Structural Health Monitoring(SHM)systems play a key role in managing buildings and infrastructure by delivering vital insights into their strength and structural integrity.There is a need for more efficient techniques...Structural Health Monitoring(SHM)systems play a key role in managing buildings and infrastructure by delivering vital insights into their strength and structural integrity.There is a need for more efficient techniques to detect defects,as traditional methods are often prone to human error,and this issue is also addressed through image processing(IP).In addition to IP,automated,accurate,and real-time detection of structural defects,such as cracks,corrosion,and material degradation that conventional inspection techniques may miss,is made possible by Artificial Intelligence(AI)technologies like Machine Learning(ML)and Deep Learning(DL).This review examines the integration of computer vision and AI techniques in Structural Health Monitoring(SHM),investigating their effectiveness in detecting various forms of structural deterioration.Also,it evaluates ML and DL models in SHM for their accuracy in identifying and assessing structural damage,ultimately enhancing safety,durability,and maintenance practices in the field.Key findings reveal that AI-powered approaches,especially those utilizing IP and DL models like CNNs,significantly improve detection efficiency and accuracy,with reported accuracies in various SHM tasks.However,significant research gaps remain,including challenges with the consistency,quality,and environmental resilience of image data,a notable lack of standardized models and datasets for training across diverse structures,and concerns regarding computational costs,model interpretability,and seamless integration with existing systems.Future work should focus on developing more robust models through data augmentation,transfer learning,and hybrid approaches,standardizing protocols,and fostering interdisciplinary collaboration to overcome these limitations and achieve more reliable,scalable,and affordable SHM systems.展开更多
Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement ...Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement in the field of material inverse design.However,VAEs are inherently prone to generating blurred images,posing challenges for precise inverse design and microstructure manufacturing.While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent,it simultaneously imposes a substantial burden on target optimization due to an excessively high search space.To address these limitations,this study adopts a Variational Autoencoder guided Conditional Diffusion Generative Model(VAE-CDGM)framework integrated with Bayesian optimization to achieve the inverse design of composite materials with targeted mechanical properties.The VAE-CDGM model synergizes the strengths of VAEs and Denoising Diffusion Probabilistic Models(DDPM),enabling the generation of high-quality,sharp images while preserving a manipulable latent space.To accommodate varying dimensional requirements of the latent space,two optimization strategies are proposed.When the latent space dimensionality is excessively high,SHapley Additive exPlanations(SHAP)sensitivity analysis is employed to identify critical latent features for optimization within a reduced subspace.Conversely,direct optimization is performed in the low-dimensional latent space of VAE-CDGM when dimensionality is modest.The results demonstrate that both strategies accurately achieve the targeted design of composite materials while circumventing the blurred reconstruction flaws of VAEs,which offers a novel pathway for the precise design of advanced materials.展开更多
The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,an...The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications.展开更多
Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises stru...Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.展开更多
Cemented and mechanically clamped types of end fittings(fitting-C and fitting-M)are commonly used in transformer bushings.During the Luding Ms 6.8 earthquake that occurred in China on September 5,2022,all transformer ...Cemented and mechanically clamped types of end fittings(fitting-C and fitting-M)are commonly used in transformer bushings.During the Luding Ms 6.8 earthquake that occurred in China on September 5,2022,all transformer bushings with the two types of end fittings in a 500 kV substation were damaged.Post-earthquake field investigations were conducted,and the failures of the two types of bushings were compared.Two elementary simulation models of the transformer-bushing systems were developed to simulate the engineering failures,and further compute their seismic responses for comparison.The results indicate that the hitch lugs of the connection flange are structurally harmful to seismic resistance.Fitting-M can decrease the bending stiffness of the bushing due to the flexible sealing rubber gasket.Since it provides a more flexible connection that dissipates energy,the peak accelerations and relative displacements at the top of the bushing are significantly lower than those of the bushing with fitting-C.Compared with fitting-C,fitting-M transfers the high-stress areas from the connection flange to the root of the porcelain,so the latter becomes the most vulnerable component.Fitting-M increases the failure risk of the low-strength porcelain,indicating the unsuitability of applying it in high-intensity fortification regions.展开更多
This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not ...This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not necessarily for real-time testing, but rather for models that involve large-scale physical sub-structures and highly nonlinear numerical models. Four case studies are presented and discussed. In the first case study, the accuracy of integration schemes including two widely used methods, namely, modified version of the implicit Newmark with fixed-number of iteration （iterative） and the operator-splitting （non-iterative） is examined through pure numerical simulations. The second case study presents the results of 10 hybrid simulations repeated with the two aforementioned integration methods considering various time steps and fixed-number of iterations for the iterative integration method. The physical sub-structure in these tests consists of a single-degree-of-freedom （SDOF） cantilever column with replaceable steel coupons that provides repeatable highly- nonlinear behavior including fracture-type strength and stiffness degradations. In case study three, the implicit Newmark with fixed-number of iterations is applied for hybrid simulations of a 1：2 scale steel moment frame that includes a relatively complex nonlinear numerical substructure. Lastly, a more complex numerical substructure is considered by constructing a nonlinear computational model of a moment frame coupled to a hybrid model ofa 1：2 scale steel gravity frame. The last two case studies are conducted on the same porotype structure and the selection of time steps and fixed number of iterations are closely examined in pre-test simulations. The generated unbalance forces is used as an index to track the equilibrium error and predict the accuracy and stability of the simulations.展开更多
