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Modified natural seawater sea-sand concrete: Linking microstructure to mechanical performance SCIE
期刊论文 | 2024 , 98 | JOURNAL OF BUILDING ENGINEERING
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Abstract :

The rich availability of seawater and sea sand offers an alternative material resource for concrete production. However, the mechanical performance and durability of such concrete might not satisfy the construction requirements. Due to this, this study has first investigated the effects of varying dosages of ultrafine metakaolin (UMK) and nano-TiO2 (NT) as the supplementary cementitious materials on the mechanical properties of concrete produced using natural, untreated seawater and sea sand. The workability, compressive strengths, elastic moduli and flexural strengths have been explored for the concrete using the unary (ordinary Portland cement, OPC), binary (OPC and UMK) and ternary (OPC, UMK and NT) mixtures. The experimental results indicated the significant enhancement in the mechanical properties of the modified concrete. The cube compressive strength, axial compressive strength, the splitting tensile strength, the elastic modulus and the flexural strength have increased by 22.29 %, 22.82 %, 9.76 %, 16.02 % and 44.44 %, respectively. After that, the microstructural aspects expressed by SEM and XRD were also investigated for revealing the contributions of the NT and the UMK to the macroscopic mechanical performance of the seawater sea-sand concrete. The SEM analysis revealed a reduction in porosity and improved interfacial zones in the concrete containing the UMK and NT. The XRD analysis confirmed that the addition of UMK and NT promoted the calcium silicate hydrate (C-S-H) gel formation, mitigating the alkali-aggregate reactions. It was found that the addition of UMK and NT could improve the microstructure of the seawater sea-sand concrete, thereby enhancing the mechanical properties. Subsequently, the corrosion test conducted in a natural marine tidal environment revealed that, after the 360 tidal corrosion cycles, only the ternary mixed concrete maintained its structural integrity without the strength degradation, highlighting its superior durability in a marine condition. Lastly, analysis of variance was also performed to statistically evaluate the effects of UMK and NT as the single or combined mixtures on the modified concrete's performance. UMK has a significant impact on the short-term mechanical performance, while NT showed long-term contribution to the performance under the corrosive environment.

Keyword :

Mechanical properties Mechanical properties Microstructure Microstructure Nano-TiO2 Nano-TiO2 Seawater sea-sand concrete Seawater sea-sand concrete Ultrafine metakaolin Ultrafine metakaolin

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GB/T 7714 Luo, Qing-Hai , Fang, Sheng-En . Modified natural seawater sea-sand concrete: Linking microstructure to mechanical performance [J]. | JOURNAL OF BUILDING ENGINEERING , 2024 , 98 .
MLA Luo, Qing-Hai 等. "Modified natural seawater sea-sand concrete: Linking microstructure to mechanical performance" . | JOURNAL OF BUILDING ENGINEERING 98 (2024) .
APA Luo, Qing-Hai , Fang, Sheng-En . Modified natural seawater sea-sand concrete: Linking microstructure to mechanical performance . | JOURNAL OF BUILDING ENGINEERING , 2024 , 98 .
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Modified natural seawater sea-sand concrete: Linking microstructure to mechanical performance Scopus
期刊论文 | 2024 , 98 | Journal of Building Engineering
Modified natural seawater sea-sand concrete: Linking microstructure to mechanical performance EI
期刊论文 | 2024 , 98 | Journal of Building Engineering
Temperature coupling effects and cable force prediction of cable-stayed bridge with steel arch tower; [钢 拱 塔 斜 拉 桥 的 温 度 耦 合 效 应 和 索 力 预 测] Scopus CSCD PKU
期刊论文 | 2024 , 46 (2) , 146-153 | Journal of Civil and Environmental Engineering
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Abstract :

