Article
Automation & Control Systems
Amir H. Gandomi, David A. Roke
Summary: In this article, an evolutionary framework for seismic response formulation of self-centering concentrically braced frame (SC-CBF) systems is proposed. Multiple SC-CBF systems were designed, and an evolutionary feature selection strategy and a hybrid multiobjective genetic programming and regression analysis were used to find the best model. The results show that the evolutionary procedure is highly effective for designing the SC-CBF system using a simple and accurate model for such a complex system.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Construction & Building Technology
Fedor Aleksandrovich Portnov, Dmitry Aleksandrovich Korolchenko
Summary: This article aims to study the behavior of aluminium structures under high temperatures. The most commonly used aluminium structures in construction and bridge construction were analyzed, and methods to increase their fire resistance were developed. Experimental results showed that these measures significantly improved the fire resistance of aluminium structures and could serve as a basis for their design.
Article
Computer Science, Artificial Intelligence
Ching-Chun Chang
Summary: Authentication mechanisms, including steganography, are crucial in defending against cybercrime. Reversible steganography has been developed to address fidelity-sensitive situations. Predictive analytics and reversible steganographic coding play vital roles in this field. While existing coding methods rely on heuristics and machine learning, this study focuses on achieving optimal coding through mathematical optimization.
CONNECTION SCIENCE
(2022)
Article
Automation & Control Systems
Weifeng Gao, Yu Li
Summary: Many evolutionary algorithms have been proposed to solve nonlinear equation systems (NESs) in the past two decades. However, the benchmark test sets have been neglected, causing a lack of representation for real-world problems. This article introduces a general toolkit for generating artificial test problems and constructs 18 test instances with diverse characteristics, aiming to design NESs. The experimental results demonstrate the poor performance of current algorithms on this new benchmark test set. Additionally, a transformation method and a two-phase method are developed to solve the transformed multimodal optimization problem, outperforming other algorithms.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Marine
Yao Meng, Xianku Zhang, Xiufeng Zhang
Summary: In order to improve the accuracy of parameter identification of ship nonlinear motion mathematical model, a novel identification scheme called nonlinear innovation GWO-SVR (NGWO-SVR) is proposed by embedding grey wolf optimizer-support vector regression (GWO-SVR) into the nonlinear innovation. The NGWO-SVR is used to identify parameters based on full-scale trial data of vessel YUKUN and the generalization of the identified parameters is verified using different trial data. The research results also include indirect sensitivity analysis of the parameters and provide reference for intelligent ship motion control and path planning.
Article
Engineering, Multidisciplinary
Zicheng Zhuang, Yi Min Xie, Qing Li, Shiwei Zhou
Summary: A body-fitted triangular/tetrahedral mesh generation algorithm is developed to generate smooth boundaries in the bi-directional evolutionary structural optimization (BESO) method. The optimization problem is regularized by adding a diffusion term in the objective function. Numerical examples show that the proposed method converges quickly and achieves natural smooth boundaries.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Civil
Semih Gonen, Kultigin Demirlioglu, Emrah Erduran
Summary: This research presents a new framework for determining the optimal sensor locations to identify the modal properties of bridges under modeling uncertainties. The framework includes finite element model generation, sensitivity study, and Monte Carlo simulations to quantify the relative amount of information at candidate sensor locations. Hierarchical clustering algorithm is used to obtain the optimal sensor locations and the number of sensors, and the OSP analysis is carried out using the Effective Independence method.
ENGINEERING STRUCTURES
(2023)
Article
Automation & Control Systems
Ye Tian, Haowen Chen, Haiping Ma, Xingyi Zhang, Kay Chen Tan, Yaochu Jin
Summary: In this paper, a hybrid algorithm is proposed to solve large-scale multi-objective optimization problems (LSMOPs) by combining differential evolution and conjugate gradient method. The proposed algorithm exhibits better convergence and diversity performance compared to existing evolutionary algorithms, mathematical programming methods, and hybrid algorithms on various benchmark and real-world LSMOPs.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2022)
Article
Engineering, Civil
Ebrahim Afsar Dizaj, Mohammad R. Salami, Mohammad M. Kashani
Summary: This paper investigates the nonlinear dynamic behavior and failure probability of multi-span RC bridges supported on piers of unequal heights. Through the development of a three-dimensional nonlinear finite element model and incremental dynamic analyses, the influence of pier height and arrangement on the seismic displacement demand and failure probability of the bridge are studied.
