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10th International Structural Engineering and Construction Conference, ISEC 2019

作者： Ren, Zhicheng Zhang, Qingwen Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters Ministry of Industry and Information Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9780996043762

At present, there are mainly three research ways on the distribution of snow load: field measurement, experimental simulation, and numerical simulation. They all need expensive equipment, specimen model used only once, and slight defective simulation software. Artificial Neural Networks (ANNs) rely on a large number of input functions to estimate unknown or known occurrences. This paper applies ANNs to predict the uneven distribution of snow loads. First, the snow load database is collected and set up, including all the data from field measurement and experimental simulation. Second, part of the data from the 1m3 model is used as a training set to train Backpropagation Neural Networks (BPNN) and Generalized Regression Neural Networks (GRNN). The parameters of the two neural networks are determined (such as the smoothing factor in the GRNN), and the rest of the data is used to examine the model;the prediction and measurement results of the two models are compared. Finally, based on different wind direction angles and wind speed, a GRNN model is established to predict the uneven snow load distribution. Through comparative analysis, GRNN is more suitable for predicting the uneven distribution of snow loads, especially in predicting snow thickness. In particular, the prediction effect of the model on the snow load distribution trend is good, and the prediction ability of the neural network model is displayed. Copyright © 2019 ISEC Press.

关键词： Neural network models

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Crack pattern prediction of laterally loaded panels with openings based on ANN method 10

Crack pattern prediction of laterally loaded panels with ope...

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10th International Structural Engineering and Construction Conference, ISEC 2019

作者： Wang, Yongfei Zhang, Yu Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters Ministry of Industry and Information Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9780996043762

In this paper, a Back Propagation Neural Network (BPNN) is used to predict crack pattern for masonry panels with opening subjected to lateral loading. The cellular automata method is used to digitalize the panels, including two steps - dividing a panel into a certain number of cells and calculating cell state values by use of a Von Neumann neighborhood model. These digitalized values are used as input data of NN model, respectively. All the experimental data is collected, including panel configuration, material property, opening ratio and location, state values, and crack pattern. The NN model is trained repeatedly, taking part of the data as a training set, to determine parameters, and the rest of the data is taken to check the model. Well-trained NN models can predict the crack pattern of any other panel. The results show that NN method is suitable for prediction of crack pattern. Comparing the two ways of prediction, the Fragility Coefficient Method gets a more precise pattern. The predicted cracks are distributed successively in some specific areas, especially in high similarity, compared with experimental crack pattern. Copyright © 2019 ISEC Press.

关键词： Forecasting

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A new numerical scheme for simulating non-gaussian and non-stationary stochastic processes

arXiv

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arXiv 2020年

作者： Zheng, Zhibao Dai, Hongzhe Wang, Yuyin Wang, Wei Key Lab of Structures Dynamic Behavior and Control Harbin Institute of Technology Ministry of Education Harbin150090 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China

This paper presents a new numerical scheme for simulating stochastic processes specified by their marginal distribution functions and covariance functions. Stochastic samples are firstly generated to automatically satisfy target marginal distribution functions. An iterative algorithm is proposed to match the simulated covariance function of stochastic samples to the target covariance function, and only a few times iterations can converge to a required accuracy. Several explicit representations, based on Karhunen-Loève expansion and Polynomial Chaos expansion, are further developed to represent the obtained stochastic samples in series forms. Proposed methods can be applied to non-gaussian and non-stationary stochastic processes, and three examples illustrate their accuracies and efficiencies. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

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Properties of precast prestressed concrete slab-on-ground based on pp-fiber reinforced alkaliactivated composite 7

Properties of precast prestressed concrete slab-on-ground ba...

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7th Asia-Pacific Conference on FRP in structures, APFIS 2019

作者： Jiang, Xiaobo Cong, Xinyu Zhou, Wei School of Civil Engineering Harbin Institute of Technology Harbin150090 China Key Lab of Structures Dynamic Behaviour and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

ISBN: (纸本)9780648752899

For providing likelihood to avoid the cracking of slab-on-ground of industrial plants and logistics warehouses, this investigation is on two aspects of materials and structure. In terms of materials, the mechanical properties, shrinkage, tensile strength, fiber distribution and the concrete stress-strain curves of PP-fiber reinforced alkali-activated materials were tested, with particular emphasis on the improvement in toughness after fiber reinforcement. In terms of structure, with using a commercial software package, the entire 3-dimensional finite element models were linear elastic structures. The prestressed structural layer and the surface layer were respectively made of fiber-reinforced and nonfiber- reinforced alkali-activated concrete, the interaction between two layers was considering by inplane shear experiment and the elastic modulus and poisson's ratio obtained from the stress-strain curve are taken as parameters of surface concrete. The sliding layer is used to reduce friction and the foundation is considered to be the Winkler model. The unidirectional and bidirectional mechanical properties and the load transfer efficiency (LTE) of the precast prestressed pavement after assembly were discussed under the complex stress state, including wheel load, stacking load, temperature stress and uneven settlement of foundation. © APFIS 2019. All right reserved.

