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Factor-based probability model for vulnerability assessment of slopes subjected to earthquakes

NATURAL HAZARDS 2025年第5期121卷 5781-5798页

作者： Hsieh, Meng-Hsun Lin, Jeng-Wen Li, Yu-Jen China Univ Technol Dept Civil Engn & Hazard Mitigat Taipei 116 Taiwan Feng Chia Univ Dept Civil Engn 100 Wenhwa Rd Taichung 407 Taiwan Ruentex Engn & Construct Co Ltd Taipei 104 Taiwan

This study explores the slope vulnerability assessment subjected to earthquakes using an environmental factor-based probability model based on data from the September 21, 1999, Chi-Chi earthquake-stricken areas of Taiwan. Satellite images were used to identify and interpret the collapsed area in the study area, and strong ground motion station data were used to evaluate the PGA. A DEM was used for topographic analysis to establish 6333 slope units. These slope units were classified into 12 categories based on environmental factors. Finally, a deterministic probability model based on the classification of environmental factors was presented. Landslide fragility functions were estimated for the 12 slope classifications. The results indicated that the important factors affecting the Chi-Chi earthquake were geology, aspect, and gradient. Geological factors indicate that the landslide probabilities of dense soil and soft rock are higher than those of hard and brittle rocks. The strong and weak aspects of the slope direction indicated that the difference in landslide probability was between about 0.05 and 0.1. The gradient factor indicates that steep slopes have a higher landslide probability.

关键词： Earthquake Environmental factor Landslide fragility function probability model Collapse rate

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Data-model driven probability model of branch power flow for distribution networks and its application to analysis of overload and line loss

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ELECTRIC POWER SYSTEMS RESEARCH 2025年 238卷

作者： Zhang, Ren Liu, Haoming Wang, Jian Cai, Haiqing Gu, Haohan Chen, Wei Chen, Zhihao Hohai Univ Sch Elect & Power Engn Nanjing Peoples R China China Southern Power Grid Elect Power Res Inst State Key Lab HVDC Guangzhou 510663 Peoples R China Natl Energy Power Grid Technol R&D Ctr Guangzhou 510663 Peoples R China Guangdong Prov Key Lab Intelligent Operat & Contro Guangzhou 510663 Peoples R China China Southern Power Grid Elect Power Res Inst CSG Key Lab Power Syst Simulat Guangzhou 510663 Peoples R China

The fluctuation of highly penetrated distributed generations (DGs) in distribution networks (DNs) increases branch overload risks, which makes the analysis uncertainty of branch power flow more complex. The probability analysis of branch power can grasp the power flow operation characteristics under uncertain conditions, which supports the power flow optimization management and ensures the safe and economic operation of DNs. Therefore, this paper proposes a data-model driven probability analysis method for branch power flow in DNs. An approximate branch power model is first derived to reveal the analytical relationship between branch power and node power. Then, based on the branch power approximation model and the forecasting error, the datasets of branch apparent power are constructed to capture the complex nonlinear characteristics of the power flow. The non-Gaussian distribution characteristics of branch apparent power and line loss are described by the optimal probability fitting method. Finally, the probability level of branch overload is evaluated and the probability distribution of line loss is analyzed. The case studies demonstrate that the branch power approximation model is highly accurate, and the probability distribution of the branch apparent power presents different characteristics. The proposed method can quickly and accurately calculate the branch overload probability level.

关键词： Distribution networks Distributed generation Branch power flow probability model Overload Line loss

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A probability model for churn flow in vertical pipes: Predicting the distribution of disturbance wave scale and void fraction

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INTERNATIONAL JOURNAL OF MULTIPHASE FLOW 2025年 186卷

作者： Liu, Haixiao Guo, Rui Sun, Deping Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China

As a complex flow state in vertical transportation pipelines, churn flow is crucial for optimizing industrial pipeline design and improving fluid transportation efficiency. This study develops a probabilistic analysis model to explore the dynamic characteristics of churn flow in vertical pipelines and its impacts on gas-liquid two-phase flow. Interfacial waves, a key feature in two-phase flow, are essential for flow state conversion and influencing heat and mass transfer processes. The model, based on dynamic equilibrium, examines the generation and dissipation of interfacial fluctuations, treating the influence of vortices on the liquid film as a Markov process. This approach allows for the statistical stabilization of churn flow under specific conditions, facilitating predictions of liquid film thickness and void fraction. These predictions consider variables such as fluid flow rate, pipe size, and fluid physical properties, with accuracy and applicability validated through experimental data. The present study also investigates the effects of gas and liquid velocities, liquid density, liquid viscosity, liquid surface tension, and pipe diameter on the liquid film thickness and the void fraction. The sensitivity analysis reveals that the pipe diameter significantly influences the liquid film thickness, the flow field is more sensitive to the gas velocity than the liquid velocity, and the liquid density notably affects both the liquid film thickness and the void fraction.

