Design Of Reinforced Concrete Structures Research Articles

Nonlinear Static Soil-Structure Interaction Analysis of Time-Dependent Soil Deformation Effects on RC Structures

Soil response and superstructure behavior are two major factors influencing the long-term performance of reinforced concrete (RC) structures. Maintaining the structural integrity of these structures over time is crucial due to the complex static interactions between the soil and the structure. This study uses a finite element model to examine the stability of RC structures, considering the long-term static interactions between the nonlinear behavior of the soil and the structure. Numerical simulations are performed on real RC beam constructions at serviceability limit states (SLS) under various loading scenarios in both homogeneous and heterogeneous soil conditions. The parametric study's results indicate that soil heterogeneity and static soil-structure interactions significantly influence the design of RC structures. The nonlinear behavior of the soil over time intensifies these impacts further. This study shows how important it is to think about different types of soil and how they interact with structures when they are not moving. This is especially true when it comes to soil that is easily compressed and changes shape over time in a nonlinear way. By incorporating these factors, the research highlights the critical need to integrate soil heterogeneity and static interaction into the design process to ensure the stability and safety of RC structures. Ultimately, the results demonstrate that accounting for these complex interactions can greatly improve the durability and reliability of RC structures in diverse soil conditions.

Dynamic behaviors of seismic-designed RC beams under asymmetrical low-velocity impact loads

Seismic-designed reinforced concrete (RC) structures could be subjected to asymmetrical low-velocity impact loads, e.g., vehicle/barge collisions and rockfall impacts, while existing studies mainly focus on the dynamic responses of symmetrical impacted scenarios. This study experimentally and numerically examined the influence of stirrup ratio and impact location on failure modes and impact behaviors of RC beams. Firstly, symmetrical and asymmetrical drop-weight tests were conducted on six RC beams, and digital image correlation technique was applied to capture the damage evolution process and dynamic responses. Then, the above test was reproduced to validate the applicability of the finite element analyses approach, and numerical simulations were further performed to explore the transformation mechanism of the failure mode of asymmetrical impacted beams. The results showed that, (i) the shear-bending capacity ratio of the beam decreased with the stirrup ratio increasing or the impact location moving towards the mid-span, causing its failure mode to transform from shear to flexural under asymmetrical impact loads; (ii) the shear bearing capacity mainly controlled the occurrence of concrete cracking of asymmetrical impacted beams, and moment bending capacity influenced the post-cracked performance; (iii) increasing the stirrup ratio improved the joint action between longitudinal bars and stirrups and enhance the confinement effect on concrete, reducing the damage degree and deformation of asymmetrical impacted beam; (iv) under the effect of shear wave propagation, asymmetrical impacted beams completed the global impact process faster than symmetrical impacted ones. Finally, a two-degree-of freedom model was established to quickly calculate the displacement-time history at the impact location of asymmetrical impacted beams. The current work could provide a helpful reference for the impact-resistant design of RC structures against asymmetrical impact loads.

Research on chloride ion permeability resistance of concretes bonded with CFRP sheets under dry-wet cycles

Considering the widespread application of carbon fibre-reinforced polymer (CFRP) as a protective material for reinforced concrete (RC) structures, this study focuses on the ability of CFRP laminates with different numbers of layers bonded to the concrete surface to reduce the ingress of chloride ions. Variations in the free chloride concentration distribution in concrete before and after CFRP bonding were explored systematically. Nonlinear fitting was applied to the experimental data to establish a calculation model for the diffusion of free chloride ions in concrete with CFRP bonded to the surface, which was subsequently validated. Based on the proposed model, the reduction in the surface chloride concentration of concrete after bonding different numbers of CFRP layers was quantified as the reduction value. Moreover, recommendations for the durable design of RC structures bonded with CFRP in wet-dry cyclic environments are provided. The results indicate that the surface chloride concentration in concrete increases continuously with increasing wet-dry cycles, eventually reaching a steady state. Compared with the concrete specimens without CFRP bonding, the bonding of one, two, or three layers of CFRP led to reductions in the stable surface chloride concentration of concrete by 70.8%, 82.6%, and 84.9%, respectively. And no obvious convection zone was observed in the concrete after CFRP bonding. The validation results of the proposed calculation model demonstrated its high accuracy, making it suitable for durable design and service life prediction.

