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Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

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Journal of Rock Mechanics and Geotechnical engineering 2024年第6期16卷 2198-2218页

作者： Mengqi Wang Y.T.Feng Shaoheng Guan Tongming Qu Zienkiewicz Centre for Computational engineering Faculty of Science and EngineeringSwansea UniversitySwanseaWalesSA18EPUK Institute of Theoretical and Computational Physics Graz University of TechnologyGraz8010Austria department of civil and Environmental engineering Hong Kong University of Science and TechnologyClearwater BayKowloonHong KongChina

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading *** this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular *** obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing *** obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved *** results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

关键词： Granular materials History-dependence Multi-layer perceptron(MLP) Discrete element method FEM-DEM Machine learning

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Low-carbon design towards sustainable city development:Integrating glass space with natural greenery

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Science China(Technological Sciences) 2024年第9期67卷 2659-2674页

作者： CAO Shi-Jie ZHANG CunKuan WANG JunQi FENG ZhuangBo CHEN Gang HAGHIGHAT Fariborz School of Architecture Southeast UniversityNanjing 210096China Jiangsu Province engineering Research Center of Urban Heat and Pollution Control Southeast UniversityNanjing 210096China Global Centre for Clean Air Research Department of Civil and Environmental EngineeringFaculty of Engineering and Physical SciencesUniversity of SurreyGuildfordGU27XHUnited Kingdom The Third Construction Co. Ltd.of China Construction Eighth Engineering DivisionNanjing 210046China Energy and Environment Group Department of BuildingCivil and Environmental EngineeringConcordia UniversityMontrealH3G 1M8Canada

The rapid urban development has caused serious problems such as high energy consumption and carbon emissions,especially under the context of climate *** are particularly energy-intensive,generating about one third of global energyrelated carbon *** with active solutions(like mechanical systems),passive solutions offer the potential to balance energy consumption,thermal comfort,and ecological *** potential solution is the integration of green glass space(GGS)into passive building *** is a transitional building space with glass curtain walls that exhibit excellent insulation performance during ***,GGS is susceptible to overheating during summer,which limits its ***,this work proposes a strategy of integrating vertical greenery into GGS,leveraging the nature-based solution of greenery(i.e.,flourishes in summer and withers in winter)to address this seasonal challenge of *** results demonstrated that the strategic application of vertical greenery can effectively mitigate the overheating in GGS and improve comprehensive *** using full coverage of vertical greenery in a linear layout,the air temperature of GGS and cooling energy consumption were largely reduced by 8.02℃and 12.2%,respectively,while the carbon abatement was enhanced by up to 101.11 *** on a comprehensive evaluation of energy,economy,and environmental benefits,it is recommended to use a greenery configuration with 50%coverage in a vertical linear layout for *** integration of greenery into building design can mitigate adverse environmental impacts,reduce energy consumption,and contribute to the sustainable development of low-carbon cities.

关键词： low-carbon design green glass space vertical greenery greenery configuration carbon abatement

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Bending results of graphene origami reinforced doubly curved shell

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Defence Technology（防务技术） 2024年第5期35卷 198-210页

作者： Nan Yang Yunhe Zou Mohammad Arefi School of Architecture and civil engineering Qiqihar UniversityQiqihar 161006HeilongjiangChina School of Mechanical engineering Inner Mongolia University of TechnologyHohhot 010051Inner MongoliaChina Inner Mongolia Key Laboratory of Special Service Intelligent Robotics Hohhot 010051Inner MongoliaChina faculty of Mechanical engineering Department of Solid MechanicsUniversity of KashanKashan87317-51167Iran

The present work investigates higher order stress,strain and deformation analyses of a shear deformable doubly curved shell manufactures by a Copper(Cu)core reinforced with graphene origami auxetic metamaterial subjected to mechanical and thermal *** effective material properties of the graphene origami auxetic reinforced Cu matrix are developed using micromechanical models cooperate both material properties of graphene and Cu in terms of temperature,volume fraction and folding *** principle of virtual work is used to derive governing equations with accounting thermal *** numerical results are analytically obtained using Navier's technique to investigate impact of significant parameters such as thermal loading,graphene amount,folding degree and directional coordinate on the stress,strain and deformation responses of the *** graphene origami materials may be used in aerospace vehicles and structures and defence technology because of their low weight and high stiffness.A verification study is presented for approving the formulation,solution methodology and numerical results.

