Exploring the Applications of Digital Twin Technology in Enhancing Sustainability in Civil Engineering:A Review

With the advent of the big data era and the rise of Industrial Revolution 4.0,digital twins(DTs)have gained sig-nificant attention in various industries.DTs offer the opportunity to combine the physical and digital worlds and aid the digital transformation of the civil engineering industry.In this paper,605 documents obtained from the search werefirst analysed using CiteSpace for literature visualisation,and an author co-occurrence network,a keyword co-occurrence network,and a keyword clustering set were obtained.Next,through a literature review of 86 papers,this paper summarises the current status of DT application in civil engineering based on a review of the origins,concepts,and implementation techniques of DTs,and it introduces the application of DTs in the full project lifecycle.This study shows that DTs have great potential to address many of the challenges faced by civil engineering.In this regard,the paper also presents some thoughts on the future directions of DT research.

Exploration and Practice of the Digital Transformation and Upgrading Paths for Civil Engineering Majors

This article examines the pathway to digital transformation and upgrading in undergraduate institutions,using the civil engineering program at Chongqing Three Gorges University as a case study,focusing on six key areas:developing a high-quality digital talent training program for civil engineering;assembling diverse resources to create a digital,multi-scenario open learning environment that encompasses teaching,research,and practical training for civil engineering undergraduates;piloting innovative digital teaching models for civil engineering undergraduates;crafting a new model for digital resource provision,utilizing self-developed and specialized resources;devising assessment methods and ongoing improvement strategies based on the achievement of students’digital competencies;and devising a new,three-dimensional,multi-modal teaching evaluation system through intelligent data capture and analysis.

Impact resistance performance and optimization of the sand-EPE composite cushion in rock sheds

Rock sheds are widely used to prevent rockfall disasters along roads in mountainous areas.To improve the capacity of rock sheds for resisting rockfall impact,a sand and expandable polyethylene(EPE)composite cushion was proposed.A series of model experiments of rockfall impact on rock sheds were conducted,and the buried depth of the EPE foam board in the sand layer was considered.The impact load and dynamic response of the rock shed were investigated.The results show that the maximum impact load and dynamic response of the rock shed roof are all significantly less than those of the sand cushion.Moreover,as the distance between the EPE foam board and rock shed roof decreases,the maximum rockfall impact force and impact pressure gradually decrease,and the maximum displacement,acceleration and strain of the rock shed first decrease and then change little.In addition,the vibration acceleration and vertical displacement of the rock shed roof decrease from the centre to the edge and decrease faster along the longitudinal direction than that along the transverse direction.In conclusion,the buffering effect of the sand-EPE composite cushion is better than that of the pure sand cushion,and the EPE foam board at a depth of 1/3 the thickness of the sand layer is appropriate.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

State-of-the-art on the anchorage performance of rock bolts subjected to shear load

Rock bolts are extensively utilized in underground engineering as a means of offering support and stability to rock masses in tunnels,mines,and other underground structures.In environments of high ground stress,faults or weak zones can frequently arise in rock formations,presenting a significant challenge for engineering and potentially leading to underground engineering collapse.Rock bolts serve as a crucial structural element for the transmission of tensile stress and are capable of withstanding shear loads to prevent sliding of weak zones within rock mass.Therefore,a complete understanding of the behavior of rock bolts subjected to shear loads is essential.This paper presents a state-of-the-art review of the research progress of rock bolts subjected to shear load in three categories:experiment,numerical simulation,and analytical model.The review focuses on the research studies and developments in this area since the 1970s,providing a comprehensive overview of numerous factors that influence the anchorage performance of rock bolts.These factors include the diameter and angle of the rock bolt installation,rock strength,grouting material,bolt material,borehole diameter,rock bolt preload,normal stress,joint surface roughness and joint expansion angle.The paper reviews the improvement of mechanical parameter setting in numerical simulation of rock bolt shear.Furthermore,it delves into the optimization of the analytical model concerning rock bolt shear theory,approached from the perspectives of both Elastic foundation beam theory coupled with Elastoplasticity theory and Structural mechanic methods.The significance of this review lies in its ability to provide insights into the mechanical behavior of rock bolts.The paper also highlights the limitations of current research and guidelines for further research of rock bolts.