Forecasting ultimate bond strength between ribbed stainless steel bar and concrete using explainable machine learning algorithms

PurposeIn recent years, there has been growing interest in the use of stainless steel (SS) in reinforced concrete (RC) structures due to its distinctive corrosion resistance and excellent mechanical properties. To ensure effective synergy between SS and concrete, it is necessary to develop a time-saving approach to accurately determine the ultimate bond strength τu between the two materials in RC structures.Design/methodology/approachThree robust machine learning (ML) models, including support vector regression (SVR), random forest (RF) and extreme gradient boosting (XGBoost), are employed to predict τu between ribbed SS and concrete. Model hyperparameters are fine-tuned using Bayesian optimization (BO) with 10-fold cross-validation. The interpretable techniques including partial dependence plots (PDPs) and Shapley additive explanation (SHAP) are also utilized to figure out the relationship between input features and output for the best model.FindingsAmong the three ML models, BO-XGBoost exhibits the strongest generalization and highest accuracy in estimating τu. According to SHAP value-based feature importance, compressive strength of concrete fc emerges as the most prominent feature, followed by concrete cover thickness c, while the embedment length to diameter ratio l/d, and the diameter d for SS are deemed less important features. Properly increasing c and fc can enhance τu between ribbed SS and concrete.Originality/valueAn online graphical user interface (GUI) has been developed based on BO-XGBoost to estimate τu. This tool can be utilized in structural design of RC structures with ribbed SS as reinforcement.

Design optimization of irregularity RC structure based on ANN-PSO

Seismic design principles advocate for simple and regular structures to minimize earthquake damage. However, this frequently does not lead to unique and aesthetically pleasing designs, leading some engineers to select irregular structures despite the potential risks. The primary aim of this investigation is to achieve the optimal design of torsional irregularity coefficients for planar irregular reinforced concrete (RC) frames under static and dynamic loads, utilizing a 3D 6-layer model. Structural ground vibration analysis was conducted using the ETABS software. By imposing limits on the torsional irregularity coefficients for each layer of the frame layout, we subsequently applied the combination of artificial neural networks (ANN) with the particle swarm optimization (PSO) algorithm, namely ANN-PSO, to address the size distribution issue across the structure. The design variables included the dimensions of the columns located in each layer of the layout. The results demonstrate that the ANN-PSO algorithm optimizes the cross-sectional area of columns with significant variations. The coefficients of the torsion inequality rule in the optimized solution closely approach the minimum values. The dimensions and orientations of the optimized columns slightly differ from the pre-optimized scheme. In the optimized scheme, the coefficients of the torsional irregularity in the Y-direction meet the requirements, preventing any torsional irregularities from occurring. The research presented an effective method, including an innovative combination of ANN-PSO and the finite element method (FEM), for designing RC structures. The findings of the research provided a practical solution to fulfill torsional regularity criteria, indicating the proposed approach is an effective method for the economical and safe design of RC structures in earthquake-prone areas. The outcomes of the present study highlighted the innovative framework to achieve optimal and safe designs for irregular RC structures while minimizing torsional damage during earthquakes.

Effects of steel bar and bi-directional erosion on chloride diffusion in reinforced concrete: A 3D mesoscale study

This work proposes a novel numerical framework to investigate 3D chloride diffusion behavior in reinforced concrete (RC). An efficient dynamic modeling approach is developed to generate the RC models with real-shaped aggregates at mesoscale. A semi-closed form solution of Fick’s second law is established to account for the time-varying chloride diffusion coefficient and surface chloride concentration through a genetic algorithm. Moreover, the effects of aggregate distribution and morphology on chloride diffusion are examined. The validated results demonstrate that the random distribution of aggregates leads to varied chloride concentration, and anisotropic aggregate morphology increases hindrance to chloride diffusion. Steel bar also affects chloride diffusion, causing an increase in chloride concentration on the steel surface. This hinder effect intensifies as the steel diameter increases and the protective layer thickness decreases. Additionally, bi-directional diffusion elevates chloride concentration on the corner steel surface, while smaller steel diameter and thicker protective layer render the corner steel bar more susceptible to bi-directional diffusion. The proposed framework has incorporated various influencing factors with comprehensive parametric analyses and holds potential for engineering design of RC structures considering durability, safety, and sustainability.

