Highly turbulent water flows,often encountered near human constructions like bridge piers,spillways,and weirs,display intricate dynamics characterized by the formation of eddies and vortices.These formations,varying i...Highly turbulent water flows,often encountered near human constructions like bridge piers,spillways,and weirs,display intricate dynamics characterized by the formation of eddies and vortices.These formations,varying in sizes and lifespans,significantly influence the distribution of fluid velocities within the flow.Subsequently,the rapid velocity fluctuations in highly turbulent flows lead to elevated shear and normal stress levels.For this reason,to meticulously study these dynamics,more often than not,physical modeling is employed for studying the impact of turbulent flows on the stability and longevity of nearby structures.Despite the effectiveness of physical modeling,various monitoring challenges arise,including flow disruption,the necessity for concurrent gauging at multiple locations,and the duration of measurements.Addressing these challenges,image velocimetry emerges as an ideal method in fluid mechanics,particularly for studying turbulent flows.To account for measurement duration,a probabilistic approach utilizing a probability density function(PDF)is suggested to mitigate uncertainty in estimated average and maximum values.However,it becomes evident that deriving the PDF is not straightforward for all turbulence-induced stresses.In response,this study proposes a novel approach by combining image velocimetry with a stochastic model to provide a generic yet accurate description of flow dynamics in such applications.This integration enables an approach based on the probability of failure,facilitating a more comprehensive analysis of turbulent flows.Such an approach is essential for estimating both short-and long-term stresses on hydraulic constructions under assessment.展开更多
Rainfall infiltration poses a disastrous threat to the slope stability in many regions around the world.This paper proposes an extreme gradient boosting(XGBoost)-based stochastic analysis framework to estimate the rai...Rainfall infiltration poses a disastrous threat to the slope stability in many regions around the world.This paper proposes an extreme gradient boosting(XGBoost)-based stochastic analysis framework to estimate the rainfall-induced slope failure probability.An unsaturated slope under rainfall infiltration in spatially varying soils is selected in this study to investigate the influences of the spatial variability of soil properties(including effective cohesion c',effective friction angleφ'and saturated hydraulic conductivity k_(s)),as well as rainfall intensity and rainfall pattern on the slope failure probability.Results show that the proposed framework in this study is capable of computing the failure probability with accuracy and high efficiency.The spatial variability of k_(s)cannot be overlooked in the reliability analysis.Otherwise,the rainfall-induced slope failure probability will be underestimated.It is found that the rain-fall intensity and rainfall pattern have significant effect on the probability of failure.Moreover,the failure probabilities under various rainfall intensities and patterns can be easily obtained with the aid of the proposed framework,which can provide timely guidance for the landslide emergency management departments.展开更多
In connection with the design of floating wind turbines,stochastic dynamic analysis is a critical task considering nonlinear wind and wave forces.To study the random structural responses of a newly designed submerged ...In connection with the design of floating wind turbines,stochastic dynamic analysis is a critical task considering nonlinear wind and wave forces.To study the random structural responses of a newly designed submerged tension leg platform(STLP)wind turbine,a set of dynamic simulations and comparison analysis with the MIT/NREL TLP wind turbine are carried out.The signal filter method is used to evaluate the mean and standard deviations of the structural response.Furthermore,the extreme responses are estimated by using the mean upcrossing rate method.The fatigue damages for blade root,tower,and mooring line are also studied according to the simulated time-series.The results and comparison analysis show that the STLP gives small surge and pitch motions and mooring line tensions in operational sea states due to the small water-plane area.Additionally,in severe sea states,the STLP gives lower extreme values of platform pitch,slightly larger surge and heave motions and better towerbase and mooring line fatigue performances than those of the MIT/NREL TLP.It is found that the STLP wind turbine has good performances in structural responses and could be a potential type for exploiting the wind resources located in deep waters.展开更多
Typically, dual-frequency geodetic grade GNSS receivers are utilized for positioning applications that require high accuracy. Single-frequency high grade receivers can be used to minimize the expenses of such dual-fre...Typically, dual-frequency geodetic grade GNSS receivers are utilized for positioning applications that require high accuracy. Single-frequency high grade receivers can be used to minimize the expenses of such dual-frequency receivers. However, user has to consider the resultant positioning accuracy. Since the evolution of low-cost single-frequency (LCSF) receivers is typically cheaper than single-frequency high grade receivers, it is possible to obtain comparable positioning accuracy if the corresponding observables are accurately modelled. In this paper, two LCSF GPS receivers are used to form short baseline. Raw GPS measurements are recorded for several consecutive days. The collected data are used to develop the stochastic model of GPS observables from such receivers. Different functions are tested to determine the best fitting model which is found to be 3 parameters exponential decay function. The new developed model is used to process different data sets and the results are compared against the traditional model. Both results from the newly developed and the traditional models are compared with the reference solution obtained from dual-frequency receiver. It is shown that the newly developed model improves the root-mean-square of the estimated horizontal coordinates by about 10% and improves the root-mean-square of the up component by about 39%.展开更多
