Showing papers in "Engineering Structures in 2020"
TL;DR: The most recently developed functionally graded graphene platelets reinforced composite (FG-GPLRC) where GPLs are non-uniformly dispersed with more GPLs in the area where they are most needed to achieve significantly improved mechanical performance has opened up a new avenue for the development of next generation structural forms with an excellent combination of high stiffness, light weight and multi-functionality.
Abstract: Owing to their superior mechanical properties, e.g. exceptionally high Young’s modulus, high strength, large specific surface area, and good thermal conductivity, graphene and its derivatives such as graphene platelets (GPLs) are excellent reinforcing nanofillers for composite materials. The most recently developed functionally graded graphene platelets reinforced composite (FG-GPLRC) where GPLs are non-uniformly dispersed with more GPLs in the area where they are most needed to achieve significantly improved mechanical performance has opened up a new avenue for the development of next generation structural forms with an excellent combination of high stiffness, light weight and multi-functionality. Research activities in this emerging area have been rapidly increasing since it was first proposed in 2017. The present paper (i) briefly reviews the mechanical properties of graphene and graphene composites; (ii) summarizes the characteristics of functionally graded materials (FGM) and reports the fabrication of FG-GPLRC; (iii) discusses the existing micromechanics models for the prediction of effective mechanical properties of GPLRC; (iv) presents a comprehensive review on the mechanical analyses of FG-GPLRC structures; and (v) discuss the key technical challenges and future research directions.
TL;DR: This paper uses extensive experimental databases to suggest random forest machine learning models for failure mode predictions of reinforced concrete columns and shear walls, employs the recently developed SHapley Additive exPlanations approach to rank input variables for identification of failure modes, and explains why the machine learning model predicts a specific failure mode for a given sample or experiment.
Abstract: Machine learning approaches can establish the complex and non-linear relationship among input and response variables for the seismic damage assessment of structures. However, lack of explainability of complex machine learning models prevents their use in such assessment. This paper uses extensive experimental databases to suggest random forest machine learning models for failure mode predictions of reinforced concrete columns and shear walls, employs the recently developed SHapley Additive exPlanations approach to rank input variables for identification of failure modes, and explains why the machine learning model predicts a specific failure mode for a given sample or experiment. A random forest model established provides an accuracy of 84% and 86% for unknown data of columns and shear walls, respectively. The geometric variables and reinforcement indices are critical parameters that influence failure modes. The study also reveals that existing strategies of failure mode identification based solely on geometric features are not enough to properly identify failure modes.
TL;DR: In this paper, a physics-guided convolutional neural network (PhyCNN) is proposed to predict building seismic response in a data-driven fashion without the need of a physicsbased analytical/numerical model.
Abstract: Accurate prediction of building’s response subjected to earthquakes makes possible to evaluate building performance. To this end, we leverage the recent advances in deep learning and develop a physics-guided convolutional neural network (PhyCNN) for data-driven structural seismic response modeling. The concept is to train a deep PhyCNN model based on limited seismic input–output datasets (e.g., from simulation or sensing) and physics constraints, and thus establish a surrogate model for structural response prediction. Available physics (e.g., the law of dynamics) can provide constraints to the network outputs, alleviate overfitting issues, reduce the need of big training datasets, and thus improve the robustness of the trained model for more reliable prediction. The surrogate model is then utilized for fragility analysis given certain limit state criteria. In addition, an unsupervised learning algorithm based on K-means clustering is also proposed to partition the datasets to training, validation and prediction categories, so as to maximize the use of limited datasets. The performance of PhyCNN is demonstrated through both numerical and experimental examples. Convincing results illustrate that PhyCNN is capable of accurately predicting building’s seismic response in a data-driven fashion without the need of a physics-based analytical/numerical model. The PhyCNN paradigm also outperforms non-physics-guided neural networks.
TL;DR: In this article, a stress-strain model was developed to better understand and simulate the behaviour of FRP-confined concrete, which consists of the following three main components: (1) a hoop strain equation elaborated from the authors' previous study on steel-constrained concrete columns for application to FRP confined concrete; (2) a modified confined concrete model considering stresspath of confining stress (or history of hoop strain); (3) Interaction between FRP and concrete.
Abstract: High-strength concrete (HSC) has higher strength-to-weight ratio and stiffness than normal-strength concrete (NSC). Therefore, the use of HSC can decrease the construction and demolition waste and embodied carbon content of structural members that enhances the urban sustainability. However, HSC is more brittle than NSC. To further push up the maximum concrete strength limit in practical construction, confining concrete by fibre-reinforced polymer (FRP) has been advocated to restore ductility. Compared with using hollow-steel tube as confinement, FRP has lighter weight, higher tensile strength, better corrosion resistance, and is more durable and flexible. Nevertheless, it is up to now a difficult task to predict accurately the uni-axial stress-strain behaviour of FRP-confined concrete since the effect of confining stress, concrete strength, hoop and axial strains are inter-related and need to be determined simultaneously. Herein, to better understand and simulate the behaviour of FRP-confined concrete, a stress-strain model has been developed, which consists of the following three main components: (1) A hoop strain equation elaborated from the authors’ previous study on steel-confined concrete columns for application to FRP-confined concrete; (2) A modified confined concrete model considering stress-path of confining stress (or history of hoop strain); (3) Interaction between FRP and concrete. The model was verified based on 321 test results obtained from the literature, the design application of the which to a broad range of FRP-confined concrete structures is thus ensured.
