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A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale

《结构与土木工程前沿（英文）》 2023年 第17卷 第12期   页码 1813-1829 doi: 10.1007/s11709-023-0007-9

摘要： Full-scale dome structures intrinsically have numerous sources of irreducible aleatoric uncertainties. A large-scale numerical simulation of the dome structure is required to quantify the effects of these sources on the dynamic performance of the structure using the finite element method (FEM). To reduce the heavy computational burden, a surrogate model of a dome structure was constructed to solve this problem. The dynamic global sensitivity of elastic and elastoplastic structures was analyzed in the uncertainty quantification framework using fully quantitative variance- and distribution-based methods through the surrogate model. The model considered the predominant sources of uncertainty that have a significant influence on the performance of the dome structure. The effects of the variables on the structural performance indicators were quantified using the sensitivity index values of the different performance states. Finally, the effects of the sample size and correlation function on the accuracy of the surrogate model as well as the effects of the surrogate accuracy and failure probability on the sensitivity index values are discussed. The results show that surrogate modeling has high computational efficiency and acceptable accuracy in the uncertainty quantification of large-scale structures subjected to earthquakes in comparison to the conventional FEM.

关键词： large-scale dome structure     surrogate model     global sensitivity analysis     uncertainty quantification     structural performance    

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Modeling the impact of uncertainty in emissions trading markets with bankable permits

Yongliang ZHANG, Bing ZHANG, Jun BI, Pan HE

《环境科学与工程前沿（英文）》 2013年 第7卷 第2期   页码 231-241 doi: 10.1007/s11783-012-0431-x

摘要： The various forms of uncertainty that firms may face in bankable emission permit trading markets will affect firms’ decision making as well as their market performance. This research explores the effect of increased uncertainty over future input costs and output prices on the temporal distribution of emission. In a dynamic programming setting, the permit price is a convex function of stochastic prices of coal and electricity. Increased uncertainty about future market conditions increases the expected permit price and causes a risk neutral firm to reduce ex ante emissions in order to smooth out marginal abatement costs over time. Finally, safety valves, both low-side and high-side, are suggested to reduce the impact of uncertainty in bankable emission trading markets.

关键词： uncertainty     bankable     emission trading     market performance    

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广义不确定性系统理论的外延综论

王清印,吕瑞华

《中国工程科学》 2005年 第7卷 第10期   页码 16-22

摘要：

在概述广义不确定性系统内涵基础上，讨论了广义不确定性系统的外延类别及其相关理论的基本研究框架和基本原理，为深入研究广义不确定性系统理论奠定了基础。

关键词： 广义不确定性信息（GUI）     不确定性数学（UM）     广义不确定性系统理论（GUST）    

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Key uncertainty events impacting on the completion time of highway construction projects

Alireza MOGHAYEDI, Abimbola WINDAPO

《工程管理前沿（英文）》 2019年 第6卷 第2期   页码 275-298 doi: 10.1007/s42524-019-0022-7

摘要： This paper examines the uncertainty events encountered in the process of constructing highways, and evaluates their impact on construction time, on highway projects in South Africa. The rationale for this examination stems from the view held by scholars that the construction of highways is a complex process, taking place in changing environments and often beset by uncertainties; and that there is a lack of appropriate evaluation of these uncertainty events occurring during the construction process. The research made use of a review of extant literature in the area of uncertainty management, and modeling in infrastructure projects, to guide the direction of the study. The inquiry process consisted of brainstorming by highway experts and interviewing them to identify the uncertainty factors that impact construction time. An uncertainty matrix for South African highway projects was developed, using a quantitative model and descriptive statistics. It emerged from the study that the uncertainty events affecting the construction time of highway projects are distributed across economic, environmental, financial, legal, political, social and technical factors. Also, it was found that each factor might account for several uncertainty events which impact on construction time differently, through a combination of the uncertainty events of the individual construction activities. Based on the obtained data, an Adaptive Neuro Fuzzy Inference System (ANFIS) has been developed, as a simple, reliable and accurate advanced machine learning technique to assess the impact of uncertainty events on the completion time of highway construction projects. To validate the ANFIS model, the Stepwise Regression (SR) models have been designed and their results are compared with the results of the ANFIS. Based on the predicted impact size of uncertainty events on the time of highway projects, it can be concluded that construction time on South African highway projects is significantly related to the social and technical uncertainties factors.

