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Development of a probability distribution model for the LJF factors It in offshore two-planar tubular DK-joints subjected to OPB moment loading

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MARINE STRUCTURES 2019年 63卷 196-214页

作者： Ahmadi, Hamid Mayeli, Vahid Univ Tabriz Fac Civil Engn Tabriz *** Iran

probability distribution models are essential for the reliability-based analysis and design of off-shore structures. The objective of the present research was developing a probability distribution model for the local joint flexibility (LJF) factor, f(LJF), in two-planar tubular DK-joints commonly found in jacket-type offshore wind turbines and oil/gas production platforms. A total of 324 finite element (FE) analyses were carried out on 81 FE models of DK-joints subjected to four types of out-of-plane bending (OPB) moment loads. Generated FE models were validated using the available experimental data, FE results, and design formulas. Based on the results of parametric FE study, a sample database was prepared for the f(LJF) values and density histograms were generated for respective samples based on the Freedman-Diaconis rule. Nine theoretical probability density functions (PDFs) were fitted to the developed histograms and the maximum likelihood (ML) method was applied to evaluate the parameters of fitted PDFs. In each case, the Kolmogorov-Smirnov and chi-squared tests were used to evaluate the goodness of fit. Finally, the lognormal model was proposed as the governing probability distribution function for the f(LJF). After substituting the values of estimated parameters, four fully defined PDFs were presented for the f(LJF) in tubular DK-joints subjected to four types of OPB moment loads.

关键词： Two-planar tubular DK-Joint Local joint flexibility (LJF) probability distribution model Maximum likelihood (ML) method Goodness-of-fit tests

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Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI

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MEDICAL IMAGE ANALYSIS 2016年 32卷 173-183页

作者： Kurugol, Sila Freiman, Moti Afacan, Onur Perez-Rossello, Jeannette M. Callahan, Michael J. Warfield, Simon K. Computat Radiol Lab Boston MA USA Boston Childrens Hosp Dept Radiol Boston MA 02111 USA Harvard Med Sch Boston MA 02111 USA

Quantitative diffusion-weighted MR imaging (DW-MRI) of the body enables characterization of the tissue microenvironment by measuring variations in the mobility of water molecules. The diffusion signal decay model parameters are increasingly used to evaluate various diseases of abdominal organs such as the liver and spleen. However, previous signal decay models (i.e., mono-exponential, bi-exponential intra-voxel incoherent motion (IVIM) and stretched exponential models) only provide insight into the average of the distribution of the signal decay rather than explicitly describe the entire range of diffusion scales. In this work, we propose a probability distribution model of incoherent motion that uses a mixture of Gamma distributions to fully characterize the multi-scale nature of diffusion within a voxel. Further, we improve the robustness of the distribution parameter estimates by integrating spatial homogeneity prior into the probability distribution model of incoherent motion (SPIM) and by using the fusion bootstrap solver (FBM) to estimate the model parameters. We evaluated the improvement in quantitative DW-MRI analysis achieved with the SPIM model in terms of accuracy, precision and reproducibility of parameter estimation in both simulated data and in 68 abdominal in-vivo DW-MRIs. Our results show that the SPIM model not only substantially reduced parameter estimation errors by up to 26%;it also significantly improved the robustness of the parameter estimates (paired Student's t-test, p < 0.0001) by reducing the coefficient of variation (CV) of estimated parameters compared to those produced by previous models. In addition, the SPIM model improves the parameter estimates reproducibility for both intra- (up to 47%) and inter-session (up to 30%) estimates compared to those generated by previous models. Thus, the SPIM model has the potential to improve accuracy, precision and robustness of quantitative abdominal DW-MRI analysis for clinical applications. (C) 201

关键词： Diffusion-weighted MRI Abdomen Liver Spleen probability distribution model Spatial homogeneity prior model fitting Markov random field

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Reduction scenarios of plastic waste emission guided by the probability distribution model to avoid additional ocean plastic pollution by 2050s

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MARINE POLLUTION BULLETIN 2024年 207卷 116791页

作者： Higuchi, Chisa Isobe, Atsuhiko Kyushu Univ Res Inst Appl Mech 6-1 Kasuga Koen Kasuga 8168580 Japan

Marine plastic pollution is progressing worldwide and will become increasingly serious if plastic waste emissions continue at the current rate or increase with economic growth. Here, we report a particle tracking-based probability distribution model for predicting the abundances of marine macroplastics and microplastics, which undergo generation, transport, and removal processes in the world's upper ocean, under various scenarios of future land-to-sea plastic waste emissions. To achieve the Osaka Blue Ocean Vision, which aims to reduce additional pollution by marine plastic litter to zero by 2050, plastic waste emission in similar to 2035 should be reduced by at least 32 % relative to 2019. It is necessary to take stringent measures such as 'system change scenario' or 'improve waste management scenario' proposed in previous studies to reduce the marine plastic pollution by 2050.