Two-stage multi-objective optimization of reinforced concrete buildings based on non-dominated sorting genetic algorithm (NSGA-III)

The colossal environmental footprint of the construction industry is a paramount ecological concern, especially in the wake of climate change threats and natural resources depletion. The present study performs a novel two-stage optimization approach for the design of reinforced concrete (RC) frame buildings to minimize the water footprint (WF) and cost, based on non-dominated sorting genetic algorithm (NSGA-III). The first stage includes multi-objective optimization (MOO) with respect to the cost and capacity of cross-sections of RC beam and column elements for any possible combination of design variables using section-based database schema (SBDBS). The second stage is MOO based on NSGA-III to minimize the volumes of reinforcing steel and concrete in RC structure considering the optimal sections generated by SBDBS as a pre-determined list for elements. Four structural archetypes consisting of 4, 8, 12, and 16-story frames were considered in the design optimization problems. The main objective of this optimization is to calculate the cost and WF of RC structures for various unit cost and WF of materials, and as a result, identify the optimal design of RC structures. The result of this optimization framework allows the decision maker to identify the optimal RC structural design for any cost or WF condition by performing a sensitivity analysis, without need for additional structural analysis or optimization. The proposed approach further allows the decision maker to consider the uncertainty of WF and cost of materials that emanate from regional or spatiotemporal variables. The results show that the shape of the optimal design Pareto front (PF) is more related to the values of unit WF of materials than the costs. To highlight the advantages of the proposed procedure, probabilistic sensitivity analysis and decision-making strategy were performed and pertinent conclusions were drawn.

Effects of Different Wall Openings on the Cyclic Behavior of Aerated Concrete Block Infilled RC Frames

In the current study, the effects of infilled reinforced concrete (RC) frames with different window and door openings under cyclic loads were investigated. For this purpose, five in-filled RC frames with different infill wall openings were produced. The main parameters to evaluate overall performance of the RC frames with infill walls, the load carrying capacities, displacement ductility, stiffness degradation and energy dissipation capacities were determined using obtained results. At the end of the study, even if the opening ratios are the equal, it has been observed that the location and number of openings have a significant effect on the behavior and failure pattern of the RC frames. Also, increase in the openings ratio decreases the load carrying capacity, and energy consumption capacity. Based on these results, it is suggested that infill walls affect the structural behavior and failure pattern. Therefore, infill wall openings should be considered in the design of RC structures.

Design of RCC Structure Instead of Brick Structure in Water Retaining and Sedimentation & Storage

The design of reinforced concrete (RCC) structures for water retaining applications has become a popular alternative to traditional brick structures. RCC structures offer advantages such as durability, strength, and resistance to weathering and water. This paper explores the design considerations and challenges associated with the use of RCC structures for water retaining applications. It discusses the design codes and criteria, including load calculations, concrete strength, and reinforcement detailing. Additionally, the paper highlights the different types of RCC structures used for water retaining applications, such as flat-bottomed tanks, elevated tanks, and circular tanks. It also examines the advantages and disadvantages of each structure type, as well as the design considerations and challenges specific to each. Finally, the paper provides insight into the construction process of RCC structures, including site preparation, formwork, reinforcement, and concrete pouring.