Material point method simulation of hydro-mechanical behaviour in twophase porous geomaterials: A state-of-the-art review

The material point method(MPM)has been gaining increasing popularity as an appropriate approach to the solution of coupled hydro-mechanical problems involving large deformation.In this paper,we survey the current state-of-the-art in the MPM simulation of hydro-mechanical behaviour in two-phase porous geomaterials.The review covers the recent advances and developments in the MPM and their extensions to capture the coupled hydro-mechanical problems involving large deformations.The focus of this review is aiming at providing a clear picture of what has or has not been developed or implemented for simulating two-phase coupled large deformation problems,which will provide some direct reference for both practitioners and researchers.

Mechanical responses of anchoring structure under triaxial cyclic loading

Dynamic load on anchoring structures(AS)within deep roadways can result in cumulative damage and failure.This study develops an experimental device designed to test AS under triaxial loads.The device enables the investigation of the mechanical response,failure mode,instability assessment criteria,and anchorage effect of AS subjected to combined cyclic dynamic-static triaxial stress paths.The results show that the peak bearing strength is positively correlated with the anchoring matrix strength,anchorage length,and edgewise compressive strength.The bearing capacity decreases significantly when the anchorage direction is severely inclined.The free face failure modes are typically transverse cracking,concave fracturing,V-shaped slipping and detachment,and spallation detachment.Besides,when the anchoring matrix strength and the anchorage length decrease while the edgewise compressive strength,loading rate,and anchorage inclination angle increase,the failure intensity rises.Instability is determined by a negative tangent modulus of the displacement-strength curve or the continued deformation increase against the general downward trend.Under cyclic loads,the driving force that breaks the rock mass along the normal vector and the rigidity of the AS are the two factors that determine roadway stability.Finally,a control measure for surrounding rock stability is proposed to reduce the internal driving force via a pressure relief method and improve the rigidity of the AS by full-length anchorage and grouting modification.

Time series prediction of reservoir bank landslide failure probability considering the spatial variability of soil properties

Historically,landslides have been the primary type of geological disaster worldwide.Generally,the stability of reservoir banks is primarily affected by rainfall and reservoir water level fluctuations.Moreover,the stability of reservoir banks changes with the long-term dynamics of external disastercausing factors.Thus,assessing the time-varying reliability of reservoir landslides remains a challenge.In this paper,a machine learning(ML)based approach is proposed to analyze the long-term reliability of reservoir bank landslides in spatially variable soils through time series prediction.This study systematically investigated the prediction performances of three ML algorithms,i.e.multilayer perceptron(MLP),convolutional neural network(CNN),and long short-term memory(LSTM).Additionally,the effects of the data quantity and data ratio on the predictive power of deep learning models are considered.The results show that all three ML models can accurately depict the changes in the time-varying failure probability of reservoir landslides.The CNN model outperforms both the MLP and LSTM models in predicting the failure probability.Furthermore,selecting the right data ratio can improve the prediction accuracy of the failure probability obtained by ML models.

Failure mechanism and infrared radiation characteristic of hard siltstone induced by stratification effect