TL;DR: In this paper, a theoretical stress-strain model for concrete-filled steel-tube (CFST) columns was developed to better understand and simulate the behavior of CFST column, which consists of the following four main components: (1) Interaction between steel tube and concrete taken into account the de-bonding effect; (2) an accurate hoop strain equation; (3) a passively confined concrete model considering stress-path dependence; (4) a three-dimensional stress-strain model for steel tube.
Abstract: High-strength concrete (HSC) has higher strength-to-weight ratio and stiffness than normal-strength concrete (NSC), which can decrease the size and embodied carbon of columns in tall buildings. Because of the brittleness of HSC, the practical design strength limit of HSC is usually limited for providing minimum ductility. One feasible way to extend this limit would be to use concrete-filled-steel-tube (CFST) column, which has a better strength-ductility performance. There are two shortcomings in theoretical models predicting the stress-strain behaviour of CFST column: (1) Most of the models did not consider the imperfect steel-concrete interface bonding due to their different dilations under axial compression; (2) A stress-path independent confining stress-strain relationship was adopted, which ignored the progressive development of tensile splitting cracks in concrete leading to a more gradual building up of confining stress under passive confinement than active pressure. Herein, to better understand and simulate the behaviour of CFST column, a theoretical stress-strain model, which consists of the following four main components, has been developed: (1) Interaction between steel tube and concrete taken into account the de-bonding effect; (2) An accurate hoop strain equation; (3) A passively confined concrete model considering stress-path dependence; (4) A three-dimensional stress-strain model for steel tube. Comparing with the measured load-strain curves obtained by the authors and other researchers, the accuracy of the proposed model in predicting the axial behaviour of CFST columns has been verified.
TL;DR: A machine learning model based on the Random Forest method, which has 86% accuracy in identifying the failure mode of shear walls, is proposed and an open-source data-driven classification model that can be used in design offices across the world is provided.
Abstract: A reinforced concrete shear wall is one of the most critical structural members in buildings, in terms of carrying lateral loads. Despite its importance, post-earthquake reconnaissance and recent experimental studies have highlighted the insufficient safety margins of shear walls. The lack of empirical and mechanics-based models prevents rapid failure mode identification of existing shear walls. This study builds on recent advances in the area of machine learning to determine the failure mode of shear walls as a function of geometric configurations, material properties, and reinforcement details. This study assembles a comprehensive database consisting of 393 experimental results for shear walls with various geometric configurations. Eight machine learning models, including Naive Bayes, K-Nearest Neighbors, Decision Tree, Random Forest, AdaBoost, XGBoost, LightGBM, and CatBoost were evaluated in this study, in order to establish the best prediction model. As a result of detailed evaluation, a machine learning model based on the Random Forest method is proposed in this paper. The proposed method has 86% accuracy in identifying the failure mode of shear walls. This study also demonstrates that aspect ratio, boundary element reinforcement indices, and wall length-to-wall thickness ratio are the critical parameters influencing the failure mode of shear walls. Finally, an open-source data-driven classification model that can be used in design offices across the world is provided in this paper. The proposed model has the flexibility to account for additional experimental results yielding new insights.
TL;DR: In this paper, a database collecting 28 CFFT columns test results is assembled for establishing a new stress-strain model that comprises the following 4 parts: (1) A model of hoop strain set up by the authors taking into account the effects of concrete splitting cracks; (2) An adjusted constitutive model of actively confined concrete incorporating confining stress path dependent effect; (3) Bi-axial stress model of FRP tube; (4) a model addressing the compatibility condition of concrete and fiber-reinforced polymer (FRP) tube.
Abstract: Confinement, such as hollow-steel tube (HST) and fibre-reinforced polymer (FRP) tube, can improve not only the loading capacity of concrete structures, but also ductility. Compared with HST, FRP tube has stronger flexural and tensile strength, as well as resistance against corrosion. It is also lighter and more durable. Thus, concrete-filled-FRP-tube (CFFT) column is ideal for new buildings’ construction for improving safety, prolonging design life and enhancing sustainability. However, their experimental studies are relatively limited, and the existing stress-strain models cannot capture their full range behaviour. Herein, to understand more thoroughly and simulate the uni-axial performance of CFFT columns, a database collecting 28 CFFT columns test results is assembled for establishing a new stress-strain model that comprises the following 4 parts: (1) A model of hoop strain set up by the authors taking into account the effects of concrete splitting cracks; (2) An adjusted constitutive model of actively confined concrete incorporating confining stress path dependent effect; (3) Bi-axial stress model of FRP tube; (4) A model addressing the compatibility condition of concrete and FRP tube. Finally, the theoretical axial stress-strain curve matches very well with those experimental curves of CFFT columns, which verifies the validity of the model proposed in this study.
TL;DR: An in-depth review of the collapse typologies is proposed, with emphasis on the current techniques to study collapse propagation, i.e., numerical, experimental and analytical.