The mechanical system of a cable-stayed bridge with a steel arch tower is different from that of a traditional cable-stayed bridge. In order to investigate the effects of ambient temperature variations on the main components of a cable-stayed bridge with a tower in an abnormal shape, an actual cable-stayed bridge with a steel arch tower has been used as the engineering prototype. The online temperature data of the onsite environment and the bridge components were first collected and used to analyze the time-varying effects of the environmental temperature on the cable forces, the tower obliquity and the stress of the main girder. Subsequently, the analysis was focused on the cable forces. The temperature variation simulation was applied to the finite element model of the bridge, and the temperature coupling effects caused by the temperature difference between different bridge components on the cable forces were analyzed. Lastly, the temperatures of the environment, the tower and the main girder were used as the inputs, while the cable forces were defined as the outputs of a long short-term memory neural network. The network was trained using the actual measurement samples of the temperatures and the cable forces. Data compression and feature extraction were realized during the training process. Then, the prediction model for the cable forces was established, and new temperature monitoring data were input into the network model for predicting the cable forces. The analysis results show that the temperature variations of the main girder and the steel arch tower follow a periodic rule and lag behind the ambient temperature. The strain variation tendency of the main girder accords well with the ambient temperature, but the latter has a time lag. The influence of the ambient temperature variation on the obliquity of the arch tower is very small without any periodic rule. A linear negative correlation is found between the cable forces and the ambient temperature. The temperature coupling effect caused by the temperature difference between different bridge components should be considered in the analysis. The long and short-term memory neural network is suitable for the data with timing characteristics. The cable force prediction model based on the neural network has high prediction accuracy, and it can be used for the real-time prediction of this bridge. © 2024 Chongqing University. All rights reserved.

Keyword :

bridge engineering bridge engineering cable force prediction cable force prediction cable-stayed bridge with a steel arch tower cable-stayed bridge with a steel arch tower long short-term memory neural network long short-term memory neural network temperature coupling effects temperature coupling effects

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GB/T 7714 Fang, S. , Qin, J. , Zhang, W. et al. Temperature coupling effects and cable force prediction of cable-stayed bridge with steel arch tower; [钢 拱 塔 斜 拉 桥 的 温 度 耦 合 效 应 和 索 力 预 测] [J]. | Journal of Civil and Environmental Engineering , 2024 , 46 (2) : 146-153 .
MLA Fang, S. et al. "Temperature coupling effects and cable force prediction of cable-stayed bridge with steel arch tower; [钢 拱 塔 斜 拉 桥 的 温 度 耦 合 效 应 和 索 力 预 测]" . | Journal of Civil and Environmental Engineering 46 . 2 (2024) : 146-153 .
APA Fang, S. , Qin, J. , Zhang, W. , Jiang, X. . Temperature coupling effects and cable force prediction of cable-stayed bridge with steel arch tower; [钢 拱 塔 斜 拉 桥 的 温 度 耦 合 效 应 和 索 力 预 测] . | Journal of Civil and Environmental Engineering , 2024 , 46 (2) , 146-153 .
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结合深度信念记忆网络的结构损伤识别
期刊论文 | 2024 , 37 (11) , 1917-1924 | 振动工程学报
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Abstract :

从结构响应信号中挖掘敏感损伤特征是基于模式分类的损伤识别方法的关键.为此,将深度信念网络和长短期记忆网络进行混合组网,通过混合学习机制有机结合了两种网络在高阶抽象特征提取和考虑数据序列相关性上的优点.将响应信号传递比值输入深度信念网络,实现初步数据压缩和特征提取,以减少响应中的冗余信息;将特征序列依次输入长短期记忆网络,以考虑响应间的相关性并获取敏感损伤特征;利用Softmax分类层对长短期记忆网络输出的特征进行分类,实现对不同结构损伤模式的识别.三维试验钢框架的损伤识别结果表明:混合学习机制能更好地训练网络参数,整体微调后更有利于后续的损伤特征分类;混合组网方式在包含数值或实测噪声的情况下仍可以有效进行数据压缩、特征提取和分类,准确识别了试验框架的多种损伤工况.

Keyword :

损伤识别 损伤识别 框架结构 框架结构 深度信念网络 深度信念网络 混合学习机制 混合学习机制 长短期记忆网络 长短期记忆网络

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GB/T 7714 方圣恩 , 刘洋 . 结合深度信念记忆网络的结构损伤识别 [J]. | 振动工程学报 , 2024 , 37 (11) : 1917-1924 .
MLA 方圣恩 et al. "结合深度信念记忆网络的结构损伤识别" . | 振动工程学报 37 . 11 (2024) : 1917-1924 .
APA 方圣恩 , 刘洋 . 结合深度信念记忆网络的结构损伤识别 . | 振动工程学报 , 2024 , 37 (11) , 1917-1924 .
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A physics-informed auto-encoder based cable force identification framework for long-span bridges SCIE
期刊论文 | 2024 , 60 | STRUCTURES
WoS CC Cited Count: 4
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Abstract :