The deformation in sedimentary rock induced by train loads has potential threat to the safe operation of tunnels. This study investigated the influence of stratification structure on the infrared radiation and temporal damage mechanism of hard siltstone. The uniaxial compression tests, coupled with acoustic emission(AE) and infrared radiation temperature(IRT) were conducted on siltstones with different stratification effects. The results revealed that the stratigraphic structure significantly affects the stress-strain response and strength degradation characteristics. The mechanical parameters exhibit anisotropy characteristics, and the stratification effect exhibits a negative correlation with the cracking stress and peak stress. The failure modes caused by the stratification effect show remarkable anisotropic features, including splitting failure(Ⅰ: 0°-22.50°, Ⅱ: 90°), composite failure(45°), and shearing failure(67.50°). The AE temporal sequences demonstrate a stepwise response characteristic to the loading stress level. The AE intensity indicates that the stress sensitivity of shearing failure and composite failure is generally greater than that of splitting failure. The IRT field has spatiotemporal migration and progressive dissimilation with stress loading and its dissimilation degree increases under higher stress levels. The stronger the stratification effect, the greater the dissimilation degree of the IRT field. The abnormal characteristic points of average infrared radiation temperature(AIRT) variance at local stress drop and peak stress can be used as early and late precursors to identify fracture instability. Theoretical analysis shows that the competitive relationship between compaction strengthening and fracturing damage intensifies the dissimilation of the infrared thermal field for an increasing stress level. The present study provides a theoretical reference for disaster warnings in hard sedimentary rock mass.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Dynamic response and failure process of horizontal-layered fractured structure rock slope under strong earthquake

Rock slope with horizontal-layered fractured structure(HLFS)has high stability in its natural state.However,a strong earthquake can induce rock fissure expansion,ultimately leading to slope failure.In this study,the dynamic response,failure mode,and spectral characteristics of rock slope with HLFS under strong earthquake conditions were investigated based on the large-scale shaking table model test.On this basis,multiple sets of numerical calculation models were further established by UDEC discrete element program.Five influencing factors were considered in the parametric study of numerical simulations,including slope height,slope angle,bedding-plane spacing and secondary joint spacing as well as bedrock dip angle.The results showed that the failure process of rock slope with HLFS under earthquake action is mainly divided into four phases,i.e.,the tensile crack of the slope shoulder joints and shear dislocation at the top bedding plane,the extension of vertical joint cracks and increase of shear displacement,the formation of step-through sliding surfaces and the instability,and finally collapse of fractured rock mass.The acceleration response of slopes exhibits elevation amplification effect and surface effect.Numerical simulations indicate that the seismic stability of slopes with HLFS exhibits a negative correlation with slope height and angle,but a positive correlation with bedding-plane spacing,joint spacing,and bedrock dip angle.The results of this study can provide a reference for seismic stability evaluation of weathered rock slopes.

Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.

Experimental,Numerical,and Analytical Studies on the Bending of Mechanically Lined Pipe

Mechanically lined pipe(MLP)is often used for offshore oil and gas transport because of its low cost and corrosion resistance.During installation and operation,the pipe may undergo severe bending deformation,which causes the liner to separate from the outer pipe and buckles,affecting the stability of the whole line.In this paper,the buckling response of MLP subjected to bending is investigated to clarify its bending characteristics by employing both experiments,numerical simulation,as theoretical methods.Two types of MLPs were manufactured with GB 45 carbon steel(SLP)and Al 6061(ALP)used as the outer pipe material,respectively.The hydraulic expansion and bending experiments of small-scale MLPs are conducted.In addition to the ovalized shape of the cross-section for the SLP specimens,the copper liner was found to wrinkle on the compressive side.In contrast,the liner of ALP remains intact without developing any wrinkling and collapse mode.In addition,a dedicated numerical framework and theoretical models were also established.It was found both the manufacturing and bending responses of the MLP can be well reproduced,and the predicted maximum moment and critical curvatures are in good agreement with the experimental results.