Residual Shear Capacity of Post-Fire RC Beams under Indirect Loading

Building fire is one of the most frequent disasters. The mechanical properties of concrete and steel will deteriorate to different degrees under fire exposure, thus weakening the bearing capacity of reinforced concrete (RC) members. Therefore, it is of great theoretical and practical significance to carry out research on the bearing capacity of RC members subjected to fire. To study the residual shear capacity of post-fire RC beams under indirect loading, static load tests were carried out on six full-scale RC beams to investigate the development of diagonal cracks and failure modes under an indirect load. Numerical models were established with ABAQUS to study the effect of the shear span-to-depth ratio and stirrup ratio on the residual shear capacity of the tested beams after fire exposure, and the shear capacity calculation method of indirectly loaded beams after high temperature is proposed. The results indicate that although the fire had no obvious affect on the failure mode of the beam under indirect loading, the fire aggravated the failure degree of the beams without additional transverse reinforcement. Moreover, the ultimate bending capacity of beams with additional transverse reinforcement decreased obviously after fire. The residual shear capacity of indirectly-loaded beams subjected to fire decreased compared with the directly-loaded beams due to the variation in the shear span-to-depth ratio and stirrup ratio. The shear capacity theoretical calculation results of the indirectly-loaded beam after high temperature were in good agreement with the tested results, and the average absolute error was 3.88%. Therefore, this calculation method for an indirectly loaded beam with a shear span-to-depth ratio less than 3.0 after fire as proposed in this paper was effective. The findings of this study are expected to provide a reference for the improved fire-resistant design of RC structures under indirect loading.

Atomic scale insight into the mechanisms of chloride induced steel corrosion in concrete

Chloride (Cl) induced steel corrosion is a major cause of durability issues of reinforced concrete (RC) structures and causes a large economic loss every year. Understanding the mechanisms of Cl induced steel corrosion in concrete is of great importance to develop anti-corrosion methods and further lowers down the repair and strengthening frequency and cost. Hence, the nature of steel depassivation and corrosion induced by Cl at atomic scale was revealed through the density functional theory (DFT) calculations to better understand the Cl induced corrosion mechanism. The results indicated that Cl species weakened the bonding of oxygen (O) with outer iron (Fe) atoms while enhanced the hybridization of O with inner Fe atoms, thus induced the breakdown of passive films. Besides, Cl facilitated the charge loss of outer Fe atoms and improved the interactions of water molecular (H2O) with these Fe atoms. When co-adsorption with O atom, hydroxyl (OH) generated by dissociative adsorption of H2O enhanced the charge loss of outer Fe atoms. Then OH strongly bonded with the neighboring Fe atoms to form the initial corrosion products, iron hydroxides (Fe-OH). The above DFT calculations are consistent with the experimental results about the steel depassivation and corrosion processes in concrete and hopefully these results can guide the anti-corrosion design of RC structures.

Machine learning algorithms in the environmental corrosion evaluation of reinforced concrete structures - A review

Accurate corrosion assessment of reinforced concrete (RC) structures is expected to improve the service life and durability of structures. However, traditional evaluation methods rely on simple regression and assumption models, which are easy to lead to unreliable evaluation results. The time-consuming and complex calculations in corrosion assessment are particularly suitable for machine learning (ML) and have already been deeply affected by the application of existing ML algorithms. The review analyzes recent ML methods for corrosion assessment of RC structures. These algorithms have recently had a significant impact on the estimation of the corrosion process, significant mechanical properties and durability of RC structures. In addition, some challenges that have emerged in corrosion evaluation and could be solved by ML algorithm are discussed critically. Through the detailed analysis of the challenges and future directions, researchers and engineers related industry will gain vital insight on the sustainable durability design of RC structures.

Effect of Interface Transition Zone and Coarse Aggregate on Microscopic Diffusion Behavior of Chloride Ion.

Concrete is a multiphase composite material composed of coarse aggregate, cement mortar, and interface transition zone (ITZ). It is of great significance to study the effect of ITZ and coarse aggregate on chloride microscopic diffusion behavior for predicting the service life of reinforced concrete (RC) structures. By introducing the random distribution function, a random coarse aggregate model considering the randomness of the thickness of the ITZ was established. Furthermore, a two-dimensional (2D) chloride ion diffusion mesoscopic model was developed by specifying different diffusion properties for different phase materials of concrete. Moreover, the effects of coarse aggregate rate, ITZ thickness, and ITZ diffusion property on chloride ion diffusion behavior were investigated in this paper. The research showed that the aggregate has hindrance and agglomeration action on chloride ion diffusion. Although the volume content of the ITZ was very small, less than 0.2% of the total volume of concrete, the effect of the ITZ on the chloride diffusion in concrete cannot be ignored. More importantly, the mechanism of promoting chloride diffusion in the ITZ was revealed through the chloride diffusion trajectory. The research revealed the transmission mechanism of chloride ions in the meso-structure of concrete and provides theoretical support for the design of RC structures in coastal areas.