In the data envelopment analysis(DEA)literature,productivity change captured by the Malmquist productivity index,especially in terms of a deterministic environment and stochastic variability in inputs and outputs,has ...In the data envelopment analysis(DEA)literature,productivity change captured by the Malmquist productivity index,especially in terms of a deterministic environment and stochastic variability in inputs and outputs,has been somewhat ignored.Therefore,this study developed a firm-specific,DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment.First,in order to estimate bank-specific efficiency,we employed a two-stage double bootstrap DEA procedure.Specifically,in the first stage,the technical efficiency scores of banks were calculated by the classic DEA model,while in the second stage,the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency.Second,we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance.Finally,an empirical investigation of the Iranian banking sector,consisting of 120 bank-year observations of 15 banks from 2014 to 2021,was performed to measure their efficiency and productivity change.Based on the findings,the explanatory variables(i.e.,the nonperforming loan ratio and the number of branches)indicated an inverse relationship with stochastic technical efficiency and productivity change.The implication of the findings is that,in order to improve the efficiency and productivity of banks,it is important to optimize these factors.展开更多
This study explores how parametric uncertainties in the production affect failure tensile loads of reinforced thermoplastic pipes(RTPs)under combined loading conditions.The stress distributions in RTPs are examined wi...This study explores how parametric uncertainties in the production affect failure tensile loads of reinforced thermoplastic pipes(RTPs)under combined loading conditions.The stress distributions in RTPs are examined with three-dimensional(3D)elasticity theory,and the analytical micromechanics of composites are evaluated.To evaluate the failure mechanisms for RTPs,3D Hashin–Yeh failure criteria are combined with the damage evolution model to establish a progressive failure model.The theoretical model has been validated through numerical simulations and axial tensile tests data.To analyze how randomness of relevant parameters affects the first-ply failure(FPF)tensile load and final failure(FF)tensile load in RTPs,many samples are produced with the Monte–Carlo approach.The stochastic analysis results are statistically evaluated through the Weibull probability density distribution function.For the randomness of production parameters,the failure tensile load of RTPs fluctuates near the mean value.As the ply number at the reinforced layer increases,the dispersion of failure tensile load increases,with a high probability that the FPF tensile load of RTPs is lower than the mean value.展开更多
Stochastic approaches are useful to quantitatively describe transportbehavior over large temporal and spatial scales while accounting for the influence of small-scalevariabilities. Numerous solutions have been develop...Stochastic approaches are useful to quantitatively describe transportbehavior over large temporal and spatial scales while accounting for the influence of small-scalevariabilities. Numerous solutions have been developed for unsatu-rated soil water flow based on thelognormal distribution of soil hydraulic conductivity. To our knowledge, no available stochasticsolutions for unsaturated flow have been derived on the basis of the normal distribution ofhydraulic conductivity. In this paper, stochastic solutions were developed for unsaturated flow byassuming the normal distribution of saturated hydraulic conductivity (K_s). Under the assumptionthat soil hydraulic properties are second-order stationary, analytical expressions for capillarytension head variance (σ_h^2 ) and effective hydraulic conductivity (K_ii~*) in stratified soilswere derived using the perturbation method. The dependence of σ_h^2 and K_ii~* on soil variabilityand mean flow variables (the mean capillary tension head and its temporal and spatial gradients) andmean flow conditions (wetting and drying) were systematically analyzed. The calculated variance ofcapillary tension head with the analytical solution derived in this paper was compared with fieldexperimental data. The good agreement indicates that the analytical solution is applicable toevaluate the variance of capillary tension head of field soils with moderate variability.展开更多
Buckling-restrained braces （BRBs） have recently become popular in the United States for use as primary members of seismic lateral-force-resisting systems. A BRB is a steel brace that does not buckle in compression b...Buckling-restrained braces （BRBs） have recently become popular in the United States for use as primary members of seismic lateral-force-resisting systems. A BRB is a steel brace that does not buckle in compression but instead yields in both tension and compression. Although design guidelines for BRB applications have been developed, systematic procedures for assessing performance and quantifying reliability are still needed. This paper presents an analytical framework for assessing buckling-restrained braced frame （BRBF） reliability when subjected to seismic loads. This framework efficiently quantifies the risk of BRB failure due to low-cycle fatigue fracture of the BRB core. The procedure includes a series of components that： （1） quantify BRB demand in terms of BRB core deformation histories generated through stochastic dynamic analyses; （2） quantify the limit-state of a BRB in terms of its remaining cumulative plastic ductility capacity based on an experimental database; and （3） evaluate the probability of BRB failure, given the quantified demand and capacity, through structural reliability analyses. Parametric studies were conducted to investigate the effects of the seismic load, and characteristics of the BRB and BRBF on the probability of brace failure. In addition, fragility curves （i.e., conditional probabilities of brace failure given ground shaking intensity parameters） were created by the proposed framework. While the framework presented in this paper is applied to the assessment of BRBFs, the modular nature of the framework components allows for application to other structural components and systems.展开更多
Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coeffi...Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coefficient and measured hydraulic head, a stochastic back analysis taking consideration of uncertainties of parameters was performed using the generalized Bayesian method. Based on the stochastic finite element method （SFEM） for a seepage field, the variable metric algorithm and the generalized Bayesian method, formulas for stochastic back analysis of the permeability coefficient were derived. A case study of seepage analysis of a sluice foundation was performed to illustrate the proposed method. The results indicate that, with the generalized Bayesian method that considers the uncertainties of measured hydraulic head, the permeability coefficient and the hydraulic head at the boundary, both the mean and standard deviation of the permeability coefficient can be obtained and the standard deviation is less than that obtained by the conventional Bayesian method. Therefore, the present method is valid and applicable.展开更多