Cable force identification is crucial for ensuring the safety and operational performance of in-service long-span bridge structures. Besides the commonly-used frequency measurements for calculating cable forces using frequency-cable force relationship formulas, more efficient and straightforward identification could be achieved by directly utilizing frequency response functions (FRFs). This study presents a novel approach that employs neural networks to model the relationship between the FRFs and cable forces, resulting in a more streamlined method for identifying cable forces on long-span bridges. Firstly, the working mechanism of an auto-encoder is merged with the unique characteristics of the FRFs, giving the cross signature assurance criterion. This criterion is then integrated into the loss function as a constraint to account for the poor interpretability of pure data-driven methodology in solving engineering problems, leading to a grey-box data-driven paradigm. Following this paradigm, a physics-informed auto-encoder (PIAE) network is employed to reduce the dimensionality of the FRF data during extracting key features. The reduced FRF data are paired with the cable forces to form training samples. The PIAE network is then trained directly on these samples for the purpose of cable force identification. Finally, the validation of the proposed method was conducted on the actual monitoring data from a cable-stayed bridge and a concrete-filled steel tubular arch bridge. Results indicate that the proposed method achieves not only high prediction accuracy, but also a good fit between the predicted and actual developmental trends of cable forces, and is well-suited for the different types of bridges.

Keyword :

Bridge structures Bridge structures Cable force identification Cable force identification Cross signature assurance criterion Cross signature assurance criterion Grey running mechanism Grey running mechanism Physics -informed auto -encoder Physics -informed auto -encoder

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GB/T 7714 Guo, Xin-Yu , Fang, Sheng-En . A physics-informed auto-encoder based cable force identification framework for long-span bridges [J]. | STRUCTURES , 2024 , 60 .
MLA Guo, Xin-Yu et al. "A physics-informed auto-encoder based cable force identification framework for long-span bridges" . | STRUCTURES 60 (2024) .
APA Guo, Xin-Yu , Fang, Sheng-En . A physics-informed auto-encoder based cable force identification framework for long-span bridges . | STRUCTURES , 2024 , 60 .
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A physics-informed auto-encoder based cable force identification framework for long-span bridges EI
期刊论文 | 2024 , 60 | Structures
A physics-informed auto-encoder based cable force identification framework for long-span bridges Scopus
期刊论文 | 2024 , 60 | Structures
Structural damage identification incorporating transmissibility functions with stacked auto-encoders; [结 合 传 递 比 与 栈 式 自 编 码 器 的 结 构 损 伤 识 别] Scopus
期刊论文 | 2024 , 37 (9) , 1460-1467 | Journal of Vibration Engineering
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Abstract :

The key to damage pattern recognition lies in digging and classifying damage features from the response data of civil structures. To this end,a stack auto-encoder network with several auto-encoder hidden layers and a Softmax classification layer is built for analyzing frame structures. A hybrid learning mechanism is adopted to combining unsupervised and supervised learning strategies. Finite element analysis is used to generate the transmissibility function samples corresponding to different scenarios of a frame structure. The transmissibility samples are then divided into training,validation,and test sets. The parameters of the auto-encoder hidden layers,such as the weights and bias,are determined by a pre-training strategy in order to avoid the phenomenon of network over fitting. A fine-tuning step is employed to adjust the pre-trained network parameters,and the network hyper parameters are further adjusted based on the validation set. The measured transmissibility data are input into the network to evaluate the damage of the frame structure. The analysis results show that the proposed method can effectively extract and classify the damage features. Both the single and double damage scenarios at the frame joints were identified with higher accuracy and better anti-noise ability than the traditional shallow neural network. © 2024 Nanjing University of Aeronautics an Astronautics. All rights reserved.

Keyword :

damage identification damage identification frame structure frame structure hybrid learning mechanism hybrid learning mechanism stacked auto-encoder stacked auto-encoder transmissibility functions transmissibility functions