Reversible control of surface wettability has wide applications in lab-on-chip systems, tunable optical lenses, and microfluidic tools. Using a graphene sheet as a sam- ple material and molecular dynamic simulations, ...Reversible control of surface wettability has wide applications in lab-on-chip systems, tunable optical lenses, and microfluidic tools. Using a graphene sheet as a sam- ple material and molecular dynamic simulations, we demon- strate that strain engineering can serve as an effective way to control the surface wettability. The contact angles 0 of water droplets on a graphene vary from 72.5° to 106° under biaxial strains ranging from -10% to 10% that are applied on the graphene layer. For an intrinsic hydrophilic surface （at zero strain）, the variation of 0 upon the applied strains is more sensitive, i.e., from 0° to 74.8°. Overall the cosines of the contact angles exhibit a linear relation with respect to the strains. In light of the inherent dependence of the contact an- gle on liquid-solid interfacial energy, we develop an analytic model to show the cos 0 as a linear function of the adsorption energy Eads of a single water molecule over the substrate sur- face. This model agrees with our molecular dynamic results very well. Together with the linear dependence of Eads on bi- axial strains, we can thus understand the effect of strains on the surface wettability. Thanks to the ease of reversibly ap- plying mechanical strains in micro/nano-electromechanical systems, we believe that strain engineering can be a promis- ing means to achieve the reversibly control of surface wetta- bility.展开更多
Accurate prediction of ductile fracture requires determining the material properties,including the parameters of the constitutive and ductile fracture model,which represent the true material response.Conventional cali...Accurate prediction of ductile fracture requires determining the material properties,including the parameters of the constitutive and ductile fracture model,which represent the true material response.Conventional calibration of material parameters often relies on a trial-and-error approach,in which the parameters are manually adjusted until the corresponding finite element model results in a response matching the experimental global response.The parameter estimates are often subjective.To address this issue,in this paper we treat the identification of material parameters as an optimization problem and introduce the particle swarm optimization(PSO)algorithm as the optimization approach.We provide material parameters of two uncoupled ductile fracture models—the Rice and Tracey void growth model(RT-VGM)and the micro-mechanical void growth model(MM-VGM),and a coupled model—the gurson-Tvergaard-Needleman(GTN)model for ASTM A36,A572 Gr.50,and A992 structural steels using an automated PSO method.By minimizing the difference between the experimental results and finite element simulations of the load-displacement curves for a set of tests of circumferentially notched tensile(CNT)bars,the calibration procedure automatically determines the parameters of the strain hardening law as well as the uncoupled models and the coupled GTN constitutive model.Validation studies show accurate prediction of the load-displacement response and ductile fracture initiation in V-notch specimens,and confirm the PSO algorithm as an effective and robust algorithm for seeking ductile fracture model parameters.PSO has excellent potential for identifying other fracture models(e.g.,shear modified GTN)with many parameters that can give rise to more accurate predictions of ductile fracture.Limitations of the PSO algorithm and the current calibrated ductile fracture models are also discussed in this paper.展开更多
Isogeometric analysis(IGA),which aims at integrating CAD and CAE models,is one of the most active research topics in both computational mechanics and computer-aided geometric design.The rapidly growing interests in IG...Isogeometric analysis(IGA),which aims at integrating CAD and CAE models,is one of the most active research topics in both computational mechanics and computer-aided geometric design.The rapidly growing interests in IGA has led to profound developments of relevant theories and applications,one of which being structural optimization.With the rapid growth of researches in IGA,this special issue contributes to highlight recent developments,challenges and opportunities of IGA and IGA-based structural design optimization,with focuses on theory development,numerical implementations and potential applications.展开更多
There is great interest in the use of natural fibers as reinforcement to obtain new construction materials due to its low cost, high availability and reduced energy consumption for its production. This paper evaluates...There is great interest in the use of natural fibers as reinforcement to obtain new construction materials due to its low cost, high availability and reduced energy consumption for its production. This paper evaluates the incorporation of sisal fibers of 20 mm and 40 mm in length and volume fraction of 0.5% and 1% for concrete masonry structural blocks, and determines the use of these units to build prisms and mini-walls. Laboratory tests were carried out to characterize the physical of blocks and mortar, in addition to the axial compression tests of the units, prisms, and mini-walls. The sisal had low apparent density and high water absorption, which is a common feature of such material due to the high incidence of permeable pores. The physical properties of the blocks with and without addition complied with the standard requirements established to validate their use. The obtained results showed that the fiber-reinforced mini-walls obtained values very close to or even higher than those obtained for the mini-walls without fibers, demonstrating better performance than the blocks and prisms.展开更多
This study numerically investigates the seismic response of a nine-story self-centering concentrically braced frame building incorporating force-limiting connections between the floor system and the lateral force-resi...This study numerically investigates the seismic response of a nine-story self-centering concentrically braced frame building incorporating force-limiting connections between the floor system and the lateral force-resisting system.Nonlinear earthquake simulations are conducted under design basis earthquake ground motions,and the results are compared against a baseline model with rigid-elastic connections.The study discusses connection design considerations and evaluates the effectiveness of force-limiting connections in mitigating higher-mode effects.The findings show that force-limiting connections significantly reduce the magnitude and variability of floor accelerations,brace forces,and connection forces,while maintaining comparable story drifts.limiting Force-connections primarily reduce the contribution of higher-mode responses,while the controlled rocking base mechanism modifies the first-mode response.Overall,the reduced dispersion in structural response improves the reliability of seismic design and enhances resilience by minimizing damage to both structural components and acceleration-sensitive nonstructural elements.展开更多
