The precise and controllable deployment of large-scale membrane sunshades is critical for future space optical systems. This study investigates the deployment mechanics of polygonal cylindrical origami configurations for these sunshades, combining theoretical modeling to confirm kinematic feasibility with physical model tests to characterize the actual deployment dynamics. Using piecewise linear regression, we find that the deployment driving force is dictated by the crease topology and exhibits a distinct multi-stage process. The results show that in contrast to single-vertex four-crease designs, the modified six-crease configuration possesses greater inherent crease rigidity, which in turn leads to a larger terminal driving force. This makes it suitable for missions requiring high-force, whereas the four-crease and conventional six-crease patterns are better for low-force deployments. By establishing a quantitative relationship between crease topology, inherent stiffness, and driving force, this research provides actionable strategies for configuration selection and force-profile tuning, crucial for the engineering design and optimization of high-precision deployable sunshades.

Infrastructure systems are characterized by inherent and deep coupling, which makes them susceptible to cascading failures and systemic collapses under extreme hazards. Consequently, vulnerability assessment and resilience enhancement technologies have emerged as critical issues for infrastructure security. This study analyzes 667 publications (1995–2025) from the WOS using CiteSpace to reveal the field’s knowledge structure and evolutionary trajectory. The analysis identifies a paradigm system shift from “singular engineering” to “coupled socio-technical” with a key inflection point between 2015 and 2018. This evolution progressed through three stages: conceptual foundation (2015–2017), systematic deepening (2018–2020), and technology-driven acceleration (2021–2023). Research focus has transitioned from disturbance resistance to absorption and adaptation, and from single hazards to multi-risk coupling. While socio-technical philosophy is widely accepted, a core paradox remains: quantitative engineering tools lag significantly behind conceptual advancements. The global landscape is led by the United States and China, with frontiers focusing on cascading failures, community resilience, and digital twins. This study concludes that future development must bridge the gap between philosophy and methodology. There is an urgent need for hybrid modeling integrating physical and social data, intelligent assessment for real-time environments, and interdisciplinary open-source platforms to translate resilience concepts into deployable engineering solutions.

Thunderstorm downbursts pose a significant threat to prestressed truss string structures (PTSS), particularly during their service life, as environmental erosion-induced corrosion can significantly weaken their resistance to collapse, thereby amplifying the destructive risks posed by downbursts. To address this issue, this study focuses on PTSS to investigate structural responses under thunderstorm downbursts while accounting for the effects of corrosion. Specifically, a deterministic-stochastic model is used to simulate the time history of wind speeds, combined with the incremental dynamic analysis (IDA) method and a local corrosion-equivalent buckling material model. This reveals the development pattern of structural deformation path migration caused by corrosion, which manifests as a shift from the buckling of members at the 1/3 span on windward side of the new structure to the buckling of members at the 1/6 span after corrosion. Through quantitative analysis of the influence of corrosion-affected areas, it was further confirmed that wind pressure imbalance is the primary cause of dynamic collapse. Subsequently, an assessment framework integrating corrosion and wind disaster variables was established: using the deflection-span ratio (lambda) and maximum mean wind speed (V-max) as indicators, combined with Latin hypercube sampling, a sample set coupling wind field morphology with corrosion-induced time-varying effects was constructed. Based on the fragility analysis results, structures with 50 years of service life exhibit a maximum increase of 160.44 % in lambda compared to new structures under the same wind speed, and a reduction of 10 similar to 15 % in Vmax required to achieve the same performance level under the same exceedance probability. This provides scientific basis and quantitative tools for assessing the wind resistance performance of structures in service.

Existing concrete bridges often exhibit strong spatial discreteness and complex prestress distribution patterns, making it difficult for limited field samples to accurately characterize the overall probability distribution of effective prestress. To address this issue, this study proposes a small-sample distribution identification method based on distribution-similarity learning. Guided by the prestress-loss transfer mechanism, key prestress-related parameters are modeled as random variables to construct a physics-informed distribution family covering both unimodal and bimodal characteristics. High-fidelity sample sets are generated, and a Sobol representativeness index is introduced to screen and diagnose sampled observations. Considering the many-to-one relationship between Gaussian-mixture-model parameters and distribution shapes, the proposed method shifts the learning objective from parameter-error minimization to distribution-similarity maximization. A joint loss function is adopted, with MMD² as the primary loss and parameter MSE as a weak regularization term. The results show that the 50-epoch model provides more stable distribution reconstruction than the 20-epoch model, and the proposed DNN outperforms the multi-start EM baseline under sparse-sample conditions. Repeated sampling analyses based on measured bridge-girder prestress data from constructed box-girder members further show that the distribution similarity generally reaches approximately 95% or above for N = 20–50 and about 98% or above when N ≥ 100. This study provides an efficient and practical approach for effective prestress distribution identification and prestress-condition assessment under limited inspection conditions.