关键词： Graphene origami Copper matrix Doubly curved Shear deformable Auxetic metamaterial

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Wave propagation of a functionally graded plate via integral variables with a hyperbolic arcsine function

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Earthquake engineering and engineering Vibration 2024年第3期23卷 547-561页

作者： Mokhtar Ellali Mokhtar Bouazza Ashraf M.Zenkour Smart structures Laboratory University of Ain TemouchentAin Temouchent 46000Algeria department of civil engineering University Tahri Mohamed of BecharBechar 08000Algeria department of Mathematics Faculty of ScienceKing Abdulaziz UniversityJeddah 21589Saudi Arabia Laboratory of Materials and Hydrology(LMH) University of Sidi Bel AbbesSidi Bel Abbes 22000Algeria department of Mathematics Faculty of ScienceKafrelsheikh UniversityKafrelsheikh 33516Egypt

Several studies on functionally graded materials(FGMs)have been done by researchers,but few studies have dealt with the impact of the modification of the properties of materials with regard to the functional propagation of the waves in *** work aims to explore the effects of changing compositional characteristics and the volume fraction of the constituent of plate materials regarding the wave propagation response of thick plates of *** model is based on a higher-order theory and a new displacement field with four unknowns that introduce indeterminate integral variables with a hyperbolic arcsine *** FGM plate is assumed to consist of a mixture of metal and ceramic,and its properties change depending on the power functions of the thickness of the plate,such as linear,quadratic,cubic,and inverse *** utilizing Hamilton’s principle,general formulae of the wave propagation were obtained to establish wave modes and phase velocity curves of the wave propagation in a functionally graded plate,including the effects of changing compositional characteristics of materials.

关键词： FGM plate effects of material properties wave propagation indeterminate integral variables inverse sinus hyperbolic function

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Automated deformation monitoring for urban subway tunnelling risk assessment: a case study from the Wuhan Metro line 12

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Journal of Earth Science 2024年

作者： Yuyong Jiao Jianfeng Qi Hongbin An Luyi Shen Fei Zheng Zhi Li You Zhang Lingling He faculty of engineering， China University of Geosciences (Wuhan) Wuhan Metro Inc. School of civil and Hydraulic engineering， Huazhong University of Science and Technology China Railway Construction Investment Group Corporation Ltd. department of civil engineering， Monash University

Monitoring deformation is of critical importance for tunnel boring projects. This importance is further amplified for the metro construction project that involves boring beneath or near susceptible civil infrastructures. Here， we present a case study that uses robotic total station to preform automated deformation monitoring inside a tunnel during the excavation. Further， enabled with the Internet of Things technology， the monitoring data are streamlined through wireless internet access points and processed by a remote control center. A complete suite of software is deployed that can 1. process the monitoring data automatically. 2. set different triggering threshold reflecting various levels of hazardous incidents. 3. storing the data for further analysis that visualize the data， quantify overall risk levels and conduct predictive modelling. Built upon this automated system， a triage of risk response protocol is established that preforms reactive treatment according to the levels of reported hazards. A de-risk process， involving third party review， is also established. Overall， this report demonstrates our effort in monitoring the tunnel’s deformation with an automated system to save cost and reduce human induced errors. This report can be a useful reference for other engineers preforming metro tunneling tasks.

