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Inverse uncertainty characteristics of pollution source identification for river chemical spill incidentsby stochastic analysis

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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Inverse identification of the mechanical parameters of a pipeline hoop and analysis of the effect of

Ye GAO, Wei SUN

《机械工程前沿（英文）》 2019年第14卷第3期页码 358-368 doi: 10.1007/s11465-019-0539-9

摘要： To create a dynamic model of a pipeline system effectively and analyze its vibration characteristics, the mechanical characteristic parameters of the pipeline hoop, such as support stiffness and damping under dynamic load, must be obtained. In this study, an inverse method was developed by utilizing measured vibration data to identify the support stiffness and damping of a hoop. The procedure of identifying such parameters was described based on the measured natural frequencies and amplitudes of the frequency response functions (FRFs) of a pipeline system supported by two hoops. A dynamic model of the pipe-hoop system was built with the finite element method, and the formulas for solving the FRF of the pipeline system were provided. On the premise of selecting initial values reasonably, an inverse identification algorithm based on sensitivity analysis was proposed. A case study was performed, and the mechanical parameters of the hoop were identified using the proposed method. After introducing the identified values into the analysis model, the reliability of the identification results was validated by comparing the predicted and measured FRFs of the pipeline. Then, the developed method was used to identify the support stiffness and damping of the pipeline hoop under different preloads of the bolts. The influence of preload was also discussed. Results indicated that the support stiffness and damping of the hoop exhibited frequency-dependent characteristics. When the preloads of the bolts increased, the support stiffness increased, whereas the support damping decreased.

关键词： inverse identification pipeline hoop frequency response function mechanical parameters preload

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Analysis of nonlinear channel friction inverse problem

CHENG Weiping, LIU Guohua

《结构与土木工程前沿（英文）》 2007年第1卷第2期页码 205-210 doi: 10.1007/s11709-007-0024-0

摘要： Based on the Backus-Gilbert inverse theory, the singular value decomposition (SVD) for general inverse matrices and the optimization algorithm are used to solve the channel friction inverse problem. The resolution and covariance friction inverse model in matrix form is developed to examine the reliability of solutions. Theoretical analyses demonstrate that the convergence rate of the general Newton optimization algorithm is in the second-order. The Wiggins method is also incorporated into the algorithm. Using the method, noise can be suppressed effectively, and the results are close to accurate solutions with proper control parameters. Also, the numerical stability can be improved.

关键词： singular SVD second-order covariance Theoretical

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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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Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis

Hao QIN, Shenwei ZHANG, Wenxing ZHOU

《结构与土木工程前沿（英文）》 2013年第7卷第3期页码 276-287 doi: 10.1007/s11709-013-0207-9

摘要： This paper describes an inverse Gaussian process-based model to characterize the growth of metal-loss corrosion defects on energy pipelines. The model parameters are evaluated using the Bayesian methodology by combining the inspection data obtained from multiple inspections with the prior distributions. The Markov Chain Monte Carlo (MCMC) simulation techniques are employed to numerically evaluate the posterior marginal distribution of each individual parameter. The measurement errors associated with the ILI tools are considered in the Bayesian inference. The application of the growth model is illustrated using an example involving real inspection data collected from an in-service pipeline in Alberta, Canada. The results indicate that the model in general can predict the growth of corrosion defects reasonably well. Parametric analyses associated with the growth model as well as reliability assessment of the pipeline based on the growth model are also included in the example. The proposed model can be used to facilitate the development and application of reliability-based pipeline corrosion management.

关键词： pipeline metal-loss corrosion inverse Gaussian process measurement error hierarchical Bayesian Markov Chain Monte Carlo (MCMC)

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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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Performance of inverse fluidized bed bioreactor in treating starch wastewater

M. RAJASIMMAN, C. KARTHIKEYAN

《化学科学与工程前沿（英文）》 2009年第3卷第3期页码 235-239 doi: 10.1007/s11705-009-0020-0

摘要： Aerobic digestion of starch industry wastewater was carried out in an inverse fluidized bed bioreactor using low-density (870 kg/m ) polypropylene particles. Experiments were carried out at different initial substrate concentrations of 2250, 4475, 6730, and 8910 mg COD/L and for various hydraulic retention times (HRT) of 40, 32, 24, 16, and 8 h. Degradation of organic matter was studied at different organic loading rates (OLR) by varying the HRT and the initial substrate concentration. From the results it was observed that the maximum COD removal of 95.6% occurred at an OLR of 1.35 kg COD/(m ·d) and the minimum of 51.8% at an OLR of 26.73 kg COD/(m ·d). The properties of biomass accumulation on the surface of particles were also studied. It was observed that constant biomass loading was achieved over the entire period of operation.