Abstract: This paper reviews the state-of-art in progressive collapse studies on framed building structures. Such types of failure start with a local damage which extension increases, up to the whole structure. First, emphasis is placed on the current techniques to study collapse propagation, i.e., numerical, experimental and analytical. In particular, the various numerical methods found in the literature are reported and discussed and the experimental studies and technologies involved in the laboratory tests are listed and compared. As reviewed, the method of analysis depends on the collapse mechanism and the triggering event. Thus, an in-depth review of the collapse typologies is proposed. Pure and mixed progressive collapse mechanisms are discussed and debated. The various triggering events, their modeling and their effects on the framed structures are examined. Details on the available literature on multi-hazard scenarios are provided. Finally, robustness techniques against progressive collapse are summarized, compared and contrasted. The paper concludes with an ambitious comprehensive list of open questions and issues covering different aspects of future needs.
TL;DR: The use of ultra-high performance concrete (UHPC) to strength existing reinforced concrete (RC) structures in flexure has been explored in recent decades as discussed by the authors, and the state of research on the flexural strengthening of RC beams or slabs with UHPC was presented.
Abstract: The use of ultra-high performance concrete (UHPC) to strength existing reinforced concrete (RC) structures in flexure has been explored in recent decades. As UHPC developed in different countries performed different properties, the effectiveness of RC structures strengthened with UHPC varies. Moreover, the lacking of code provisions restricts the wide application of this novel strengthening technology. It is necessary to review experimental studies for the guidance of code elaboration. In this research, the state of research on the flexural strengthening of RC beams or slabs with UHPC was presented. From the technical literature review, an experimental database was established. In order to examine the effectiveness of strengthening schemes with UHPC, size effect, and mechanical properties of RC beams or slabs, pre-damage degree for RC, strengthening configuration, characteristics of UHPC layer, curing conditions for UHPC and interfacial preparation for concrete substrate were discussed. In the literature review presented, different failure modes of UHPC-RC composite members under flexure were also identified. Then, analytical and numerical models developed in the literature to reproduce structural response and to predict cracking and ultimate capacity of strengthened beams or slabs with UHPC were summarized, and a comparison between these models was presented. The experimental evidence showed that UHPC could be used to increase the flexural strength of RC beams or slabs. Also, a cost analysis comparing with other strengthening techniques (such as CFRP) was presented. Finally, some future work is recommended to complement this promising strengthening technique for existing RC structures under flexure.
TL;DR: In this paper, the authors present a theoretical study on effects of combined impact and blast loadings on the failure behaviors and dynamic responses of a typical reinforced concrete (RC) column commonly used in medium-rise buildings.
Abstract: This paper presents a theoretical study on effects of combined impact and blast loadings on the failure behaviors and dynamic responses of a typical reinforced concrete (RC) column commonly used in medium-rise buildings. In the view of absence in current testing facility for simulating the combined loading, this investigation is carried out using numerical simulations in LS-DYNA. The vulnerability of the RC column to several loading-related parameters including the loading sequence, the time lag (tL) between the onsets of the applied loads, the axial load ratio (ALR), the loading location, and the impact velocity (Vimpact) is ideally assessed using a damage index (DI) on the basis of the column residual axial load carrying capacity. In order to calculate the DI, a multi-step loading methodology is proposed based on the combinations of static axial, and transient dynamic loadings. This paper is an ideally numerical exercise to evaluate different loading scenarios on RC columns varying in terms of some new parameters including ALR and the loading location compared to those studied for beams in the previous studies. From the FE simulations, it is obtained that the combination of a middle-rate impact loading and a close-in explosion provides more intensive loading conditions when they apply at the same elevation on the column. However, the combination of an identical impact loading with a far-field detonation leads to more severe failures when they are applied at different elevations. In addition, the priority of impact loading rather than explosion provides more intensive combined loading scenarios and causes more severe spallation and global failures in the column. By evaluating the effects of the time lag parameter, it is found that the column experiences greater shear forces and more severe global damages when the sequent detonation is applied at the time of the initial peak impact force. Furthermore, for the combined loading scenarios in which the loads applied to the column mid-height, the sensitivity thresholds of the damage index to ALR and Vimpact parameters are different from those calculated under sole impact and explosion loadings.
TL;DR: A novel optimal T MDI design formulation is proposed to address occupants’ comfort in wind-excited slender tall buildings susceptible to vortex shedding (VS) effects and to explore optimal TMDI’s potential for transforming part of the wind-induced kinetic energy to usable electricity in tall buildings.
Abstract: The tuned mass-damper-inerter (TMDI) couples the classical tuned mass-damper (TMD) with an inerter device which develops a resisting force proportional to the relative acceleration of its ends by the “inertance” constant. Previous works demonstrated that the TMDI leads to efficient broadband vibration control for a range of different structures under different dynamic excitations. This paper proposes a novel optimal TMDI design formulation to address occupants’ comfort in wind-excited slender tall buildings susceptible to vortex shedding (VS) effects and to explore optimal TMDI’s potential for transforming part of the wind-induced kinetic energy to usable electricity in tall buildings. Attention is focused on investigating benefits of TMDIs with different inertial properties (i.e., secondary mass/weight and inertance) configured in different topologies defined by the number of floors spanned by the inerter device to connect the secondary mass to the building structure. Optimally designed TMDIs for a wide range of inertial properties and three different topologies are obtained through numerical solution of the underlying optimization problem for a benchmark 305.9 m tall building with more than 6 height-to-width ratio subjected to experimentally calibrated spatially-correlated across-wind force field accounting for VS effects. Fixed performance design graphs on the TMDI inertial (mass-inertance) plane are furnished demonstrating that any fixed structural performance level in terms of occupants’ comfort (i.e., peak top floor acceleration) can be achieved through lightweight TMDIs as long as sufficient inertance is provided. Further, TMDI robustness to host structure properties and to reference wind velocity is shown to increase by increasing inertance or by spanning more floors in connecting the secondary mass with the host structure by the inerter. Lastly, it is found that increased available energy for harvesting in wind excited tall buildings is achieved by incorporating electromagnetic motors in TMDIs with varying damping property, while concurrent reduced floor acceleration and increased available energy for harvesting is accomplished by TMDI topologies with inerters spanning more floors.