This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC)...This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC).For dataset collection,an extensive experimental program was designed to estimate the unconfined compressive strength(Qu)of heavy metal-contaminated soils collected from awide range of land use pattern,i.e.residential,industrial and roadside soils.Accordingly,a robust comparison of predictive performances of four data-driven models including extreme learning machines(ELMs),gene expression programming(GEP),random forests(RFs),and multiple linear regression(MLR)has been presented.For completeness,a comprehensive experimental database has been established and partitioned into 80%for training and 20%for testing the developed models.Inputs included varying levels of heavy metals like Cd,Cu,Cr,Pb and Zn,along with OPC.The results revealed that the GEP model outperformed its counterparts:explaining approximately 96%of the variability in both training(R2=0.964)and testing phases(R^(2)=0.961),and thus achieving the lowest RMSE and MAE values.ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics.GEP also provided the benefit of traceable mathematical equation,enhancing its applicability not just as a predictive but also as an explanatory tool.Despite its insights,the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region,which may affect the generalizability of the findings to different contamination profiles or environmental conditions.The study recommends GEP for predicting Qu in heavy metal-contaminated soils,and suggests further research to adapt these models to different environmental conditions.展开更多
This paper presents an improved understanding of coupled hydro-thermo-mechanical(HTM) hydraulic fracturing of quasi-brittle rock using the bonded particle model(BPM) within the discrete element method(DEM). BPM has be...This paper presents an improved understanding of coupled hydro-thermo-mechanical(HTM) hydraulic fracturing of quasi-brittle rock using the bonded particle model(BPM) within the discrete element method(DEM). BPM has been recently extended by the authors to account for coupled convective econductive heat flow and transport, and to enable full hydro-thermal fluidesolid coupled modeling.The application of the work is on enhanced geothermal systems(EGSs), and hydraulic fracturing of hot dry rock(HDR) is studied in terms of the impact of temperature difference between rock and a flowing fracturing fluid. Micro-mechanical investigation of temperature and fracturing fluid effects on hydraulic fracturing damage in rocks is presented. It was found that fracture is shorter with pronounced secondary microcracking along the main fracture for the case when the convectiveeconductive thermal heat exchange is considered. First, the convection heat exchange during low-viscosity fluid infiltration in permeable rock around the wellbore causes significant rock cooling, where a finger-like fluid infiltration was observed. Second, fluid infiltration inhibits pressure rise during pumping and delays fracture initiation and propagation. Additionally, thermal damage occurs in the whole area around the wellbore due to rock cooling and cold fluid infiltration. The size of a damaged area around the wellbore increases with decreasing fluid dynamic viscosity. Fluid and rock compressibility ratio was found to have significant effect on the fracture propagation velocity.展开更多
Two full-scale experiments using controlled blasting were conducted in the Port of Tokachi on Hokkaido Island, Japan,to assess the behavior of piles and pipelines subjected to lateral spreading.Test specimens were ext...Two full-scale experiments using controlled blasting were conducted in the Port of Tokachi on Hokkaido Island, Japan,to assess the behavior of piles and pipelines subjected to lateral spreading.Test specimens were extensively instrumented with strain gauges to measure the distribution of moment during lateral spreading.This allowed us to compute the loading condition,as well as to conduct damage and performance assessments on the piles and pipelines.This paper presents the test results and discussions on the response of single piles and pipelines observed from the full-scale experiments.Based on the test results,it can be concluded that using controlled blasting successfully liquefied the soil,and subsequently induced lateral spreading.The movements of the single pile,as well as the transverse pipelines,were approximately the same as the free field soil movement.Observed moment distribution of the single pile indicated that global translation of the liquefied soil layer provided insignificant force to the pile.In addition,the degree of fixity at the pile tip significantly affected the moment along the pile as well as the pile head displacement.The pile with a higher degree of fixity at the pile tip had smaller pile head displacement but larger maximum moment.展开更多
Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data ...Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.展开更多
Deposition patterns can significantly affect residual stress distribution in additive manufacturing processes.In this paper,a novel pattern,the S-pattern,is proposed for the metal additive manufacturing process.The fi...Deposition patterns can significantly affect residual stress distribution in additive manufacturing processes.In this paper,a novel pattern,the S-pattern,is proposed for the metal additive manufacturing process.The finite element method is used to study the temperature field and the stress field of a cuboid structure under the S-pattern and five other representative patterns:zig-zag,raster,alternate-line,in-out spiral,and out-in spiral.The results show that the S-pattern achieves the lowest values of both equivalent residual stress and maximum principal residual stress,and the warpage of the S-pattern is close to that of counterparts.By analyzing the temperature and stress fields under all patterns,it is found that the residual stress distribution is determined by the uniformity of temperature distribution which is correlated with the peak temperatures of corners.The equivalent residual stress and the maximum principal residual stress are inversely correlated with the average peak temperature and the minimum peak temperature of corners,respectively.These correlations between temperature and residual stress provide an effective approach to evaluate the residual stress of different patterns and guide the deposition process in practice.展开更多