关键词： inverse fluidization low-density particles polypropylene starch biofilm

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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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Jack up reliability analysis: An overview

Ahmad IDRIS, Indra Sati Hamonangan HARAHAP, Montasir Osman Ahmed ALI

《结构与土木工程前沿（英文）》 2018年第12卷第4期页码 504-514 doi: 10.1007/s11709-017-0443-5

摘要： Jack up is a mobile unit used for oil and gas exploration and production in offshore fields. On demand, the unit is moved and installed in a given location and used for a period up to 12 months before being un-installed and moved to another location. Due to its mobility and re-usability, when the unit is offered for use in a given offshore location, its suitability in terms of safe operation is evaluated in accordance with the guidelines of Site Specific Assessment (SSA) of jack up. When the unit failed safety assessment criteria, the guideline recommended that it is re-assessed by increasing the complexity of the assumptions and methods used. Reliability analysis theories are one of the frameworks recommended for the safety assessment of the units. With recent developments in uncertainty and reliability analysis of structures subject to stochastic excitation, this study aims at providing a review on the past developments in jack up reliability analysis and to identify possible future directions. The results from literature reviewed shows that failure probabilities vary significantly with analysis method used. In addition, from the variants of reliability analysis approach, the method of time dependent reliability for dynamic structures subject to stochastic excitation have not been implemented on jack ups. Consequently, suggestions were made on the areas that need further examination for improvement of the efficiency in safety assessment of the units using reliability theories.

关键词： jack up reliability analysis uncertainty analysis review of jack up

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Seismic performance of viaducts with probabilistic method

ZHU Xi, WANG Jianmin

《结构与土木工程前沿（英文）》 2007年第1卷第3期页码 267-273 doi: 10.1007/s11709-007-0034-y

摘要： Due to the uncertainty of both ground motions and structural capacity, it is necessary to consider the seismic performance of viaduct structures using the probabilistic method. The risk is quantified by a procedure on the basis of a numerical determination of the fragility curves. A group of ground motions, Large Magnitude-Short Distance Bin (LMSR-N), selected specially due to its response spectra, is accorded well with the corresponding spectra of the Chinese code for seismic design. The characteristic values of the curvature ductility factors for the serviceability and the damage control limit states are obtained, and two equations for estimating the characteristic values of the curvature ductility factors are developed through regression analysis. Then, the serviceability and damage control limit states were proposed. Three damage states were constituted according the results of the experiment by Pacific Earthquake Engineering Research (PEER) Center. The analytical fragility curves were obtained specifically, using both Capacity Spectrum Method (CSM) (non-linear static) analysis and Ineremental Dynamic Method (IDM) (non-linear dynamic) analysis, respectively, in this paper. The structural fragility curves developed by CSM method can help make the structural analysis simple and quick, avoiding the implementation of the dynamic response history analysis (RHA). Although the dynamic RHA requires a lot of complicated analysis for the structure, the results from RHA are reliable and accurate. Fragility curves are powerful tools for use in performance-based seismic bridge design.

关键词： uncertainty Earthquake Engineering regression analysis accurate fragility

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Uncertainty analysis on aquatic environmental impacts of urban land use change

ZHOU Jiquan, LIU Yi, CHEN Jining, YU Fanxian

《环境科学与工程前沿（英文）》 2008年第2卷第4期页码 494-504 doi: 10.1007/s11783-008-0072-2

摘要： Uncertainties hamper the implementation of strategic environmental assessment (SEA). In order to quantitatively characterize the uncertainties of environmental impacts, this paper develops an integrated methodology through uncertainty analysis on land use change, which combines the scenario analysis approach, stochastic simulation technique, and statistics. Dalian city in China was taken as a case study in the present work. The results predict that the Fuzhou River poses the highest environmental pollution risk with a probability of 89.63% for COD in 2020. Furthermore, the Biliu River, Fuzhou River, Zhuang River, and Dasha River have 100% probabilities for NH-N. NH-N is a more critical pollutant than COD for all rivers. For COD, industry is the critical pollution source for all rivers except the Zhuang River. For NH-N, agriculture is the critical pollution source for the Biliu River, Yingna River, and Dasha River, sewage for the Fuzhou River and Zhuang River, and industry for the Dengsha River. This methodology can provide useful information, such as environmental risk, environmental pressure, and extremely environmental impact, especially under considerations of uncertainties. It can also help to ascertain the significance of each pollution source and its priority for control in urban planning.