TL;DR: In this paper, the compressive behavior of bamboo scrimber columns under cyclic compressive loading was investigated for the first time and a cyclic stress-strain model, including the envelope and the unloading and reloading segments, was developed for predicting the entire cyclic strain response of the scrimber, which can be used to simulate the seismic response of bamboo structures.
Abstract: Bamboo has become a promising construction material for replacing nonrenewable and polluting materials due to its ecological characteristics, low carbon content, high axial strength, favorable flexibility, and associated energy savings. Although the excellent flexibility and recovery abilities of bamboo have been recognized, their quantitative description has not yet been established. To quantitatively describe the flexibility and recovery performance of bamboo, the compressive behavior of bamboo scrimber columns under cyclic compressive loading was investigated for the first time. The results illustrate that the failure modes of bamboo scrimber columns include buckling, shearing and splitting, and the residual plastic strain ratio of bamboo scrimber is far lower than that of concrete in a high strain range. A cyclic stress-strain model, including the envelope and the unloading and reloading segments of the cyclic stress-strain curve, was developed for predicting the entire cyclic stress-strain response of bamboo scrimber. The proposed model is able to accurately predict the entire cyclic stress-strain response of bamboo scrimber and provides a quantitative description of the flexibility and recovery abilities of bamboo, which can be used to simulate the seismic response of bamboo structures.
TL;DR: A state-of-the-art review of the main applications of soft computing techniques to relevant structural and earthquake engineering problems is proposed, including the applications of fuzzy computing, evolutionary computing, swarm intelligence, and neural networks.
Abstract: Although civil engineering problems are often characterized by significant levels of complexity, they are generally approached and solved by combining several practitioners’ skills, such as intuition, past experience, logical reasoning, mathematical elaborations, and physical sense. This is also the case of problems in structural and earthquake engineering whose solution is generally based on the so-called “engineer’s judgment”. However, heuristic theories and algorithms within the framework of “soft computing” can provide a more rational and systematic way to approach and solve problems in these areas. As a matter of fact, the aforementioned algorithms have been recently utilized in several branches of engineering and applied sciences. This paper proposes a state-of-the-art review of the main applications of soft computing techniques to relevant structural and earthquake engineering problems. Specifically, the applications of fuzzy computing, evolutionary computing, swarm intelligence, and neural networks, as well as their hybrid combinations, are analyzed with the aim to examine their capability and limitations in modeling, simulation, and optimization problems.
TL;DR: The results clearly infer that the proposed data-driven ML framework can effectively predict failure mode and shear capacity of prestressed and non-prestressed UHPC beams with varying reinforcement detailing and configurations.
Abstract: This paper presents a data-driven machine learning (ML) framework for predicting failure mode and shear capacity of Ultra High Performance Concrete (UHPC) beams. To this end, a comprehensive database on 360 reported tests on UHPC beams with different geometric, fiber properties, loading and material characteristics was collected. This database was then analyzed utilizing different ML algorithms including, support vector machine (SVM), artificial neural networks (ANN), k-nearest neighbor (k-NN), and genetic programing (GP), to identify key parameters governing failure pattern and shear capacity of UHPC beams. The outcome of this analysis is a computational-based ML framework that is capable of identifying failure mode of UHPC beams and simplified expressions for predicting shear capacity of UHPC beams. Predictions obtained from the proposed framework was compared against the values obtained from design equations in codes, and also results from full-scale tests to show the reliability of the proposed approach. The results clearly infer that the proposed data-driven ML framework can effectively predict failure mode and shear capacity of prestressed and non-prestressed UHPC beams with varying reinforcement detailing and configurations.
TL;DR: Three domain adaptation techniques, namely joint training, sequential training, and ensemble learning are proposed and implemented to develop robust crack detection models that work on both datasets regardless of the material environment, demonstrate that the proposed techniques are able to successfully produce accuracies comparable to those of thematerial-specific models.
Abstract: Infrastructure defect detection solutions based on computer vision have recently emerged as powerful tools with applications in both traditional inspection practices, as well as robotic inspections. These applications involve the collection of images from a wide range of infrastructure systems with heterogeneous characteristics such as conditions, materials, surface appearances and textures. Consequently, defect detection models need to be sufficiently robust to accommodate this type of heterogeneity. Existing image-based crack detection literature almost entirely focuses on models tailored to crack detection in either concrete or asphalt surfaces with prior knowledge of the material involved and studies on crack detection in more than one material are needed for truly automated inspection systems. This paper focuses on the adaptability of deep learning-based crack detection models across common construction materials. To investigate this problem, a residual convolutional neural network architecture was trained and tested on two separate concrete and asphalt crack image data sets and compared with existing baselines. These tests demonstrated that the change of material significantly reduces crack detection accuracy of a tailored model. In response, three domain adaptation techniques, namely joint training, sequential training, and ensemble learning are proposed and implemented to develop robust crack detection models that work on both datasets regardless of the material environment. Results demonstrate that the proposed techniques are able to successfully produce accuracies comparable to those of the material-specific models, without prior knowledge of the material.