A model for evaluating structural damage of recycled aggregate concrete filled steel tube （RCFST） columns under seismic effects is proposed in this paper. The proposed model takes the lateral deformation and the eff...A model for evaluating structural damage of recycled aggregate concrete filled steel tube （RCFST） columns under seismic effects is proposed in this paper. The proposed model takes the lateral deformation and the effect of repeated cyclic loading into account. Available test results were collected and utilized to calibrate the parameters of the proposed model. A seismic test for six RCFST columns was also performed to validate the proposed damage assessment model. The main test parameters were the recycled coarse aggregate （RCA） replacement percentage and the bond-slip property. The test results indicated that the seismic performance of the RCFST member depends on the RCA contents and their damage index increases as the RCA replacement percentage increases. It is also indicated that the damage degree of RCFST changes with the variation of the RCA replacement percentage. Finally, comparisons between the RCA contents, lateral deformation ratio and damage degree were implemented. It is suggested that an improvement procedure should be implemented in order to compensate for the performance difference between the RCFST and normal concrete filled steel tubes （CFST）.展开更多
The OpenSees computational platform has allowed unprecedented opportunities for conducting seismic nonlinear soil-structure interaction simulations.On the geotechnical side,capabilities such as coupled solid-fluid for...The OpenSees computational platform has allowed unprecedented opportunities for conducting seismic nonlinear soil-structure interaction simulations.On the geotechnical side,capabilities such as coupled solid-fluid formulations and nonlinear incrementalplasticity approaches allow for representation of the involved dynamic/seismic responses.This paper presents recent research that facilitated such endeavors in terms of response of ground-foundation-structure systems using advanced material modeling techniques and high-performance computing resources.Representative numerical results are shown for large-scale soil-structure systems,and ground modification liquefaction countermeasures.In addition,graphical user interface enabling tools for routine usage of such 3D simulation environments are presented,as an important element in support of wider adoption and practical applications.In this context,Performance-Based Earthquake Engineering(PBEE)analysis of bridge-ground systems is highlighted as an important topical application.展开更多
In the past 20 years,recycled aggregate concrete(RAC),as a type of low-carbon concrete,has become a worldwide focus of research.However,the design methodology for RAC structural components remains a challenge.Conseque...In the past 20 years,recycled aggregate concrete(RAC),as a type of low-carbon concrete,has become a worldwide focus of research.However,the design methodology for RAC structural components remains a challenge.Consequently,demands for a unified design of natural aggregate concrete(NAC)and RAC components have been presented.Accordingly,this study analyses the necessity of a unified design theory and provides an in-depth demonstration of the strength determination,compressive constitutive relationship,and design method of concrete components.The coefficient of variation of RAC strength is found to be generally higher than that of NAC strength.The compressive and tensile strengths of RAC can be defined and determined using the same method as that used for NAC.The uniaxial compressive constitutive relationship between NAC and RAC has a unified mathematical expression.However,the elastic modulus of RAC decreases,and its brittleness exhibits an increasing trend compared with that of NAC.Finally,to unify the design formulae of RAC and NAC components for bearing capacity,modification factors for RAC components are proposed considering safety and reliability.Additionally,the feasibility of the proposed unified time-dependent design theory is demonstrated in terms of conceptual design and structural measures considering the effects of strength degradation and reinforcement corrosion.It is believed that this study enriches and develops the basic theory of concrete structures.展开更多
The serviceability of water supply networks(WSNs)under seismic loads has significant importance for estimating the probable losses and the impact of diminished functionality on affected communities.The innovation pres...The serviceability of water supply networks(WSNs)under seismic loads has significant importance for estimating the probable losses and the impact of diminished functionality on affected communities.The innovation presented in this paper is suggesting a new strategy to evaluate the seismic serviceability of WSNs,utilizing their operational physical mechanism.On one hand,this method can obtain the seismic serviceability of each node as well as entire WSNs.On the other hand,this method can dynamically reflect the propagation of randomness from ground motions to WSNs.First,a finite element model is established to capture the seismic response of buried pipe networks,and a leakage model is suggested to obtain the leakage area of WSNs.Second,the transient flow analysis of WSNs with or without leakage is derived to obtain dynamic water flow and pressure.Third,the seismic serviceability of WSNs is analyzed based on the probability density evolution method(PDEM).Finally,the seismic serviceability of a real WSN in Mianzhu city is assessed to illustrate the method.The case study shows that randomness from the ground motions can obviously affect the leakage state and the probability density of the nodal head during earthquakes.展开更多
文摘Structural Health Monitoring(SHM)systems play a key role in managing buildings and infrastructure by delivering vital insights into their strength and structural integrity.There is a need for more efficient techniques to detect defects,as traditional methods are often prone to human error,and this issue is also addressed through image processing(IP).In addition to IP,automated,accurate,and real-time detection of structural defects,such as cracks,corrosion,and material degradation that conventional inspection techniques may miss,is made possible by Artificial Intelligence(AI)technologies like Machine Learning(ML)and Deep Learning(DL).This review examines the integration of computer vision and AI techniques in Structural Health Monitoring(SHM),investigating their effectiveness in detecting various forms of structural deterioration.Also,it evaluates ML and DL models in SHM for their accuracy in identifying and assessing structural damage,ultimately enhancing safety,durability,and maintenance practices in the field.Key findings reveal that AI-powered approaches,especially those utilizing IP and DL models like CNNs,significantly improve detection efficiency and accuracy,with reported accuracies in various SHM tasks.However,significant research gaps remain,including challenges with the consistency,quality,and environmental resilience of image data,a notable lack of standardized models and datasets for training across diverse structures,and concerns regarding computational costs,model interpretability,and seamless integration with existing systems.Future work should focus on developing more robust models through data augmentation,transfer learning,and hybrid approaches,standardizing protocols,and fostering interdisciplinary collaboration to overcome these limitations and achieve more reliable,scalable,and affordable SHM systems.