关键词： Stress-strain curves

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A sample-based stochastic finite element method for structural reliability analysis

arXiv

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arXiv 2020年

This paper presents a new methodology for structural reliability analysis via stochastic finite element method (SFEM). A novel sample-based SFEM is firstly used to compute structural stochastic responses of all spatial points at the same time, which decouples the stochastic response into a combination of a series of deterministic responses with random variable coefficients, and solves corresponding stochastic finite element equation through an iterative algorithm. Based on the stochastic response obtained by the SFEM, the limit state function described by the stochastic response and the multidimensional integral encountered in reliability analysis can be computed without any difficulties, and failure probabilities of all spatial points are calculated once time. The proposed method can be applied to high-dimensional stochastic problems, and one of the most challenging issues encountered in high-dimensional reliability analysis, known as Curse of Dimensionality, can be circumvented without expensive computational costs. Three practical ex- Copyright © 2020, The Authors. All rights reserved.

关键词： Reliability analysis

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Corrigendum to “Experimental evaluation of mechanical properties and microstructure for recycled aggregate concrete collaboratively modified with nano-silica and mixed fibers” [Constr. Build. Mater. 403 (2023) 133125]

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Construction and Building Materials 2023年 404卷

作者： Hang Sun Liang Luo Huan Yuan Xi Li School of Transportation and Science Engineering Harbin Institute of Technology Harbin 150090 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin 150090 China School of Civil Engineering Harbin Institute of Technology Harbin 150090 China

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Machine learning for bridge wind engineering

Advances in Wind Engineering

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Advances in Wind Engineering 2024年第1期1卷

作者： Zeyu Zhang Shanwu Li Hui Feng Xuxi Zhou Nan Xu Hui Li Shujin Laima Wenli Chen School of Civil Engineering Harbin Institute of Technology Harbin 150090 China Department of Mechanical Engineering-Engineering Mechanics Michigan Technological University Houghton MI 49931 USA Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin 150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin 150090 China

Modeling and control are primary domains in bridge wind engineering. The natural wind field characteristics (e.g., non-stationary, non-uniform, spatial-temporal changing characteristics) and the wind-bridge interaction processes are physically complex and exhibit strong nonlinearity. The lack of analyzing these complex physical processes based on first principles makes it difficult for traditional modeling and control methods to accurately characterize or control wind field and wind-induced vibration of bridges. Data-driven automatic modeling and control is a new expansion direction in bridge wind engineering due to the extensive valuable historical data available and the complex, high-dimensional character of the state space and action space of the agent in active control. Machine Learning (ML) has been shown versatile for various modeling and control tasks in bridge wind engineering due to its excellent ability to automatically extract space features efficiently and make wonderful decisions facing complicated tasks without manual interval. Starting from an overview of the basic concepts and methods of ML, this review will comprehensively analyze and summarize the application of ML methods in various aspects of bridge wind engineering, including wind fields, static aerodynamic reconstruction, wind-induced vibrations and control based on reinforcement learning, in order to enable readers to have a full knowledge of the potential of ML in various subfields. The essence of these tasks is to rely on data-driven minds to solve tricky problems that cannot be solved based on first principles. ML will continue to integrate and coexist with wind engineering of bridges and generate new revolutions in both theories and applications owing to its powerful information-processing and modeling-learning ability.