Effective reinforcement ratio of RC beams: Validation of modelling assumptions with high‐resolution strain data

AbstractConcrete tensile stresses influence the cracking behaviour and the stiffness of reinforced concrete (RC) members. Most design codes account for this tension stiffening effect using an effective reinforcement ratio. Although this ratio has a significant influence on the design of RC structures, its quantification is controversial in many cases, and typically relies on empirical geometry‐based expressions. One main reason for this knowledge gap is that the area of concrete in tension can only be verified indirectly, for example, through crack widths and spacings and using a suitable mechanical model. This indirect validation is subject to considerable uncertainty as it depends on parameters that scatter (e.g., bond stresses and the concrete tensile strength), and further assumptions relating internal stresses to the applied loads are required. This article outlines how refined measurements of the reinforcing steel strains and the concrete deformations in the compression zone, combining distributed fibre optic sensing (DFOS) and digital image correlation (DIC), can be used in order to obtain a more reliable quantification of the parameters affecting tension stiffening and hence, the effective reinforcement ratio. Selected models are validated against experimental data of an RC beam tested under four‐point bending, underlining the potential of DFOS and DIC as valuable tools for a better understanding of RC structures and the enhancement of mechanical models.

Explicitly Assessing the Durability of RC Structures Considering Spatial Variability and Correlation

The durability design of reinforced concrete (RC) structures that are exposed to aggressive environmental attacks (e.g., corrosion due to chloride ingress in marine environment) plays a vital role in ensuring the structural serviceability within a reference period of interest. Existing approaches for the durability design and assessment of RC structures have, for the most part, not considered the spatial distribution of corrosion-related structural properties. In this paper, a closed-form approach is developed for durability assessment of RC structures, where the structural dimension, spatial variability, and correlation of structural properties such as the concrete cover thickness and the chloride diffusion coefficient are taken into account. The corrosion and crack initiations of an emerged tube tunnel segment that was used in the Hong Kong-Zhuhai-Macau bridge project were assessed to demonstrate the applicability of the proposed approach. The accuracy of the method was verified through a comparison with Monte Carlo simulation results based on two-dimensional random field modeling. The proposed method can be used to efficiently assess the durability performance of RC structures in the marine environment and has the potential to become an efficient tool to guide the durability design of RC structures subjected to corrosion.

Chloride penetration in freeze–thaw induced cracking concrete: A numerical study

Reinforced concrete (RC) structures, serving in marine and cold environments, are attacked by freeze–thaw cycles (FTCs) and chloride penetration, both of which can cause serious deterioration of RC structures. Existing studies lack of models considering the development of pore structure, as well as crack propagation caused by freeze and thaw. In this study, a multi-phase numerical model is proposed for studying chloride transport in concrete under FTCs. Unlike the existing models, the diffusion coefficient in the presented work is associated with the evolution of pore structure, and the induced crack is considered to be time-dependent and propagates with cycles of freeze–thaw action. The validity of the presented model is verified against a set of third-party experiments. Some important factors, such as FTCs, crack width, porosity, connectivity and most probable pore diameter factor are elaborated to illustrate how these factors affect chloride transport. The findings can bring insights to the durability design of RC structures serving in cold or marine regions.