This paper investigates the uplink throughput of Cognitive Radio Cellular Networks(CRCNs).As oppose to traditional performance evaluation schemes which mainly adopt complex system level simulations,we use the theoreti...This paper investigates the uplink throughput of Cognitive Radio Cellular Networks(CRCNs).As oppose to traditional performance evaluation schemes which mainly adopt complex system level simulations,we use the theoretical framework of stochastic geometry to provide a tractable and accurate analysis of the uplink throughput in the CRCN.By modelling the positions of User Equipments(UEs)and Base Stations(BSs)as Poisson Point Processes(PPPs),we analyse and derive expressions for the link rate and the cell throughput in the Primary(PR)and Secondary(SR)networks.The expressions show that the throughput of the CRCN is mainly affected by the density ratios between the UEs and the BSs in both the PR and SR networks.Besides,a comparative analysis of the link rate between random and regular BS deployments is concluded,and the results confirm the accuracy of our analysis.Furthermore,we define the cognitive throughput gain and derive an expression which is dominated by the traffic load in the PR network.展开更多
In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problema...In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problematic in several situations,for example(a)when input proportions change in the long run,(b)when inputs are heterogeneous,and(c)when firms face ex-ante price uncertainty in making their production decisions.To address these situations,a scale elasticity evaluation was performed using a value-based cost efficiency model.However,this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data.Therefore,in this study,we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty.An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years(1998–2005)was made to compare inferences about their efficiency and scale properties.The key findings are as follows:First,both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints.However,both models yield the same results at a tolerance level of 0.5,implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks.Second,the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart.Third,public banks exhibit higher efficiency than private and foreign banks.Finally,public and old private banks mostly exhibit either decreasing or constant returns to scale,whereas foreign and new private banks experience either increasing or decreasing returns to scale.Although the application of our proposed stochastic model is illustrative,it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs,which have ample potential for reaping scale and scope benefits.展开更多
Correspondence factor analysis(CFA)was used in conjunction with linear regression analysis to examine the structure-activity relationships of 50 benzene derivatives tested on Pimephales promelas.From nine molecular de...Correspondence factor analysis(CFA)was used in conjunction with linear regression analysis to examine the structure-activity relationships of 50 benzene derivatives tested on Pimephales promelas.From nine molecular descriptors(numbers of C,H,O,N,Br,Cl,NO_2,OH,and NH_2 included in the molecules),CFA made it possible to define five new independent variables which were introduced in a stepwise regression analysis procedure to describe the acute toxicity(96-h LC_(50))of the aromatic compounds.The model log 1/C=-0.727F_1+1.248F_3+4.052(r=0.918; s=0.270)is more relevant to describe the ecotoxicological behavior of the studied compounds on the fathead minnow than that obtained with principal components(log 1/C=0.151 PC_1 -0.271 PC_2+4.124;r=0.737;s=0.460).The heuristic potency of this particular statistical analysis,which is called stochastic regression analysis,is discussed in detail.1989 Academic Press,Inc.展开更多
The stochastic cracking and healing behaviors of reaction-diffusion growth of thin filmswere studied by means of Markov processes analysis. We chose the thermal growth ofoxide scales on metals as an example of reactio...The stochastic cracking and healing behaviors of reaction-diffusion growth of thin filmswere studied by means of Markov processes analysis. We chose the thermal growth ofoxide scales on metals as an example of reaction-diffusion growth. The thermal growthof oxide films follows power law when no cracking occurs. Our results showed that thegrowth kinetics under stochastic cracking and healing conditions was different fromthat without cracking. It might be altered to either pseudo-linear or pseudo-power lawsdependent upon the intensity and frequency of the cracking of the films. When thehoping items dominated, the growth followed pseudo-linear law; when the diffusionalitems dominated, it followed pseudo-power law with the exponentials lower than theintrinsical values. The numerical results were in good agreement with the meassuredkinetics of isothermal and cyclic oxidation of NiAl-0.1 Y (at. %) alloys in air at 1273K.展开更多
Wellbore drilling operations frequently entail the combination of a wide range of variables. This is underpinned by the numerous factors that must be considered in order to ensure safety and productivity. The heteroge...Wellbore drilling operations frequently entail the combination of a wide range of variables. This is underpinned by the numerous factors that must be considered in order to ensure safety and productivity. The heterogeneity and sometimes unpredictable behaviour of underground systems increases the sensitivity of drilling activities. Quite often the operating parameters are set to certify effective and efficient working processes. However, failings in the management of drilling and operating conditions sometimes result in catastrophes such as well collapse or fluid loss. This study investigates the hypothesis that optimising drilling parameters, for instance mud pressure, is crucial if the margin of safe operating conditions is to be properly defined. This was conducted via two main stages： first a deterministic analysis--where the operating conditions are predicted by conventional modelling procedures--and then a probabilistic analysis via stochastic simulations--where a window of optimised operation conditions can be obtained. The outcome of additional stochastic analyses can be used to improve results derived from deterministic models. The incorporation of stochastic techniques in the evaluation of wellbore instability indicates that margins of the safe mud weight window are adjustable and can be extended considerably beyond the limits of deterministic predictions. The safe mud window is influenced and hence can also be amended based on the degree of uncertainty and the permissible level of confidence. The refinement of results from deterministic analyses by additional stochastic simulations is vital if a more accurate and reliable representation of safe in situ and operating conditions is to be obtained during wellbore operations.展开更多