Article
Computer Science, Artificial Intelligence
Guang Li, Jie Wang, Jing Liang, Caitong Yue, Tai-shan Lou
Summary: In this study, a sliding window-based method for parameter optimisation of data stream trend anomaly detection algorithm is proposed. The method treats data stream anomaly detection as a two-objective optimisation problem and uses three optimisation algorithms and ensemble strategies to obtain the optimal parameter settings. Through verification of multiple real parameter data, it is found that this method can achieve optimal parameter settings and provide a reference for the parameter setting of data stream trend anomaly detection algorithm based on sliding window.
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION
(2022)
Article
Engineering, Mechanical
Marco Zucca, Emanuele Reccia, Nicola Longarini, Victor Eremeyev, Pietro Crespi
Summary: This paper analyzes the structural behavior of an existing reinforced concrete bridge subjected to corrosion effects due to carbonation. An efficient procedure based on the implementation of a Finite Element Model (FEM) with Timoshenko beam elements is used. The safety level of the bridge is evaluated considering different load conditions and a retrofitting intervention is proposed.
ENGINEERING FAILURE ANALYSIS
(2023)
Article
Mechanics
Zhenghao Ding, Jun Li, Hong Hao
Summary: An evolutionary algorithm-based artificial neural network is used to identify structural damage and nonlinear hysteresis parameters, with principal component analysis reducing redundant dimensionality of data. The approach successfully addresses the challenge of vanishing or exploding gradients in training the ANN model, achieving accurate identification of system parameters.
INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS
(2022)
Article
Engineering, Multidisciplinary
Yongsheng Han, Bin Xu, Zunyi Duan, Xiaodong Huang
Summary: This paper proposes a new methodology for structural topology optimization that takes into account non-linear continuum damage for stress minimization design. A quasi-static non-local damage model is integrated into a linear finite element analysis to model the structural damage, and the Bi-directional Evolutionary Structural Optimization (BESO) method is used to address singularity issues. The effectiveness of the proposed method is demonstrated through numerical tests and comparison with stiffness maximization design.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Automation & Control Systems
Konstantinos Zisis, Charalampos P. Bechlioulis, George A. Rovithakis
Summary: In this article, we propose an adaptive parameter estimation problem based on the theoretical foundations of radial basis function neural networks, which is solved using the prescribed performance control methodology. This approach provides a compact and user-configurable method for identifying the dynamics of open-loop nonlinear plants in any region of interest.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Engineering, Geological
Ebrahim Afsar Dizaj, Mohammad M. Kashani
Summary: This study investigates the nonlinear dynamic behavior, failure mechanism, and failure probability of reinforced concrete bridge piers under the influence of corrosion damage, non-stationary ground motions, and cross-sectional shape. The results show that the failure mechanism of the corroded bridge piers significantly depends on the ground motion type and cross-sectional shape.
BULLETIN OF EARTHQUAKE ENGINEERING
(2022)
Article
Engineering, Civil
Angelo Aloisio, Matteo Pelliciari, Alessandro Vittorio Bergami, Rocco Alaggio, Bruno Briseghella, Massimo Fragiacomo
Summary: This article defines pinching of RC and wood joints by examining their response differences under repeated cycles. The study shows that RC exhibits higher resilience and stability compared to wood structures.
