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Progressive collapse mechanism of three-dimensional self-centering precast concrete frame with infill walls and slabs

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Engineering Failure Analysis 2025年

作者： Haoran Wang Shuang Li Feng Lin School of Civil Engineering Shenyang Jianzhu University Shenyang 110168 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education 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 Department of Structural Engineering Tongji University Shanghai 200092 China Key Laboratory of Performance Evolution and Control for Engineering Structures of Ministry of Education Shanghai 200092 China

In this study, the effects of infill walls and slabs on the progressive collapse resistance of three-dimension (3D) self-centering precast concrete (PC) frame under corner column failure, middle column failure and internal column failure scenarios were numerically investigated. Based on the verified numerical modeling methods, the failure modes and collapse mechanism of twelve 3D self-centering PC frames were analyzed. The results indicated that the number of spans connected to the failure column will directly influence the progressive collapse resisting-capacity of 3D self-centering PC frames. Compared with slabs, infill walls improved the progressive collapse resistance of 3D self-centering PC frame more obviously. For failure span with small aspect ratio, the presence of infill walls and slabs did not alter the failure mode of the structure. With the aspect ratio of the failure span increased, for 3D self-centering infilled PC frame, the stronger constraint of surrounding frame enhanced the overall stiffness of the infill walls, resulting in a change in the failure mode of the frame. When the slab was arranged, since the larger stiffness of the slabs improved the shear capacity of the beam section, the main concrete damage were still concentrated at the beam ends. A simplified calculation method considering the resistance contribution of structural and non-structural members was proposed to predict the vertical resistance of 3D self-centering PC frame structures under different failure column scenarios in the compressive arch action (CAA) stage.

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Interfacial Interaction of CFRP Reinforced Steel Beam structures

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Journal of Architectural Environment & Structural Engineering Research 2020年第4期3卷 2-8页

作者： Huaping Wang Hengyang Li Siyuan Feng Tao Song School of Civil Engineering and Mechanics Lanzhou UniversityLanzhouGansu730000China Key Lab of Structures Dynamic Behavior and Control(Harbin Institute of Technology) Ministry of EducationHarbinHeilongjiang150090China

Due to the increase of service life,the phenomenon of performance degradation of bridge structures becomes more and more *** is important to strengthen the bridge structures so as to restore the resistance level and extend the normal service *** fiber reinforced polymer(CFRP)materials are thus used for the assembly reinforcement of bridges for the advantages of high strength,light weight,corrosion resistance and long-term stability of physical and chemical properties,*** view of this,based on the previous theoretical study and the established formula of the interfacial shear stress of CFRP reinforced steel beam and the normal stress of CFRP plate,this paper discusses the sensitive parameters that affect the interfacial interaction of CFRP strengthened beam *** the analysis,the priority design indicators and suggestions are accordingly given for the design of reinforced beam ***’s modulus of CFRP composite and shear modulus of the adhesive have the greatest influence on the interfacial interaction,which should be carefully *** is suggested that CFRP material with Ec close to 300 GPa and thickness no less than 3 mm,and adhesive material with Ga less than 5 GPa and 3-mm thickness can be adopted in CFRP reinforced steel *** conclusions of this paper can provide guidance for the interfacial damage control of CFRP reinforced steel beam structures.

关键词： CFRP reinforced steel beam Interfacial interaction Shear stress Parametric analysis Design instruction

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Essential Stressing State Features of Laterally Loaded Masonry Wall Panels Revealed from Experimental Displacements

Research Square

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Research Square 2021年

作者： Liu, Bai Li, Rui Zhang, Yu Zhou, Guangchun Key Lab of Structures Dynamic Behavior and Control of China Ministry of Education Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology School of Civil Engineering Harbin Institute of Technology Harbin150090 China Urban and Engineering Disaster Prevention Laboratory Institute of Engineering Mechanics China Earthquake Administration Harbin150086 China

This study reveals the essential and general working features of laterally loaded masonry (LLM) wall panels from their experimental displacements by applying structural stressing state theory. Firstly, the generalized work of force is proposed to express the stressing state mode and its characteristic parameter. Then, the Mann-Kendall criterion is applied to detect the mutation point in the curve of the characteristic parameter with the load increase. Correspondingly, it is verified that the evolution of the stressing state mode also embodies the mutation feature. The stressing state mutation feature is inherent and common as the embodiment of the natural law from quantitative change to qualitative change of a system. The stressing state mutation feature reveals the starting point of structural failure process, which could update the existing definition of structural failure load. Further, the elastoplastic branch (EPB) point is revealed referring to the updated failure load, which might be directly taken as the design load with the rational margin of safety. In a sense, this paper presents a new way to address the classic issue of structural load-bearing capacity uncertainty and to update the existing design codes of LLM wall panels. © 2021, CC BY.

关键词： Fracture mechanics

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Experimental investigation of shear behavior in precast concrete beams with steel bolted splice connections

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structures 2025年 78卷

作者： Khalil Abualtayef Wei Zhou School of Civil Engineering Harbin Institute of Technology Harbin 150090 China Key Lab of Structures Dynamic Behavior and Control Ministry of Education School of Civil Engineering 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 School of Civil Engineering Harbin Institute of Technology Harbin 150090 China