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Uncertainty propagation analysis by an extended sparse grid technique

X. Y. JIA, C. JIANG, C. M. FU, B. Y. NI, C. S. WANG, M. H. PING

《机械工程前沿（英文）》 2019年第14卷第1期页码 33-46 doi: 10.1007/s11465-018-0514-x

摘要： In this paper, an uncertainty propagation analysis method is developed based on an extended sparse grid technique and maximum entropy principle, aiming at improving the solving accuracy of the high-order moments and hence the fitting accuracy of the probability density function (PDF) of the system response. The proposed method incorporates the extended Gauss integration into the uncertainty propagation analysis. Moreover, assisted by the Rosenblatt transformation, the various types of extended integration points are transformed into the extended Gauss-Hermite integration points, which makes the method suitable for any type of continuous distribution. Subsequently, within the sparse grid numerical integration framework, the statistical moments of the system response are obtained based on the transformed points. Furthermore, based on the maximum entropy principle, the obtained first four-order statistical moments are used to fit the PDF of the system response. Finally, three numerical examples are investigated to demonstrate the effectiveness of the proposed method, which includes two mathematical problems with explicit expressions and an engineering application with a black-box model.

关键词： uncertainty propagation analysis extended sparse grid maximum entropy principle extended Gauss integration Rosenblatt transformation high-order moments analysis

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Efficient conversion of lignin to alkylphenols over highly stable inverse spinel MnFeO catalysts

《化学科学与工程前沿（英文）》 2023年第17卷第8期页码 1085-1095 doi: 10.1007/s11705-022-2236-1

摘要： The aromatic properties of lignin make it a promising source of valuable chemicals and fuels. Developing efficient and stable catalysts to effectively convert lignin into high-value chemicals is challenging. In this work, MnFe₂O₄ spinel catalysts with oxygen-rich vacancies and porous distribution were synthesized by a simple solvothermal process and used to catalyze the depolymerization of lignin in an isopropanol solvent system. The specific surface area was 110.5 m²∙g^–1, which substantially increased the active sites for lignin depolymerization compared to Fe₃O₄. The conversion of lignin reached 94%, and the selectivity of alkylphenols exceeded 90% after 5 h at 250 °C. Underpinned by characterizations, products, and density functional theory analysis, the results showed that the catalytic performance of MnFe₂O₄ was attributed to the composition of Mn and Fe with strong Mn–O–Fe synergy. In addition, the cycling experiments and characterization showed that the depolymerized lignin on MnFe₂O₄ has excellent cycling stability. Thus, our work provides valuable insights into the mechanism of lignin catalytic depolymerization and paves the way for the industrial-scale application of this process.

关键词： lignin depolymerization spinel catalysts hydrogenation

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Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based on Inverse

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.018

摘要： The forward design of trajectory planning strategies requires preset trajectory optimization functions, resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits. In addition, owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios, it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters. Therefore, an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed. First, numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset. Subsequently, a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory. Furthermore, a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function, and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed. Finally, the proposed strategy is verified based on real driving scenarios. The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the “emergency degree” of obstacle avoidance and the state of the vehicle. Moreover, this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories, effectively improving the adaptability and acceptability of trajectories in driving scenarios.

关键词： Obstacle avoidance trajectory planning Inverse reinforcement theory Anthropomorphic Adaptive driving scenarios

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Risk analysis methods of the water resources system under uncertainty

Zeying GUI,Chenglong ZHANG,Mo Li,Ping GUO

《农业科学与工程前沿（英文）》 2015年第2卷第3期页码 205-215 doi: 10.15302/J-FASE-2015073

摘要： The main characteristic of the water resources system (WRS) is its great complexity and uncertainty, which makes it highly desirable to carry out a risk analysis of the WRS. The natural environmental, social economic conditions as well as limitations of human cognitive ability are possible sources of the uncertainties that need to be taken into account in the risk analysis process. In this paper the inherent stochastic uncertainty and cognitive subjective uncertainty of the WRS are discussed first, from both objective and subjective perspectives. Then the quantitative characterization methods of risk analysis are introduced, including three criteria (reliability, resiliency and vulnerability) and five basic optimization models (the expected risk value model, conditional value at risk model, chance-constrained risk model, minimizing probability of risk events model, and the multi-objective optimization model). Finally, this paper focuses on the various methods of risk analysis under uncertainty, which are summarized as random, fuzzy and mixed methods. A more comprehensive risk analysis methodology for the WRS is proposed based on the comparison of the advantages, disadvantages and applicable conditions of these three methods. This paper provides a decision support of risk analysis for researchers, policy makers and stakeholders of the WRS.

关键词： water resources system evaluation criterion optimization model risk analysis method uncertainty