STRUCTURE AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Mechanics
J. Melchiorre, A. Manuello, F. Marmo, S. Adriaenssens, G. C. Marano
Summary: This paper presents an alternative approach for solving static and kinematic ordinary differential equations for curved beams. The approach uses a finite-difference method and enables the evaluation of the best solution sets considering various arch shapes, loading combinations, cross-section variations, and global radius of arch curvature. The method is applied to 4 different arch case studies and shows good agreement with numerical finite element results. It is useful for the (preliminary) design of arches.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2023)
Article
Computer Science, Interdisciplinary Applications
Marco Martino Rosso, Giulia Marasco, Salvatore Aiello, Angelo Aloisio, Bernardino Chiaia, Giuseppe Carlo Marano
Summary: In this study, an artificial intelligence-based automatic road tunnel defects hierarchical classification framework was developed to improve the efficiency of indirect surveying methods. Deep learning and image processing techniques were used to analyze GPR tunnel linings profiles and detect tunnel linings defects, providing an assessment of the tunnel's overall health state.
COMPUTERS & STRUCTURES
(2023)
Article
Mechanics
Stefano Sirotti, Matteo Pelliciari, Angelo Aloisio, Angelo Marcello Tarantino
Summary: This study proposes an analytical formula to compute the pressure-deflection curves of pre-stretched circular membranes. The formula is calibrated by fitting numerical solutions and can be used for both compressible and incompressible materials. A code is available for computing the formula.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2023)
Article
Mechanics
Matteo Pelliciari, Federico Oyedeji Falope, Luca Lanzoni, Angelo Marcello Tarantino
Summary: The von Mises truss has been extensively studied for its applications in multistable and morphing structures. This study presents a nonlinear solution in finite elasticity, taking into account material nonlinearities, and extends the investigation to the case of a horizontal load. A new hyperelastic model is proposed to capture the hardening behavior of rubbers under large stretches. Additionally, a new formulation in nonlinear elasticity is presented to predict Euler buckling, which considers shear deformation and shows good agreement with finite element and experimental results.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2023)
Article
Engineering, Civil
Angelo Aloisio, Matteo Pelliciari, Junqing Xue, Massimo Fragiacomo, Bruno Briseghella
Summary: This study estimates the effect of a pre-hole filled with high-damping material on the inelastic response spectrum of Integral Abutment Bridges (IAB) with pile foundation, using a calibrated theoretical model based on experimental data.
JOURNAL OF EARTHQUAKE ENGINEERING
(2023)
Review
Engineering, Geological
Giuseppe Carlo Marano, Marco Martino Rosso, Angelo Aloisio, Giansalvo Cirrincione
Summary: Deep learning, particularly through generative adversarial networks (GANs), offers an innovative and beneficial way to generate reliable synthetic data for seismic studies. This study provides a comprehensive review of recent research on GAN-based synthetic generation of ground motion signals and seismic events, which is relevant to various fields such as earth and planetary science, geology, and civil engineering. Understanding the strengths and limitations of current adversarial learning studies in seismology can guide future research efforts.
BULLETIN OF EARTHQUAKE ENGINEERING
(2023)
Article
Construction & Building Technology
Beibei Xiong, Devid Falliano, Luciana Restuccia, Fabio Di Trapani, Cristoforo Demartino, Giuseppe Carlo Marano
Summary: This paper presents a pilot study on the high-strain rate compressive behavior of a novel concrete with substituted recycled plastic aggregates. The study investigates two different substitution strategies and four different replacement levels. The results show that the proposed material has promising high-strain rate compressive behavior, making it suitable for protective techniques against impact and blast loads.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Construction & Building Technology
Angelo Aloisio, Yuri De Santis, Matteo Pelliciari, Marco Martino Rosso, Massimo Fragiacomo, Roberto Tomasi
Summary: This paper investigates the buckling of screws loaded in compression inserted into timber members. The current model for screw buckling based on EC5 proposal has shortcomings in terms of analytical expression and imperfection coefficient. This paper proposes a simple analytical expression for screw buckling and adopts a more accurate expression for lateral deformation based on experimental observation. Furthermore, a FE model and Markov chain Monte Carlo analysis are used to estimate the defect coefficients and validate the proposed deterministic capacity model.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Construction & Building Technology
Valentina Boretti, Laura Sardone, Luis Alberto Bohorquez Grateron, Davide Masera, Giuseppe Carlo Marano, Marco Domaneschi
Summary: This document proposes a generative approach to enhance the efficiency of bridge design by reducing computational costs and modeling efforts. It introduces a workflow that creates flexible geometric models by modifying parameter settings, and aims to define a modeling and analysis strategy for multi-girder composite bridge projects. The results integrate building information modeling (BIM) to explore complex geometries and find cost-effective solutions.