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GB/T 7714 Fang, S.-E. , Liu, Y. , Zhang, X.-H. . Structural damage identification incorporating transmissibility functions with stacked auto-encoders; [结 合 传 递 比 与 栈 式 自 编 码 器 的 结 构 损 伤 识 别] [J]. | Journal of Vibration Engineering , 2024 , 37 (9) : 1460-1467 .
MLA Fang, S.-E. et al. "Structural damage identification incorporating transmissibility functions with stacked auto-encoders; [结 合 传 递 比 与 栈 式 自 编 码 器 的 结 构 损 伤 识 别]" . | Journal of Vibration Engineering 37 . 9 (2024) : 1460-1467 .
APA Fang, S.-E. , Liu, Y. , Zhang, X.-H. . Structural damage identification incorporating transmissibility functions with stacked auto-encoders; [结 合 传 递 比 与 栈 式 自 编 码 器 的 结 构 损 伤 识 别] . | Journal of Vibration Engineering , 2024 , 37 (9) , 1460-1467 .
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Structural damage identification incorporating transmissibility functions with stacked auto-encoders EI
期刊论文 | 2024 , 37 (9) , 1460-1467 | Journal of Vibration Engineering
System Updating and Response Prediction of a Cable-Stayed Bridge Based on Digital Twins EI CSCD PKU
期刊论文 | 2024 , 44 (1) , 11-17 and 193 | Journal of Vibration, Measurement and Diagnosis
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Abstract :

Traditional modeling approaches are difficult to reflect the slight changes of bridge system parameters and responses. Due to this,digital twins are adopted as the high fidelity mapping models for a bridge system. Firstly,the definition of digital twins comprises three parts of a physical twin layer,a digital twin layer and an information interaction medium. The digital twin model inside the digital twin layer is the virtual mapping of the bridge physical entity,and the real-time information transmission between the two layers is achieved by the information interaction medium. Secondly,in view of practical applications,three modeling principles of structural informatization,information digitization and data modelization are proposed to realize the informatization and visualization of the bridge physical entity. Thereby,the digital twin model with high fidelity is established for the cable-stayed bridge. Lastly,the monitoring data of a back-stay cable of an actual bridge are adopted as the perceptual information,and the changed cable parameters are fed to the digital twin model for twin model updating and response prediction. The analyses results demonstrate that the proposed digital twin modeling method can effectively reflect the parameter changes of the actual bridge. Then the corresponding slight variations of the cable force,the tower top deviation and the mid-span deflection of the main girder are predicted by the twin model. © 2024 Nanjing University of Aeronautics an Astronautics. All rights reserved.

Keyword :

Cables Cables Cable stayed bridges Cable stayed bridges Data visualization Data visualization Mapping Mapping

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GB/T 7714 Fang, Shengen , Guo, Xinyu . System Updating and Response Prediction of a Cable-Stayed Bridge Based on Digital Twins [J]. | Journal of Vibration, Measurement and Diagnosis , 2024 , 44 (1) : 11-17 and 193 .
MLA Fang, Shengen et al. "System Updating and Response Prediction of a Cable-Stayed Bridge Based on Digital Twins" . | Journal of Vibration, Measurement and Diagnosis 44 . 1 (2024) : 11-17 and 193 .
APA Fang, Shengen , Guo, Xinyu . System Updating and Response Prediction of a Cable-Stayed Bridge Based on Digital Twins . | Journal of Vibration, Measurement and Diagnosis , 2024 , 44 (1) , 11-17 and 193 .
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System Updating and Response Prediction of a Cable-Stayed Bridge Based on Digital Twins; [结 合 数 字 孪 生 的 斜 拉 桥 系 统 更 新 和 响 应 预 测] Scopus CSCD PKU
期刊论文 | 2024 , 44 (1) , 11-17and193 | Journal of Vibration, Measurement and Diagnosis
结合数字孪生的斜拉桥系统更新和响应预测 CSCD PKU
期刊论文 | 2024 , 44 (01) , 11-17,193 | 振动.测试与诊断
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Abstract :

由于传统建模方法难以反馈桥梁系统参数和响应的细微变化,为此提出了以数字孪生体作为结构系统的高保真映射模型。首先,定义数字孪生体包含物理孪生层、数字孪生层和信息交互媒介3部分,数字孪生层的孪生模型是对斜拉桥物理实体的虚拟映射,通过信息交互媒介实现不同层间信息的实时传递;其次,针对具体应用提出了结构信息化、信息数据化和数据模型化3条建模准则,实现对斜拉桥物理实体的信息勾勒和可视化过程,建立高保真的斜拉桥数字孪生模型;最后,以一座实桥端锚索的监测数据为感知信息,将变化的索参数实时反馈给孪生模型,实现模型更新和响应预测。研究结果表明,所提出的数字孪生建模方法能及时反馈实桥的参数变化,并预测由此造成的索力、塔顶偏位及主梁跨中挠度的细微改变。