关键词： Macroplastics Microplastics Plastic reduction scenarios Osaka Blue Ocean vision probability distribution model Particle tracking model

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Investigation on error model of in-vehicle acoustic transfer function based on the human body scattering effects

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2025年

作者： Zeng, Zhipeng Huang, Shuang Guo, Hui Yuan, Tao Liu, Ningning Sun, Yixia Shanghai Univ Engn Sci Sch Mech & Automot Engn Longteng Rd 333 Shanghai 201620 Peoples R China

Sound field control technology enhances the passenger experience by processing signals. The effectiveness of sound field control depends on the accurate measurement of the acoustic transfer function (ATF) and the ability to resist interference from acoustic environment. Due to the difficulty in obtaining the distribution of ATF errors caused by human body scattering and the constantly changing sitting situation inside the car, a method to establish an ATF error model for the vehicle interior is proposed in this paper. Firstly, to obtain errors for the probability distribution of ATF errors inside the vehicle, the actual ATF were obtained through experimental testing. Then, combined with psychoacoustics and kernel density estimation methods, the probability distribution of the ATF errors in each Bark frequency band was calculated. Finally, the relevant parameters of the error model were determined using probability density function to establish the ATF error model, and the model was applied and verified through multizone sound field control of the in-vehicle environment. The results show that the use of the ATF error model proposed in this paper effectively improves the control effect of the in-vehicle sound field, providing an effective approach for establishing the ATF error model for the in-vehicle sound field.

关键词： Acoustic transfer function probability distribution model sound field control vehicle interior human body scattering effects

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Benchmarks for permanent carbon in low-carbon probabilistic design of concrete structures: A case study of China

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JOURNAL OF CLEANER PRODUCTION 2025年 489卷

作者： Guan, Xiangshuo Xiao, Jianzhuang Xia, Bing Xiao, Xuwen Noguchi, Takafumi Tongji Univ Coll Civil Engn Dept Struct Engn 1239 Siping Rd Shanghai 200092 Peoples R China Guangxi Univ Inst Sci & Technol Carbon Peak & Neutral Nanning 530004 Peoples R China Hong Kong Polytech Univ Dept Civil & Environm Engn Hong Kong Peoples R China Chinese Acad Engn Beijing 100088 Peoples R China Univ Tokyo Grad Sch Engn Dept Architecture Bldg Mat Engn Lab Tokyo 1138654 Japan

China currently accounts for over 25% of global anthropogenic carbon emissions. Cutting down the carbon emissions of the construction industry is a major task for achieving the carbon neutrality goal in China. However, research on benchmarks and probability distribution models for China's embodied carbon emissions remains insufficient. To address this gap, this study defined "permanent carbon" by distinguishing the low time- variability part of embodied carbon emissions in buildings. Based on samples of 114 buildings in China, statistical and regression methods were utilized to construct a prior probability distribution model for permanent carbon of concrete structures, considering differences in building types. By applying Bayesian updating methods, posterior distributions were obtained based on latest region-specific information, addressing the issue of outdated data over time. Taking the East China region as an example, we found that the regional adjustment significantly affected carbon emission estimates, with varying adjustment factors for different building types. Transportation carbon emission benchmarks were influenced by transportation modes and distances, while distribution types remained stable. This study employs the Bayesian updating method in a novel way to help establish carbon emission benchmarks, support the formulation of carbon reduction targets, and aid the low carbon design during the early stage of building projects.

关键词： Concrete structures Permanent carbon probability distribution model Carbon benchmark Regional adjustment

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A Study on probability distribution models for Multiple Wind Speeds 5

A Study on Probability Distribution Models for Multiple Wind...

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5th Asia Conference on Power and Electrical Engineering (ACPEE)

作者： Li, Yudun Yang, Chao Wang, Xin Geng, Yujie State Grid Shandong Elect Power Res Inst Jinan Peoples R China State Grid Shandong Elect Power Co Jinan Peoples R China

ISBN: (纸本)9781728152813

The large-scale development of wind energy leads to the integration of multiple wind farms into a power system in a region. Due to the geographic locations of wind farms, wind speeds at different sites show certain dependence between each other, which has a considerable impact on the wind energy potential. An essential step in studying the impaction is the construction of relatively accurate wind speed models incorporating the dependence. In this paper, four probabilistic models of multiple wind speeds are introduced, including conditional distribution model, correlation matrix transformation model, normal transformation model and copula function model. The modeling procedure and simulation methodology are illustrated. The model accuracy is analyzed and compared using two actual wind speed data. Useful conclusions are obtained for further study and application.

