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不确定性 9

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1)幂模型 1

2R-1C模型;嵌入式系统;参数估计;非迭代方法;二次型 1

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Shallow foundation response variability due to soil and model parameter uncertainty

Prishati RAYCHOWDHURY,Sumit JINDAL

《结构与土木工程前沿(英文)》 2014年 第8卷 第3期   页码 237-251 doi: 10.1007/s11709-014-0242-1

摘要: Geotechnical uncertainties may play crucial role in response prediction of a structure with substantial soil-foundation-structure-interaction (SFSI) effects. Since the behavior of a soil-foundation system may significantly alter the response of the structure supported by it, and consequently several design decisions, it is extremely important to identify and characterize the relevant parameters. Moreover, the modeling approach and the parameters required for the modeling are also critically important for the response prediction. The present work intends to investigate the effect of soil and model parameter uncertainty on the response of shallow foundation-structure systems resting on dry dense sand. The SFSI is modeled using a beam-on-nonlinear-winkler-foundation (BNWF) concept, where soil beneath the foundation is assumed to be an assembly of discrete, nonlinear elements composed of springs, dashpots and gap elements. The sensitivity of both soil and model input parameters on shallow foundation responses are investigated using first-order second-moment (FOSM) analysis and Monte Carlo simulation through Latin hypercube sampling technique. It has been observed that the degree of accuracy in predicting the responses of the shallow foundation is highly sensitive soil parameters, such as friction angle, Poisson’s ratio and shear modulus, rather than model parameters, such as stiffness intensity ratio and spring spacing; indicating the importance of proper characterization of soil parameters for reliable soil-foundation response analysis.

关键词: shallow foun dation     sensitivity analysis     centrifuge data     first-order-second-moment (FOSM) method     parameter uncertainty    

新安江模型参数有效优化及不确定性评估

王文川,程春田,邱林,杨斌斌

《中国工程科学》 2010年 第12卷 第3期   页码 100-107

摘要:

应用新安江模型进行水文模拟时,由于模型本身的不足及参数多、信息量少等原因,会出现率定的最优参数组不唯一、不稳定等问题。考虑到以往的参数优选,都只得出一个参数组,不能反映出其不确定性状况。提出应用基于马尔可夫链蒙特卡罗(MCMC)理论的SCEM-UA算法,通过双牌流域以1 h为时段间隔的36场典型洪水数据对新安江模型参数进行优选和不确定性评估。结果表明,该算法能很好地推出新安江模型参数的后验概率分布;率定和检验结果分析也表明,应用SCEM-UA算法对新安江模型进行优选和不确定评估是有效和可行的。

关键词: 新安江模型     参数率定     不确定性评估     SCEM-UA    

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    

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    

Processing parameter optimization of fiber laser beam welding using an ensemble of metamodels and MOABC

《机械工程前沿(英文)》 2022年 第17卷 第4期 doi: 10.1007/s11465-022-0703-5

摘要: In fiber laser beam welding (LBW), the selection of optimal processing parameters is challenging and plays a key role in improving the bead geometry and welding quality. This study proposes a multi-objective optimization framework by combining an ensemble of metamodels (EMs) with the multi-objective artificial bee colony algorithm (MOABC) to identify the optimal welding parameters. An inverse proportional weighting method that considers the leave-one-out prediction error is presented to construct EM, which incorporates the competitive strengths of three metamodels. EM constructs the correlation between processing parameters (laser power, welding speed, and distance defocus) and bead geometries (bead width, depth of penetration, neck width, and neck depth) with average errors of 10.95%, 7.04%, 7.63%, and 8.62%, respectively. On the basis of EM, MOABC is employed to approximate the Pareto front, and verification experiments show that the relative errors are less than 14.67%. Furthermore, the main effect and the interaction effect of processing parameters on bead geometries are studied. Results demonstrate that the proposed EM-MOABC is effective in guiding actual fiber LBW applications.

关键词: laser beam welding     parameter optimization     metamodel     multi-objective    

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)    

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

《结构与土木工程前沿(英文)》 2013年 第7卷 第2期   页码 133-136 doi: 10.1007/s11709-013-0202-1

摘要: This article examines the capability of Gaussian process regression (GPR) for prediction of effective stress parameter ( ) of unsaturated soil. GPR method proceeds by parameterising a covariance function, and then infers the parameters given the data set. Input variables of GPR are net confining pressure ( ), saturated volumetric water content ( ), residual water content ( ), bubbling pressure ( ), suction ( ) and fitting parameter ( ). A comparative study has been carried out between the developed GPR and Artificial Neural Network (ANN) models. A sensitivity analysis has been done to determine the effect of each input parameter on . The developed GPR gives the variance of predicted . The results show that the developed GPR is reliable model for prediction of of unsaturated soil.

关键词: unsaturated soil     effective stress parameter     Gaussian process regression (GPR)     artificial neural network (ANN)     variance    

1000 MW ultra-supercritical turbine steam parameter optimization

FENG Weizhong

《能源前沿(英文)》 2008年 第2卷 第2期   页码 187-193 doi: 10.1007/s11708-008-0030-5

摘要: The 2 × 1000 MW ultra-supercritical steam turbine of Shanghai Waigaoqiao Phase III project, which uses grid frequency regulation and overload control through an overload valve, is manufactured by Shanghai Turbine Company using Siemens technology. Through optimization, the steam pressure is regarded as the criterion between constant pressure and sliding pressure operation. At high circulating water temperature, the turbine overload valve is kept closed when the unit load is lower than 1000 MW while at other circulating water temperatures the turbine can run in sliding pressure operation when the unit load is higher than 1000 MW and the pressure is lower than 27 MPa This increases the unit operation efficiency. The 3D bending technology in the critical piping helps to reduce the project investment and minimize the reheat system pressure drop which improves the unit operation efficiency and safety. By choosing lower circulating water design temperature and by setting the individual Boiler Feedwater Turbine condenser to reduce the exhaust steam flow and the heat load to the main condenser, the unit average back pressure and the terminal temperature difference are minimized. Therefore, the unit heat efficiency is increased.