Rate-dependent compressive behavior of concrete confined with Large-Rupture-Strain (LRS) FRP

The polyethylene naphthalene (PEN) and polyethylene terephthalate (PET) fibers have a tensile rupture strain of over 5%, and hence they are referred to as large-rupture-strain (LRS) fiber reinforced polymer (FRP) materials. Their large rupture strain characteristics may contribute to significant improvement of the impact resistance of reinforced concrete (RC) structures. This study investigates the strain rate effect on LRS FRP-confined concrete through Split Hopkinson Pressure Bar (SHPB) test. Results revealed that LRS FRP-confined concrete specimens exhibited superior impact resistance behaviors compared to the counterpart confined with CFRP composites when subjected to a single impact. The critical strain, compressive strength and toughness of the LRS FRP-confined concrete specimen increased with increasing strain rate. Due to the large rupture strain characteristics, the LRS FRP-confined concrete specimen virtually had no visible damage after a single impact. To study the damage evolution mechanism of concrete, the specimens were impacted for multiple times with the same energy until the failure of the specimen. Due to progressive concrete damage, the dynamic compressive strength and toughness experienced a decrease during multiple impacts. These findings might promote the application of LRS FRP materials in the field of impact resistance design of RC structures as a promising external jacketing material.

Numerical investigation of external sulfate attack and its effect on chloride binding and diffusion in concrete

Reinforced concrete (RC) structures may suffer from serious durability problems during long-term service. To investigate the deterioration of RC structures subjected to the dual attacks of chlorides and sulfates, this study proposes a coupled model for external sulfate attack (ESA) and its effect on chloride binding and diffusion. To account for the influence of sulfate attack on chloride binding, a reduction function is proposed. The effect of sulfate-induced damage on the chloride diffusion and chloride binding is considered through a damage function. The coupled model is validated against third-party experimental data from multiple perspectives. Some important factors such as solution concentration, immersion time, curing time and water-cement ratio, as well as how these factors affect the impact of sulfate attack on chloride transport, were elaborated. The findings may bring insights to the durability design of RC structures serving in harsh environments.

Framework for fragility assessment of reinforced concrete portal frame subjected to elevated temperature

Despite realizing the importance of risk-based frameworks in fire engineering, current fire safety guidelines are largely prescriptive and over-conservative in nature, which do not consider the effect of uncertainties influencing the fire resistance of the structural systems. In this context, a probabilistic framework is presented to investigate vulnerability of a reinforced concrete (RC) portal frame subjected to fire. Here, a three-dimensional (3-D) nonlinear finite element (FE) model for the RC portal frame exposed to elevated temperature is developed, and transient thermo-mechanical analysis is carried out by duly incorporating temperature variation of thermal and mechanical properties of concrete and steel rebar. Probabilistic study is conducted by developing fragility curves based on limit state of deflection to quantify the vulnerability of the structural members exposed to fire loading. Parametric studies are conducted by varying the material properties of the RC portal frame to investigate the influence of uncertainties in the fire loading on its structural performance and fragility. The failure probability starts at a higher fire load density (450 MJ/m2) for the structure with higher concrete grade as compared to the relatively lower fire load density (200 MJ/m2) for lower grade. Therefore, the fire resistance of the RC structures has been recommended to be based on the strength of the member, rather than merely sizes of the members. The proposed stochastic analysis framework, thereby, provides a rational approach to improve the performance-based fire design of RC structures at member and structure levels by identifying the parameters affecting the structural fire resistance.

Deformation-based performance index of corroded reinforced concrete beams

In order to implement the life-cycle oriented performance-based seismic design of reinforced concrete (RC) structures, quantification of seismic performance indexes for corroded RC members is necessary. Firstly, the material strain-based criteria to classify damage limit states for RC members were proposed. Numerical analysis was conducted with the aid of the software ABAQUS to investigate the deformation behaviour of RC beams. Corrosion ratio of steel reinforcement, shear span ratio and longitudinal reinforcement ratio were considered as the main analytical parameters. It is found that for RC beams with corrosion ratio not exceeding 7.5%, the corrosion ratio of steel reinforcement has little effect on the deformation behaviour of RC beams. For RC beams with corrosion ratio lager than 7.5%, the deformation capacity is significantly affected by the reinforcement corrosion ratio. Based on numerical simulation results, expressions for estimating deformations of corroded RC beams at yield and ultimate limit states were derived, respectively. The deformation limits corresponding to the individual damage limit state of corroded RC beams were proposed. The research results can be utilized for life-cycle oriented seismic performance evaluation and design of RC structures.