关键词： probability model Churn flow Interfacial wave Vortex Liquid film thickness Void fraction

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Investigation on probability model of bending moment-rotation relationship for bolt-ball joints

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JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH 2025年 226卷

作者： San, Bing-Bing Xu, Shi-Zhuo Shan, Zhi-Wei Chen, Wei Looi, Daniel Ting-Wee Hohai Univ Coll Civil & Transportat Engn Nanjing 210098 Peoples R China Southeast Univ China Pakistan Belt & Rd Joint Lab Smart Disaster Nanjing 211189 Peoples R China China Univ Min & Technol Xuzhou Key Lab Fire Safety Engn Struct Xuzhou 221116 Peoples R China Sunway Univ Sch Engn & Technol Civil Engn Bandar Sunway 47500 Selangor Malaysia

As a representative semi-rigid connection, accurately predicting the mechanical properties of bolt-ball joints is of significant importance for structural design. The impact of axial load should be considered in the derivation for the initial stiffness of bolt-ball joints and its bending moment capacity. Because of the variability of geometric dimension and stochastic mechanical property of material, there is a degree of randomness in the actual mechanical behavior of the joints. In order to quantify the randomness in the bending performance, theoretical study was first carried out for the initial stiffness and bending moment capacity of the joint considering effects of axial load, which can accurately predict the bending mechanical performance of bolt-ball joints. Furthermore, the Monte Carlo method was utilized to study the impact of uncertainties in material mechanical properties, joint geometric dimensions, and assembly tightness on the bending performance. Utilizing the Latin Hypercube Sampling (LHS) methodology, a dataset comprising 10,000 samples were systematically extracted for each of the five distinct sizes of bolt-ball joints, and their stochastic responses for initial stiffness and bending moment capacity were obtained using Matlab software. Moreover, the additional variability in initial stiffness and bending moment capacity due to model uncertainty was considered and quantified. By combining the randomness of initial stiffness and bending moment capacity with the additional variability, a three-parameter power function model with random parameters was developed to establish a probabilistic model for the bending momentrotation relationship of bolt-ball joints.

关键词： Bolt-ball joints Initial stiffness Bending moment capacity Axial load effect probability model

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A probability model for predicting the bubble size distribution in slug flow in vertical pipes

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INTERNATIONAL JOURNAL OF MULTIPHASE FLOW 2025年 187卷

作者： Liu, Haixiao Wang, Jiawen Sun, Deping Tianjin Univ State Key Lab Hydraul Engn Simulat & Safety Tianjin 300072 Peoples R China

In deep-sea mineral exploitation, slug flow shows promise for efficient mineral air-lifting but also poses risks of serious production safety accidents. Accurate prediction of the two-phase distribution in the liquid slug is crucial for efficient mineral lifting and accident prevention. This study develops a probability model for predicting the bubble size distribution of slug flow in vertical pipes. The liquid slug is divided into the near wake and far wake regions based on Taylor bubble wake influence. In the near wake, the vortex tears the liquid film at the tail of the Taylor bubble and generates new bubbles, while pushing the old bubbles to move towards the Taylor bubble, facilitating gas exchange between the Taylor bubble and the liquid slug. In the far wake region, vortices and random collisions enable dispersed bubbles to exchange gas with each other. These gas exchange processes occur continuously and maintain dynamic equilibrium in stable slug flow. Calculating the probability of the generation and death of a single bubble, along with the analysis of the bubble behavior, yields a probability model for predicting the bubble size distribution. The model is validated using experimental data and shows good consistency. The study investigated factors affecting the distribution of bubble size in slug flow, including gas phase velocity, liquid phase velocity, liquid density, liquid viscosity, and surface tension.

关键词： probability model Slug flow Bubble size distribution Bubble coalescence Bubble breakage

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probability model for gravel sediment entrainment in turbulent flows

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JOURNAL OF HYDRO-ENVIRONMENT RESEARCH 2013年第3期7卷 154-160页

作者： Ma, Jianmin M. Xu, Dong Bai, Yuchuan C. Williams, John J. R. Univ London Sch Mat Sci & Engn London E1 4NS England Tianjin Univ Sch Civil Engn Res Inst Sediment River & Coastal Engn Tianjin 300072 Peoples R China

This paper reports a stochastic model for the prediction of rollover movement probability of gravel particles in turbulent flow. The model is based on the data of a Direct Numerical Simulation of turbulent flow over a rough bed, which is represented by one layer uniform sphere particles. The locations of effective drag and lift forces are explored, as well as the ratio of drag and lift coefficients. The comparison between rollover and pickup probability models indicates that pickup model is valid for cases of critical shear stress less than 0.1 while rollover model works for critical shear stress larger than 0.1. Thus it is reasonable to take into consideration of both of the two models to predict sediment transport behavior in turbulent flows, especially for fluvial rivers which contain different kinds of sediment particles. (C) 2013 International Association for Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.

