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学者姓名：方圣恩
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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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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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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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Structural health monitoring (SHM) data have a large volume, increasing the cost of data storage and transmission and the difficulties of structural parameter identification. The compressed sensing (CS) theory provides a signal acquisition and analysis strategy. Signal reconstruction using limited measurements and CS has attracted significant interest. However, the dynamic responses obtained from civil engineering structures contain noise, resulting in sparse samples and reducing the signal reconstruction accuracy. Therefore, we propose an optimization algorithm for the measurement matrix integrating the Karhunen-Loeve transform (KLT) and approximate QR decomposition (KLT-QR) to improve the accuracy of dynamic response reconstruction of SHM data. The KLT reduces the correlation between the measurement matrix and the sparse basis. The approximate QR decomposition is used to improve the independence between the column vectors of the measurement matrix, optimizing the measurement matrix. The experimental results for a laboratory steel beam indicate that the proposed KLT-QR algorithm outperforms three other algorithms regarding the accuracy of dynamic response reconstruction (acceleration, displacement, and strain), especially at high compression ratios. The acceleration responses from the Ji'an Bridge are utilized to verify the advantages of the proposed algorithm. The results demonstrate that the KLT-QR algorithm has the highest accuracy of reconstructing the vibration signals and yields better Fourier spectra than the conventional Gaussian measurement matrix.
Keyword ：
compressed sensing compressed sensing Gaussian measurement matrix Gaussian measurement matrix optimization optimization response reconstruction response reconstruction Structural health monitoring Structural health monitoring
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| GB/T 7714 | Zhang, Xiao Hua , Xiao, Xing Yong , Yang, Ze Peng et al. Response reconstruction based on measurement matrix optimization in compressed sensing for structural health monitoring [J]. | ADVANCES IN STRUCTURAL ENGINEERING , 2024 . |
| MLA | Zhang, Xiao Hua et al. "Response reconstruction based on measurement matrix optimization in compressed sensing for structural health monitoring" . | ADVANCES IN STRUCTURAL ENGINEERING (2024) . |
| APA | Zhang, Xiao Hua , Xiao, Xing Yong , Yang, Ze Peng , Fang, Sheng En . Response reconstruction based on measurement matrix optimization in compressed sensing for structural health monitoring . | ADVANCES IN STRUCTURAL ENGINEERING , 2024 . |
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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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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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The nature of damage identification is close to a pattern recognition process that classifies different damage patterns. The na & iuml;ve Bayes classifier (NBC) can effectively handle multiple-classification problems by choosing patterns with high probabilities. Therefore, by absorbing the autoregressive model with exogenous inputs (the ARX model), an ARX-Na & iuml;ve Bayes damage identification strategy has been proposed in which the autoregressive coefficients of the ARX model are taken as the sensitive damage feature. The classification training and test sample datasets are then built on these coefficients corresponding to various damage scenarios. The model order of an AR model is first determined for the subsequent order selection of the ARX model, whose autoregressive coefficients are further used to construct the NBC. This procedure can enhance the pattern recognition robustness to uncertainties such as measurement noises. Different damage patterns are determined by calculating the sum of logarithmic likelihoods of testing samples. The effectiveness of the proposed method has been verified against a bridge benchmark model having different damage scenarios under the noise pollution. In addition, an experimental five-story shear frame structure was adopted for validation, showing that compared with the SVM algorithm suitable for handling binary classification problems, the proposed method excels in multi-classification of damage patterns.
Keyword ：
damage patterns damage patterns na & iuml;ve bayesian classifier na & iuml;ve bayesian classifier Structural damage identification Structural damage identification the ARX model the ARX model uncertainties uncertainties
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| GB/T 7714 | Zheng, Jin-Ling , Fang, Sheng-En , Wang, Si-Rong . ARX-Naïve Bayes based structural damage identification [J]. | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 . |
| MLA | Zheng, Jin-Ling et al. "ARX-Naïve Bayes based structural damage identification" . | NONDESTRUCTIVE TESTING AND EVALUATION (2024) . |
| APA | Zheng, Jin-Ling , Fang, Sheng-En , Wang, Si-Rong . ARX-Naïve Bayes based structural damage identification . | NONDESTRUCTIVE TESTING AND EVALUATION , 2024 . |
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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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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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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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