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CONTENTS
Volume 30, Number 6, June 2026
 

Abstract
This paper presents a novel method to simulate the dynamic movement of grasshopper swarms, focusing on incorporating natural environmental factors—specifically wind and gravity—into the Grasshopper Optimization Algorithm (GOA). This enhanced version of the GOA algorithm, the Enhanced Grasshopper Optimization Algorithm (EGOA), is designed to improve both the exploration and exploitation phases of the optimization process. By integrating gravity and wind effects through specific transfer functions, the EGOA dynamically adjusts the swarm's behavior, enabling a more realistic and effective search mechanism within the algorithmic framework. The engineering significance of this work is highlighted through the application of EGOA to complex engineering problems, including damage identification in different structural systems. Since examples in damage detection of the structures are varied in size and degrees of freedom (DOF), choosing a capable optimization algorithm, which can handle this inverse problem without trapping in local optimums, is crucial. The objective function is defined based on frequencies and mode shapes of the structure in the damaged and undamaged states. Also, the design variables are the location and intensity of the damage in elements, which are achieved using optimization algorithms. Moreover, to simulate the real conditions in sensing the modal data, frequencies, and mode shapes are contaminated with noise. The effectiveness of the EGOA is rigorously tested against standard mathematical functions commonly used in optimization analyses. In this regard, five case studies were used for damage detection in various structures, including different 2D and 3D truss and frame structures with different scenarios of damage. The performance of EGOA is further validated through comparisons with established metaheuristic algorithms, including PSO, CSS, GWO, and CGO, demonstrating superior accuracy and stability in both mathematical benchmarks and structural damage detection. Additionally, experimental validation on a full-scale three-story steel frame confirms EGOA's practical efficacy, achieving precise damage localization and severity estimation with minimal false alarms and relative errors in modal properties. The results show that the proposed EGOA effectively addresses these complex nonlinear problems and maintains consistent performance across a large domain search space.

Key Words
damage identification; grasshopper optimization algorithm; inverse problem; structures

Address
Shahnam Aghanezhad, Seyed Arash Mousavi Ghasemi: Department of Civil Engineering, Ta.C., Islamic Azad University, Tabriz, Iran
Bahman Farahmand Azar: Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran

Abstract
This paper introduces a simplified model for the dynamic analysis of 2D rectangular storage tanks. The model employs an added mass method to eliminate the need for fluid domain modeling while accounting for liquid sloshing effects. Key parameters such as impulsive and convective vibration periods (sloshing) as well as seismic responses (displacements and base shear forces) are computed and validated against results from a fluid-structure interaction model based on the (U, P) formulation. The validation also considered mesh sensitivity, reservoir flexibility, and liquid compressibility. For three tank geometries with varying H/L ratios under different seismic loads, the proposed model produced highly satisfactory results, confirming its efficacy as a reliable computational tool for rectangular reservoir design.

Key Words
2D finite elements; fluid-structure interaction; free surface sloshing; rectangular tanks; simplified procedures

Address
Lyes Ramdani, Abdelkader Tahakourt: Laboratoire de Génie de la Construction et Architecture (LGCA), Faculté de Technologie, Université de Bejaia, 06000 Bejaia, Algeria
Nourredine Belhamdi: Département d'Architecture, Faculté de Technologie, Université de Bejaia, 06000 Bejaia, Algeria

Abstract
The present study examines the seismic response of a Dam-Reservoir-Layered Foundation (DRLF) system with varying foundation layer depths. The foundation behaviour due to the stratification, interaction effects and site amplification is also investigated. Three configurations (S1, S2, and S3) with different foundation depths and the same foundation width across all systems are analysed, each further modified with distinct layer arrangements (C1, C2, and C3) for soft, medium, and unweathered rock layers. Non-linear time-history analyses were performed using 11 spectrum-compatible ground motions. The target PGA is determined through deterministic seismic hazard analysis, using the response spectrum from IS 1893: Part 1-2016. Results indicate significant variation in the DRLF system's response with changes in foundation layer depth. Interestingly, a soft layer at the surface amplifies the dam's response compared to other configurations. A proportional decrease in response parameters has been observed with increasing foundation depth. This demonstrates that seismic amplification is more prominent in shallower foundations than in deeper ones.

Key Words
concrete gravity dam; damage assessment; dynamic analysis; nonlinear analysis; numerical simulation; seismic response

Address
Department of Civil Engineering, Visvesvaraya National Institute of Technology, Nagpur 440010, India

Abstract
To enhance the seismic resilience of prefabricated steel frame structures, an innovative spring-friction self-centering energy dissipative brace (SF-SCEDB) is proposed. This brace achieves independent control of restoring forces and energy dissipation via helical springs as the self-centering system and friction shims as the energy dissipation system. First, the structural details, assembly process, and operational principles of the SF-SCEDB are elaborated. Subsequently, finite element models using ABAQUS are employed to quantitatively analyze the self-centering capacity, energy dissipation efficiency, and stiffness of the brace. Simulation results demonstrated that the hysteretic curve was flag-shaped with negligible residual deformation under cyclic loading. Parametric studies revealed that increasing the stiffness of helical springs and pre-compression length of helical springs enhanced both energy dissipation and self-centering abilities. However, higher bolt preload and friction coefficients of the friction shims improved energy dissipation at the expense of self-centering capability. The SF-SCEDB exhibits excellent hysteretic behavior and robust self-centering performance, making it promising for mitigating earthquake-induced damage and accelerating post-seismic rehabilitation in steel frames.