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    

Structural parameter design method for a fast-steering mirror based on a closed-loop bandwidth

Guozhen CHEN, Pinkuan LIU, Han DING

《机械工程前沿(英文)》 2020年 第15卷 第1期   页码 55-65 doi: 10.1007/s11465-019-0545-y

摘要: When a fast-steering mirror (FSM) system is designed, satisfying the performance requirements before fabrication and assembly is vital. This study proposes a structural parameter design approach for an FSM system based on the quantitative analysis of the required closed-loop bandwidth. First, the open-loop transfer function of the FSM system is derived. In accordance with the transfer function, the notch filter and proportional-integral (PI) feedback controller are designed as a closed-loop controller. The gains of the PI controller are determined by maximizing the closed-loop bandwidth while ensuring the robustness of the system. Then, the two unknown variables of rotational radius and stiffness in the open-loop transfer function are optimized, considering the bandwidth as a constraint condition. Finally, the structural parameters of the stage are determined on the basis of the optimized results of rotational radius and stiffness. Simulations are conducted to verify the theoretical analysis. A prototype of the FSM system is fabricated, and corresponding experimental tests are conducted. Experimental results indicate that the bandwidth of the proposed FSM system is 117.6 Hz, which satisfies the minimum bandwidth requirement of 100 Hz.

关键词: fast-steering mirror     structural parameter     PI controller     bandwidth     notch filter    

Energy efficient cutting parameter optimization

Xingzheng CHEN, Congbo LI, Ying TANG, Li LI, Hongcheng LI

《机械工程前沿(英文)》 2021年 第16卷 第2期   页码 221-248 doi: 10.1007/s11465-020-0627-x

摘要: Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

关键词: energy efficiency     cutting parameter     optimization     machining process    

Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

Xueping PAN, Ping JU, Feng WU, Yuqing JIN

《机械工程前沿(英文)》 2017年 第12卷 第3期   页码 367-376 doi: 10.1007/s11465-017-0429-y

摘要:

A new hierarchical parameter estimation method for doubly fed induction generator (DFIG) and drive train system in a wind turbine generator (WTG) is proposed in this paper. Firstly, the parameters of the DFIG and the drive train are estimated locally under different types of disturbances. Secondly, a coordination estimation method is further applied to identify the parameters of the DFIG and the drive train simultaneously with the purpose of attaining the global optimal estimation results. The main benefit of the proposed scheme is the improved estimation accuracy. Estimation results confirm the applicability of the proposed estimation technique.

关键词: wind turbine generator     DFIG     drive train system     hierarchical parameter estimation method     trajectory sensitivity technique    

Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

《结构与土木工程前沿(英文)》 2019年 第13卷 第5期   页码 1082-1094 doi: 10.1007/s11709-019-0537-3

摘要: An out-put only modal parameter identification method based on variational mode decomposition (VMD) is developed for civil structure identifications. The recently developed VMD technique is utilized to decompose the free decay response (FDR) of a structure into to modal responses. A novel procedure is developed to calculate the instantaneous modal frequencies and instantaneous modal damping ratios. The proposed identification method can straightforwardly extract the mode shape vectors using the modal responses extracted from the FDRs at all available sensors on the structure. A series of numerical and experimental case studies are conducted to demonstrate the efficiency and highlight the superiority of the proposed method in modal parameter identification using both free vibration and ambient vibration data. The results of the present method are compared with those of the empirical mode decomposition-based method, and the superiorities of the present method are verified. The proposed method is proved to be efficient and accurate in modal parameter identification for both linear and nonlinear civil structures, including structures with closely spaced modes, sudden modal parameter variation, and amplitude-dependent modal parameters, etc.

关键词: modal parameter identification     variational mode decomposition     civil structure     nonlinear system     closely spaced modes    

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    

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    

标题 作者 时间 类型 操作

Shallow foundation response variability due to soil and model parameter uncertainty

Prishati RAYCHOWDHURY,Sumit JINDAL

期刊论文

新安江模型参数有效优化及不确定性评估

王文川,程春田,邱林,杨斌斌

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

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

Alireza MOGHAYEDI, Abimbola WINDAPO

期刊论文

Processing parameter optimization of fiber laser beam welding using an ensemble of metamodels and MOABC

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

Determination of effective stress parameter of unsaturated soils: A Gaussian process regression approach

Pijush Samui, Jagan J

期刊论文

1000 MW ultra-supercritical turbine steam parameter optimization

FENG Weizhong

期刊论文

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

期刊论文

Structural parameter design method for a fast-steering mirror based on a closed-loop bandwidth

Guozhen CHEN, Pinkuan LIU, Han DING

期刊论文

Energy efficient cutting parameter optimization

Xingzheng CHEN, Congbo LI, Ying TANG, Li LI, Hongcheng LI

期刊论文

Hierarchical parameter estimation of DFIG and drive train system in a wind turbine generator

Xueping PAN, Ping JU, Feng WU, Yuqing JIN

期刊论文

Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

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

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