Dynamic probabilistic analysis of stress and deformation for bladed disk assemblies of aeroengine

In order to describe and control the stress distribution and total deformation of bladed disk assemblies used in the aeroengine, a highly efficient and precise method of probabilistic analysis which is called extremum response surface method(ERSM) is produced based on the previous deterministic analysis results with the finite element model(FEM). In this work, many key nonlinear factors, such as the dynamic feature of the temperature load, the centrifugal force and the boundary conditions, are taken into consideration for the model. The changing patterns with time of bladed disk assemblies about stress distribution and total deformation are obtained during the deterministic analysis, and at the same time, the largest deformation and stress nodes of bladed disk assemblies are found and taken as input target of probabilistic analysis in a scientific and reasonable way. Not only their reliability, historical sample, extreme response surface(ERS) and the cumulative probability distribution function but also their sensitivity and effect probability are obtained. Main factors affecting stress distribution and total deformation of bladed disk assemblies are investigated through the sensitivity analysis of the model. Finally, compared with the response surface method(RSM) and the Monte Carlo simulation(MCS), the results show that this new approach is effective.

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.

An aligned mixture probabilistic principal component analysis for fault detection of multimode chemical processes

A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.

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.

Comprehensive Analysis of Caching Performance under Probabilistic Traffic Patterns for Content Centric Networking

The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology.

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.

Upgrade to Nuclear Power Plant Krsko Internal Flooding Probabilistic Safety Analysis

The original internal flooding probabilistic safety analysis （PSA） study of Krsko Nuclear Power Plant （two-loop Pressurized Water Reactor （PWR） plant of Westinghouse design） was performed in mid nineties and limited to reactor core damage risk （Level 1 PSA）. In 2003, it was, together with other safety and hazard analyses, subject to the Periodic Safety Review （PSR）. In the PSR, it was stated that methodological PSA approaches and guidelines have evoluted during the past decade and several observations were provided, concerning the area screening process, residual risk and treatment of plant damage states and risk from radioactivity releases （i.e., Level 2 PSA）. In order to address the PSR observations, upgrade ofKrsko NPP internal flooding PSA was undertaken. The area screening process was revisited in order to cover the areas without automatic reactor trip equipment. The model was extended to Level 2. Residual risk was estimated at both Level 1 and Level 2, in terms of core damage frequency （CDF） and large early release frequency （LERF）, respectively.

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.

Probabilistic seismic stability of three-dimensional slopes by pseudo-dynamic approach

Probabilistic analysis is a rational approach for engineering design because it provides more insight than traditional deterministic analysis. Probabilistic evaluation on seismic stability of three dimensional (3D) slopes is studied in this paper. The slope safety factor is computed by combining the kinematic approach of limit analysis using a three-dimensional rotational failure mechanism with the pseudo-dynamic approach. The variability of input parameters, including six pseudo-dynamic parameters and two soil shear strength parameters, are taken into account by means of Monte-Carlo Simulations (MCS) method. The influences of pseudo-dynamic input variables on the computed failure probabilities are investigated and discussed. It is shown that the obtained failure probabilities increase with the pseudo-dynamic input variables and the pseudo-dynamic approach gives more conservative failure probability estimates compared with the pseudo-static approach.

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.