This paper proposes a hybrid algorithm based on the physics-informed kernel function neural networks(PIKFNNs)and the direct probability integral method(DPIM)for calculating the probability density function of stochast...This paper proposes a hybrid algorithm based on the physics-informed kernel function neural networks(PIKFNNs)and the direct probability integral method(DPIM)for calculating the probability density function of stochastic responses for structures in the deep marine environment.The underwater acoustic information is predicted utilizing the PIKFNNs,which integrate prior physical information.Subsequently,a novel uncertainty quantification analysis method,the DPIM,is introduced to establish a stochastic response analysis model of underwater acoustic propagation.The effects of random load,variable sound speed,fluctuating ocean density,and random material properties of shell on the underwater stochastic sound pressure are numerically analyzed,providing a probabilistic insight for assessing the mechanical behavior of structures in the deep marine environment.展开更多
The performance of interfered cooperative ad-hoc networks is analyzed by stochastic geometry analysis and a selection region of relay is presented. First, assuming that the distribution of nodes in the random network ...The performance of interfered cooperative ad-hoc networks is analyzed by stochastic geometry analysis and a selection region of relay is presented. First, assuming that the distribution of nodes in the random network follows the Poisson point process （PPP）, a closed-form expression of the outage probability is derived for the best relay selection （BRS） scheme. Secondly, the capacity of the network is presented for this scheme. Finally, a performance factor is defined to evaluate the performance gain obtained from the BRS. By using this factor, a relay selection region is found to guarantee the performance gain from the BRS. The analysis and simulation results show that the performance of the BRS not only depends on the densities of source nodes and relay nodes but also on the factors of networks such as the path loss factor and the decoding threshold. And the BRS has a greater advantage than direct transmission （DT） in hush environments such as the long transmission distances, much interference and the high decoding thresholds.展开更多
Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduce...Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.展开更多
Magnesium alloys have been investigated as biodegradable implant materials since the last century. Non-uniform degradation caused by local corrosion limits their application, and no appropriate technology has been use...Magnesium alloys have been investigated as biodegradable implant materials since the last century. Non-uniform degradation caused by local corrosion limits their application, and no appropriate technology has been used in the research. In this study, electrochemical noise has been used to study the pit corrosion on magnesium alloy AZ31 in four types of simulated body solutions, and the data have been analyzed using wavelet analysis and stochastic theory. Combining these with the conventional polarization curves, mass loss tests and scanning electron microscopy, the electrochemical noise results implied that AZ31 alloy in normal saline has the fastest corrosion rate, a high pit initiation rate, and maximum pit growth probability. In Hanks＇ balanced salt solution and phosphate-buffered saline, AZ31 alloy has a high pit initiation rate and larger pit growth probability, while in simulated body fluid, AZ31 alloy has the slowest corrosion rate, lowest pit initiation rate and smallest pit growth probability.展开更多
This paper introduces an orthogonal expansion method for general stochastic processes. In the method, a normalized orthogonal function of time variable t is first introduced to carry out the decomposition of a stochas...This paper introduces an orthogonal expansion method for general stochastic processes. In the method, a normalized orthogonal function of time variable t is first introduced to carry out the decomposition of a stochastic process and then a correlated matrix decomposition technique, which transforms a correlated random vector into a vector of standard uncorrelated random variables, is used to complete a double orthogonal decomposition of the stochastic processes. Considering the relationship between the Hartley transform and Fourier transform of a real-valued function, it is suggested that the first orthogonal expansion in the above process is carried out using the Hartley basis function instead of the trigonometric basis function in practical applications. The seismic ground motion is investigated using the above method. In order to capture the main probabilistic characteristics of the seismic ground motion, it is proposed to directly carry out the orthogonal expansion of the seismic displacements. The case study shows that the proposed method is feasible to represent the seismic ground motion with only a few random variables. In the second part of the paper, the probability density evolution method （PDEM） is employed to study the stochastic response of nonlinear structures subjected to earthquake excitations. In the PDEM, a completely uncoupled one-dimensional partial differential equation, the generalized density evolution equation, plays a central role in governing the stochastic seismic responses of the nonlinear structure. The solution to this equation will yield the instantaneous probability density function of the responses. Computational algorithms to solve the probability density evolution equation are described. An example, which deals with a nonlinear frame structure subjected to stochastic ground motions, is illustrated to validate the above approach.展开更多
文摘Highly turbulent water flows,often encountered near human constructions like bridge piers,spillways,and weirs,display intricate dynamics characterized by the formation of eddies and vortices.These formations,varying in sizes and lifespans,significantly influence the distribution of fluid velocities within the flow.Subsequently,the rapid velocity fluctuations in highly turbulent flows lead to elevated shear and normal stress levels.For this reason,to meticulously study these dynamics,more often than not,physical modeling is employed for studying the impact of turbulent flows on the stability and longevity of nearby structures.Despite the effectiveness of physical modeling,various monitoring challenges arise,including flow disruption,the necessity for concurrent gauging at multiple locations,and the duration of measurements.Addressing these challenges,image velocimetry emerges as an ideal method in fluid mechanics,particularly for studying turbulent flows.To account for measurement duration,a probabilistic approach utilizing a probability density function(PDF)is suggested to mitigate uncertainty in estimated average and maximum values.However,it becomes evident that deriving the PDF is not straightforward for all turbulence-induced stresses.In response,this study proposes a novel approach by combining image velocimetry with a stochastic model to provide a generic yet accurate description of flow dynamics in such applications.This integration enables an approach based on the probability of failure,facilitating a more comprehensive analysis of turbulent flows.Such an approach is essential for estimating both short-and long-term stresses on hydraulic constructions under assessment.