Corrosion and prestress loss are the key factors affecting the safety and durability of prestressed steel structures. In this paper, the effects of corrosion of bars and prestress loss on the progressive collapse behavior of truss string structures (TSSs) in coastal areas under cable failure are investigated. First, a reasonable time-varying corrosion model is selected and combined with a modified equivalent buckling material model to propose an analysis method for the progressive collapse of prestressed steel structures considering the localized corrosion effect of bars. It was found that after 50 years of service, the progressive collapse resistance (PCR) of TSSs decreased by 18 % similar to 40 %. Specifically, when the service life reached 70 years, and the circumferential corrosion ratio (alpha) and axial corrosion ratio (beta) were 0.25 and 1.0, respectively, the PCR appeared to fall below the design load. In addition, the longer the service time is, the more obvious the effect of the corrosion pattern on the PCR of the structure. As an example, for a structure in service for 50 years, the maximum decrease in PCR was about 20 % when alpha increased from 0.25 to 1.0. These results indicate that the effects of corrosion of bars and prestress loss on the whole process of progressive collapse dynamic behavior of large-span prestressed steel structures should not be neglected. Finally, a time-varying degradation prediction model was developed, which can be used to evaluate the PCR of TSSs under cable failure.

As a vertical load-bearing component designed for support-free construction, the staged prestressed composite beam (SPCB) exhibits broad application potential in long-span and heavy-load structures. Accurate prediction of the full mechanical response of SPCB is critical for assessing structural safety and design economy. To address the challenge of limited data samples for such components, this work developed a hybrid deep learning framework integrated with data augmentation techniques to achieve high-precision prediction of SPCB's momentdisplacement curves. Prior to deep learning, an analytical model for moment-displacement curves was established for the first time using the finite strip method and the conjugate beam method. The model's accuracy was experimentally validated through bending tests on four specimens, thereby forming a high-quality benchmark dataset. Subsequently, a Variational Autoencoder based on Gated Recurrent Units (GRU-VAE) was developed to generate physically consistent synthetic samples. The similarity between the original and synthetic data was systematically evaluated using Pearson correlation analysis and dimensionality reduction visualization methods. Ultimately, a Bidirectional Long Short-Term Memory (BiLSTM) network was applied, leveraging its bidirectional temporal capturing capacity to achieve precise prediction of SPCB's moment-displacement curves. The testing results demonstrate that the proposed data augmentation method improved both the model's predictive accuracy and generalization ability, providing a novel approach for structural performance prediction under small-sample conditions.

This study proposes a physics-guided multi-stage deep learning (PG-MSDL) model for rapid prediction of incremental dynamic analysis (IDA) curves of prestressed concrete (PC) frames with infill walls, considering interior and exterior column removal conditions. Eighteen high-dimensional parameters, related to physical and geometric properties, including sectional dimensions and material properties of concrete, reinforcement, steel strands, and infill walls, are used as input variables. Purely data-driven models, such as XGBoost and Transformer, are first investigated, but their prediction accuracy is limited. By integrating physics-based performances and finite element results, the PG-MSDL model markedly improves the prediction of IDA curve evolution and key performance points, enhancing robustness and accuracy under highly nonlinear responses. Furthermore, a Sobol global sensitivity analysis based on the surrogate model reveals that infill wall properties dominate load-related responses, whereas displacement responses are more sensitive to structural parameter interactions. The proposed approach provides an efficient and reliable method for predicting progressive collapse behavior of PC frames under high-dimensional uncertainty.

Amid increasingly frequent extreme natural disasters, highly interconnected urban systems, and mounting operational pressures, enhancing the safety and resilience of urban infrastructure has become a vital strategy for safeguarding national security and advancing sustainable development. However, a significant gap persists between the current state of resilience-related technologies and the practical demands of building resilient cities, highlighting the urgent need for a systematic review of relevant technical systems and recent research progress. This study analyzes the current state and future development trends of urban infrastructure resilience technologies across five key domains: natural disaster forecasting and early warning, infrastructure vulnerability and risk assessment, functionality degradation and resilience evaluation, resilience enhancement and design, and emergency response and decision-making optimization. The study finds that while resilience-based disaster prevention has shifted the focus of infrastructure safety from structural robustness to system-level functionality and post-disaster recovery, and intelligent disaster prevention has greatly enhanced the efficiency and accuracy of disaster sensing, forecasting, and emergency response, several major challenges persist. These challenges include the absence of unified standards for resilience technologies, insufficient multi-hazard joint modeling, weak cross-system coordination, poor generalization and interpretability of intelligent models, and limited transparency in decision-making processes. Looking ahead, a key development trend will involve building a unified theoretical framework and standardized system for infrastructure safety and resilience. This should be supported by an intelligent technology system characterized by data empowerment, language-driven interaction, and cognitive reasoning, facilitating multi-source data fusion, cross-modal knowledge transfer, multi-hazard joint assessment, system-level coordination, and high interpretability with transparent mechanisms. Furthermore, the study offers development recommendations from the aspects of institutional support, intelligent enablement and resource allocation, as well as technical standardization, aiming to provide theoretical foundations and practical guidance for systematically enhancing urban infrastructure resilience in China.

