried out for frequent, occasional and rare earthquake occurrences in the Tianshui region, which can provide a valuable reference for landslide hazard management and infrastructure design in mountainous seismic zones.

Post-failure analysis of landslides in spatially varying soil deposits using stochastic material point method

This paper presents the probabilistic analysis of landslides in spatially variable soil deposits, modeled by a stochastic framework which integrates the random field theory with generalized interpolation material point method(GIMP). Random fields are simulated using Cholesky matrix decomposition(CMD) method and Latin hypercube sampling(LHS) method, which represent material properties discretized into sets of random soil shear strength variables with statistical properties. The approach is applied to landslides in clayey deposits under undrained conditions with random fields of undrained shear strength parameters, in order to quantify the uncertainties of post-failure behavior at different scales of fluctuation(SOF) and coefficients of variation(COV). Results show that the employed approach can reliably simulate the whole landslide process and assess the uncertainties of runout motions. It is demonstrated that the natural heterogeneity of shear strength in landslides notably influences their post-failure behavior. Compared with a homogeneous landslide model which yields conservative results and underestimation of the risks, consideration of heterogeneity shows larger landslide influence zones. With SOF values increasing, the variances of influence zones also increase, and with higher values of COV, the mean values of the influence zone also increase, resulting in higher uncertainties of post-failure behavior.

A NEW TWO-POINT ADAPTIVE NONLINEAR APPROXIMATION METHOD FOR RELIABILITY ANALYSIS

A two-point adaptive nonlinear approximation (referred to as TANA4) suitable for reliability analysis is proposed. Transformed and normalized random variables in probabilistic analysis could become negative and pose a challenge to the earlier developed two-point approxi- mations; thus a suitable method that can address this issue is needed. In the method proposed, the nonlinearity indices of intervening variables are limited to integers. Then, on the basis of the present method, an improved sequential approximation of the limit state surface for reliability analysis is presented. With the gradient projection method, the data points for the limit state surface approximation are selected on the original limit state surface, which e?ectively repre- sents the nature of the original response function. On the basis of this new approximation, the reliability is estimated using a ?rst-order second-moment method. Various examples, including both structural and non-structural ones, are presented to show the e?ectiveness of the method proposed.

A Hybrid Particle Swarm Optimization and Genetic Algorithm for Model Updating of A Pier-Type Structure Using Experimental Modal Analysis

Conventional design of pier structures is based on the assumption of fully rigid joints. In practice, the real connections are semi-rigid that cause changes in dynamic characteristics. In this study, quality of the joints is investigated by considering changes in natural frequencies. For this purpose, numerical and experimental modal analyses are carried out on related physical model of a pier type structure. When numerical results are evaluated,natural frequencies generally do not match the expected experimental results. Uncertainties in different aspects of engineering problems are always a challenge for researchers. The numerical models which are constructed on the basis of highly idealized scheme may not be able to represent all of the physical aspects of the physical one. For this study, determination of percentage of semi-rigid joints is considered as an optimization problem based on the numerical and experimental frequencies. Probabilistic sensitivity analysis is also used to determine the search space.A new technique of optimization problem is solved by a combination of smart particle swarm optimization(PSO)and genetic algorithms, and a complicated and efficient system for model updating process is introduced. It is observed that the hybrid PSO-Genetic algorithm is applicable and appropriate in model updating process. It performs better than PSO algorithm, considering the good agreement between theoretical frequencies and experimental ones,before and after model updating.

Comparative Study on Response Surfaces for Reliability Analysis of Spatially Variable Soil Slope

This paper focuses on the performance of the second-order polynomial-based response surfaces on the reliability of spatially variable soil slope. A single response surface constructed to approximate the slope system failure performance function G（X） （called single RS） and multiple response surfaces constructed on finite number of slip surfaces （called multiple RS） are developed, respectively. Single RS and multiple RS are applied to evaluate the system failure probability pf for a cohesive soil slope together with Monte Carlo simulation （MCS）. It is found thatpe calculated by single RS deviates significantly from that obtained by searching a large number of potential slip surfaces, and this deviation becomes insignificant with the decrease of the number of random variables or the increase of the scale of fluctuation. In other words, single RS cannot approximate G（X） with reasonable accuracy. The value of pc from multiple response surfaces fits well with that obtained by searching a large number of potential slip surfaces. That is, multiple RS can estimate G（X） with reasonable accuracy.