基金the National Key R&D Program of China(No.2019YFC1509600)National Natural Science Foundation of China(Nos.52008058 and 52108299)China Postdoctoral Science Foundation(No,2021M693740).
文摘Rainfall infiltration poses a disastrous threat to the slope stability in many regions around the world.This paper proposes an extreme gradient boosting(XGBoost)-based stochastic analysis framework to estimate the rainfall-induced slope failure probability.An unsaturated slope under rainfall infiltration in spatially varying soils is selected in this study to investigate the influences of the spatial variability of soil properties(including effective cohesion c',effective friction angleφ'and saturated hydraulic conductivity k_(s)),as well as rainfall intensity and rainfall pattern on the slope failure probability.Results show that the proposed framework in this study is capable of computing the failure probability with accuracy and high efficiency.The spatial variability of k_(s)cannot be overlooked in the reliability analysis.Otherwise,the rainfall-induced slope failure probability will be underestimated.It is found that the rain-fall intensity and rainfall pattern have significant effect on the probability of failure.Moreover,the failure probabilities under various rainfall intensities and patterns can be easily obtained with the aid of the proposed framework,which can provide timely guidance for the landslide emergency management departments.
基金the National Natural Science Foundation of China(Grant No.51809135)the National Natural Science Foundation of China-Shandong Joint Fund(Grant No.U1806227)the Natural Science Foundation of Shandong Province(Grant No.ZR2018BEE047).
文摘In connection with the design of floating wind turbines,stochastic dynamic analysis is a critical task considering nonlinear wind and wave forces.To study the random structural responses of a newly designed submerged tension leg platform(STLP)wind turbine,a set of dynamic simulations and comparison analysis with the MIT/NREL TLP wind turbine are carried out.The signal filter method is used to evaluate the mean and standard deviations of the structural response.Furthermore,the extreme responses are estimated by using the mean upcrossing rate method.The fatigue damages for blade root,tower,and mooring line are also studied according to the simulated time-series.The results and comparison analysis show that the STLP gives small surge and pitch motions and mooring line tensions in operational sea states due to the small water-plane area.Additionally,in severe sea states,the STLP gives lower extreme values of platform pitch,slightly larger surge and heave motions and better towerbase and mooring line fatigue performances than those of the MIT/NREL TLP.It is found that the STLP wind turbine has good performances in structural responses and could be a potential type for exploiting the wind resources located in deep waters.
文摘Typically, dual-frequency geodetic grade GNSS receivers are utilized for positioning applications that require high accuracy. Single-frequency high grade receivers can be used to minimize the expenses of such dual-frequency receivers. However, user has to consider the resultant positioning accuracy. Since the evolution of low-cost single-frequency (LCSF) receivers is typically cheaper than single-frequency high grade receivers, it is possible to obtain comparable positioning accuracy if the corresponding observables are accurately modelled. In this paper, two LCSF GPS receivers are used to form short baseline. Raw GPS measurements are recorded for several consecutive days. The collected data are used to develop the stochastic model of GPS observables from such receivers. Different functions are tested to determine the best fitting model which is found to be 3 parameters exponential decay function. The new developed model is used to process different data sets and the results are compared against the traditional model. Both results from the newly developed and the traditional models are compared with the reference solution obtained from dual-frequency receiver. It is shown that the newly developed model improves the root-mean-square of the estimated horizontal coordinates by about 10% and improves the root-mean-square of the up component by about 39%.
文摘In the data envelopment analysis(DEA)literature,productivity change captured by the Malmquist productivity index,especially in terms of a deterministic environment and stochastic variability in inputs and outputs,has been somewhat ignored.Therefore,this study developed a firm-specific,DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment.First,in order to estimate bank-specific efficiency,we employed a two-stage double bootstrap DEA procedure.Specifically,in the first stage,the technical efficiency scores of banks were calculated by the classic DEA model,while in the second stage,the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency.Second,we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance.Finally,an empirical investigation of the Iranian banking sector,consisting of 120 bank-year observations of 15 banks from 2014 to 2021,was performed to measure their efficiency and productivity change.Based on the findings,the explanatory variables(i.e.,the nonperforming loan ratio and the number of branches)indicated an inverse relationship with stochastic technical efficiency and productivity change.The implication of the findings is that,in order to improve the efficiency and productivity of banks,it is important to optimize these factors.