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Influence of Various Earth-Retaining Walls on the Dynamic Response Comparison Based on 3D Modeling

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Computer Modeling in engineering & Sciences 2024年第6期139卷 2835-2863页

作者： Muhammad Akbar Huali Pan Jiangcheng Huang Bilal Ahmed Guoqiang Ou Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu610000China Institute of International Rivers and Eco-Security Yunnan UniversityKunming650500China department of Structural engineering Faculty of Civil EngineeringDoctoral SchoolAkademicka 2Silesian University of TechnologyGliwice44-100Poland

The present work aims to assess earthquake-induced earth-retaining(ER)wall *** study is on the dynamics analysis of various earth-retaining wall designs in hollow precast concrete panels,reinforcement concrete facing panels,and gravity-type earth-retaining *** finite element(FE)simulations utilized a 3D plane strain condition to model full-scale ER walls and numerous nonlinear dynamics *** seismic performance of differentmodels,which includes reinforcement concrete panels and gravity-type and hollowprecast concrete ER walls,was simulated and examined using the FE *** also displays comparative studies such as stress distribution,deflection of the wall,acceleration across the wall height,lateral wall displacement,lateral wall pressure,and backfill plastic *** components of the created ER walls were found throughout this research *** is a granular reinforcement backfill,while the other is a wall-facing panel and base *** dynamic response effects of varied earth-retaining walls have also been *** was discovered that the facing panel of the model significantly impacts the earthquake-induced displacement of ER *** proposed analytical model’s validity has been evaluated and compared with the reinforcement concrete facing panels,gravity-type ER wall,scientifically available data,and American Association of State Highway and Transportation Officials(AASHTO)guidelines results based on FE *** results of the observations indicate that the hollow prefabricated concrete ER wall is the most feasible option due to its lower displacement and high-stress distribution compared to the two *** methodology and results of this study establish standards for future analogous investigations and professionals,particularly in light of the increasing computational capabilities of desktop computers.

关键词： Seismic analysis finite element modeling earth-retaining ER walls dynamic response structural resilience

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Introduction to the Special Issue on Computational Intelligent Systems for Solving Complex engineering Problems: Principles and Applications

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2023-2027页

作者： Danial Jahed Armaghani Ahmed SalihMohammed Ramesh Murlidhar Bhatawdekar Pouyan Fakharian Ashutosh Kainthola Wael Imad Mahmood School of civil and Environmental engineering University of Technology SydneyUltimoNSW 2007Australia College of engineering University of SulaimaniKurdistan46001Iraq engineering department American University of IraqSulaimaniKurdistan46001Iraq Centre of Tropical Geoengineering(GEOTROPIK) Institute of Smart Infrastructure and Innovative Engineering(ISIIC)Faculty of Civil EngineeringUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia faculty of civil engineering Semnan UniversitySemnanIran Geo-engineering and Computing Laboratory Banaras Hindu UniversityVaranasi221005India Scientific Research Centre Soran UniversitySoranErbilKurdistan-Region44008Iraq

Computational Intelligent(CI)systems represent a pivotal intersection of cutting-edge technologies and complex engineering challenges aimed at solving real-world *** comprehensive body of work delves into the realm of CI,which is designed to tackle intricate and multifaceted engineering problems through advanced computational *** history of CI systems is a fascinating journey that spans several decades and has its roots in the development of artificial intelligence and machine learning *** a wide array of practical examples and case studies,this special issue bridges the gap between theoretical concepts and practical implementation,shedding light on how CI systems can optimize processes,design solutions,and inform decisions in complex engineering *** compilation stands as an essential resource for both novice learners and seasoned practitioners,offering a holistic perspective on the potential of CI in reshaping the future of engineering problem-solving.

关键词： offering bridges landscape

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Intelligent Diagnosis of Highway Bridge Technical Condition Based on Defect Information

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Structural Durability & Health Monitoring 2024年第6期18卷 871-889页

作者： Yanxue Ma Xiaoling Liu Bing Wang Ying Liu faculty of Maritime and Transportation Ningbo UniversityNingbo315211China School of civil&Environmental engineering and Geography Science Ningbo UniversityNingbo315211China