关键词： Artificial intelligence Machine learning Bridge wind engineering

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Static and fatigue performances of clip anchorage system for FRP rod used in cable

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Engineering structures 2025年 339卷

作者： Guijun Xian Yanzhao Niu Jingwei Tian Chenggao Li Qingrui Yue Rui Guo Key Lab of Structures Dynamic Behavior and Control (Harbin Institute of Technology) Ministry of Education Harbin Heilongjiang 150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin 150090 China School of Civil Engineering Harbin Institute of Technology Harbin Heilongjiang 150090 China Research Institute of Urbanization and Urban Safety School of Civil and Resource Engineering University of Science and Technology Beijing Beijing China

To obtain the static and fatigue performances and provide the design parameters of FRP rod for the application in cable structures, the design and preparation method of steel clip anchor, steel clip anchor with aluminum sleeve and adhesive layer are presented in the present paper. The effect of taper difference, preload and anchor type on static and fatigue performances is studied by tensile and fatigue test, and the optimal design and application parameters of anchor are obtained. The results show that the peak shear stress of the rod at the front end of anchor can be reduced effectively by setting 0.1 ° taper difference, and the bearing capacity is increased by 40.7 %, 12.1 % and 5.3 % compared with 0 ° and 0.2 ° taper difference for steel clip anchor, steel clip anchor with aluminum sleeve and adhesive layer. The slippage of anchor can be reduced effectively with the increase of preload, which improves the critical slippage load of anchor. In addition, the stress concentration of rod inside the anchor can be reduced with the addition of low modulus adhesive layer between steel clip and rod, which reduces the sensitivity of tensile performances to taper difference and delays the fatigue damage accumulation process of rod inside the anchor, the anchoring efficiency and fatigue resistance increases by 10.9 % and 61.4 % compared with steel clip anchor, respectively.

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Study on the calculation method of ice load of icebreaker in straight line state 25

Study on the calculation method of ice load of icebreaker in...

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25th International Conference on Port and Ocean Engineering under Arctic Conditions, POAC 2019

作者： Li, Liang Wang, Wei Ma, Haichong Meng, Xiangbin Han, Guangchun Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

Ice action is the primary factor that affecting the navigation of icebreaker in the ice area. The ice-breaking load also directly impacts on the construction and design of the icebreaker. Therefore, reasonable calculation of ice-breaking load has become the most important issue at present. Focusing on ice cover, this paper presented a theoretical model for calculating the ice-breaking resistance of the icebreaker. The presented model is based on the combination of semi-infinite beam and infinite beam along and perpendicular to the moving direction of the icebreaker on elastic foundation, respectively. The influence factors such as buoyancy and ice failure criterion are considered in this model. Then, authors compared the theoretical calculation formula with the existing empirical formula and theoretical formula to verify the feasibility of the presented calculation model in this paper. This model can provide theoretical reference for the design and construction of polar region icebreakers. © 2019, Lulea University of Technology. All rights reserved.

关键词： Icebreakers

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大型液化天然气储罐在冲击荷载下的动力响应数值研究（英文）

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2019年第11期20卷 823-837页

作者： Chen YAN Xi-mei ZHAI Yong-hui WANG Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of TechnologyHarbin 150090China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbin 150090China

目的:研究冲击荷载各参数对于液化天然气(LNG)储罐的动力响应结果,定义LNG储罐受到冲击荷载时的破坏模式,并分析不同破坏模式下的破坏机理,为工程防御冲击荷载提供有效的理论研究基础。创新点:1.建立精细化的LNG储罐有限元模型;2.定义LN... 详细信息

目的:研究冲击荷载各参数对于液化天然气(LNG)储罐的动力响应结果,定义LNG储罐受到冲击荷载时的破坏模式,并分析不同破坏模式下的破坏机理,为工程防御冲击荷载提供有效的理论研究基础。创新点:1.建立精细化的LNG储罐有限元模型;2.定义LNG储罐在冲击荷载下的破坏模式并揭示其破坏机理;3.提出损伤因子Df可区分三种冲击破坏模式。方法:1.通过有限元模拟,进行冲击荷载的参数分析,得到不同冲击荷载对于LNG储罐的动力响应(图6和7);2.根据数值模拟结果,定义LNG储罐受到冲击荷载时的破坏模式(图8),并分析其破坏机理(图10和11);3.通过经验公式验算LNG储罐抵御冲击荷载的可靠性。结论:1. LNG储罐薄弱部位为外罐和环梁及底板的连接部位;2. LNG储罐受到冲击荷载的破坏模式分为局部变形、混凝土剥落和穿透三种;本研究得到了各种破坏模式下的破坏机理,并定义了损伤因子Df来区分三种破坏模式;3.通过经验公式验算,LNG储罐可以抵御英国规范建议的冲击荷载和法兰的冲击;DOE-standard公式计算结果最为保守。

关键词： LNG储罐冲击动力响应数值模拟破坏机理

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