TL;DR: In this paper, the authors investigated the fragility of a 200m high concrete face rockfill dam (CFRD) subjected to mainshock-aftershock sequences based on multiple stripes analysis (MSA).
Abstract: Numerous earthquake disasters have demonstrated that secondary damage to structures induced by aftershocks may seriously threaten the seismic safety of structures since the mainshock may have already weakened structural integrity. This paper investigates the fragility of a 200-m high concrete face rockfill dam (CFRD) subjected to mainshock-aftershock sequences based on multiple stripes analysis (MSA). A modified generalized plasticity model and a plastic-damage model are used to describe the nonlinearity of the rockfills and the concrete face slabs, respectively. A series of nonlinear dynamic time history analyses for the CFRD under mainshock-aftershock sequences with different intensity combinations are conducted. The analysis focuses on the deformations, the shear strains and the damage index (DI) of the face slabs. According to the analysis results, the vertical deformation is the best indicator of the cumulative damage inflicted by aftershocks on the high CFRD. Then, considering the importance of face slab damage to the integrity and performance of the CFRD, the influences of aftershocks on the probability of the CFRD reaching a specific limit state are discussed based on vertical deformation and DI. The results reveal that aftershocks can significantly increase the fragility of the CFRD when it has been damaged by mainshocks.
TL;DR: In this article, the partial safety factor corresponding to the resistance model uncertainties in the use of nonlinear finite element analyses (NLFEAs) for reinforced concrete systems subjected to cyclic loads is assessed.
Abstract: This study assesses the partial safety factor corresponding to the resistance model uncertainties in the use of non-linear finite element analyses (NLFEAs) for reinforced concrete systems subjected to cyclic loads. Specifically, various walls experimentally tested are considered for this investigation and are simulated through two-dimensional (i.e., plane stress) finite element (NLFE) models. The comparison between the global resistances from the plane stress NLFE structural models and the experimental tests is carried out considering the possible modelling hypotheses available in relation to the mechanical response of reinforced concrete structural systems subjected to cyclic loads. After that, a probabilistic processing of the abovementioned epistemic uncertainties is carried out in line with a Bayesian updating. In detail, each prior distribution of the resistance model uncertainty related to a specific combination of the modelling hypotheses is computed and successively updated with the data achieved from the other models to estimate the posterior distribution. Hence, the coefficient of variation and the mean value of the resistance model uncertainties are evaluated and the corresponding partial safety factor is assessed in line with the NLFEA safety formats of reinforced concrete systems for seismic analyses.
TL;DR: In this paper, the authors presented an experimental study on monotonic axial compressive behavior of carbon FRP (CFRP) confined steel tube confined concrete (STCC) stub column and an analytical study on the confinement mechanism of and the ultimate axial bearing capacity of the elements.
Abstract: Steel tube confined concrete (STCC) is widely used in the vertical members of high-rise buildings such as columns. The axial load is not directly resisted by the steel tube in STCC, but is resisted via the interfacial frictional stress between steel tube and concrete core, which is different with that of concrete filled steel tube (CFT) members and would effectively suppress the outward local buckling of steel tube at early stage. Recently, fibre-reinforced polymer (FRP) confined STCC presents a potential to enhance the ductility and durability of such vertical elements. This paper presents an experimental study on monotonic axial compressive behaviour of carbon FRP (CFRP) confined STCC (CFRP-STCC) stub column and an analytical study on the confinement mechanism of and the ultimate axial bearing capacity of the elements. A three-stage confinement mechanism involving the different contributions of the steel tube and the CFRP wrap in CFRP-STCC elements was proposed based on the test results. A prediction model of the ultimate axial bearing capacity of CFRP-STCC stub columns was developed subsequently. Results show that the presence of CFRP wrap enhances effectively the load-bearing capacity and the ductility of steel tube confined plain concrete and reinforced concrete elements, and significantly prevents the local buckling of the steel tubes in the elements. The proposed prediction model of ultimate axial bearing capacity assesses test results with a great agreement.
TL;DR: It was found that the vehicle in the non-moving state can catch more bridge frequencies than in the moving state, and the contact-point response performs better than the car-body response, which can be used to detect the first few frequencies of the bridge, including the torsional frequency.
Abstract: This paper presents the measurement results of bridge frequencies by a test vehicle in non-moving and moving states. The self-made test vehicle fitted with vibration sensors is a two-wheel trailer, intentionally used to simulate the theoretical single degree-of-freedom system. The two-span bridge selected is located in the Chongqing University campus. For the purpose of comparison, the bridge frequencies were firstly measured by direct deployment of vibration sensors on the bridge. The dynamic properties of the test vehicle in the non-moving state, including the transmissibility, are examined in detail. Based on the measured car-body response, the contact-point response of the vehicle with the bridge was calculated by a backward procedure that allows the vehicle frequency to be eliminated. It was found that the vehicle in the non-moving state can catch more bridge frequencies than in the moving state. Both the car-body and contact-point responses agree well the results by direct measurement. But the contact-point response performs better than the car-body response, which can be used to detect the first few frequencies of the bridge, including the torsional frequency.