文摘Inverse design of advanced materials represents a pivotal challenge in materials science.Leveraging the latent space of Variational Autoencoders(VAEs)for material optimization has emerged as a significant advancement in the field of material inverse design.However,VAEs are inherently prone to generating blurred images,posing challenges for precise inverse design and microstructure manufacturing.While increasing the dimensionality of the VAE latent space can mitigate reconstruction blurriness to some extent,it simultaneously imposes a substantial burden on target optimization due to an excessively high search space.To address these limitations,this study adopts a Variational Autoencoder guided Conditional Diffusion Generative Model(VAE-CDGM)framework integrated with Bayesian optimization to achieve the inverse design of composite materials with targeted mechanical properties.The VAE-CDGM model synergizes the strengths of VAEs and Denoising Diffusion Probabilistic Models(DDPM),enabling the generation of high-quality,sharp images while preserving a manipulable latent space.To accommodate varying dimensional requirements of the latent space,two optimization strategies are proposed.When the latent space dimensionality is excessively high,SHapley Additive exPlanations(SHAP)sensitivity analysis is employed to identify critical latent features for optimization within a reduced subspace.Conversely,direct optimization is performed in the low-dimensional latent space of VAE-CDGM when dimensionality is modest.The results demonstrate that both strategies accurately achieve the targeted design of composite materials while circumventing the blurred reconstruction flaws of VAEs,which offers a novel pathway for the precise design of advanced materials.
文摘The biological stabilization of soil using microbially induced carbonate precipitation(MICP)employs ureolytic bacteria to precipitate calcium carbonate(CaCO3),which binds soil particles,enhancing strength,stiffness,and erosion resistance.The unconfinedcompressive strength(UCS),a key measure of soil strength,is critical in geotechnical engineering as it directly reflectsthe mechanical stability of treated soils.This study integrates explainable artificialintelligence(XAI)with geotechnical insights to model the UCS of MICP-treated sands.Using 517 experimental data points and a combination of various input variables—including median grain size(D50),coefficientof uniformity(Cu),void ratio(e),urea concentration(Mu),calcium concentration(Mc),optical density(OD)of bacterial solution,pH,and total injection volume(Vt)—fivemachine learning(ML)models,including eXtreme gradient boosting(XGBoost),Light gradient boosting machine(LightGBM),random forest(RF),gene expression programming(GEP),and multivariate adaptive regression splines(MARS),were developed and optimized.The ensemble models(XGBoost,LightGBM,and RF)were optimized using the Chernobyl disaster optimizer(CDO),a recently developed metaheuristic algorithm.Of these,LightGBM-CDO achieved the highest accuracy for UCS prediction.XAI techniques like feature importance analysis(FIA),SHapley additive exPlanations(SHAP),and partial dependence plots(PDPs)were also used to investigate the complex non-linear relationships between the input and output variables.The results obtained have demonstrated that the XAI-driven models can enhance the predictive accuracy and interpretability of MICP processes,offering a sustainable pathway for optimizing geotechnical applications.
文摘Optimization is the key to obtaining efficient utilization of resources in structural design.Due to the complex nature of truss systems,this study presents a method based on metaheuristic modelling that minimises structural weight under stress and frequency constraints.Two new algorithms,the Red Kite Optimization Algorithm(ROA)and Secretary Bird Optimization Algorithm(SBOA),are utilized on five benchmark trusses with 10,18,37,72,and 200-bar trusses.Both algorithms are evaluated against benchmarks in the literature.The results indicate that SBOA always reaches a lighter optimal.Designs with reducing structural weight ranging from 0.02%to 0.15%compared to ROA,and up to 6%–8%as compared to conventional algorithms.In addition,SBOA can achieve 15%–20%faster convergence speed and 10%–18%reduction in computational time with a smaller standard deviation over independent runs,which demonstrates its robustness and reliability.It is indicated that the adaptive exploration mechanism of SBOA,especially its Levy flight–based search strategy,can obviously improve optimization performance for low-and high-dimensional trusses.The research has implications in the context of promoting bio-inspired optimization techniques by demonstrating the viability of SBOA,a reliable model for large-scale structural design that provides significant enhancements in performance and convergence behavior.
基金National Natural Science Foundation of China under Grant No.51878508。
文摘Cemented and mechanically clamped types of end fittings(fitting-C and fitting-M)are commonly used in transformer bushings.During the Luding Ms 6.8 earthquake that occurred in China on September 5,2022,all transformer bushings with the two types of end fittings in a 500 kV substation were damaged.Post-earthquake field investigations were conducted,and the failures of the two types of bushings were compared.Two elementary simulation models of the transformer-bushing systems were developed to simulate the engineering failures,and further compute their seismic responses for comparison.The results indicate that the hitch lugs of the connection flange are structurally harmful to seismic resistance.Fitting-M can decrease the bending stiffness of the bushing due to the flexible sealing rubber gasket.Since it provides a more flexible connection that dissipates energy,the peak accelerations and relative displacements at the top of the bushing are significantly lower than those of the bushing with fitting-C.Compared with fitting-C,fitting-M transfers the high-stress areas from the connection flange to the root of the porcelain,so the latter becomes the most vulnerable component.Fitting-M increases the failure risk of the low-strength porcelain,indicating the unsuitability of applying it in high-intensity fortification regions.
基金National Science Foundation(NSF)under grant No.CMMI-0748111
文摘This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not necessarily for real-time testing, but rather for models that involve large-scale physical sub-structures and highly nonlinear numerical models. Four case studies are presented and discussed. In the first case study, the accuracy of integration schemes including two widely used methods, namely, modified version of the implicit Newmark with fixed-number of iteration （iterative） and the operator-splitting （non-iterative） is examined through pure numerical simulations. The second case study presents the results of 10 hybrid simulations repeated with the two aforementioned integration methods considering various time steps and fixed-number of iterations for the iterative integration method. The physical sub-structure in these tests consists of a single-degree-of-freedom （SDOF） cantilever column with replaceable steel coupons that provides repeatable highly- nonlinear behavior including fracture-type strength and stiffness degradations. In case study three, the implicit Newmark with fixed-number of iterations is applied for hybrid simulations of a 1：2 scale steel moment frame that includes a relatively complex nonlinear numerical substructure. Lastly, a more complex numerical substructure is considered by constructing a nonlinear computational model of a moment frame coupled to a hybrid model ofa 1：2 scale steel gravity frame. The last two case studies are conducted on the same porotype structure and the selection of time steps and fixed number of iterations are closely examined in pre-test simulations. The generated unbalance forces is used as an index to track the equilibrium error and predict the accuracy and stability of the simulations.