关键词： ANFIS     construction time     impact assessment     highway project     South Africa     uncertainty    

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Uncertainty of concrete strength in shear and flexural behavior of beams using lattice modeling

《结构与土木工程前沿（英文）》 2023年 第17卷 第2期   页码 306-325 doi: 10.1007/s11709-022-0890-5

摘要： This paper numerically studied the effect of uncertainty and random distribution of concrete strength in beams failing in shear and flexure using lattice modeling, which is suitable for statistical analysis. The independent variables of this study included the level of strength reduction and the number of members with reduced strength. Three levels of material deficiency (i.e., 10%, 20%, 30%) were randomly introduced to 5%, 10%, 15%, and 20% of members. To provide a database and reliable results, 1000 analyses were carried out (a total of 24000 analyses) using the MATLAB software for each combination. Comparative studies were conducted for both shear- and flexure-deficit beams under four-point loading and results were compared using finite element software where relevant. Capability of lattice modeling was highlighted as an efficient tool to account for uncertainty in statistical studies. Results showed that the number of deficient members had a more significant effect on beam capacity compared to the level of strength deficiency. The scatter of random load-capacities was higher in flexure (range: 0.680–0.990) than that of shear (range: 0.795–0.996). Finally, nonlinear regression relationships were established with coefficient of correlation values (R2) above 0.90, which captured the overall load–deflection response and level of load reduction.

关键词： lattice modeling     shear failure     flexural failure     uncertainty     deficiency     numerical simulation    

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Evaluation of measurement uncertainty of the high-speed variable-slit system based on the Monte Carlo

Yin ZHANG, Jianwei WU, Kunpeng XING, Zhongpu WEN, Jiubin TAN

《机械工程前沿（英文）》 2020年 第15卷 第4期   页码 517-537 doi: 10.1007/s11465-020-0589-z

摘要： This paper presents a dynamic and static error transfer model and uncertainty evaluation method for a high-speed variable-slit system based on a two-dimensional orthogonal double-layer air-floating guide rail structure. The motion accuracy of the scanning blade is affected by both the moving component it is attached to and the moving component of the following blade during high-speed motion. First, an error transfer model of the high-speed variable-slit system is established, and the influence coefficients are calculated for each source of error associated with the accuracy of the blade motion. Then, the maximum range of each error source is determined by simulation and experiment. Finally, the uncertainty of the blade displacement measurement is evaluated using the Monte Carlo method. The proposed model can evaluate the performance of the complex mechanical system and be used to guide the design.

关键词： air-floating guide rail     error transfer model     driving and following structure     dynamic error     uncertainty evaluation     Monte Carlo method    

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Probabilistic seismic response and uncertainty analysis of continuous bridges under near-fault ground

Hai-Bin MA, Wei-Dong ZHUO, Davide LAVORATO, Camillo NUTI, Gabriele FIORENTINO, Giuseppe Carlo MARANO, Rita GRECO, Bruno BRISEGHELLA

