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26th Australasian Conference on the Mechanics of structures and Materials, ACMSM 2023

作者： Li, Fengze Zhi, Xudong Zhu, Enchun Wang, Duozhi Zhang, Rong School of Civil Engineering Harbin Institute of Technology Harbin China Key Lab of Structures Dynamic Behaviour and Control of the Ministry of Education Harbin Institute of Technology Harbin China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin China Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering Mechanics China Earthquake Administration Harbin China Key Laboratory of Earthquake Disaster Mitigation Ministry of Emergency Management Harbin China

ISBN: (纸本)9789819733965

The large-span spatial hub structure is an important urban lifeline project with complex structure form and many types of internal non-structural components. As one of the main non-structural components, the safety of the piping system is important to ensure the normal use of the overall function of the large span hub structure. Once damage occurs to the piping system under the action of earthquake, it will affect the traffic operation and urban rescue, resulting in incalculable casualties and property damage. To assess the impact of diverse connection locations on the piping system’s response, this study investigates acceleration and response amplification factors at various positions within the reticulated shell structure. Through this analysis, we underscore the critical need to consider the spatial coupling effect for the piping system within the reticulated shell structure. In this study, the seismic response and damage modes of the internal piping system in a prevalent type of reticulated shell structures are investigated. This is achieved by establishing a coupled finite element model of the reticulated shell structure and the piping system. Three distinct damage modes of the piping system and their corresponding computational signs are identified, facilitating the creation of fragility curves for the piping system. The results highlight significant variation in the damage degree of the piping system at different locations. Additionally, past studies have shown a notable probability of damage to piping systems, even under very slight ground shaking, emphasizing the necessity for careful consideration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Shells (structures)

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Multi-Level Fusion Method Based on Improved Stacked Hourglass Network for Edge Detection

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SSRN 2024年

作者： Li, Shuang Chen, Yicheng Li, Changqing Feng, Chang Zhai, Changhai 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 The Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

Edge detection is one of the most challenging tasks in computer vision due to the complexity of various objects and backgrounds. Previous efforts in edge detection often faced significant difficulties, resulting in many fine details being overlooked and coarser edges being detected. This study adopts a stacked hourglass network as the backbone of the architecture, and extracts edge information at different receptive fields using convolution kernels of varying sizes. In the data fusion segment, the CBAM (Convolutional Block Attention Module) attention mechanism is employed to integrate five distinct types of captured edge information. The method was trained on the BIPED (Barcelona Images for Perceptual Edge Detection) dataset, and the results show that it achieved favorable outcomes on the ODS, OIS, and AP metrics in the test sets. Furthermore, the method also demonstrated great predictive performance on UDED (Unified Dataset for Edge Detection) dataset, delivering clearer boundary features. © 2024, The Authors. All rights reserved.

关键词： Data fusion

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Energy Harvesting of Novel Smart Concrete Based on Nanotechnology: Experimental and Numerical

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SSRN 2024年

作者： Zhang, Mingming Zhu, Lihua Gao, Shan Yuan, Hanquan Liu, Tong School of Civil Engineering Xi’an University of Architecture and Technology Shaanxi Xi’an710055 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China

This paper focuses on energy harvesting and smart controls in concrete structures using both experimental and theoretical approaches. The growing demand for sustainable energy solutions has led to innovations in materials like concrete, which offer energy conversion and efficient control possibilities. This study introduces a novel concept for concrete structures using piezoelectric nanoparticles, specifically zinc oxide nanoparticles (ZnO), offering three key benefits: (a) enhanced strength, (b) energy harvesting and storage, and (c) smart control. The experimental phase involves modifying concrete structures with energy harvesting technologies. Dispersion of nanoparticles in water is a key challenge, addressed through magnetic stirring, ultrasonic homogenization, and mechanical stirring. Multiple concrete specimens with nanoparticles were produced, followed by tests including compressive strength assessments, energy harvesting under mechanical loads, and intelligent control of concrete deflection through voltage application. On the theoretical front, modeling and numerical methods predict the behavior of energy harvesting concrete structures. The precise five-parameter theory, accounting for Poisson's effect, is employed for modeling. After deriving governing equations, differential quadrature numerical technique computes deflection and output voltage. Comparisons and validations are made between experimental and simulation results. The experiments reveal that the optimal ZnO nanoparticle content is 0.9%, leading to significant compressive strength improvements of 22.14%, 27.31%, and 34.28% for 7, 14, and 28-day samples, respectively, compared to controls. Beyond this content, compressive strength diminishes. Moreover, 0.9% ZnO-concrete produces an output voltage of 32 volts, well-justified technically and economically. Additionally, +50V voltage induces 9.2mm deformation, while -50V voltage yields 5.8mm, showcasing a substantial 63% deformation alteration potenti

关键词： Energy harvesting

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Probabilistic Prediction of Post-Earthquake Rubble Risk Distribution Range for Bottom Frame structures