基金supported by the National Natural Science Foundation of China(11172149)the financial support from the IBM World Community Grid project "Computing for Clean Water"+2 种基金the Boeing-Tsinghua Joint Research Project "New Air Filtration Materials"grant 2012 from engineering faculty of Monash Universitysupported by an award under the Merit Allocation Scheme on the Australia NCI National Facility at the ANU
文摘Reversible control of surface wettability has wide applications in lab-on-chip systems, tunable optical lenses, and microfluidic tools. Using a graphene sheet as a sam- ple material and molecular dynamic simulations, we demon- strate that strain engineering can serve as an effective way to control the surface wettability. The contact angles 0 of water droplets on a graphene vary from 72.5° to 106° under biaxial strains ranging from -10% to 10% that are applied on the graphene layer. For an intrinsic hydrophilic surface （at zero strain）, the variation of 0 upon the applied strains is more sensitive, i.e., from 0° to 74.8°. Overall the cosines of the contact angles exhibit a linear relation with respect to the strains. In light of the inherent dependence of the contact an- gle on liquid-solid interfacial energy, we develop an analytic model to show the cos 0 as a linear function of the adsorption energy Eads of a single water molecule over the substrate sur- face. This model agrees with our molecular dynamic results very well. Together with the linear dependence of Eads on bi- axial strains, we can thus understand the effect of strains on the surface wettability. Thanks to the ease of reversibly ap- plying mechanical strains in micro/nano-electromechanical systems, we believe that strain engineering can be a promis- ing means to achieve the reversibly control of surface wetta- bility.
基金the National Natural Science Foundation of China(No.51908416)the Shanghai Pujiang Program(No.19PJ1409500)the Fundamental Research Funds for the Central Universities,China。
文摘Accurate prediction of ductile fracture requires determining the material properties,including the parameters of the constitutive and ductile fracture model,which represent the true material response.Conventional calibration of material parameters often relies on a trial-and-error approach,in which the parameters are manually adjusted until the corresponding finite element model results in a response matching the experimental global response.The parameter estimates are often subjective.To address this issue,in this paper we treat the identification of material parameters as an optimization problem and introduce the particle swarm optimization(PSO)algorithm as the optimization approach.We provide material parameters of two uncoupled ductile fracture models—the Rice and Tracey void growth model(RT-VGM)and the micro-mechanical void growth model(MM-VGM),and a coupled model—the gurson-Tvergaard-Needleman(GTN)model for ASTM A36,A572 Gr.50,and A992 structural steels using an automated PSO method.By minimizing the difference between the experimental results and finite element simulations of the load-displacement curves for a set of tests of circumferentially notched tensile(CNT)bars,the calibration procedure automatically determines the parameters of the strain hardening law as well as the uncoupled models and the coupled GTN constitutive model.Validation studies show accurate prediction of the load-displacement response and ductile fracture initiation in V-notch specimens,and confirm the PSO algorithm as an effective and robust algorithm for seeking ductile fracture model parameters.PSO has excellent potential for identifying other fracture models(e.g.,shear modified GTN)with many parameters that can give rise to more accurate predictions of ductile fracture.Limitations of the PSO algorithm and the current calibrated ductile fracture models are also discussed in this paper.
基金This work has been supported by National Natural Science Foundation of China(51705158),Guangdong Basic and Applied Basic Research Foundation(2019A1515011783)Guangdong Regular Institutions of Characteristic Innovation Project(2017KTSCX176)KEY Laboratory of Robotics and Intelligent Equipment of Guangdong Regular Institutions of Higher Education(2017KSYS009).These supports are gratefully acknowledged.
文摘Isogeometric analysis(IGA),which aims at integrating CAD and CAE models,is one of the most active research topics in both computational mechanics and computer-aided geometric design.The rapidly growing interests in IGA has led to profound developments of relevant theories and applications,one of which being structural optimization.With the rapid growth of researches in IGA,this special issue contributes to highlight recent developments,challenges and opportunities of IGA and IGA-based structural design optimization,with focuses on theory development,numerical implementations and potential applications.
文摘There is great interest in the use of natural fibers as reinforcement to obtain new construction materials due to its low cost, high availability and reduced energy consumption for its production. This paper evaluates the incorporation of sisal fibers of 20 mm and 40 mm in length and volume fraction of 0.5% and 1% for concrete masonry structural blocks, and determines the use of these units to build prisms and mini-walls. Laboratory tests were carried out to characterize the physical of blocks and mortar, in addition to the axial compression tests of the units, prisms, and mini-walls. The sisal had low apparent density and high water absorption, which is a common feature of such material due to the high incidence of permeable pores. The physical properties of the blocks with and without addition complied with the standard requirements established to validate their use. The obtained results showed that the fiber-reinforced mini-walls obtained values very close to or even higher than those obtained for the mini-walls without fibers, demonstrating better performance than the blocks and prisms.