Article
Construction & Building Technology
Raffaele Cucuzza, Angelo Aloisio, Federico Accornero, Antonella Marinelli, Elisa Bassoli, Giuseppe Carlo Marano
Summary: This paper compares numerical and analytical predictions for the shear capacity of fibre-reinforced concrete beams based on experimental literature tests. The authors compared the outcomes of a FE model using the DamageTC3d constitutive model, a literature formulation, and the current proposal of the Eurocode 2 draft for fibre-reinforced structures. The paper evaluates the sensitivity of the beam response to the fracture energy Gf, modified after the Model Code 2010 formulation. The investigation reveals a dependence of the estimated fracture energy on the beam size. Furthermore, the comparison between the numerical estimates and the analytical predictions using the MC2010 and the current EC2 draft proves that the error is substantially independent of the model selection but is strongly affected by the specific case study. This fact confirms the absence of weaknesses in the numerical modelling and highlights the aleatoric uncertainties of the experimental data.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Engineering, Civil
Stefano Sirotti, Angelo Aloisio, Matteo Pelliciari, Bruno Briseghella
Summary: The direct displacement-based design (DDBD) is based on the equivalence between the nonlinear hysteretic response of a structure and a simple linear oscillator with equivalent viscous damping (EVD). However, the existing simple relationships exhibit large dispersion and uncertainty due to the neglect of specific properties of the structural system. This paper proposes an original approach to estimate the EVD of infilled reinforced concrete (RC) frames.
ENGINEERING STRUCTURES
(2023)
Article
Construction & Building Technology
Jun-Qing Xue, Jian-Ping Huang, Alessandra Fiore, Bruno Briseghella, Giuseppe C. Marano
Summary: In this paper, the experimental parameters and results of compressed circular CFST columns with circumferential debonding gap (CDG) are summarized. Detailed finite element simulation procedures based on ABAQUS are introduced and verified by test results. A database of compressed circular CFST columns with and without CDG is established, and new formulations to predict the mechanical behavior of specimens are derived using Evolutionary Polynomial Regression (EPR) methodology, demonstrating good accuracy and low complexity.
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH
(2023)
Proceedings Paper
Construction & Building Technology
Giuseppe C. Marano, Marco M. Rosso, J. Melchiorre
Summary: Scientific research in seismic protection techniques is an active and important field. The main goal is to reduce the impact of earthquakes on structures and infrastructure, minimizing human and socio-economic losses in the long term. Base isolation systems and energy dissipation-based solutions, such as dampers, play a crucial role in this protection. Optimization procedures using computational intelligence metaheuristic algorithms are becoming popular, leading to cost-effective and innovative design solutions.
SEISMIC ISOLATION, ENERGY DISSIPATION AND ACTIVE VIBRATION CONTROL OF STRUCTURES, 17WCSI 2022
(2023)
Proceedings Paper
Engineering, Civil
Marco M. Rosso, Angelo Aloisio, Raffaele Cucuzza, Giuseppe C. Marano, Rocco Alaggio
Summary: This study analyzes the role of ballast in the dynamic train-track-bridge interaction and experimentally validates the mathematical model. The results indicate the significant role of ballast in absorbing train vibrations.
EUROPEAN WORKSHOP ON STRUCTURAL HEALTH MONITORING (EWSHM 2022), VOL 1
(2023)