Keyword :

信息交互媒介 信息交互媒介 孪生模型更新 孪生模型更新 建模框架和准则 建模框架和准则 数字孪生体 数字孪生体 斜拉桥 斜拉桥

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GB/T 7714 方圣恩 , 郭新宇 . 结合数字孪生的斜拉桥系统更新和响应预测 [J]. | 振动.测试与诊断 , 2024 , 44 (01) : 11-17,193 .
MLA 方圣恩 et al. "结合数字孪生的斜拉桥系统更新和响应预测" . | 振动.测试与诊断 44 . 01 (2024) : 11-17,193 .
APA 方圣恩 , 郭新宇 . 结合数字孪生的斜拉桥系统更新和响应预测 . | 振动.测试与诊断 , 2024 , 44 (01) , 11-17,193 .
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结合数字孪生的斜拉桥系统更新和响应预测 CSCD PKU
期刊论文 | 2024 , 44 (1) , 11-17 | 振动、测试与诊断
Hybrid reliability analysis of structures using fuzzy Bayesian interval estimation SCIE
期刊论文 | 2024 , 307 | ENGINEERING STRUCTURES
WoS CC Cited Count: 1
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Abstract :

In most real-world cases, an in-service structure doesn't always follow the two-state hypothesis under which the structure stays at an intact or completely failed state. Structural failure is sometimes regarded as a fuzzy event, and the actual failure boundary has a certain level of ambiguity that affects the structural limit state function under a fuzzy failure criterion. Under such circumstance, structural reliability should be solved within a hybrid reliability analysis framework involving the coupled effect of randomness and fuzziness. A fuzzy Bayesian interval estimation strategy has been proposed for this purpose. Structural parameters and external loads having fuzziness are decomposed and extended to fuzzy sets. The interval bounds of the distribution characteristics of the fuzzy parameters and loads are estimated using the fuzzy Bayesian estimation. Then an equivalent performance function is defined considering the fuzziness of the failure criterion. After that, the failure probability is computed under different interval combinations. The structural failure probability is expressed by an interval, instead of a traditional deterministic value. The solution process provides a better estimation of failure boundaries taking into account parameter ambiguities. The proposed method has been successfully verified against a plane steel frame structure and the IASC-ASCE benchmark test frame. It was found that the estimated failure probability intervals embraced the deterministic value predicted by the Monte Carlo simulation.

Keyword :

Equivalent performance function Equivalent performance function Failure probability interval Failure probability interval Fuzzy Bayesian estimation Fuzzy Bayesian estimation Fuzzy failure criterion Fuzzy failure criterion Hybrid reliability analysis Hybrid reliability analysis

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GB/T 7714 Fang, Sheng-En , Zheng, Jin-Ling , Wang, Si-Rong . Hybrid reliability analysis of structures using fuzzy Bayesian interval estimation [J]. | ENGINEERING STRUCTURES , 2024 , 307 .
MLA Fang, Sheng-En et al. "Hybrid reliability analysis of structures using fuzzy Bayesian interval estimation" . | ENGINEERING STRUCTURES 307 (2024) .
APA Fang, Sheng-En , Zheng, Jin-Ling , Wang, Si-Rong . Hybrid reliability analysis of structures using fuzzy Bayesian interval estimation . | ENGINEERING STRUCTURES , 2024 , 307 .
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Hybrid reliability analysis of structures using fuzzy Bayesian interval estimation Scopus
期刊论文 | 2024 , 307 | Engineering Structures
Hybrid reliability analysis of structures using fuzzy Bayesian interval estimation EI
期刊论文 | 2024 , 307 | Engineering Structures
Quasi-static testing based structural modal parameter estimation SCIE
期刊论文 | 2024 , 39 (8) , 2774-2797 | NONDESTRUCTIVE TESTING AND EVALUATION
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Abstract :

Structural modal identification is generally implemented within a dynamic framework, requiring multidisciplinary knowledge and adequate operational experience. This preliminary study attempts to explore an easy-to-handle quasi-static alternative method for dynamics-based modal identification of beam-type structures. Acceleration time-history data are replaced by quasi-static deflections induced by slow moving loads. A concept of quasi-static deflection influence surface is proposed based on the theory of influence lines and the principle of virtual work. Its analytical expression is simplified into a deflection matrix by choosing specific points on the surface according to deflection measurement coordinates. The matrix form is divided by external loads to obtain a generalised quasi-static flexibility matrix, which is used to replace the inversion of the global stiffness matrix in the modal eigenvalue equation. The lumped-mass method is also employed to establish the mass matrix. Subsequently, the eigenvalue equation is analytically solved seeking for modal frequencies and mode shapeswithout performing modal tests. The feasibility of the proposed method has been successfully verified against three experimental examples including a continuous box girder with variable cross sections. It was observed that the modal frequencies and mode shapes estimated by the proposed method were very close to those given by the dynamically modal tests.