基金financial support provided by Lehigh University,the Advanced Technology for Large Structural Systems(ATLSS)Engineering Research Center,and the Department of Structural Engineering at the University of California,San Diegolarge research team led by Professor Robert B.Fleischman under the project“NEESR:Inertial Force-Limiting Floor Anchorage Systems for Seismic Resistant Building Structures”with the support of grants from the National Science Foundation,award no.CMMI-1135033in the George E.Brown,Jr.Network for Earthquake gineering En-Simulation Research(NEESR)program and award no.CMMI-0402490 for the George E.Brown,Jr.Network for Earthquake ing Engineer-Simulation(NEES)consortium operations.
文摘This study numerically investigates the seismic response of a nine-story self-centering concentrically braced frame building incorporating force-limiting connections between the floor system and the lateral force-resisting system.Nonlinear earthquake simulations are conducted under design basis earthquake ground motions,and the results are compared against a baseline model with rigid-elastic connections.The study discusses connection design considerations and evaluates the effectiveness of force-limiting connections in mitigating higher-mode effects.The findings show that force-limiting connections significantly reduce the magnitude and variability of floor accelerations,brace forces,and connection forces,while maintaining comparable story drifts.limiting Force-connections primarily reduce the contribution of higher-mode responses,while the controlled rocking base mechanism modifies the first-mode response.Overall,the reduced dispersion in structural response improves the reliability of seismic design and enhances resilience by minimizing damage to both structural components and acceleration-sensitive nonstructural elements.
基金funded by the Natural Science Foundation of China(Grant No.52090084)was partially supported by the Sand Hazards and Opportunities for Resilience,Energy,and Sustainability(SHORES)Center,funded by Tamkeen under the NYUAD Research Institute Award CG013.
文摘This study focuses on empirical modeling of the strength characteristics of urban soils contaminated with heavy metals using machine learning tools and their subsequent stabilization with ordinary Portland cement(OPC).For dataset collection,an extensive experimental program was designed to estimate the unconfined compressive strength(Qu)of heavy metal-contaminated soils collected from awide range of land use pattern,i.e.residential,industrial and roadside soils.Accordingly,a robust comparison of predictive performances of four data-driven models including extreme learning machines(ELMs),gene expression programming(GEP),random forests(RFs),and multiple linear regression(MLR)has been presented.For completeness,a comprehensive experimental database has been established and partitioned into 80%for training and 20%for testing the developed models.Inputs included varying levels of heavy metals like Cd,Cu,Cr,Pb and Zn,along with OPC.The results revealed that the GEP model outperformed its counterparts:explaining approximately 96%of the variability in both training(R2=0.964)and testing phases(R^(2)=0.961),and thus achieving the lowest RMSE and MAE values.ELM performed commendably but was slightly less accurate than GEP whereas MLR had the lowest performance metrics.GEP also provided the benefit of traceable mathematical equation,enhancing its applicability not just as a predictive but also as an explanatory tool.Despite its insights,the study is limited by its focus on a specific set of heavy metals and urban soil samples of a particular region,which may affect the generalizability of the findings to different contamination profiles or environmental conditions.The study recommends GEP for predicting Qu in heavy metal-contaminated soils,and suggests further research to adapt these models to different environmental conditions.
基金Financial support provided by the U.S. Department of Energy under DOE Grant No. DE-FE0002760
文摘This paper presents an improved understanding of coupled hydro-thermo-mechanical(HTM) hydraulic fracturing of quasi-brittle rock using the bonded particle model(BPM) within the discrete element method(DEM). BPM has been recently extended by the authors to account for coupled convective econductive heat flow and transport, and to enable full hydro-thermal fluidesolid coupled modeling.The application of the work is on enhanced geothermal systems(EGSs), and hydraulic fracturing of hot dry rock(HDR) is studied in terms of the impact of temperature difference between rock and a flowing fracturing fluid. Micro-mechanical investigation of temperature and fracturing fluid effects on hydraulic fracturing damage in rocks is presented. It was found that fracture is shorter with pronounced secondary microcracking along the main fracture for the case when the convectiveeconductive thermal heat exchange is considered. First, the convection heat exchange during low-viscosity fluid infiltration in permeable rock around the wellbore causes significant rock cooling, where a finger-like fluid infiltration was observed. Second, fluid infiltration inhibits pressure rise during pumping and delays fracture initiation and propagation. Additionally, thermal damage occurs in the whole area around the wellbore due to rock cooling and cold fluid infiltration. The size of a damaged area around the wellbore increases with decreasing fluid dynamic viscosity. Fluid and rock compressibility ratio was found to have significant effect on the fracture propagation velocity.
文摘Two full-scale experiments using controlled blasting were conducted in the Port of Tokachi on Hokkaido Island, Japan,to assess the behavior of piles and pipelines subjected to lateral spreading.Test specimens were extensively instrumented with strain gauges to measure the distribution of moment during lateral spreading.This allowed us to compute the loading condition,as well as to conduct damage and performance assessments on the piles and pipelines.This paper presents the test results and discussions on the response of single piles and pipelines observed from the full-scale experiments.Based on the test results,it can be concluded that using controlled blasting successfully liquefied the soil,and subsequently induced lateral spreading.The movements of the single pile,as well as the transverse pipelines,were approximately the same as the free field soil movement.Observed moment distribution of the single pile indicated that global translation of the liquefied soil layer provided insignificant force to the pile.In addition,the degree of fixity at the pile tip significantly affected the moment along the pile as well as the pile head displacement.The pile with a higher degree of fixity at the pile tip had smaller pile head displacement but larger maximum moment.
文摘Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.