TL;DR: In this article, the buckling resistance of a novel active multidisciplinary sandwich plate (AMSP) under in-plane mechanical load or temperature change has been investigated, where an advanced porous core reinforced with carbon nanotubes (CNTs) integrated between two active piezoelectric faces.
Abstract: This work presents the buckling resistance of a novel active multidisciplinary sandwich plate (AMSP) under in-plane mechanical load or temperature change. The proposed sandwich plate includes an advanced porous core reinforced with carbon nanotubes (CNTs) integrated between two active piezoelectric faces. Functional graded (FG) profiles are considered for the dispersions of CNTs and porosity along the thickness of core layer. In addition, the effect of CNT agglomeration in core layer on the buckling resistance of the proposed AMSP has been studied by employing Eshelby-Mori-Tanaka (EMT)'s approach. A third order shear deformation theory (TSDT) of plates is adopted to obtain governing Eigen value equations for the thermal and mechanical buckling analyses of AMSP. The critical buckling resistance of each analysis has been extracted from the governing equations through a developed mesh-free solution based on moving least squares (MLSs) shape functions. The impacts of porosity, CNTs and geometrical dimensions on the buckling resistance of AMSPs have been investigated. The results show that embedding porosity in core results in a slight reduction in mechanical responses and a significant improvement in thermal buckling resistance. Moreover, reinforcing core layer with CNTs leads to remarkable drop and increase in thermal and mechanical buckling resistances, respectively. However, the formation of CNT agglomerations significantly reduces such CNTs impacts.
TL;DR: In this paper, a bio-inspired multi-cell corrugated tube for energy absorption is proposed, which consists of two parts: an inner rib and a corrugation tube into which the inner rib is inserted.
Abstract: This paper proposes a bio-inspired multi-cell corrugated tube for use in energy absorption. The proposed structure consists of two parts: an inner rib and a corrugated tube into which the inner rib is inserted. The structure of the corrugated tube is specified using a cosine expression based on two parameters, that is, the number of cosine wave crests and their amplitude. Two inner ribs with different sections (X-shaped and Y-shaped) were designed and the crashworthiness of the resulting tubes was analyzed. The crashworthiness was determined using the finite-element program LS-DYNA. The numerical results show that the modes of collapse of the multi-cell corrugated tubes can be classified into four types: unstable, diamond, ring, and mixed modes. Each mode is strongly affected by the number of cosine wave crests and their amplitude. By analyzing the force–displacement performance and crashworthiness indicators, it was found that tubes with appropriate number of wave crests and amplitudes, and inner rib shape experience lower initial peak forces and increase energy absorption and specific energy absorption (compared with a traditional straight tube with the same inner rib). The undulation in the load-carrying capacity is also decreased. Thus, the multi-cell corrugated tubes have good crashworthiness.
TL;DR: A performance-oriented design procedure aimed at achieving a target displacement demand of the combined CSS + SMAGD system under the maximum credible design earthquake and a parametric study comprising a variety of CSS and SMAGD properties reveals that the proposed isolation layout is suitable to limit the maximum displacement under ultimate limit state earthquakes.
Abstract: The flag-shaped hysteretic behavior of Shape Memory Alloys (SMAs) can be conveniently used for developing efficient isolation systems, providing energy dissipation without implying residual displacements. This work presents a base isolation layout that combines low-friction curved surface sliders (CSSs) with SMA gap dampers (SMAGDs). The proposed SMAGDs are formed by a group of SMA wires placed in parallel with the CSS isolation system and connected to it through a sliding pin and a slotted ring in order to accomplish the “gap damper” feature. Based on this installation configuration, SMAGDs introduce additional stiffening and energy dissipation to the isolation system only when the displacement of the CSS exceeds a certain threshold or gap displacement d gap , while not being engaged for lower displacements. Consequently, the system exhibits a phased behavior, meaning that its reaction force depends on the amplitude of the displacement. This is particularly convenient for limiting seismic displacements while avoiding at the same time undesirable effects such as high structural accelerations and poor re-centering capability exhibited by alternative systems at low-intensity excitations, e.g. systems based on high-friction CSSs or combinations of CSSs with traditional supplemental energy dissipation devices. The paper describes a preliminary design procedure and the evaluation of the seismic performance of the proposed CSS + SMGAGD system. A leading design parameter of the SMAGDs is the overall cross-sectional area of the SMA wires, which is designed here through a direct displacement based procedure, by introducing some reasonable assumptions for the definition of the linear equivalent mechanical properties of CSS, SMAGD and combined CSS + SMAGD system. This performance-oriented design procedure is aimed at achieving a target displacement demand of the combined CSS + SMAGD system under the maximum credible design earthquake. A parametric study comprising a variety of CSS and SMAGD properties reveals that the proposed isolation layout is suitable to limit the maximum displacement under ultimate limit state earthquakes, providing at the same time satisfactory energy dissipation along with high re-centering capability, and outperforms both low-friction CSSs and high-friction CSSs.
TL;DR: In this paper, the authors presented the first-ever axial compression test on RACFCTs having three different slenderness ratios ranging from 20 to 40; the effect of the recycled coarse aggregate (RA) replacement ratio is also examined.
