Abstract
This paper investigates the nonlinear transient response of geometrically imperfect magneto-electroelastic (MEE) annular plates subjected to explosive blast loading. The governing equations are formulated based on first-order shear deformation theory, Maxwell's equations, and the Euler–Lagrange principle, incorporating geometric nonlinearity and multifield coupling. The resulting system is solved numerically using the Runge–Kutta method. Time-history curves and phase trajectory diagrams are employed to illustrate the effects of key parameters, including ambient temperature, electric and magnetic potentials, damping coefficient, positive phase duration, and peak blast pressure. Parametric analysis reveals several key findings: (1) elevated temperatures amplify vibration amplitudes and phase velocities due to thermal expansion and stress; (2) electric potentials intensify dynamic responses, while magnetic potentials exert a suppressive effect, with magnetic dominance enabling dual-parameter optimization; (3) increasing the damping coefficient significantly reduces oscillation amplitudes and accelerates energy dissipation, enhancing blast resilience; and (4) higher blast load parameters (peak pressure and positive phase duration) increase total impulse and thereby exacerbate structural vibrations. These findings highlight the complex interactions among electromechanical coupling, imperfection sensitivity, and transient loading conditions. The study provides new insights into the design of smart MEE annular plates under extreme environments, offering a foundation for optimizing electromagnetic parameters and damping characteristics to improve structural stability and blast resistance.
Key Words
annular plates; blast load; Magneto-electro-elastic plate; thermal effect
Abstract
Online model updating of bridge structures during operation represents a critical challenge in structural health monitoring. A two-stage online model updating strategy for long-span cable-stayed bridges is developed using the Guanhe Bridge as a case study. In Stage 1, a reference finite element model accounting for parameter uncertainties is established through a sensitivity-based interval response surface method with historical offline data. Sensitivity analysis, optimal Latin hypercube sampling, and multi-objective optimization via a multi-island genetic algorithm are integrated. An average relative error within 0.5% is achieved for the target frequencies. The resulting model captures the uncertainty range of operational parameters and serves as a reliable benchmark for online updating. In Stage 2, online-identified frequency information is incorporated into a deterministic model updating process, enabling rapid dynamic model updates. This finite element model updating, based on online modal frequencies, yields a maximum relative error of 0.86% for the second horizontal mode H2. The uncertainty of the updated parameters is substantially reduced, and the credibility of the results is enhanced. Dynamic model updates are thus achieved on a shorter time scale. This two-stage method provides theoretical foundations and technical support for online safety state assessment of cable-stayed bridges.
Key Words
cable-stayed bridge; interval response surface method; multi-island genetic algorithm; online model updating; sensitivity analysis; uncertainty quantification
Address
Hong Li, Kun Zhang, Zhouhong Zong: Engineering Research Center for Safety and Protection against Explosion and Impact of Ministry of Education, School of Civil Engineering, Southeast University, Nanjing, Jiangsu, 211189, China
Jie Niu: School of Civil Engineering and Architecture, Nanjing Institute of Technology, Nanjing, Jiangsu, 211189, China
Abstract
Performing dynamic reliability of structures is an resource-intensive task because it involves a threenested loop computation: the first loop over different structural members, the second loop over discretized time steps,
and the third loop over random variables sampled from pre-described probability distributions. To address this challenging problem, this study first designed a feature aggregation process using various techniques such as zeropadding, broadcasting, and position encoding to combine different time-invariant random variables, historical responses, and ground motion into a unified three-dimensional feature tensor. Next, we developed a computationally efficient yet highly accurate metamodel based on a modern selective state space deep learning architecture. Third, a mixed-multiple layer perceptron projection layer is employed to generate outputs with desirable prediction lengths and number of channels. To demonstrate the viability of the proposed method, two examples are presented: one involving a two-dimensional planar frame structure and the other a three-dimensional spatial frame structure. The obtained results demonstrate that the proposed method is consistently more accurate than numerous counterparts, accelerates the seismic reliability analysis of large-size Monte Carlo populations by approximately 5.5 times compared with FEM, and achieves a mean deviation of the reliability index of about 6%. Supplemental studies, including hyperparameter optimization and comparison studies, have been performed, providing further insights into the performance of the proposed method.