Keyword :

generalised quasi-static flexibility matrix generalised quasi-static flexibility matrix modal eigenvalue equation modal eigenvalue equation modal parameter estimation modal parameter estimation quasi-static deflection influence surface quasi-static deflection influence surface Structural dynamics Structural dynamics

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GB/T 7714 Fang, Sheng-En , Huang, Ji-Yuan , Zhang, Xiao-Hua . Quasi-static testing based structural modal parameter estimation [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 , 39 (8) : 2774-2797 .
MLA Fang, Sheng-En et al. "Quasi-static testing based structural modal parameter estimation" . | NONDESTRUCTIVE TESTING AND EVALUATION 39 . 8 (2024) : 2774-2797 .
APA Fang, Sheng-En , Huang, Ji-Yuan , Zhang, Xiao-Hua . Quasi-static testing based structural modal parameter estimation . | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 , 39 (8) , 2774-2797 .
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Quasi-static testing based structural modal parameter estimation EI
期刊论文 | 2024 , 39 (8) , 2774-2797 | Nondestructive Testing and Evaluation
Quasi-static testing based structural modal parameter estimation Scopus
期刊论文 | 2024 , 39 (8) , 2774-2797 | Nondestructive Testing and Evaluation
钢拱塔斜拉桥的温度耦合效应和索力预测 PKU CSCD
期刊论文 | 2024 , 46 (02) , 146-153 | 土木与环境工程学报(中英文)
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Abstract :

钢拱塔斜拉桥的受力体系与传统斜拉桥有所不同,为研究环境温度变化对这种异形桥塔斜拉桥主要受力部件的影响,以某钢拱塔斜拉桥为工程背景,首先基于在线监测获取的环境和部件温度数据,分析斜拉索索力、拱塔倾角和主梁应变的温度时变效应;然后以斜拉索为研究对象,通过该桥的有限元模型升降温模拟,分析各部件温差引起的温度耦合效应对拉索索力的影响;最后以环境温度、主梁温度、桥塔温度为输入,索力为输出,利用长短期记忆神经网络对实测索力-温度数据进行映射,实现数据压缩和特征提取,建立温度-索力预测模型,再对网络模型输入新的温度监测数据,以预测索力。研究结果表明:主梁和钢拱塔温度变化具有周期性,且滞后于环境温度;主梁应变与环境温度的变化趋势基本一致但具有一定的滞后性,环境温度变化对拱塔倾角的影响很小且没有周期性规律;索力与环境温度呈线性负相关,且需要考虑斜拉桥各部件的温差所引起的温度耦合效应;长短期记忆神经网络对带有时序特性的数据训练效果好,建立的温度-索力关系模型准确度高,可用于该桥索力的实时预测。

Keyword :

桥梁工程 桥梁工程 温度耦合效应 温度耦合效应 索力预测 索力预测 钢拱塔斜拉桥 钢拱塔斜拉桥 长短期记忆神经网络 长短期记忆神经网络

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GB/T 7714 方圣恩 , 秦劲东 , 张玮 et al. 钢拱塔斜拉桥的温度耦合效应和索力预测 [J]. | 土木与环境工程学报(中英文) , 2024 , 46 (02) : 146-153 .
MLA 方圣恩 et al. "钢拱塔斜拉桥的温度耦合效应和索力预测" . | 土木与环境工程学报(中英文) 46 . 02 (2024) : 146-153 .
APA 方圣恩 , 秦劲东 , 张玮 , 江星 . 钢拱塔斜拉桥的温度耦合效应和索力预测 . | 土木与环境工程学报(中英文) , 2024 , 46 (02) , 146-153 .
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钢拱塔斜拉桥的温度耦合效应和索力预测 CSCD PKU
期刊论文 | 2024 , 46 (2) , 146-153 | 土木与环境工程学报(中英文)
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