Concrete Structures Research Articles

Long-short-term memory model for quantitative analysis of corrosion products in concrete

A quantitative analysis model is proposed to describe the content evolution of corrosion products in concrete structures subjected to sulfate or chloride attack. The model is inspired by the idea of the Long-Short-Term Memory (LSTM) algorithm in the machine learning field. For establishing the relationship between engineering data and theoretical computations, the training samples of the model are generated by solving the rate equations of the sulfate corrosion reactions in concrete with wide-range initial conditions and validated by the existing experimental data. The Pearson correlation coefficient is employed to determine the model features. The model performance is comprehensively evaluated and discussed. The results show that the proposed model has enough accuracy and feasibility. It could effectively predict the contents of the corrosion products during the sulfate attack by several input values rather than the initial contents of all chemical constituents. The proposed model builds a bridge between experimental methods and theoretical predictions, adequately inheriting their advantages.

Vision-guided crack identification and size quantification framework for dam underwater concrete structures

Remotely operated vehicles with cameras provide a non-contact inspection solution for dam underwater structural defect detection. However, manual information extraction methods suffer from problems like labor costs and high misjudgment. This study proposes an integrated dam underwater crack identification and size quantification framework using machine vision and deep learning. First, a real-time automatic detection framework for dam underwater cracks is built via You Only Look Once v5 (YOLOv5), and four different backbone detectors are introduced to balance detection accuracy and speed. Then, the Swin-Transformer module is inserted into the YOLOv5 model to enhance its feature extraction capability and small object detection capability. Next, a method for measuring the true size of cracks was constructed based on deep learning and infrared laser rangefinders. In this study, physical model experiments and actual engineering projects are combined to validate the generalization capability of the proposed crack identification and size quantification method. Experimental results show that the Swin-Transformer-based YOLOv5 model effectively balances detection accuracy and speed with a precision of 0.986, a recall of 0.979, a mean average precision of 0.985, and a frame rate of 68 frames per second in detecting underwater crack images with 768 × 576 pixels. In addition, the proposed method can accurately identify and detect cracks in complex underwater scenes, including obstacle interference, tilt shooting angle, uneven illumination, and turbid water scenarios. Moreover, the method proposed in this paper can quantify the overall size and geometric parameters of underwater cracks with relatively small errors.

Experimental Test and Analytical Calculation on Residual Strength of Prestressed Concrete T-Beams After Fire

High temperatures during a fire can lead to the evaporation of moisture and the degradation of hydration products within concrete, consequently compromising its mechanical properties. This paper thoroughly investigates the effect of fire-induced high temperatures on the residual load-bearing capacity of concrete structures, with a focus on prestressed concrete T-beams. By conducting constant temperature tests and residual load-bearing capacity tests, complemented by finite element modeling, this study examines the degradation of mechanical properties in prestressed concrete T-beams due to fire exposure and its impact on post-fire residual load-bearing capacity. Additionally, an equivalent concrete compressive strength method was employed to propose a calculation method for concrete material degradation under high temperatures and a corresponding concrete strength reduction factor. Simplified calculations were also performed for the high-temperature damage to reinforcement and prestressed tendons, leading to the derivation of a simplified formula for the residual load-bearing capacity of post-fire prestressed concrete T-beams. The results indicate that in prestressed concrete T-beams exposed to fire, an increase in holding time results in more severe damage modes, accelerated crack propagation, and wider crack widths during bending failure. Under the same load, a longer holding time corresponds to a more pronounced reduction in deflection. At holding times of 60 min, 120 min, and 180 min, the prestress losses were 48.17%, 85.16%, and 93.26%, respectively. The cracking load decreased by 15%, 27%, and 42%, while the residual load-bearing capacity decreased by 11%, 21%, and 28%. Comparison with experimental data demonstrates that both the finite element model and the simplified calculation formula exhibit high accuracy, offering a reliable reference for the performance evaluation of post-fire prestressed concrete T-beams.

Bond of FRP bars in fine‐grained alkali‐activated concrete

AbstractAlkali‐activated cement (AAC) is an alternative binder with a promising potential to replace ordinary Portland cement (OPC) and mitigate its environmental issues. The use of fiber‐reinforced polymer (FRP) reinforcements with AAC concrete enables the development of corrosion‐resistant, environmentally friendly reinforced concrete structures. Bond behavior is critical in reinforced concrete structures and must be thoroughly studied for such new alternative materials. This study employs pullout tests to investigate the bond behavior between FRP bars and fine‐grained AAC concrete. Three fine‐grained AAC concretes with low to high strength, glass and carbon FRP bars and wrapped, milled, and smooth surface treatments were examined. The effect of bar casting position was also investigated. The compressive strength showed a significant influence on the bond strength. An average bond strength of approximately 18 MPa was observed for both glass and carbon FRP bars when used with 65 MPa concrete. Both the glass and carbon FRP bars with wrapping showed a lower bond strength than their milled FRP bars counterparts. The carbon bars without surface preparation (smooth bars) resulted in a much lower bond strength, around 4 MPa. In terms of casting positions, the bars cast in the middle section of the concrete block showed a higher bond strength than those at the bottom and top.