This paper proposes a theoretical model correlating cable tension and frequency, incorporating the influence of intermediate transverse constraints. A theoretical vibration equation, considering these constraints, was derived to map the relationship between cable tension and frequency. Theoretical and numerical solutions for this equation were developed and validated. The impact of intermediate constraints on the cable tension-frequency relationship was subsequently analyzed. Results indicate that the theoretical numerical solutions provide accurate and efficient predictions for both single and multiple intermediate constraints, while the theoretical analytical solution is limited to single-constraint scenarios. Factors such as stiffness, position, and quantity of intermediate constraints significantly influenced the cable tension-frequency relationship, with these factors exhibiting coupled effects. At low constraint stiffness, the squared first-order frequency exhibited a linear correlation with cable tension, irrespective of constraint quantity or position. As stiffness increased, this relationship transitioned from linear to nonlinear, characterized by an initial convex upward curve before stabilizing into a linear segment for varying intermediate constraint configurations.

Post-earthquake rescue efficiency is crucial for urban seismic resilience. However, building collapse patterns, which critically determine rescue difficulty, remain inadequately addressed in urban disaster policies. This study proposes a policy-oriented methodology for quantifying seismic rescue difficulty in urban areas based on building collapse patterns. First, a code-compliant parametric rapid modeling algorithm was developed, integrating a hybrid simulation approach that combines the multi-degree-of-freedom (MDOF) model with the Discrete Element Method (DEM) to enable building cluster collapse simulation. Furthermore, a multi-dimensional analysis model integrating both qualitative and quantitative metrics was established to analyze collapse patterns. The reliability of this approach was validated through Wenchuan earthquake case studies. Based on this validated approach, a rescue difficulty assessment model incorporating the Survival Space Index (SSI) and the Rescue Route Complexity Index (RRCI) was developed to quantify post-earthquake rescue difficulty. Finally, a case study was conducted in Beijing's Tongzhou District that categorized collapsed buildings into four rescue difficulty levels, and corresponding rescue strategies were subsequently discussed. These findings provide valuable insights for optimizing post-earthquake rescue strategies and resource allocation, thereby enhancing urban disaster response capabilities and contributing to seismic-resilient city development.

This study focuses on a critical aspect of bridge engineering – the evaluation of cable forces, paying particular attention to the cables that are internally constrained by elastic supports. Detecting these cable forces is important for the safety and stability of bridges. The practical problem introduces a novel mathematical challenge: how to effectively address string vibration equations with one or multiple internal elastic supports, which remains a theoretical issue not fully solved in engineering. To tackle this, it is necessary to firstly establish an appropriate mathematical model and accurately define initial-boundary value problems. We then formulate the well-posedness of the solution using both classical and weak solution approaches, supplementing the existing numerical results available in engineering. Meanwhile, we attempt to use PINNs (Physics-Informed Neural Networks) instead of traditional FEM (Finite Element Method) in engineering. Consequently, in contrast to the classical solution method, we demonstrate that for a string with finite elastic supports, the weak solution method not only improves mathematical modeling efficiency but also simplifies the process of explaining the well-posedness of the solution.