Anisotropic shearing mechanism of Kangding slate:Experimental investigation and numerical analysis

The shear mechanical behavior is regarded as an essential factor affecting the stability of the surrounding rocks in underground engineering.The shear strength and failure mechanisms of layered rock are significantly affected by the foliation angles.Direct shear tests were conducted on cubic slate samples with foliation angles of 0°,30°,45°,60°,and 90°.The effect of foliation angles on failure patterns,acoustic emission(AE)characteristics,and shear strength parameters was analyzed.Based on AE characteristics,the slate failure process could be divided into four stages:quiet period,step-like increasing period,dramatic increasing period,and remission period.A new empirical expression of cohesion for layered rock was proposed,which was compared with linear and sinusoidal cohesion expressions based on the results made by this paper and previous experiments.The comparative analysis demonstrated that the new expression has better prediction ability than other expressions.The proposed empirical equation was used for direct shear simulations with the combined finite-discrete element method(FDEM),and it was found to align well with the experimental results.Considering both computational efficiency and accuracy,it was recommended to use a shear rate of 0.01 m/s for FDEM to carry out direct shear simulations.To balance the relationship between the number of elements and the simulation results in the direct shear simulations,the recommended element size is 1 mm.

Lateral earth pressure of granular backfills on retaining walls with expanded polystyrene geofoam inclusions under limited surcharge loading

Existing studies have focused on the behavior of the retaining wall equipped with expanded polystyrene(EPS)geofoam inclusions under semi-infinite surcharge loading rather than limited surcharge loading.In this paper,the failure mode and the earth pressure acting on the rigid retaining wall with EPS geofoam inclusions and granular backfills(henceforth referred to as EPS-wall),under limited surcharge loading are investigated through two-and three-dimensional model tests.The testing results show that different from the sliding of almost all the backfill in the EPS-wall under semi-infinite surcharge loading,only an approximately triangular backfill slides in the wall under limited surcharge loading.The distribution of the lateral earth pressure on the EPS-wall under limited surcharge loading is non-linear,and the distribution changes from the increase of the wall depth to the decrease with the increase of the limited surcharge loading.An approach based on the force equilibrium of a differential element is developed to predict the lateral earth pressure behind the EPS-wall subjected to limited surcharge loading,and its performance was fully validated by the three-dimensional model tests.

Computer vision-aided DEM study on the compaction characteristics of graded subgrade filler considering realistic coarse particle shapes

The compaction quality of subgrade filler strongly affects subgrade settlement.The main objective of this research is to analyze the macro-and micro-mechanical compaction characteristics of subgrade filler based on the real shape of coarse particles.First,an improved Viola-Jones algorithm is employed to establish a digitalized 2D particle database for coarse particle shape evaluation and discrete modeling purposes of subgrade filler.Shape indexes of 2D subgrade filler are then computed and statistically analyzed.Finally,numerical simulations are performed to quantitatively investigate the effects of the aspect ratio(AR)and interparticle friction coefficient(μ)on the macro-and micro-mechanical compaction characteristics of subgrade filler based on the discrete element method(DEM).The results show that with the increasing AR,the coarse particles are narrower,leading to the increasing movement of fine particles during compaction,which indicates that it is difficult for slender coarse particles to inhibit the migration of fine particles.Moreover,the average displacement of particles is strongly influenced by the AR,indicating that their occlusion under power relies on particle shapes.The dis-placement and velocity of fine particles are much greater than those of the coarse particles,which shows that compaction is primarily a migration of fine particles.Under the cyclic load,the interparticle friction coefficientμhas little effect on the internal structure of the sample;under the quasi-static loads,however,the increase inμwill lead to a significant increase in the porosity of the sample.This study could not only provide a novel approach to investigate the compaction mechanism but also establish a new theoretical basis for the evaluation of intelligent subgrade compaction.