Key Words
adjustable friction energy dissipation system; finite element model; hysteretic behavior; restoring force model; seismic performance; self-centering brace

Address
Yang Chen: 1) School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200444, China; 2) China-Pakistan Belt and Road Joint Laboratory on Smart Disaster Prevention of Major Infrastructures, Southeast University, Nanjing, 211189, China
Cheng Chen: School of Mechanics and Engineering Science, Shanghai University, Shanghai, 200444, China
Jun Tang: Quakesafe Technologies Co., Ltd, Kunming, Yunnan,650200, China
Shiqiang Feng, Yong Yang: Department of Civil Engineering, Xi'an University of Architecture & Technology, Xi'an, Shaanxi 710055, China

Abstract
The structural safety of high-speed railway bridges in mountainous, seismic-prone regions is severely challenged by the concurrent hazards of earthquakes and foundation scour. This study presents a systematic investigation into how three key, design-controllable pier material parameters—concrete strength, longitudinal reinforcement strength, and reinforcement ratio—affect the system-level seismic fragility of a typical simply-supported girder bridge under both scoured and non-scoured conditions. A refined numerical model was developed in OpenSees and validated against dynamic response characteristics. Incremental Dynamic Analysis (IDA) was carried out using a suite of spectrally matched ground motions. A newly proposed "Synergistic Effect Index" quantifies the interaction between improvements in different material parameters. The results clearly identify the reinforcement ratio as the most influential parameter: increasing the reinforcement ratio from 0.5053% to 1.5097% reduces the probability of severe damage at PGA=0.4 g by approximately 25% under non-scoured conditions and 22% under scoured conditions. Although scour consistently increases fragility—reducing median seismic capacity by 16-18% across all material configurations—targeted material optimization still offers significant benefit. Notably, under high-intensity shaking (PGA=0.4 g) with scour present, pairwise combinations of material upgrades exhibit an antagonistic effect (Synergistic Effect Index=0.82-0.85), meaning their combined benefit is less than the sum of individual improvements. From these findings, the study proposes a practical, three-tiered design strategy: prioritizing reinforcement ratio optimization (target range 1.0%-1.3%), rationally upgrading material grades, and integrating mandatory scour protection measures. This integrated approach provides a clear and resilient design pathway for bridges facing combined seismic and scour threats.

Key Words
material parameters; scour; seismic fragility; simply-supported girder bridge; synergistic effect

Address
School of Environmental and Civil Engineering, Chengdu University of Technology, No. 1, East Third Road, Erxianqiao, Chenghua District, Chengdu 610000, Sichuan Province, China

Abstract
Input energy is the critical theoretical foundation for performance-based seismic design, as it directly reflects the energy demands imposed on structures during seismic events, thereby offering more physically meaningful metrics for structural performance assessment and design. However, relatively little attention has been devoted to the development of ground motion prediction equations (GMPEs) for near-fault elastoplastic input energy. Based on the NGA-West2 ground motion database, this study selects moment magnitude (Mw), average velocity of shear waves in the uppermost 30 m (VS30), fault type, and rupture distance as key characteristic variables. A machine-learning-based support vector regression (SVR) framework is employed to predict constant-strength relative input energy, with model hyperparameters globally optimized using the particle swarm optimization (PSO) algorithm. These methodological choices aim to enhance the generalization capability and prediction accuracy of PSO-SVR machine-learning-based GMPEs. The rationality of the PSO-SVR machine-learning-based GMPEs fitting was verified through residual analysis and the influence of explanatory variables on the prediction results. The results show that the PSO-SVR machine-learning-based GMPEs for constant-strength relative input energy proposed demonstrates higher accuracy and stability in the prediction of near-fault ground motion data. The findings provide reliable references for performance-based seismic design and contribute valuable insights to the application of machine learning methods in earthquake engineering.

Key Words
constant-strength relative input energy; constant-strength; ground-motion prediction equations; machine learning; near-fault ground motions

Address
Juanjuan Gao, Qinghui Lai, Hui Chen: Wenzhou Key Laboratory of Intelligent Lifeline Protection and Emergency Technology for Resilient City, Wenzhou University of Technology, Wenzhou 325035, China
Daehyeon Kim: Department of Civil Engineering, Chosun University, Gwangju, 61452, Republic of Korea

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