To study the effects of the jacking stress level, height and strength ratio of the prestress tendons (λ) on the seismic performance of unbonded prestressed concrete (UPC) beams, six UPC beams and one reinforced concrete (RC) beam were tested under cyclic loads. The hysteretic characteristics, skeleton curves, ductility properties, energy dissipation capacity, strain distribution of reinforcement and self-centering capability of the specimens were studied and discussed. Numerical parameter analysis was also carried out by using OpenSees. The results indicate that three failure modes of UPC beams under cyclic loading were observed, namely the tension-failure mode involving a broken rebar, the compression-failure mode involving concrete crushing and the balanced failure. By considering the influence of the prestress position and magnitude, the modified reinforcing index ω was proposed to determine the failure mode. The ω is suggested to be less than 0.3 to ensure sufficient ductility. The effective stress level is linearly and positively related to the stiffness from cracking to yield Kcr and the ultimate bearing capacity of the UPC beam under cyclic loading. The stiffness of the UPC beam is slightly larger than that of the RC beam before yielding, and significantly greater than that of the RC beam after yielding. Due to the large strength reserve after yielding, the integrated seismic performance of the UPC beam is similar to that of the RC beam. When the λ was unchanged, the increase in the relative height of the prestressed tendons αh is beneficial for the overall performance factor F, ductility and crack control. The stiffness degradation performance depends on the λ but is independent of the αh. The total energy dissipation of the non-tensioned UPC specimen was 59% higher than that of the RC beam. The cumulative total energy dissipation of the tensioned UPC specimen was only 13% lower than that of the RC beam with the same number of cycles, indicating that the UPC specimen had a considerable energy dissipation capacity.

Aided by the scaled boundary finite element method (SBFEM), analytical precise integration solutions to the transverse free vibration responses of functionally graded piezoelectric composite plates are provided for the first time. Distributions of the functionally graded piezoelectric materials follow arbitrary mathematical formulae as concerns the in-plane unidirectional or bidirectional coordinates. The vibration behaviors of piezoelectric composite plates with various geometrical shapes, multifarious boundary constraints and any number of laminae can be explored by the introduced technique. Additionally, the shear correction factors and assumptions on the changing patterns of mechanical and electrical variables are not needed to be offered in the employed methodology. The proposed approach regards only four quantities containing three elastic displacement components and the electric potential as the primary unknowns, which can be denoted as an analytical matrix exponent in terms of the thickness coordinate. Only two-dimensional high-order spectral elements are adopted to discretize the in-plane surface of the plate with less nodes and degree of freedoms, which promotes to lowering the calculative expense and advancing the computational efficiency. The introduced scaled boundary coordinate system and the dual vector technology are helpful to simplify the basic partial differential equations of piezoelectric materials into the first order ordinary differential SBFEM governing equation, from which the highly accurate global stiffness matrix are constructed by dine of the precise integration technique (PIT). With the aid of the kinetic energy scheme and compatibility conditions between neighboring layers, the whole mass matrix for the laminated piezoelectric plates can be built. According to solving the eigenvalue equation, the precise integration solutions to free vibration frequencies can be acquired. Finally, numerical experiments are afforded to elucidate the high precision and fast convergence of the present method. Moreover, the effect of different boundary constraints, gradation parameters and aspect ratios on the transverse vibration responses of in-plane-wise functionally graded piezoelectric composite plates is revealed.

Considering the wind loads and track irregularity as external excitation, the wind-train-bridge dynamic analysis model considering the longitudinal freedom of train is established in the present study. In the model, the wind load of train bridge system under the train-induced wind field and the combined wind field is obtained by employing Computational Fluid Dynamics (CFD) method. With the CRH2 high-speed train and a 10-span simply-supported box girder bridge as an example, the whole history of the train running on the bridge under the combined effect of train-induced wind and crosswind is simulated to analyze the dynamic response of the train-bridge system. In addition, the operational safety indicators of the train are evaluated. According to the obtained results, the dynamic response of vehicles and bridges increases with the train speed without the consideration of the crosswind. In the combined wind field, the train-induced wind exerts a greater impact on the dynamic response of the vehicle, but has a less influence on that of the bridge simultaneously. Moreover, the influence of wind velocity is greater than that of train speed. When the wind-train-bridge dynamic response analysis is carried out based on traditional methods, the calculated wind load of the train-bridge system is too high, making the calculated responses too large to be consistent with actual values.

为得到沪通公铁两用长江大桥(后简称沪通大桥)桥址区风速时程序列,对沪通大桥开展了现场风速实测,对桥址区的风场特性进行分析,得到基于实测数据的风速谱,并将其与规范给出的风速谱进行参数对比.之后采用基于实测风速谱显式分解的谐波合成法,将该桥的三维脉动风速场简化为多个线状的一维脉动风速场,分别对两个主塔、公路桥面、铁路桥面的脉动风速进行数值模拟,模拟值与目标值吻合较好.结果表明:采用实测的风速谱参数可以很好地得到大跨度桥梁数值模拟三维脉动风场,并与规范给出的统一功率谱有一定的差异性,体现了规范谱应用于不同地区,尤其是复杂气象条件时的局限性.得到的基于实测风特性的大跨度斜拉桥风速时程序列,为桥梁的风振分析提供了基础,具有良好的实用效果.