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SSRN 2024年

作者： He, Yuhan Zhai, Changhai Wen, Weiping Key Lab of Structures Dynamic Behavior and Control The Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disaster The Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China

The rubble generated by the massive collapse of street-front buildings after an earthquake can seriously block roads, affecting the connectivity of the road network in a city and causing serious damage. In order to achieve the needs of urban planning, buildings facing the street are mainly bottom frame structures that cater for both commercial and residential use. However, once an earthquake occurs, the poor seismic performance of the bottom frame structures is quite prone to collapse, which produces a large amount of rubble and brings a great burden to the post-earthquake traffic system. In this paper, based on finite element models for various cases, considering the uncertainty of seismic intensity and height of the bottom frame structure, and combining with the fragility of structural collapse, we propose a method to predict the risk range of the bottom frame structure rubble to quantify the capacity of the transportation system after the earthquake, which can better assess the seismic resilience of the transportation system in the urban area. © 2024, The Authors. All rights reserved.

关键词： Earthquakes

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An active learning method based on Monte Carlo dropout neural network for high-dimensional reliability analysis

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Reliability Engineering and System Safety 2025年 262卷

作者： Sun, Huabin Bao, Yuequan 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 Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China School of Civil Engineering Harbin Institute of Technology Harbin150090 China

In structural reliability analysis, the AK-MCS method, which combines Kriging and Monte Carlo Simulation, is well-acknowledged for its effectiveness but struggles with accuracy and efficiency in high-dimensional and nonlinear scenarios. To leverage the advantages and circumvent the limitations of AK-MCS, an active learning method based on the Monte Carlo dropout (MC-dropout) neural network is proposed. The MC-dropout neural network-based surrogate model provides both predictive mean and standard deviation in complex scenarios with a limited number of samples. By identifying candidate samples and utilizing a learning function that considers predictive mean and standard deviation, the method selects new samples close to the limit state surface with significant uncertainties to update the surrogate model. An ensemble of MC-dropout neural networks is then used to obtain a reliable failure probability. Two convergence criteria are introduced to determine the termination of the active learning process. Two numerical examples, a cantilever beam and an actual cable-stayed bridge are used to demonstrate the efficacy of the proposed method. The results show that the MC-dropout neural network-based surrogate model exhibits adaptivity and flexibility in handling high-dimensional and nonlinear scenarios and the proposed method achieves a relatively accurate failure probability with a limited number of samples. © 2025 Elsevier Ltd

关键词： Failure rate

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Structural Health Diagnosis Under Limited Supervision

Structural Health Diagnosis Under Limited Supervision

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IABSE Congress Nanjing 2022 - Bridges and structures: Connection, Integration and Harmonisation

作者： Xu, Yang Li, Hui Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin China Key Lab of Structures Dynamics Behavior and Control of the Ministry of Education Harbin China Harbin Institute of Technology Harbin China

ISBN: (纸本)9783857481840

Structural health diagnosis has been investigated following a data-driven machine learning paradigm. However, the model accuracy and generalization capability highly rely on the quality and diversity of datasets. This study established a framework for structural health diagnosis under limited supervision. Firstly, an image augmentation algorithm of random elastic deformation, a novel neural network with self-attention and subnet modules, and a task-aware few-shot meta learning method were proposed for vision-based damage recognition. Secondly, deep learning networks were established to model intra- and inter-class temporal and probabilistic correlations of different quasi-static responses for condition assessment. Finally, a two-stage convergence criterion merging with the subset simulation and Kriging surrogate model was designed for reliability evaluation. Real-world applications on large-scale infrastructure demonstrated the effectiveness. © IABSE Congress Nanjing 2022 - Bridges and structures: Connection, Integration and Harmonisation, Report. All rights reserved.

关键词： Computer vision

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A machine learning based solver for pressure Poisson equations

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Theoretical & Applied Mechanics Letters 2022年第5期12卷 315-321页

作者： Ruilin Chen Xiaowei Jin Hui Li Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of TechnologyHarbin 150090China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of TechnologyHarbin 150090China Guangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications Harbin Institute of Technology(Shenzhen)Shenzhen 518055China

When using the projection method(or fractional step method)to solve the incompressible Navier-Stokes equations,the projection step involves solving a large-scale pressure Poisson equation(PPE),which is computationally expensive and *** this study,a machine learning based method is proposed to solve the large-scale *** machine learning(ML)-block is used to completely or partially(if not sufficiently accurate)replace the traditional PPE iterative solver thus accelerating the solution of the incompressible Navier-Stokes *** ML-block is designed as a multi-scale graph neural network(GNN)framework,in which the original high-resolution graph corresponds to the discrete grids of the solution domain,graphs with the same resolution are connected by graph convolution operation,and graphs with different resolutions are connected by down/up prolongation *** well trained MLblock will act as a general-purpose PPE solver for a certain kind of flow *** proposed method is verified via solving two-dimensional Kolmogorov flows(Re=1000 and Re=5000)with different source *** the premise of achieving a specified high precision(ML-block partially replaces the traditional iterative solver),the ML-block provides a better initial iteration value for the traditional iterative solver,which greatly reduces the number of iterations of the traditional iterative solver and speeds up the solution of the *** experiments show that the ML-block has great advantages in accelerating the solving of the Navier-Stokes equations while ensuring high accuracy.