《结构与土木工程前沿（英文）》 2019年 第13卷 第6期   页码 1510-1519 doi: 10.1007/s11709-019-0577-8

摘要： Performance-based seismic design can generate predictable structure damage result with given seismic hazard. However, there are multiple sources of uncertainties in the seismic design process that can affect desired performance predictability. This paper mainly focuses on the effects of near-fault pulse-like ground motions and the uncertainties in bridge modeling on the seismic demands of regular continuous highway bridges. By modeling a regular continuous bridge with OpenSees software, a series of nonlinear dynamic time-history analysis of the bridge at three different site conditions under near-fault pulse-like ground motions are carried out. The relationships between different Intensity Measure (IM) parameters and the Engineering Demand Parameter (EDP) are discussed. After selecting the peak ground acceleration as the most correlated IM parameter and the drift ratio of the bridge column as the EDP parameter, a probabilistic seismic demand model is developed for near-fault earthquake ground motions for 3 different site conditions. On this basis, the uncertainty analysis is conducted with the key sources of uncertainty during the finite element modeling. All the results are quantified by the “swing” base on the specific distribution range of each uncertainty parameter both in near-fault and far-fault cases. All the ground motions are selected from PEER database, while the bridge case study is a typical regular highway bridge designed in accordance with the Chinese Guidelines for Seismic Design of Highway Bridges. The results show that PGA is a proper IM parameter for setting up a linear probabilistic seismic demand model; damping ratio, pier diameter and concrete strength are the main uncertainty parameters during bridge modeling, which should be considered both in near-fault and far-fault ground motion cases.

关键词： continuous bridge     probabilistic seismic demand model     Intensity Measure     near-fault     uncertainty    

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知识表示中的不确定性

李德毅

《中国工程科学》 2000年 第2卷 第10期   页码 73-79

摘要：

知识表示一直是人工智能研究中的一个瓶颈，其难点在于知识中隐含有不确定性，即模糊性和随机性。文章提出用云模型3个数字特征（期望值，熵，超熵）来描述一个定性概念，用熵来关联模糊性和随机性。代表定性概念的云的某一次定量值，被称为云滴，可以用它对此概念的贡献度来衡量，许许多多云滴构成云，实现定性和定量之间的随时转换，反映了知识表示中的不确定性。论文以此对我国农历24个节气进行了新的量化解释。云方法已经用于数据开采、智能控制、跳频电台和大系统效能评估中，取得明显的效果。

关键词： 知识表示     定性概念     不确定性     云模型     数宇特征    

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temperature in automotive engines over coldstart operation in the presence of different random noises and uncertainty

Nasser L. AZAD,Ahmad MOZAFFARI

《机械工程前沿（英文）》 2015年 第10卷 第4期   页码 405-412 doi: 10.1007/s11465-015-0354-x

摘要：

The main scope of the current study is to develop a systematic stochastic model to capture the undesired uncertainty and random noises on the key parameters affecting the catalyst temperature over the coldstart operation of automotive engine systems. In the recent years, a number of articles have been published which aim at the modeling and analysis of automotive engines’ behavior during coldstart operations by using regression modeling methods. Regarding highly nonlinear and uncertain nature of the coldstart operation, calibration of the engine system’s variables, for instance the catalyst temperature, is deemed to be an intricate task, and it is unlikely to develop an exact physics-based nonlinear model. This encourages automotive engineers to take advantage of knowledge-based modeling tools and regression approaches. However, there exist rare reports which propose an efficient tool for coping with the uncertainty associated with the collected database. Here, the authors introduce a random noise to experimentally derived data and simulate an uncertain database as a representative of the engine system’s behavior over coldstart operations. Then, by using a Gaussian process regression machine (GPRM), a reliable model is used for the sake of analysis of the engine’s behavior. The simulation results attest the efficacy of GPRM for the considered case study. The research outcomes confirm that it is possible to develop a practical calibration tool which can be reliably used for modeling the catalyst temperature.

关键词： automotive engine     calibration     coldstart operation     Gaussian process regression machine (GPRM)     uncertainty and random noises    

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广义不确定性系统理论的基本构思

王清印,郭立田,谢建华,刘志勇

《中国工程科学》 2004年 第6卷 第3期   页码 25-29

摘要：

论述了不确定性系统理论的国内外发展概况，给出了不确定性信息定义及其广义不确定性系统理论（GUST）的定义，论述了广义不确定性系统理论的基本内涵、基本结构及其科学意义。

关键词： 不确定性信息     广义不确定性系统     基本结构    

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An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit

Zunaira Asif, Zhi Chen

《环境科学与工程前沿（英文）》 2019年 第13卷 第5期 doi: 10.1007/s11783-019-1156-x

摘要： Air Pollution Control model is developed for open-pit metal mines. Model will aid decision makers to select a cost-effective solution. Open-pit metal mines contribute toward air pollution and without effective control techniques manifests the risk of violation of environmental guidelines. This paper establishes a stochastic approach to conceptualize the air pollution control model to attain a sustainable solution. The model is formulated for decision makers to select the least costly treatment method using linear programming with a defined objective function and multi-constraints. Furthermore, an integrated fuzzy based risk assessment approach is applied to examine uncertainties and evaluate an ambient air quality systematically. The applicability of the optimized model is explored through an open-pit metal mine case study, in North America. This method also incorporates the meteorological data as input to accommodate the local conditions. The uncertainties in the inputs, and predicted concentration are accomplished by probabilistic analysis using Monte Carlo simulation method. The output results are obtained to select the cost-effective pollution control technologies for PM2.5, PM10, NOx, SO2 and greenhouse gases. The risk level is divided into three types (loose, medium and strict) using a triangular fuzzy membership approach based on different environmental guidelines. Fuzzy logic is then used to identify environmental risk through stochastic simulated cumulative distribution functions of pollutant concentration. Thus, an integrated modeling approach can be used as a decision tool for decision makers to select the cost-effective technology to control air pollution.

关键词： Air pollution     Decision analysis     Linear programming     Mining     Optimization     Fuzzy     Monte Carlo    

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Geological risk prediction under uncertainty in tunnel excavation using online learning and hidden Markov

《工程管理前沿（英文）》 doi: 10.1007/s42524-024-0082-1

摘要： The accurate estimation of geological risks is essential for preventing geohazards, and ensuring efficient and safe construction processes. This study proposes a method, the online hidden Markov model (OHMM), which combines online learning with the hidden Markov model to estimate geological risks. The OHMM is tailored for the continuous nature of observational data, allowing it to adaptively update with each new piece of data. To address the challenge of limited data in the early stages of construction, we use pre-construction borehole samples as additional data. This approach extends the short sequence of observed data to match the length of a complete sequence through an observation extension mechanism. The effectiveness of the OHMM, equipped with this observation extension mechanism, is demonstrated in a case study that models geological risks for a tunnel excavation project in Singapore. The OHMM outperforms traditional methods, including the hidden Markov model, long short-term memory network, neural network, and support vector machine, in predicting geological risks ahead of the tunnel boring machine. Notably, the OHMM can accurately forecast geological risks in areas yet to be constructed, using limited observational and site investigation data. This research advances geological risk prediction models by offering an online updating capability for tunnel excavation and construction projects. It enables early-stage risk prediction and provides long-term forecasts with minimal historical data requirements, maximizing the use of site investigation data.

关键词： geological risk prediction     machine learning     online learning     hidden Markov model     borehole logging    

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Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents

Jiping Jiang, Feng Han, Yi Zheng, Nannan Wang, Yixing Yuan

《环境科学与工程前沿（英文）》 2018年 第12卷 第5期 doi: 10.1007/s11783-018-1081-4

摘要：

Uncertainty rules of pollution source inversion are revealed by stochastic analysis

A release load is most easily inversed and source locations own largest uncertainty

Instantaneous spill assumption has much less uncertainty than continuous spill

The estimated release locations and times negatively deviate from real values

The new findings improve monitoring network design and emergency response to spills

关键词： River chemical spills     Emergency response     Pollution source inversion     Inverse uncertainty analysis     Regional Sensitivity Analysis method (RSA)     Monte Carlo analysis toolbox (MCAT)    

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Uncertainty assessment in hydro-mechanical-coupled analysis of saturated porous medium applying fuzzy