基金financially supported by the National Natural Science Foundation of China(Grant No.U2006226]the National Key Research and Development Program of China(Grant No.2016YFC0303800)。
文摘This study explores how parametric uncertainties in the production affect failure tensile loads of reinforced thermoplastic pipes(RTPs)under combined loading conditions.The stress distributions in RTPs are examined with three-dimensional(3D)elasticity theory,and the analytical micromechanics of composites are evaluated.To evaluate the failure mechanisms for RTPs,3D Hashin–Yeh failure criteria are combined with the damage evolution model to establish a progressive failure model.The theoretical model has been validated through numerical simulations and axial tensile tests data.To analyze how randomness of relevant parameters affects the first-ply failure(FPF)tensile load and final failure(FF)tensile load in RTPs,many samples are produced with the Monte–Carlo approach.The stochastic analysis results are statistically evaluated through the Weibull probability density distribution function.For the randomness of production parameters,the failure tensile load of RTPs fluctuates near the mean value.As the ply number at the reinforced layer increases,the dispersion of failure tensile load increases,with a high probability that the FPF tensile load of RTPs is lower than the mean value.
基金This work was supported by the National NaturaI Science Foundation of China(Grant Nos:59509007,59879028)the Major State Basic Research Development Program of China(Grant No:G1999045700)the Fok Ying Tung Education Foundation.(Grant No:71027)
文摘Stochastic approaches are useful to quantitatively describe transportbehavior over large temporal and spatial scales while accounting for the influence of small-scalevariabilities. Numerous solutions have been developed for unsatu-rated soil water flow based on thelognormal distribution of soil hydraulic conductivity. To our knowledge, no available stochasticsolutions for unsaturated flow have been derived on the basis of the normal distribution ofhydraulic conductivity. In this paper, stochastic solutions were developed for unsaturated flow byassuming the normal distribution of saturated hydraulic conductivity (K_s). Under the assumptionthat soil hydraulic properties are second-order stationary, analytical expressions for capillarytension head variance (σ_h^2 ) and effective hydraulic conductivity (K_ii~*) in stratified soilswere derived using the perturbation method. The dependence of σ_h^2 and K_ii~* on soil variabilityand mean flow variables (the mean capillary tension head and its temporal and spatial gradients) andmean flow conditions (wetting and drying) were systematically analyzed. The calculated variance ofcapillary tension head with the analytical solution derived in this paper was compared with fieldexperimental data. The good agreement indicates that the analytical solution is applicable toevaluate the variance of capillary tension head of field soils with moderate variability.
基金Federal Highway Administration Under Grant No. DDEGRD-06-X-00408
文摘Buckling-restrained braces （BRBs） have recently become popular in the United States for use as primary members of seismic lateral-force-resisting systems. A BRB is a steel brace that does not buckle in compression but instead yields in both tension and compression. Although design guidelines for BRB applications have been developed, systematic procedures for assessing performance and quantifying reliability are still needed. This paper presents an analytical framework for assessing buckling-restrained braced frame （BRBF） reliability when subjected to seismic loads. This framework efficiently quantifies the risk of BRB failure due to low-cycle fatigue fracture of the BRB core. The procedure includes a series of components that： （1） quantify BRB demand in terms of BRB core deformation histories generated through stochastic dynamic analyses; （2） quantify the limit-state of a BRB in terms of its remaining cumulative plastic ductility capacity based on an experimental database; and （3） evaluate the probability of BRB failure, given the quantified demand and capacity, through structural reliability analyses. Parametric studies were conducted to investigate the effects of the seismic load, and characteristics of the BRB and BRBF on the probability of brace failure. In addition, fragility curves （i.e., conditional probabilities of brace failure given ground shaking intensity parameters） were created by the proposed framework. While the framework presented in this paper is applied to the assessment of BRBFs, the modular nature of the framework components allows for application to other structural components and systems.
基金supported by the National Natural Science Foundation of China (Grant No. 50579090)the National Basic Research Program of China (973 Program, Grant No. 2007CB714102)National Science and Technology Support Program of China (Program for the Eleventh Five-Year Plan, Grant No. 2006BAB04A06)
文摘Owing to the fact that the conventional deterministic back analysis of the permeability coefficient cannot reflect the uncertainties of parameters, including the hydraulic head at the boundary, the permeability coefficient and measured hydraulic head, a stochastic back analysis taking consideration of uncertainties of parameters was performed using the generalized Bayesian method. Based on the stochastic finite element method （SFEM） for a seepage field, the variable metric algorithm and the generalized Bayesian method, formulas for stochastic back analysis of the permeability coefficient were derived. A case study of seepage analysis of a sluice foundation was performed to illustrate the proposed method. The results indicate that, with the generalized Bayesian method that considers the uncertainties of measured hydraulic head, the permeability coefficient and the hydraulic head at the boundary, both the mean and standard deviation of the permeability coefficient can be obtained and the standard deviation is less than that obtained by the conventional Bayesian method. Therefore, the present method is valid and applicable.
基金supported by the National Key Basic Research Program of China (973 Program)under Grant No. 2009CB320401the National Natural Science Foundation of China under Grants No. 61171099, No. 61101117+1 种基金the National Key Scientific and Technological Project of China under Grants No. 2012ZX03004005-002, No. 2012ZX03003-007the Fundamental Research Funds for the Central Universities under Grant No. BUPT2012RC0112
文摘This paper investigates the uplink throughput of Cognitive Radio Cellular Networks(CRCNs).As oppose to traditional performance evaluation schemes which mainly adopt complex system level simulations,we use the theoretical framework of stochastic geometry to provide a tractable and accurate analysis of the uplink throughput in the CRCN.By modelling the positions of User Equipments(UEs)and Base Stations(BSs)as Poisson Point Processes(PPPs),we analyse and derive expressions for the link rate and the cell throughput in the Primary(PR)and Secondary(SR)networks.The expressions show that the throughput of the CRCN is mainly affected by the density ratios between the UEs and the BSs in both the PR and SR networks.Besides,a comparative analysis of the link rate between random and regular BS deployments is concluded,and the results confirm the accuracy of our analysis.Furthermore,we define the cognitive throughput gain and derive an expression which is dominated by the traffic load in the PR network.