In the bridge technical condition assessment standards,the evaluation of bridge conditions primarily relies on the defects identified through manual inspections,which are determined using the comprehensive hierarchical analysis ***,the relationship between the defects and the technical condition of the bridges warrants further *** address this situation,this paper proposes a machine learning-based intelligent diagnosis model for the technical condition of highway ***,collect the inspection records of highway bridges in a certain region of China,then standardize the severity of diverse defects in accordance with relevant ***,in order to enhance the independence between the defects,the key defect indicators were screened using Principal Component Analysis(PCA)in combination with the weights of the building *** on this,an enhanced Naive Bayesian Classification(NBC)algorithm is established for the intelligent diagnosis of technical conditions of highway bridges,juxtaposed with four other algorithms for ***,key defect variables that affect changes in bridge grades are *** results showed that the technical condition level of the superstructure had the highest correlation with cracks;the PCA-NBC algorithm achieved an accuracy of 93.50%of the predicted values,which was the highest improvement of 19.43%over other *** purpose of this paper is to provide inspectors with a convenient and predictive information-rich method to intelligently diagnose the technical condition of bridges based on bridge *** results of this research can help bridge inspectors and even non-specialists to better understand the condition of bridge defects.

关键词： Highway bridges defects Naive Bayesian classification principal component analysis machine learning

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Forecasting measured responses of structures using temporal deep learning and dual attention

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Frontiers of Structural and civil engineering 2024年第6期18卷 832-850页

作者： Viet-Hung DANG Trong-Phu NGUYEN Thi-Lien PHAM Huan X.NGUYEN department of Structural Mechanics Hanoi University of Civil EngineeringHanoi 11600Vietnam faculty of Applied Science University of Economics-Technology for IndustriesHanoi 11600Vietnam London Digital Twin Research Centre Faculty of Science and TechnologyMiddlesex UniversityLondon NW44BTUK International School Vietnam National UniversityHanoi 11600Vietnam

The objective of this study is to develop a novel and efficient model for forecasting the nonlinear behavior of structures in response to time-varying random *** key idea is to design a deep learning architecture to leverage the relationships,between external excitations and structure's vibration signals,and between historical values and future values,within multiple time-series *** proposed method consists of two main steps:the first step applies a global attention mechanism to combine multiple-measured time series and time-varying excitation into a weighted time series before feeding it to a temporal architecture;the second step utilizes a self-attention mechanism followed by a fully connected layer to predict multi-step future *** viability of the proposed method is demonstrated via two case studies involving synthetic data from a three-dimensional(3D)reinforced concrete structure and experimental data from an 18-story steel ***,comparison and robustness studies are carried out,showing that the proposed method outperforms conventional methods and maintains high performance in the presence of noise with an amplitude of less than 10%.

关键词： structural dynamic time-varying excitation deep learning signal processing response forecasting

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A deep neural network based surrogate model for damage identification in full-scale structures with incomplete noisy measurements

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Frontiers of Structural and civil engineering 2024年第3期18卷 393-410页

作者： Tram BUI-NGOC Duy-Khuong LY Tam T TRUONG Chanachai THONGCHOM T.NGUYEN-THOI Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam faculty of Mechanical-Electrical and Computer engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam faculty of civil engineering School of TechnologyVan Lang UniversityHo Chi Minh City 70000Vietnam department of Computer Science Aarhus UniversityAarhus 8000Denmark Thammasat University research unit in structural and foundation engineering Department of Civil EngineeringThammasat UniversityPathumthani 12120Thailand Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh City 70000Vietnam Thammasat School of engineering Thammasat UniversityPathumthani 12120Thailand

The paper introduces a novel approach for detecting structural damage in full-scale structures using surrogate models generated from incomplete modal data and deep neural networks(DNNs).A significant challenge in this field is the limited availability of measurement data for full-scale structures,which is addressed in this paper by generating data sets using a reduced finite element(FE)model constructed by SAP2000 software and the MATLAB programming *** surrogate models are trained using response data obtained from the monitored structure through a limited number of measurement *** proposed approach involves training a single surrogate model that can quickly predict the location and severity of damage for all potential *** achieve the most generalized surrogate model,the study explores different types of layers and hyperparameters of the training algorithm and employs state-of-the-art techniques to avoid overfitting and to accelerate the training *** approach’s effectiveness,efficiency,and applicability are demonstrated by two numerical *** study also verifies the robustness of the proposed approach on data sets with sparse and noisy measured ***,the proposed approach is a promising alternative to traditional approaches that rely on FE model updating and optimization algorithms,which can be computationally *** approach also shows potential for broader applications in structural damage detection.

关键词： vibration-based damage detection deep neural network full-scale structures finite element model updating noisy incomplete modal data

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