Abstract: Aiming to expand the structural applications of recycled aggregate concrete (RAC), the innovative approach of using the hybrid form of RAC-filled glass-fiber-reinforced polymer (GFRP)–steel composite tube columns (RACFCTs) is particularly striking because of their optimal combining of fiber-reinforced polymer (FRP), RAC and steel. The existing research relevant to RACFCTs is limited and is mainly concerned with seismic performance. This paper presents the first-ever axial compression test on RACFCTs having three different slenderness ratios ranging from 20 to 40; the effect of the recycled coarse aggregate (RA) replacement ratio is also examined. The main performance aspects evaluated in this study were the failure mode, ultimate condition, axial load–lateral deflection curves, load–strain curves, and dilation behavior. The test results clearly show the benefit of the GFRP–steel composite tube on the compression behavior of the columns. The test results also demonstrate that the RACFCTs with a high RA replacement ratio and a high slenderness ratio had more ductile behavior. Finally, a design equation for predicting the maximum capacity of RACFCTs was derived, and its applicability was examined. The proposed formula produced a close estimate of the test results.
TL;DR: A probabilistic approach for characterization of the regression pattern between bridge temperature and expansion joint displacement by use of Structural Health Monitoring data and for SHM-based condition assessment and damage alarm of bridge expansion joints is developed in the Bayesian context.
Abstract: Premature failure of bridge expansion joints has been increasingly observed in recent years, and nowadays it becomes a major concern of bridge owners. A better understanding of their performance in service is highly desired. Deterministic linear regression models between bridge temperature and expansion joint displacement have widely been adopted to characterize the in-service performance of bridge expansion joints. When such a regression pattern is elicited using real-time monitoring data, the deterministic models fail to account for uncertainty inherent in the monitoring data and interpret the model error. In this study, a probabilistic approach for characterization of the regression pattern between bridge temperature and expansion joint displacement by use of Structural Health Monitoring (SHM) data and for SHM-based condition assessment and damage alarm of bridge expansion joints is developed in the Bayesian context. The proposed approach enables to account for the uncertainty contained in the monitoring data and quantify the model error and the prediction uncertainty. By combining the Bayesian regression model and reliability theory, an anomaly index is formulated to evaluate the health condition of the expansion joint when newly collected monitoring data are available and to provide damage alarm once the probability of damage exceeds a certain threshold. In the case study, real-world monitoring data acquired from a cable-stayed bridge are used to illustrate the proposed approach, including examining the appropriateness of the design values of expansion joint displacements under extreme temperatures in serviceability limit state.
TL;DR: In this article, the authors proposed a novel SMA-steel coupled reinforcement for concrete bridge piers, which is intended to achieve the balance between self-centering and energy dissipation capacities.
Abstract: Concrete bridge piers with conventional steel reinforcing bars are vulnerable to strong earthquakes by inducing significant residual deformations, which substantially weakens the seismic resilience of bridges. Superelastic shape memory alloy (SMA) bars showing superior self-centering capacities are desirable substitutes to steel reinforcements to minimize the seismically-induced residual deformations of piers. Nevertheless, high cost, difficult machining, and lack of sufficient energy dissipation are the primary restraining factors to a wide implementation of SMA reinforcements. This study proposes a novel SMA-steel coupled reinforcement for concrete bridge piers, which is intended to achieve the balance between self-centering and energy dissipation capacities. Probabilistic seismic fragility analyses are conducted on the prototype bridge with either pure steel, SMA-steel coupled, or pure SMA reinforcements to evaluate their probability of damage at different limit states. Seismic loss analyses are further performed to compare the relative cost-effectiveness of different patterns of reinforcements. The results indicate that an optimal amount ratio between SMA and steel bars can be found for the coupled reinforcements, which shows lower vulnerabilities and higher resilience under earthquakes than the other reinforcement patterns. The direct repair loss and the indirect downtime loss after earthquakes are considerably reduced when the SMA reinforcing bars are introduced. The coupled reinforcement with the optimal SMA-steel amount ratio shows the most effectiveness in mitigating the long-term economic impacts induced by seismic hazards within the lifetime of the bridge.
TL;DR: In this paper, a flexural test was performed on steel-UHPC composite beams with stud connectors (SU-S) and bolt connectors(SU-B) at the interface.
Abstract: Using ultra-high performance concrete (UHPC) in the hogging moment regions of composite beams might significantly enhance their cracking and flexural performance. In the present paper, the flexural test was performed on steel-UHPC composite beams with stud connectors (SU-S) and bolt connectors (SU-B) at the interface. Crack resistance, ultimate flexural capacity, failure modes, and deformation characteristics of SU-S and SU-B under hogging moment were investigated. The test results showed that steel-UHPC composite beams exhibited excellent cracking and flexural performance under the hogging moment. As compared to the steel-normal strength concrete (NSC) composite beam (SC-S), cracking load and ultimate flexural capacity of steel-UHPC composite beams increased by around 340% and 26%, respectively. Moreover, the length and width of cracks in the UHPC flange plate developed slowly with load. Many short and small cracks were observed, having a close spacing in the UHPC flange plate. However, ductility and rotation capacity of both SU-S and SU-B under the hogging moment were smaller than those of SC-S. Due to the bolts’ slip in SU-B, the tensile stress in the UHPC flange plate was reduced, resulting in higher crack resistance and rotation capacity than SU-S, while its flexural stiffness and ultimate flexural capacity were slightly smaller than those of SU-S. Finally, theoretical formulas were proposed for calculation of the slip moment, moment at crack width of 0.05 mm and ultimate moment of the steel-UHPC composite beams under the hogging moment. The test results verify the applicability of these formulas to predict flexural capacity of the steel-UHPC composite beams.