文摘In the nonparametric data envelopment analysis literature,scale elasticity is evaluated in two alternative ways:using either the technical efficiency model or the cost efficiency model.This evaluation becomes problematic in several situations,for example(a)when input proportions change in the long run,(b)when inputs are heterogeneous,and(c)when firms face ex-ante price uncertainty in making their production decisions.To address these situations,a scale elasticity evaluation was performed using a value-based cost efficiency model.However,this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data.Therefore,in this study,we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty.An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years(1998–2005)was made to compare inferences about their efficiency and scale properties.The key findings are as follows:First,both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints.However,both models yield the same results at a tolerance level of 0.5,implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks.Second,the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart.Third,public banks exhibit higher efficiency than private and foreign banks.Finally,public and old private banks mostly exhibit either decreasing or constant returns to scale,whereas foreign and new private banks experience either increasing or decreasing returns to scale.Although the application of our proposed stochastic model is illustrative,it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs,which have ample potential for reaping scale and scope benefits.
文摘Correspondence factor analysis(CFA)was used in conjunction with linear regression analysis to examine the structure-activity relationships of 50 benzene derivatives tested on Pimephales promelas.From nine molecular descriptors(numbers of C,H,O,N,Br,Cl,NO_2,OH,and NH_2 included in the molecules),CFA made it possible to define five new independent variables which were introduced in a stepwise regression analysis procedure to describe the acute toxicity(96-h LC_(50))of the aromatic compounds.The model log 1/C=-0.727F_1+1.248F_3+4.052(r=0.918; s=0.270)is more relevant to describe the ecotoxicological behavior of the studied compounds on the fathead minnow than that obtained with principal components(log 1/C=0.151 PC_1 -0.271 PC_2+4.124;r=0.737;s=0.460).The heuristic potency of this particular statistical analysis,which is called stochastic regression analysis,is discussed in detail.1989 Academic Press,Inc.
基金supported by Hundred-Talent Project of Chinese Academy of Sciencesby the National Natural Science Foundation of China for Young Scientist
文摘The stochastic cracking and healing behaviors of reaction-diffusion growth of thin filmswere studied by means of Markov processes analysis. We chose the thermal growth ofoxide scales on metals as an example of reaction-diffusion growth. The thermal growthof oxide films follows power law when no cracking occurs. Our results showed that thegrowth kinetics under stochastic cracking and healing conditions was different fromthat without cracking. It might be altered to either pseudo-linear or pseudo-power lawsdependent upon the intensity and frequency of the cracking of the films. When thehoping items dominated, the growth followed pseudo-linear law; when the diffusionalitems dominated, it followed pseudo-power law with the exponentials lower than theintrinsical values. The numerical results were in good agreement with the meassuredkinetics of isothermal and cyclic oxidation of NiAl-0.1 Y (at. %) alloys in air at 1273K.
文摘Wellbore drilling operations frequently entail the combination of a wide range of variables. This is underpinned by the numerous factors that must be considered in order to ensure safety and productivity. The heterogeneity and sometimes unpredictable behaviour of underground systems increases the sensitivity of drilling activities. Quite often the operating parameters are set to certify effective and efficient working processes. However, failings in the management of drilling and operating conditions sometimes result in catastrophes such as well collapse or fluid loss. This study investigates the hypothesis that optimising drilling parameters, for instance mud pressure, is crucial if the margin of safe operating conditions is to be properly defined. This was conducted via two main stages： first a deterministic analysis--where the operating conditions are predicted by conventional modelling procedures--and then a probabilistic analysis via stochastic simulations--where a window of optimised operation conditions can be obtained. The outcome of additional stochastic analyses can be used to improve results derived from deterministic models. The incorporation of stochastic techniques in the evaluation of wellbore instability indicates that margins of the safe mud weight window are adjustable and can be extended considerably beyond the limits of deterministic predictions. The safe mud window is influenced and hence can also be amended based on the degree of uncertainty and the permissible level of confidence. The refinement of results from deterministic analyses by additional stochastic simulations is vital if a more accurate and reliable representation of safe in situ and operating conditions is to be obtained during wellbore operations.
基金the National Natural Science Foundation of China,Grant Number:12372196,12302258,52325803,U22A20229,12402238State Key Laboratory of Ocean Engineering(Shanghai Jiao Tong University),Grant Number:GKZD010089+2 种基金the Six Talent Peaks Project in Jiangsu Province of China,Grant Number:2019-KTHY-009Jiangsu Funding Program for Excellent Postdoctoral Talent,Grant Number:2023ZB506Postdoctoral Fellowship Program of CPSF,Grant Number:GZC20230667。
文摘This paper proposes a hybrid algorithm based on the physics-informed kernel function neural networks(PIKFNNs)and the direct probability integral method(DPIM)for calculating the probability density function of stochastic responses for structures in the deep marine environment.The underwater acoustic information is predicted utilizing the PIKFNNs,which integrate prior physical information.Subsequently,a novel uncertainty quantification analysis method,the DPIM,is introduced to establish a stochastic response analysis model of underwater acoustic propagation.The effects of random load,variable sound speed,fluctuating ocean density,and random material properties of shell on the underwater stochastic sound pressure are numerically analyzed,providing a probabilistic insight for assessing the mechanical behavior of structures in the deep marine environment.