Precast concrete structures with bolted connections offer significant advantages, including shorter construction times, improved quality control, and enhanced structural performance. This study investigates the shear behavior of precast concrete beams with steel-bolted splice connections (PCBSBs), which join the discontinuity of two short concrete beam segments, under monotonic loading. Afterwards, the shear performance of PCBSB beams was experimentally and analytically investigated. Six full-scale PCBSB specimens and one control concrete beam were tested to evaluate the effects of key parameters include the shear span ratio and steel plate thickness. The test results show that the failure modes of PCBSB beams are similar to those of reinforcement concrete beams, and the crack propagations can be well controlled by the steel plate thickness. Using a steel bolted connection with a thickness of 3 mm and 5 mm increased the shear crack load by 9 % and 24 %, respectively. After the loading reached 65 % of the peak load, the deflection of steel bolted connection begins to increase more than the shear load deflection till peak load. For beams with long shear span ratio, increase of steel plate thickness led to increase the stiffness, and peak load. Higher a/d ratios increase deflection and shift failure modes from ductile (shear-compression) to brittle (shear-tension). Finally, the experimental shear capacities of the PCBSBs exceeded the predictions of the GB, ACI, EN, and CSA standards for beams with a/d ratios of 1.5 and 2.0. However, discrepancies were observed for beams with a/d of 3.0, where flexural behavior becomes more dominant. Based on these findings, a preliminary design recommendation was proposed. Further studies were recommended to investigate the performance of beams with shorter a/d ratios and varying dimensions to optimize connection efficiency.

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Big-data driven building retrofitting: An integrated support vector machines and fuzzy c-means clustering method

Big-data driven building retrofitting: An integrated support...

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World Sustainable Built Environment - Beyond 2020, WSBE 2020

作者： Lu, Weizhuo Feng, Kailun Department of Civil Environmental and Natural Resources Engineering Luleå University of Technology Sweden Department of Construction Management Harbin Institute of Technology Harbin150009 China 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 Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

It has become a mainstream to use physical models to quantify expected energy savings from alternative retrofit methods and technologies. However, they are not suitable for predicting energy use of buildings when detailed and specified input parameters are unavailable. The overall purpose of the research is to support the stakeholders in taking decisions on refurbishments options when not all of physical information is available, in order to achieve the Swedish Energy Agency's measurements of near-zero energy buildings. The research will transfer big data from Swedish Energy Performance Certificates for building retrofitting. A Support Vector Machines and Fuzzy C-means clustering (SVM-FCM) integrated machine learning algorithm is used directly to extract the case-specific knowledge from EPC big data regarding building characteristics and energy saving of retrofit measures. It enables to prioritize retrofit measures and compute their expected energy savings for buildings. This proposed data driven method is an attempt of taking advantage of big data for practical building retrofit selection. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Support vector machines

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Three-Dimensional Reconstruction and Monitoring of Large-Scale structures via Real-Time Multi-vision System 11th

Three-Dimensional Reconstruction and Monitoring of Large-Sca...

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11th International Symposium on Intelligence Computation and Applications, ISICA 2019

作者： Tang, Yunchao Chen, Mingyou Wu, Xiangguo Huang, Kuangyu Wu, Fengyun Zou, Xiangjun He, Yuxin College of Urban and Rural Construction Zhongkai University of Agriculture and Engineering Guangzhou510225 China Key Laboratory of Key Technology on Agricultural Machine and Equipment College of Engineering South China Agricultural University Guangzhou510642 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education and School of Civil Engineering Harbin Institute of Technology Harbin150001 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

ISBN: (纸本)9789811555763

A four-ocular vision system is proposed for the three-dimensional (3D) reconstruction of large-scale concrete-filled steel tube (CFST) materials under complex testing conditions. These measurements are vitally important for evaluating the seismic performance and 3D deformation of large-scale specimens. A four-ocular vision system is constructed to sample the large-scale CFST, then point cloud acquisition, filtering, and stitching algorithms are applied to obtain 3D point cloud of the specimen surface. Novel point cloud correction algorithms based on geometric features and deep learning are proposed to correct the coordinates of the stitched point cloud. The proposed algorithms center on the stitching error of the multi-view point cloud and the geometric and spatial characteristics of the targets for error compensation, which makes them highly adaptive and efficient. A high-accuracy multi-view 3D model for the purposes of real-time complex surface monitoring can be obtained via this method. Performance indicators of the two algorithms were evaluated on actual tasks. The cross-section diameters at specific heights in the reconstructed models were calculated and compared against laser range finder data to test the performance of the proposed method. A visual tracking test on a CFST under cyclic loading shows that the reconstructed output well reflects the complex 3D surface after point cloud correction and meets the requirements for dynamic monitoring. The proposed method is applicable to complex environments featuring dynamic movement, mechanical vibration, and continuously changing features. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Vibrations (mechanical)

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

arXiv

引用

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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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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Machine-learning-based methods for output-only structural modal identification

arXiv

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arXiv 2020年

作者： Bao, Yuequan Liu, Dawei Tang, Zhiyi Li, Hui Key Lab of Structures Dynamic Behavior Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Intelligent Disaster Mitigation Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

In this study, we propose a machine-learning-based approach to identify the modal parameters of the output-only data for structural health monitoring (SHM) that makes full use of the characteristic of independence of modal responses and the principle of machine learning. By taking advantage of the independence feature of each mode, we use the principle of unsupervised learning, making the training process of the deep neural network become the process of modal separation. A self-coding deep neural network is designed to identify the structural modal parameters from the vibration data of structures. The mixture signals, that is, the structural response data, are used as the input of the neural network. Then we use a complex cost function to restrict the training process of the neural network, making the output of the third layer the modal responses we want, and the weights of the last two layers are mode shapes. The deep neural network is essentially a nonlinear objective function optimization problem. A novel loss function is proposed to constrain the independent feature with consideration of uncorrelation and non-Gaussianity to restrict the designed neural network to obtain the structural modal parameters. A numerical example of a simple structure and an example of actual SHM data from a cable-stayed bridge are presented to illustrate the modal parameter identification ability of the proposed approach. The results show the approach's good capability in blindly extracting modal information from system responses. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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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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