TL;DR: The reliability-based approach is adopted to quantify the structural robustness of reinforced concrete (RC) structures subjected to progressive collapse since it is a trade-off between comprehensiveness and operability.
Abstract: Robustness is the most comprehensive and acceptable index that describes the ability of structures to withstand progressive collapse induced by accidental extreme events such as impact, explosion and terrorist attacks. As found in the literature, several approaches have been proposed to quantify the robustness of a structure, e.g., approaches based on deterministic structural performance, failure probabilities (or the collapse reliabilities), and collapse risks. In this paper, the reliability-based approach is adopted to quantify the structural robustness of reinforced concrete (RC) structures subjected to progressive collapse since it is a trade-off between comprehensiveness and operability. An efficient calculation framework is developed based on the probability density evolution method (PDEM). Emphasis is placed on two aspects, i.e., the progressive collapse behavior modeling and the evaluation of the structural reliability. The static nonlinear pushdown method is employed to represent the progressive collapse capacity of the structures, and the force-based frame element is used to generate the finite element model. Then, the PDEM incorporated with the equivalent extreme value event is used to capture the reliability indices before and after progressive collapse. With the reliability indices, the robustness index can be easily computed. The developed framework is applied to two prototype RC frames designed in accordance with the Chinese design code. The reliability and robustness indices of the frames under different initial local damage scenarios (namely, removal of columns in typical pushdown method) are obtained, and the influences of the position of the initial damage scenarios on the robustness are also discussed.
TL;DR: In this paper, the authors investigated the stress-strain response, failure pattern and criteria of CTB under triaxial compression loading with various confining pressures and components and revealed how the confining pressure influences the deformation behavior of the CTB.
Abstract: A full understanding of the mechanical response of cemented tailings backfill (CTB) under various loading scenarios is beneficial for mining engineering applications This study experimentally investigates the stress–strain response, failure pattern and criteria of CTB under triaxial compression loading with various confining pressures and components Microstructural analyses are also conducted to reveal how the confining pressure influences the deformation behavior of CTB Later, triaxial compression strength data are used to calibrate the constitutive parameters of the Holmquist-Johnson-Cook (HJC) model for CTB Following the HJC model calibration, a split Hopkinson pressure bar (SHPB) model is established by using the commercial finite element software LS-DYNA to evaluate the effect of the lateral initial confinement and end-friction confinement on the dynamic compression strength of CTB with various components
TL;DR: In this article, a new shape memory alloy (SMA) washer spring-based self-centering rocking (SCR) system was proposed for bridge piers, which combines the advantage of the existing rocking pier solution with extra benefits such as simplified construction, excellent fatigue and corrosion resistance, and extra locking mechanism which safely prevents the pier from excessive rocking.
Abstract: The emergence of rocking bridge piers provides the community of civil engineers with a broader vision of next-generation seismic-resilient bridge design. This study introduces a new type of shape memory alloy (SMA) washer spring-based self-centering rocking (SCR) systems which could be an important addition to the existing rocking pier family. The proposed system combines the advantage of the existing rocking pier solution with extra benefits such as simplified construction, excellent fatigue and corrosion resistance, and extra “locking mechanism” which safely prevents the pier from excessive rocking. The working principle of the SCR piers is discussed first, and five tests are subsequently carried out on proof-of-concept SCR pier specimens. This is followed by a further numerical study examining an extended range of design parameters. The SCR pier shows excellent self-centering capability with minimal damage to the pier, which is attributed to the intended gap-opening deformation mode. Moderate energy dissipation is offered by the SMA washer springs, and once they are fully flattened, further drift is provided by the flexural deformation of the pier itself. The SMA washers can be used repeatedly with no need for repair/replacement, and the highly flexible stack pattern caters to different design objectives and requirements. An effective supplementary source of energy dissipation is enabled by installing steel angles at the gap opening interface. The experimental and numerical investigations provide a strong proof of feasibility of this innovative structural system.
TL;DR: In this article, a single-degree-of-freedom (SDOF) model was proposed to quantify the effects of service load, initial velocity, initial displacements, and damping ratio on the dynamic response.
Abstract: Unbonded post-tensioned precast concrete (UPPC) frame exhibits excellent performance in resisting seismic load from experimental tests and post-earthquake investigations. However, the behavior of UPPC frames subjected to extreme load such as the loss of a column due to explosion is still not well studied. To fill this knowledge gap, in this paper, four 1/2 scaled UPPC beam-column substructures were tested under both quasi-static and dynamic loading regimes. The comparative study between these two test-regimes were subsequently performed, which provides a clear understanding of the difference of these two test methods in progressive collapse studies for other researchers. The test results indicated that UPPC frames achieved required load redistribution capacity to mitigate progressive collapse. The failure modes of the frames observed in dynamic test were quite similar to that in quasi-static tests. Moreover, it was found that strain rate effects were insignificant for progressive collapse events caused by suddenly column removal. Based on the measured load resisting function from quasi-static tests, a single-degree-of-freedom (SDOF) model, with the consideration of strain hardening and softening, was developed. After validation, the proposed SDOF model was used to quantify the effects of service load, initial velocity, initial displacements, and damping ratio on the dynamic response. It was found that the damping ratio, non-zero initial velocity and initial displacement are the three most influential parameters.