基金The National Science and Technology Major Project(No. 2011ZX03005-004-03 )the National Natural Science Foundation of China (No. 61171081)the Science and Technology Support Program of Jiangsu Province (No. BE2011187)
文摘The performance of interfered cooperative ad-hoc networks is analyzed by stochastic geometry analysis and a selection region of relay is presented. First, assuming that the distribution of nodes in the random network follows the Poisson point process （PPP）, a closed-form expression of the outage probability is derived for the best relay selection （BRS） scheme. Secondly, the capacity of the network is presented for this scheme. Finally, a performance factor is defined to evaluate the performance gain obtained from the BRS. By using this factor, a relay selection region is found to guarantee the performance gain from the BRS. The analysis and simulation results show that the performance of the BRS not only depends on the densities of source nodes and relay nodes but also on the factors of networks such as the path loss factor and the decoding threshold. And the BRS has a greater advantage than direct transmission （DT） in hush environments such as the long transmission distances, much interference and the high decoding thresholds.
基金Projects(51708558,51878673,U1734208,52078485,U1934217,U1934209)supported by the National Natural Science Foundation of ChinaProject(2020JJ5740)supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(KF2020-03)supported by the Key Open Fund of State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures,ChinaProject(2020-Special-02)supported by the Science and Technology Research and Development Program of China Railway Group Limited。
文摘Random dynamic responses caused by the uncertainty of structural parameters of the coupled train-ballasted track-subgrade system under train loading can pose safety concerns to the train operation.This paper introduced a computational model for analyzing probabilistic dynamic responses of three-dimensional(3D)coupled train-ballasted track-subgrade system(TBTSS),where the coupling effects of uncertain rail irregularities,stiffness and damping properties of ballast and subgrade layers were simultaneously considered.The number theoretical method(NTM)was employed to design discrete points for the multi-dimensional stochastic parameters.The time-histories of stochastic dynamic vibrations of the TBSS with systematically uncertain structural parameters were calculated accurately and efficiently by employing the probability density evolution method(PDEM).The model-predicted results were consistent with those by the Monte Carlo simulation method.A sensitivity study was performed to assess the relative importance of those uncertain structural parameters,based on which a case study was presented to explore the stochastic probability evolution mechanism of such train-ballasted track-subgrade system.
基金financially supported by the National Natural Science Foundation of China(Nos.51701221 and 51501201)
文摘Magnesium alloys have been investigated as biodegradable implant materials since the last century. Non-uniform degradation caused by local corrosion limits their application, and no appropriate technology has been used in the research. In this study, electrochemical noise has been used to study the pit corrosion on magnesium alloy AZ31 in four types of simulated body solutions, and the data have been analyzed using wavelet analysis and stochastic theory. Combining these with the conventional polarization curves, mass loss tests and scanning electron microscopy, the electrochemical noise results implied that AZ31 alloy in normal saline has the fastest corrosion rate, a high pit initiation rate, and maximum pit growth probability. In Hanks＇ balanced salt solution and phosphate-buffered saline, AZ31 alloy has a high pit initiation rate and larger pit growth probability, while in simulated body fluid, AZ31 alloy has the slowest corrosion rate, lowest pit initiation rate and smallest pit growth probability.
基金National Natural Science Foundation of China for Innovative Research Groups Under Grant No.50321803 & 50621062National Natural Science Foundation of China Under Grant No.50808113 & 10872148
文摘This paper introduces an orthogonal expansion method for general stochastic processes. In the method, a normalized orthogonal function of time variable t is first introduced to carry out the decomposition of a stochastic process and then a correlated matrix decomposition technique, which transforms a correlated random vector into a vector of standard uncorrelated random variables, is used to complete a double orthogonal decomposition of the stochastic processes. Considering the relationship between the Hartley transform and Fourier transform of a real-valued function, it is suggested that the first orthogonal expansion in the above process is carried out using the Hartley basis function instead of the trigonometric basis function in practical applications. The seismic ground motion is investigated using the above method. In order to capture the main probabilistic characteristics of the seismic ground motion, it is proposed to directly carry out the orthogonal expansion of the seismic displacements. The case study shows that the proposed method is feasible to represent the seismic ground motion with only a few random variables. In the second part of the paper, the probability density evolution method （PDEM） is employed to study the stochastic response of nonlinear structures subjected to earthquake excitations. In the PDEM, a completely uncoupled one-dimensional partial differential equation, the generalized density evolution equation, plays a central role in governing the stochastic seismic responses of the nonlinear structure. The solution to this equation will yield the instantaneous probability density function of the responses. Computational algorithms to solve the probability density evolution equation are described. An example, which deals with a nonlinear frame structure subjected to stochastic ground motions, is illustrated to validate the above approach.
