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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
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
Arash SEKHAVATIAN, Asskar Janalizadeh CHOOBBASTI
《结构与土木工程前沿(英文)》 2019年 第13卷 第1期 页码 66-80 doi: 10.1007/s11709-018-0461-y
关键词: uncertainty reliability analysis deep excavations random set method finite difference method
Applying the spectral stochastic finite element method in multiple-random field RC structures
Abbas YAZDANI
《结构与土木工程前沿(英文)》 2022年 第16卷 第4期 页码 434-447 doi: 10.1007/s11709-022-0820-6
关键词: uncertainty spectral stochastic finite element method correlation length reliability assessment reinforced concrete beam/slab
He XIA, Fei GAO, Xuan WU, Nan ZHANG, Guido DE ROECK, Geert DEGRANDE
《结构与土木工程前沿(英文)》 2009年 第3卷 第1期 页码 9-17 doi: 10.1007/s11709-009-0010-9
关键词: railway elevated structure bridge station vibration noise environment
裂缝性储层数据驱动模型证伪与不确定性量化 Article
方军龄, 龚斌, Jef Caers
《工程(英文)》 2022年 第18卷 第11期 页码 116-128 doi: 10.1016/j.eng.2022.04.015
天然裂缝的许多特性是不确定的,如裂缝的空间分布、岩石物理特性和流体流动性能。贝叶斯定理提供了一个框架来量化地质建模和流动模拟的不确定性,从而支持储层物性预测。贝叶斯方法在裂缝性储层中的应用大多局限于合成案例。然而,在现场应用中,一个主要问题是贝叶斯先验是被证伪的,因为它不能预测油气藏的生产历史。在本文中,我们展示了如何利用全局敏感性分析(GSA)来确定先验被证伪的原因。然后,我们采用近似贝叶斯计算(ABC)方法,结合基于决策树的代理模型来拟合生产历史。我们将这两种方法应用于一个复杂的裂缝性油气藏,其中综合考虑了所有不确定因素,包括油层物理特性、岩石物理特性、流体特性、离散裂缝参数以及压力和渗透率的动态变化。我们成功地找出了证伪的几个原因。结果表明,我们提出的方法可以有效地量化裂缝性储层建模和流动模拟的不确定性。此外,关键参数的不确定性,如裂缝开度和断层传导率,得到了降低。
Simulation of heterogeneous two-phase media using random fields and level sets
George STEFANOU
《结构与土木工程前沿(英文)》 2015年 第9卷 第2期 页码 114-120 doi: 10.1007/s11709-014-0267-5
关键词: microstructure random fields level sets shape recovery two-phase media
Probabilistic analysis of secant piles with random geometric imperfections
《结构与土木工程前沿(英文)》 2021年 第15卷 第3期 页码 682-695 doi: 10.1007/s11709-021-0703-2
关键词: secant piles ultrasonic cross-hole testing probabilistic analysis reliability-based design random imperfections
Xi F. XU
《结构与土木工程前沿(英文)》 2015年 第9卷 第2期 页码 107-113 doi: 10.1007/s11709-014-0268-4
关键词: multiscale finite element settlement perturbation random field geotechnical
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
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
关键词: ANFIS construction time impact assessment highway project South Africa uncertainty
Named entity recognition for Chinese construction documents based on conditional random field
《工程管理前沿(英文)》 2023年 第10卷 第2期 页码 237-249 doi: 10.1007/s42524-021-0179-8
王清印,吕瑞华
《中国工程科学》 2005年 第7卷 第10期 页码 16-22
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。
Bruno SUDRET,Hung Xuan DANG,Marc BERVEILLER,Asmahana ZEGHADI,Thierry YALAMAS
《结构与土木工程前沿(英文)》 2015年 第9卷 第2期 页码 121-140 doi: 10.1007/s11709-015-0290-1
关键词: polycrystalline aggregates crystal plasticity random fields spatial variability correlation structure
Crack propagation with different radius local random damage based on peridynamic theory
《结构与土木工程前沿(英文)》 2021年 第15卷 第5期 页码 1238-1248 doi: 10.1007/s11709-021-0695-y
Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
Diego CABRERA,Fernando SANCHO,René-Vinicio SÁNCHEZ,Grover ZURITA,Mariela CERRADA,Chuan LI,Rafael E. VÁSQUEZ
《机械工程前沿(英文)》 2015年 第10卷 第3期 页码 277-286 doi: 10.1007/s11465-015-0348-8
This paper addresses the development of a random forest classifier for the multi-class fault diagnosis in spur gearboxes. The vibration signal’s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients’ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters’ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.
关键词: fault diagnosis spur gearbox wavelet packet decomposition random forest
标题 作者 时间 类型 操作
of catalyst temperature in automotive engines over coldstart operation in the presence of different randomnoises and uncertainty: Implementation of generalized Gaussian process regression machine
Nasser L. AZAD,Ahmad MOZAFFARI
期刊论文
Application of random set method in a deep excavation: based on a case study in Tehran cemented alluvium
Arash SEKHAVATIAN, Asskar Janalizadeh CHOOBBASTI
期刊论文
Applying the spectral stochastic finite element method in multiple-random field RC structures
Abbas YAZDANI
期刊论文
Running train induced vibrations and noises of elevated railway structures and their influences on environment
He XIA, Fei GAO, Xuan WU, Nan ZHANG, Guido DE ROECK, Geert DEGRANDE
期刊论文
Multiscale stochastic finite element method on random field modeling of geotechnical problems – a fast
Xi F. XU
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
Characterization of random stress fields obtained from polycrystalline aggregate calculations using multi-scale
Bruno SUDRET,Hung Xuan DANG,Marc BERVEILLER,Asmahana ZEGHADI,Thierry YALAMAS
期刊论文