基金funded by the Chinese Scholarship Council and the Research Council of Norway through the Petromaks2 program(Project No.281927)the BIA Program(Project No.269558)。
文摘Deposition patterns can significantly affect residual stress distribution in additive manufacturing processes.In this paper,a novel pattern,the S-pattern,is proposed for the metal additive manufacturing process.The finite element method is used to study the temperature field and the stress field of a cuboid structure under the S-pattern and five other representative patterns:zig-zag,raster,alternate-line,in-out spiral,and out-in spiral.The results show that the S-pattern achieves the lowest values of both equivalent residual stress and maximum principal residual stress,and the warpage of the S-pattern is close to that of counterparts.By analyzing the temperature and stress fields under all patterns,it is found that the residual stress distribution is determined by the uniformity of temperature distribution which is correlated with the peak temperatures of corners.The equivalent residual stress and the maximum principal residual stress are inversely correlated with the average peak temperature and the minimum peak temperature of corners,respectively.These correlations between temperature and residual stress provide an effective approach to evaluate the residual stress of different patterns and guide the deposition process in practice.
基金the National Natural Science Foundation of China under Grant Nos.51408346 and 51438007the Shanghai Science and Technique Committee under Grant No.14231201300
文摘A model for evaluating structural damage of recycled aggregate concrete filled steel tube （RCFST） columns under seismic effects is proposed in this paper. The proposed model takes the lateral deformation and the effect of repeated cyclic loading into account. Available test results were collected and utilized to calibrate the parameters of the proposed model. A seismic test for six RCFST columns was also performed to validate the proposed damage assessment model. The main test parameters were the recycled coarse aggregate （RCA） replacement percentage and the bond-slip property. The test results indicated that the seismic performance of the RCFST member depends on the RCA contents and their damage index increases as the RCA replacement percentage increases. It is also indicated that the damage degree of RCFST changes with the variation of the RCA replacement percentage. Finally, comparisons between the RCA contents, lateral deformation ratio and damage degree were implemented. It is suggested that an improvement procedure should be implemented in order to compensate for the performance difference between the RCFST and normal concrete filled steel tubes （CFST）.
基金This research was supported by the Pacific Earthquake Engineering Research(PEER)Center,Caltrans,and the National Science Foundation(Grant CMMI-1201195,OISE-1445712).Additional support was provided by National Science Foundation(NSF)through computing resources provided by San Diego Supercomputer Center(SDSC)and Texas Advanced Computing Center(TACC).The Wharf layout information was provided by Dr.Arul K.Arulmoli,Principal,Earth Mechanics,Inc.
文摘The OpenSees computational platform has allowed unprecedented opportunities for conducting seismic nonlinear soil-structure interaction simulations.On the geotechnical side,capabilities such as coupled solid-fluid formulations and nonlinear incrementalplasticity approaches allow for representation of the involved dynamic/seismic responses.This paper presents recent research that facilitated such endeavors in terms of response of ground-foundation-structure systems using advanced material modeling techniques and high-performance computing resources.Representative numerical results are shown for large-scale soil-structure systems,and ground modification liquefaction countermeasures.In addition,graphical user interface enabling tools for routine usage of such 3D simulation environments are presented,as an important element in support of wider adoption and practical applications.In this context,Performance-Based Earthquake Engineering(PBEE)analysis of bridge-ground systems is highlighted as an important topical application.
基金the financial support from the Distinguished Young Scholars of China by the National Natural Science Foundation of China(51325802)the National Natural Science Foundation of China(51178340,52078358,and 52008304)。
文摘In the past 20 years,recycled aggregate concrete(RAC),as a type of low-carbon concrete,has become a worldwide focus of research.However,the design methodology for RAC structural components remains a challenge.Consequently,demands for a unified design of natural aggregate concrete(NAC)and RAC components have been presented.Accordingly,this study analyses the necessity of a unified design theory and provides an in-depth demonstration of the strength determination,compressive constitutive relationship,and design method of concrete components.The coefficient of variation of RAC strength is found to be generally higher than that of NAC strength.The compressive and tensile strengths of RAC can be defined and determined using the same method as that used for NAC.The uniaxial compressive constitutive relationship between NAC and RAC has a unified mathematical expression.However,the elastic modulus of RAC decreases,and its brittleness exhibits an increasing trend compared with that of NAC.Finally,to unify the design formulae of RAC and NAC components for bearing capacity,modification factors for RAC components are proposed considering safety and reliability.Additionally,the feasibility of the proposed unified time-dependent design theory is demonstrated in terms of conceptual design and structural measures considering the effects of strength degradation and reinforcement corrosion.It is believed that this study enriches and develops the basic theory of concrete structures.
基金National Natural Science Foundation of China under Grant No.5210082055China Postdoctoral Science Foundation under Grant No.2021M690278。
文摘The serviceability of water supply networks(WSNs)under seismic loads has significant importance for estimating the probable losses and the impact of diminished functionality on affected communities.The innovation presented in this paper is suggesting a new strategy to evaluate the seismic serviceability of WSNs,utilizing their operational physical mechanism.On one hand,this method can obtain the seismic serviceability of each node as well as entire WSNs.On the other hand,this method can dynamically reflect the propagation of randomness from ground motions to WSNs.First,a finite element model is established to capture the seismic response of buried pipe networks,and a leakage model is suggested to obtain the leakage area of WSNs.Second,the transient flow analysis of WSNs with or without leakage is derived to obtain dynamic water flow and pressure.Third,the seismic serviceability of WSNs is analyzed based on the probability density evolution method(PDEM).Finally,the seismic serviceability of a real WSN in Mianzhu city is assessed to illustrate the method.The case study shows that randomness from the ground motions can obviously affect the leakage state and the probability density of the nodal head during earthquakes.