Early Triassic Volcanic Rocks in the Western Yarlung Zangbo Suture Zone:Implications for the Opening of the Neo-Tethys Ocean

In this study,zircon U-Pb dating of volcanic rocks from the Zhongba ophiolite of the Yarlung Zangbo Suture Zone(YZSZ)in southern Xizang(Tibet)yielded an age of 247±3 Ma.According to whole rock geochemical and Sr-NdPb isotopic data,the Early Triassic samples could be divided into two groups:Group 1 with P-MORB affinity,showing initial^(87)Sr/^(86)Sr ratios of 0.70253–0.70602,ε_(Nd)(t)values of 4.2–5.3,(^(206)Pb/^(204)Pb)_(t)ratios of 16.353–18.222,(^(207)Pb/^(204)Pb)_(t)ratios of 15.454–15.564,and(^(208)Pb/^(204)Pb)_(t)ratios of 35.665–38.136;Group 2 with OIB affinity,showing initial^(87)Sr/^(86)Sr ratios of 0.70249–0.70513,ε_(Nd)(t)values of 4.4–4.9,(^(206)Pb/^(204)Pb)_(t)ratios of 17.140–18.328,(^(207)Pb/^(204)Pb)_(t)ratios of 15.491–15.575,and(^(208)Pb/^(204)Pb)_(t)ratios of 36.051–38.247.Group 2 rocks formed by partial melting of the mantle source enriched by a former plume,and assimilated continental crustal material during melt ascension.The formation of Group 1 rocks corresponds to the mixing of OIB melts,with the same components as Group 2 and N-MORBs.The Zhongba Early Triassic rocks belong to the continental margin type ophiolite and formed in the continental–oceanic transition zone during the initial opening of the Neo-Tethys in southern Xizang(Tibet).

Effects of seepage pressure on the mechanical behaviors and microstructure of sandstone

Surrounding rocks of underground engineering are subjected to long-term seepage pressure,which can deteriorate the mechanical properties and cause serious disasters.In order to understand the impact of seepage pressure on the mechanical property of sandstone,uniaxial compression tests,P-wave velocity measurements,and nuclear magnetic resonance(NMR)tests were conducted on saturated sandstone samples with varied seepage pressures(i.e.0 MPa,3 MPa,4 MPa,5 MPa,6 MPa,7 MPa).The results demonstrate that the mechanical parameters(uniaxial compressive strength,peak strain,elastic modulus,and brittleness index),total energy,elastic strain energy,as well as elastic strain energy ratio,decrease with increasing seepage pressure,while the dissipation energy and dissipation energy ratio increase.Moreover,as seepage pressure increases,the micro-pores gradually transform into meso-pores and macro-pores.This increases the cumulative porosity of sandstone and decreases P-wave velocity.The numerical results indicate that as seepage pressure rises,the number of tensile cracks increases progressively,the angle range of microcracks is basically from 50-120to 80-100,and as a result,the failure mode transforms to the tensile-shear mixed failure mode.Finally,the effects of seepage pressure on mechanical properties were discussed.The results show that decrease in the effective stress and cohesion under the action of seepage pressure could lead to deterioration of strength behaviors of sandstone.

Reliability analysis of slope stability by neural network,principal component analysis,and transfer learning techniques

The prediction of slope stability is considered as one of the critical concerns in geotechnical engineering.Conventional stochastic analysis with spatially variable slopes is time-consuming and highly computation-demanding.To assess the slope stability problems with a more desirable computational effort,many machine learning(ML)algorithms have been proposed.However,most ML-based techniques require that the training data must be in the same feature space and have the same distribution,and the model may need to be rebuilt when the spatial distribution changes.This paper presents a new ML-based algorithm,which combines the principal component analysis(PCA)-based neural network(NN)and transfer learning(TL)techniques(i.e.PCAeNNeTL)to conduct the stability analysis of slopes with different spatial distributions.The Monte Carlo coupled with finite element simulation is first conducted for data acquisition considering the spatial variability of cohesive strength or friction angle of soils from eight slopes with the same geometry.The PCA method is incorporated into the neural network algorithm(i.e.PCA-NN)to increase the computational efficiency by reducing the input variables.It is found that the PCA-NN algorithm performs well in improving the prediction of slope stability for a given slope in terms of the computational accuracy and computational effort when compared with the other two algorithms(i.e.NN and decision trees,DT).Furthermore,the PCAeNNeTL algorithm shows great potential in assessing the stability of slope even with fewer training data.