关键词： Pressure Poisson equation Machine learning Projection method Multi-scale GNN

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Development and Application of an Automated On-Site Measuring Robot for Post-Construction Quality control

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SSRN 2024年

作者： Wu, Hangzi Yang, Yan China Construction Eighth Engineering Division Co. Ltd. Shanghai200112 China Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Harbin Institute of Technology Harbin150090 China

Traditional manual methods for on-site quality measurement are often inefficient. Existing robots, typically combining a robot dog with 3D laser scanners, encounter challenges like significant storage requirements, dependence on specialized post-processing software, and high costs. Robots with multiple sensors may face limitations in handling diverse measurement items. Therefore, this paper produces a cost-effective and fully automated on-site measuring robot. In comparison to commercial 3D laser scanners, the hardware system's cost is reduced by 30%, and the data storage space sees a 90% reduction by retaining effective point cloud data during the processing of data. The robot is proficient in measuring dimensions, wall evenness, alignments, floor height, and internal and external corner *** experiments confirm the reliability of the measured data, displaying minimal discrepancies compared to manual measurements. In practical applications, the robot demonstrates a 40% efficiency improvement over manual measurements, resulting in a minimum 50% reduction in labor costs. © 2024, The Authors. All rights reserved.

关键词： Robots

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STUDY ON THE RESPONSE OF PRESTRESSED REINFORCED CONCRETE SlabS WITH HIGH REINFORCEMENT RATIO UNDER LOW SPEED IMPACT 29

STUDY ON THE RESPONSE OF PRESTRESSED REINFORCED CONCRETE SLA...

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2022 29th International Conference on Nuclear Engineering, ICONE 2022

作者： Mengyan, Song Di, Jiang Changkai, Li Chaoqi, Zhang Xudong, Zhi China Nuclear Power Engineering Co. Ltd. Beijing China Harbin Institute of Technology Key Lab of Structures Dynamic Behaviour and Control The Ministry of Education Harbin China

ISBN: (纸本)9780791886397

Since the 9.11 incident, the impact of large commercial airliners on nuclear power plants and other important national facilities has attracted worldwide attention. The safety of flying objects hitting nuclear containment has become one of the important research topics in the field of nuclear power generation. In this paper, the impact resistance of non-prestressed and prestressed concrete slabs is studied through detailed experiments and numerical studies. By non-bonding rear sheeting, prestress of about 10MPa is applied to concrete slabs measuring 1400mm×600mm, which are then hit by hemispherical steel hammers (590kg) at heights of 2m and 4m above the center of the span. The impact force, displacement, and the reinforced concrete slab and the prestressed concrete slab are compared. In LS-DYNA finite element software, the CSCM concrete structure model is used to study the numerical values of the experiments carried out. It has been found that with the increase of impact energy, the deformation produced by reinforced concrete slabs increases and is not recoverable. On the other hand, after applying presession, the impact force of prestressed concrete slabs was increased by 53.8% and displacement was reduced by 45% due to the increase of the stiffness of the plate. The maximum reproduction deviation of the impact force and displacement values is 17% and 14%, respectively. The research results will be applied to the structural dynamic impact protection design of nuclear power plant containment. Copyright © 2022 by ASME.

关键词： Reinforced concrete

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Sublimation of composite ice and its influence on performance of ice shells

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International Journal of Space structures 2021年第1期36卷 67-77页

作者： Wu, Yue Huang, Junkai Chen, Jiafeng 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 of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin China China Academy of Building Research Co. Ltd Beijing China

The long-span ice composite shell structure is a new type of ice and snow structure developed in recent years. The engineering practice of ice composite shell shows that sublimation is one of the important reasons for its damage and even collapse. In this paper, we firstly supplemented the existing H-K equation and obtained the revised ice sublimation equation through indoor evaporative plate experiment considering the influence of admixtures and wind speed. Afterwards, combining the simulations of solar radiation and CFD, the numerical simulation of sublimation distribution on the surface of were realized by programming in Grasshopper platform. During sublimation, the thickness of the ice composite shell decreases by 0.38 mm every 10 days and the sublimation rate on the sunny side was 1.7 times that on the shady side. Finally, the static performance and stability of the sublimated ice composite spherical shell were analyzed. After 70 days of sublimation, the thickness of the ice composite shell structure becomes thinner and uneven, which leads its sensitivity to external load increases. © The Author(s) 2021.

关键词： Ice

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