关键词： Direct numerical simulation probability model Gravel sediment Rollover movement Turbulent flow

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probability model of solid to liquid-like transition of a fluid suspension after a shear flow onset

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INTERNATIONAL JOURNAL OF MULTIPHASE FLOW 2008年第5期34卷 477-483页

作者： Nouar, C. Riha, P. Acad Sci Czech Republic Inst Hydrodynam CZ-16612 Prague Czech Republic Nancy Univ CNRS LEMTA UMR 7563 F-54504 Vandoeuvre Les Nancy France

The complexity of interactions of different origin between particles in dense fluid suspensions limits application of the concepts of classical mechanics for finding a relation between individual particles dynamics, and the macroscopic dynamic response. For this reason, the probability model of suspension flow after a shear flow onset is proposed that incorporates our certain lack of understanding of environments effects. These effects are identified in the model with the random rate of particles arrival to flow. The multiplication rule is used to sweep from the individual particles to the entire system. The resulting probability of the system shift to flow represents well the measured boundary position, separating the flowing suspension from its solid-like state, and proves thus the appropriate choice of representation of the particle interaction effects. (c) 2008 Published by Elsevier Ltd.

关键词： laminar suspension flow liquid-liquid interface probability model

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probability model FOR STUDYING SPECTRAL ANOMALOUS GEOPHYSICAL FIELDS

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STUDIA GEOPHYSICA ET GEODAETICA 1975年第1期19卷 1-7页

作者： KUBACKOVA, L SLOVAK ACAD SCI GEOPHYS INSTDUBRAVSKA CESTA89930 BRATISLAVACZECHOSLOVAKIA

The paper is a contribution to the stochastic analysis of geophysical fields. Using Mercer's theorem, the theorem of the resolution of Hilbert's random field ξ(x), continuous with respect to the quadratic mean, into a general Fourier series which converges uniformly with respect to the quadratic mean to ξ(x), is proved.

关键词： Fourier Fourier Series probability model Random Field Structural Geology

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probability model FOR ESTIMATING 3-PHASE RELATIVE PERMEABILITY

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JOURNAL OF PETROLEUM TECHNOLOGY 1970年第2期22卷 214-&页

作者： STONE, HL (Esso Production Research Co.)

With the method described here, three-phase relative permeability data may be estimated from two sets of more easily measured two-phase data - water displacing oil, and gas displacing oil. The resulting data compare favorably with the limited experimental data available in the literature, so that they may be used to estimate three-phase data for combination-drive reservoir calculations. Introduction Although thorough analysis of combination gas- and water-drive reservoirs requires three-phase relative permeability data, the effort involved in determining permeability data, the effort involved in determining these data experimentally generally rules out such a direct approach. Refs. 1 through 4 suggest, however, that more easily measured two-phase data can be used to predict the relative permeability to both the wetting and nonwetting fluids in three-phase flow. This report describes a method of using two sets of two-phase data to predict the relative permeability of the intermediate wettability phase in a three-phase system. Use is made of probability concepts and appropriate empirical definitions. This technique may be regarded as a means of interpolating between the two sets of two-phase data to obtain the three-phase relative permeability. In many reservoirs that involve three-phase flow, only gas and oil are mobile in the upper portion of the reservoir; in the lower portion, water and oil are the phases of high mobility. The probability model is phases of high mobility. The probability model is such that it will yield the correct two-phase data when only two phases are flowing, and will provide interpolated data for three-phase flow that are consistent and continuous functions of the phase saturations. It will be shown later that these interpolated values agree with the available three-phase data within experimental uncertainty. Although the method applies to either a preferentially water-wet or a preferentially oil-wet system, preferentially water-wet or a pref

关键词： flow in porous media three-phase system fluid saturation Upstream Oil & Gas hysteresis effect residual oil Dalton Berea core Artificial Intelligence probability model Flow in porous media Formation Evaluation & Management Reservoir Fluid Dynamics

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probability model and Simulation Method of Electric Vehicle Charging Load on Distribution Network

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2014年第9期42卷 879-888页

作者： Zhou, Niancheng Xiong, Xicong Wang, Qianggang Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Chongqing 400044 Peoples R China

This article studies the charging characteristics of different kinds of electric vehicles and, in particular, improves the sampling method of initial state-of-charge for hybrid electric vehicles. With consideration of the influences that the charging time may exert on a customer choice of charging start time, and introducing the quantity of simultaneously charging electric vehicles, a probability model of a hybrid electric vehicle charging load is built. Then an improved probability simulation method of charging demand is proposed for multiple kinds of electric vehicles connected with a distribution grid. Finally, the impact of charging electric vehicles is analyzed based on an IEEE 34-node test feeder.

关键词： pure electric vehicle distribution network hierarchical classification hybrid electric vehicle state-of-charge charging load Monte Carlo simulation probability model quick charging battery swap

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