关键词： multiple wind speed probability distribution model dependence wind energy

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distribution system reliability worth analysis with the customer cost model based on RBF neural network

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IEEE TRANSACTIONS ON POWER DELIVERY 2003年第3期18卷 1015-1021页

作者： Lin, WM Zhan, TS Yang, CD Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung 804 Taiwan Yung Ta Inst Technol Dept Elect Engn Pingtung 909 Taiwan

Reliability worth analysis is an important tool for distribution systems planning and operations. The interruption cost model used in the analysis directly affects the accuracy of the reliability worth evaluation. In this paper, two interruption cost models including an average or aggregated model (AAM), and a probabilistic distribution model (PDM) are proposed by using the radial basis function (RBF) neural network with orthogonal least-squares (OLS) learning method. The residential and industrial interruption costs in AAM and PDM were integrated by the proposed neural network technique. A Monte-Carlo time sequential simulation technique was adopted for worth assessment. The technique is tested by evaluating the reliability worth of a Taipower system for the installation of disconnected switches, lateral fuses, transformers, and alternative supplies. The results show that the two cost models result in very different interruption costs, and PDM may be more realistic in modeling the system.

关键词： average or aggregate model distribution system planning interruption cost model Monte-Carlo time sequential simulation probability distribution model radial basis function (RBF) neural network reliability worth

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A multi-objective optimization model and its evolution-based solutions for the fingertip localization problem

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PATTERN RECOGNITION 2018年 74卷 385-405页

作者： Gong, Dunwei Liu, Ke China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221116 Peoples R China Qingdao Univ Sci & Technol Sch Informat Sci & Technol Qingdao 266061 Peoples R China

Exact fingertip positions are of particular importance to the fingertip-based human-computer interaction. We build a multi-objective optimization model for the problem of fingertip localization, and present a method to solve the above model based on evolutionary algorithms. When building the model, we take the positions of a series of pixels as the decision variable, the shape of the hand-edge curve corresponding to each of the pixels as one objective function, and the distance between each of the pixels and the gravity center of the palm as the other objective function. In addition, based on the correlation among the positions of pixels of the fingertip regions, we present a multi-objective estimation of distribution algorithm to solve the model so as to obtain the best pixel set, thus gaining the fingertip positions. The experimental results demonstrate the effectiveness of the proposed model and algorithm. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Fingertip localization Multi-objective optimization Estimation of distribution algorithm probability distribution model

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Study on Discrete Fracture Network model and Rock Mass Quality Evaluation of Tunnel Surrounding Rock

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BUILDINGS 2024年第9期14卷 2983页

作者： Sun, Shunxian Tian, Haiguang Zhang, Zhanjun Diao, Zhaoke Deng, Longhua Yang, Xuxu Guo, Junwei Qingdao Chengfa Urban Renewal Co Ltd Qingdao 266041 Peoples R China Qingdao Metro Planning & Design Inst Co Ltd Qingdao 266100 Peoples R China Shandong Univ Sci & Technol Shandong Key Lab Civil Engn Disaster Prevent & Mit Qingdao 266590 Peoples R China

In order to fully explore the development degree and distribution law of the structural plane of a tunnel surrounding rock in three-dimensional space, this paper studies the geometric characteristic parameters of a structural plane in the study area through field investigation, data acquisition and statistical analysis. The structural plane is divided into three dominant groups by using DIPS. v5. 103 software. The probability distribution model of occurrence, trace length, diameter and spacing of the structural plane is established. This paper focuses on the error correction of structural plane occurrence and the estimation of average trace length based on the rectangular window method. The discrete fracture network model is generated by using MATLAB R2021b software, and the discrete fracture network model is verified from three aspects: structural plane occurrence, average trace length and area density. The verification results are compared with the measured data, and the simulation results are in line with the actual situation on site. Based on the discrete fracture network model, the volume joint number of rock mass is calculated. Based on the JSR index, BQ classification method and RQD classification, the development degree of fractures and surrounding rock classification in this area are evaluated. A method of surrounding rock classification based on three evaluation indexes is discussed to comprehensively and accurately classify the quality of rock mass in this area.

关键词： structural plane probability distribution model discrete fracture network model surrounding rock classification

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Probabilistic load flow computation with polynomial normal transformation and Latin hypercube sampling

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IET GENERATION TRANSMISSION & distribution 2013年第5期7卷 474-482页

作者： Cai, Defu Shi, Dongyuan Chen, Jinfu Huazhong Univ Sci & Technol Coll Elect & Elect Engn State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China

A probabilistic load flow method based on polynomial normal transformation (PNT) and Latin hypercube sampling (LHS) is proposed. The correlation between input random variables has been taken into consideration. The proposed method uses the statistical moments and correlation matrix of input random variables instead of their marginal distribution functions and joint distribution functions, which are very difficult to be obtained, to establish their probability distribution models by PNT and LHS. The statistical moments and probability distribution functions of node voltage and line flow are calculated by Monte Carlo simulation method. Performance of the proposed method is investigated using IEEE 14-bus and IEEE 118-bus test systems. The impacts of correlation factor on the statistical moments of power injections and system operation are analysed. Finally, conclusions are duly drawn.

关键词： IEEE standards load flow Monte Carlo methods polynomial matrices sampling methods statistical distributions power injection statistical moment correlation factor IEEE 118-bus test system IEEE 14-bus test system Monte Carlo simulation method node voltage line flow probability distribution model random variable correlation matrix LHS PNT Latin hypercube sampling polynomial normal transformation probabilistic load flow computation

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