Key Words
deep learning; state-space architecture; structural dynamic; time-series data
Address
Trong-Phu Nguyen, Viet-Hung Dang: Faculty of Building and Industrial Construction, Hanoi University of Civil Engineering, Hanoi, Vietnam
Abstract
This study presents a validated, comparative seismic performance assessment of common Albanian URM archetypes in Albania, a country recognized for its high seismic risk and large stock of masonry structures. Three representative URM buildings: two, three and five story with red and silicate clay bricks, are modelled and analyzed using the 3Muri software, to evaluate their seismic capacity and vulnerability. Experimental material tests were used to determine mechanical properties for each building, which were then applied in macro-modelling for pushover analyses according to Eurocode 8. The seismic performance was assessed at three limit states: Damage Limitation, Significant Damage, and Near Collapse, by identifying peak ground acceleration thresholds for each damage limit. Moreover, the analytical predictions were validated against field observations from the major Durrës earthquake (November 26, 2019). The two-story building demonstrated greater strength, under higher ground motions, whereas the three-story building was more vulnerable to damage. For the five-story cases, the structure with red clay bricks showed superior strength and ductility, while the silicate brick model showed lower seismic resistance and a more brittle response. Comparison with site observations after the 2019 Durrës earthquake confirmed that the predicted damage states aligned with the real damage seen in inspected buildings, particularly for non-structural and shear cracking in the masonry walls.
Abstract
Blast-resistant design of steel structures requires a clear understanding of system-level response under extreme demands. Traditional approaches lack quantitative performance criteria across different lateral load-resisting
systems. This study investigates two- and five-story moment-resisting frames (MRF), concentrically braced frames (CBF), and dual MRF-SPSW systems under blast loading at 5 m and 10 m standoff distances. Incremental Dynamic Analysis (IDA) was employed, with interstory drift ratio and von Mises stress as performance indicators. The numerical model was validated against scaled experimental tests, showing less than 5% deviation in stiffness and strength. MRFs exhibited the most favorable performance, with significantly lower drift demands and higher collapse prevention (CP) capacities. CBFs showed intermediate performance, while SPSWs, despite their high initial stiffness, experienced concentrated damage and amplified upper-story drifts. Increasing standoff distance enhanced resilience, tripling the blast capacity of MRFs. The findings establish drift-based performance benchmarks and highlight system-specific vulnerabilities, offering practical guidance for performance-based blast-resistant design.
Abstract
This article presents, for the first time, the aero-thermo-poroelastic supersonic flutter characteristics of geometrically nonlinear, functionally graded, saturated porous material (FGSPM) plates subjected to yawed flow angle. The Refined shear deformation plate theory (RSDPT), in conjunction with von Karman's nonlinear relations and the supersonic piston theory, accounting for yawed flow angle, is used to construct the FGSPM plate. The temperature-dependent effective material properties of the FGSPM plate vary continuously across the thickness. The pores under saturated fluid-filled conditions are considered for the analysis. Consequently, the constitutive equations are derived by utilizing linear poroelasticity theory. Additionally, by integrating Hamilton's principle with a nonlinear finite element technique, the governing equations of a supersonic FGSPM plate are developed. Then, the direct iterative procedure is used to obtain the geometrically nonlinear numerical solutions. Special emphasis is placed on understanding the effects of various parameters, such as aerodynamic pressure, yawed airflow angle, Skempton coefficient, temperature gradients, saturated porosity distributions, porosity volume index, volume fraction grading index, and boundary conditions, on the analysis of nonlinear flutter bounds of the FGSPM plate. The study shows that saturated fluid in the pores of the FGSPM plate significantly affects the flutter bounds compared to the plate in drained conditions.
Key Words
FGM; panel flutter; poroelasticity theory; saturated pores; thermal effects; von Karman's nonlinearity; yawed supersonic flow
Address
H.S. Naveen Kumar: Department of Mechanical Engineering, Government Polytechnic, Holenarasipura, Karnataka, 573211, India
Subhaschandra Kattimani: Department of Mechanical Engineering, National Institute of Technology Karnataka,
Surathkal, Mangalore, 575025, India
