Yue Liu

Accurate finite element models are essential for structural condition assessment, yet nominal material properties and idealized boundary conditions can produce systematic discrepancies between numerical and measured dynamics. This study proposes a physics-constrained sparse response-surface framework that combines Elastic Net basis selection, mechanically prescribed monotonicity, adaptive sample enrichment, and identifiability-aware uncertainty assessment within a transparent finite element model-updating procedure. A scaled steel truss was tested using millimeter-wave radar, and the first three vertical natural frequencies were identified by stochastic subspace identification. The resulting sparse polynomial surrogate was independently validated before bounded inversion and ANSYS back-substitution. The mean frequency error decreased from 5.55% to 0.82%. Jacobian and bootstrap analyses further showed that several combinations of material and boundary parameters can reproduce similar modal responses, so the updated parameters are best interpreted as a coupled equivalent calibration state rather than unique direct measurements. The proposed framework therefore improves physical consistency and computational efficiency while explicitly retaining the uncertainty associated with weakly identifiable parameter directions.

Large stadiums commonly employ long-span spatial steel roof systems and require efficient non-contact monitoring. This study presents a millimeter-wave-radar-based detection and safety assessment method for a large in-service stadium roof. Ambient vibration tests were conducted on a representative steel truss using millimeter-wave radar and co-located accelerometers, and the modal frequencies and mode shapes were identified using peak picking and stochastic subspace identification. An undamaged finite-element model was established to interpret the measured modal information and simulate local stiffness-reduction scenarios. The first four vertical frequencies identified by radar were 3.32, 7.03, 10.35, and 13.18 Hz, compared with 3.32, 7.03, 10.35, and 13.48 Hz obtained from the accelerometers. The first three frequencies were identical at the reported precision, and the fourth-frequency difference was approximately 2.2%. Numerical results showed that the modal-curvature-based Safety Indicator was sensitive to local stiffness degradation and could indicate approximate abnormal regions. No pronounced localized modal anomaly was observed in the field-tested truss, consistent with the on-site inspection. The study demonstrates an integrated workflow combining non-contact radar measurement, operational modal identification, finite-element-supported interpretation, and preliminary condition assessment for large stadium roofs.

To address the limitations of traditional structural damage identification methods in terms of reliance on high-fidelity baseline models and sensitivity to minor damage, this paper proposes a novel physics-informed and data-driven approach based on the modal curvature variation coefficient. A damage-sensitive feature derived from the rate of change in the radius of curvature is established, providing a clear mathematical and physical interpretation to reduce model error interference and enhance local damage localization. The effectiveness of the proposed method is validated through a 1:20 scale model experiment of a main truss from a large stadium steel roof. A total of 33 experimental cases were designed, simulating single and multiple damage scenarios with varying severity levels (large, medium, and small). Multi-source monitoring techniques, including millimeter-wave radar interferometry, laser displacement sensors, high-resolution vision-based measurement, and accelerometers, were integrated. Modal parameters were extracted using the Stochastic Subspace Identification (SSI) method, and the finite element model was updated via a high-order response surface methodology. Numerical simulations and experimental results demonstrate that the proposed modal curvature variation coefficient is highly sensitive to local stiffness degradation and accurately locates both single and multiple large/medium damage regions. In cases involving multiple minor damages, the method effectively identifies the damaged areas but exhibits a risk of false positives in undamaged sections. The millimeter-wave radar measurements exhibit strong agreement with laser displacement data, confirming its viability for non-contact structural health monitoring. This research provides a robust technical framework and experimental foundation for condition assessment and early damage warning in large-scale engineering structures.

The central buckle is essential for maintaining longitudinal stability in suspension bridges. However, conventional steel buckles are often excessively stiff, leading to stress concentration and insufficient durability. Moreover, they tend to perform poorly under fatigue loading conditions. This study proposes a novel flexible central buckle system based on a Carbon Fiber-Reinforced Polymer (CFRP) to address these limitations. This study proposes a novel flexible central buckle system based on Carbon Fiber-Reinforced Polymer (CFRP) to address these limitations. Taking the long-span Shiziyang Suspension Bridge as a case study, a finite element model is developed to investigate the effects of CFRP central buckles with eight different stiffness levels on the static and dynamic responses of the bridge. The results indicate that a CFRP central buckle with a low elastic modulus achieves comparable displacement control performance to that of traditional steel buckles, while inducing significantly lower internal forces, demonstrating strong potential as a substitute. Based on this finding, a coordinated control strategy combining the CFRP central buckle with end-span restraining devices is proposed. This integrated system reduces midspan displacement and central buckle internal force by 61.1% and 49.8%, respectively. Considering both performance and cost-efficiency, a low-modulus CFRP material such as T300 is recommended. The proposed approach offers a new and effective solution for longitudinal control in ultra-long-span suspension bridges.