Farhoud KALATEH, Farideh HOSSEINEJAD

《结构与土木工程前沿（英文）》 2020年 第14卷 第2期   页码 387-410 doi: 10.1007/s11709-019-0601-z

摘要： The purpose of the present study was to develop a fuzzy finite element method, for uncertainty quantification of saturated soil properties on dynamic response of porous media, and also to discrete the coupled dynamic equations known as - hydro-mechanical equations. Input parameters included fuzzy numbers of Poisson’s ratio, Young’s modulus, and permeability coefficient as uncertain material of soil properties. Triangular membership functions were applied to obtain the intervals of input parameters in five membership grades, followed up by a minute examination of the effects of input parameters uncertainty on dynamic behavior of porous media. Calculations were for the optimized combinations of upper and lower bounds of input parameters to reveal soil response including displacement and pore water pressure via fuzzy numbers. Fuzzy analysis procedure was verified, and several numerical examples were analyzed by the developed method, including a dynamic analysis of elastic soil column and elastic foundation under ramp loading. Results indicated that the range of calculated displacements and pore pressure were dependent upon the number of fuzzy parameters and uncertainty of parameters within equations. Moreover, it was revealed that for the input variations looser sands were more sensitive than dense ones.

关键词： fuzzy finite element method     saturated soil     hydro-mechanical coupled equations     coupled analysis     uncertainty analysis    

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不确定性推理理论在卫星故障检测和诊断中的应用

杨天社,李怀祖,曹雨平

《中国工程科学》 2003年 第5卷 第2期   页码 68-74

摘要：

推理理论一般分为确定性推理理论和不确定性推理理论。传统的卫星故障检测和诊断应用的是确定性推理。然而，在卫星故障检测和诊断的实践中，仅使用确定性推理是很难对某些故障进行检测和诊断的，因为这时需要合情推理和容错能力。不确定性推理理论可以满足此要求。目前，航天领域的许多专家和实际工作者正致力于应用不确定性推理理论检测和诊断那些用确定性推理无法检测和诊断的故障。不确定性推理理论包括诸如包含度理论、粗糙集理论、证据推理理论、概率推理理论、模糊推理理论等。笔者研究的卫星故障检测和诊断的三种新方法，分别应用了包含度理论、粗糙集理论和证据推理理论。

关键词： 卫星     故障     检测     诊断     不确定性推理    

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标题 作者 时间 类型 操作

A surrogate model for uncertainty quantification and global sensitivity analysis of nonlinear large-scale

期刊论文

Modeling the impact of uncertainty in emissions trading markets with bankable permits

Yongliang ZHANG, Bing ZHANG, Jun BI, Pan HE

期刊论文

广义不确定性系统理论的外延综论

王清印,吕瑞华

期刊论文

Key uncertainty events impacting on the completion time of highway construction projects

Alireza MOGHAYEDI, Abimbola WINDAPO

期刊论文

Uncertainty of concrete strength in shear and flexural behavior of beams using lattice modeling

期刊论文

Evaluation of measurement uncertainty of the high-speed variable-slit system based on the Monte Carlo

Yin ZHANG, Jianwei WU, Kunpeng XING, Zhongpu WEN, Jiubin TAN

期刊论文

Probabilistic seismic response and uncertainty analysis of continuous bridges under near-fault ground

Hai-Bin MA, Wei-Dong ZHUO, Davide LAVORATO, Camillo NUTI, Gabriele FIORENTINO, Giuseppe Carlo MARANO, Rita GRECO, Bruno BRISEGHELLA

期刊论文

知识表示中的不确定性

李德毅

期刊论文

temperature in automotive engines over coldstart operation in the presence of different random noises and uncertainty

Nasser L. AZAD,Ahmad MOZAFFARI

期刊论文

广义不确定性系统理论的基本构思

王清印,郭立田,谢建华,刘志勇

期刊论文

An integrated optimization and simulation approach for air pollution control under uncertainty in open-pit

Zunaira Asif, Zhi Chen

期刊论文

Geological risk prediction under uncertainty in tunnel excavation using online learning and hidden Markov

期刊论文

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents

Jiping Jiang, Feng Han, Yi Zheng, Nannan Wang, Yixing Yuan

期刊论文

Uncertainty assessment in hydro-mechanical-coupled analysis of saturated porous medium applying fuzzy

Farhoud KALATEH, Farideh HOSSEINEJAD

期刊论文

不确定性推理理论在卫星故障检测和诊断中的应用

杨天社,李怀祖,曹雨平

期刊论文