Fracture Characteristics and Tensile Strength Prediction of Rock–Concrete Composite Discs Under Radial Compression

To investigate the fracture mechanism of rock–concrete (R–C) systems with an interface crack, Brazilian splitting tests were conducted, with a focus on understanding the influence of the interface crack angle on failure patterns, energy evolution, and RA/AF characteristics. The study addresses a critical issue in rock–concrete structures, particularly how crack propagation differs with varying crack angles, which has direct implications for structural integrity. The experimental results show that the failure paths in R–C disc specimens are highly dependent on the interface crack angle. For crack angles of 0°, 15°, 30°, and 45°, cracks initiate from the tips of the interface crack and propagate toward the loading ends. However, for angles of 60°, 75°, and 90°, crack initiation shifts away from the interface crack tips. The AE parameters RA (rise time/amplitude) and AF (average frequency) were used to characterize different failure patterns, while energy evolution analysis revealed that the highest percentage of energy consumption occurs at a crack angle of 45°, indicating intense microcrack activity. Moreover, a novel tensile strength prediction model, incorporating macro–micro damage interactions caused by both microcracks and macrocracks, was developed to explain the failure mechanisms in R–C specimens under radial compression. The model was validated through experimental results, demonstrating its potential for predicting failure behavior in R–C systems. This study offers insights into the fracture mechanics of R–C structures, advancing the understanding of their failure mechanisms and providing a reliable model for tensile strength prediction.

Seismic capacity evaluation of corroded reinforced concrete frame structures

Seismic capacity evaluation of corroded reinforced concrete frame structures

Comparative analysis of armid fiber reinforced polymer for strengthening reinforced concrete beam‐column joints under cyclic loading

AbstractThis research investigates the structural performance and failure mechanisms of beam‐column joints reinforced with aramid fiber‐reinforced polymer to bolster the durability and seismic resilience of concrete structures. It meticulously selects and proportions materials such as ordinary Portland cement Grade 53 cement, fine and coarse aggregates meeting IS: 383–1970 standards, and water conforming to IS: 456–2000 specifications. Tests confirm the high quality of ordinary Portland cement, crucial for optimal beam‐column joint performance, while carbon fiber‐reinforced polymer enhances structural integrity with its lightweight composition and substantial tensile strength (3800 MPa–4200 MPa). Failure analysis reveals that non‐aramid fiber reinforced polymer wrapped beam‐column joint specimens predominantly failed due to concrete crushing, whereas aramid fiber‐reinforced polymer‐wrapped specimens failed due to fracture in the aramid fiber‐reinforced polymer composite, emphasizing stress concentration areas. This study underscores the pivotal role of stress distribution in failure mechanisms and underscores the significance of robust reinforcement design in bolstering structural resilience. These insights advance retrofitting strategies and reinforce techniques aimed at enhancing the longevity and seismic resistance of concrete structures.

Peridynamics simulations of the damage of reinforced concrete structures under radial blasting

Concrete is prone to damage under explosive loads, which can cause a large number of casualties and property losses. The concrete fragmentation process during explosion is transient and dynamic, and the experimental measurement of such events is difficult and risky to conduct, and the intermediate explosion process is difficult to observe in the experimental tests. Therefore, the numerical simulation is an ideal method to model and simulate the explosion process of concrete. Different from the traditional finite element method, Peridynamics (PD) method uses the spatial integral equation to replace the traditional local differential equation to solve the fragmentation problem with massive and complex discontinuous patterns. In this study, a peridynamics (PD) model is developed to simulate the failure process of reinforced concrete (RC) structures under radial blasting. Concrete PD models with different cavity sizes and reinforcement conditions were established and calibrated with the experimental data. We find that the crack growth and damage pattern obtained in the peridynamics simulation is consistent with the experiment test results, which verifies the feasibility of peridynamics method as a modeling tool for modeling concrete damage under explosive load and for evaluating anti-explosion performance of RC concrete structures.

Nonlinear finite element model updating and fourier neural operator for digital twin of reinforced concrete containment vessel under seismic excitations

A series of unidirectional seismic excitation tests on a 1/20 scaled reinforced concrete containment vessel (RCCV) specimen was conducted using a 6-DOF shake table. This study presents the development of a digital twin to accurately capture the complex behavior of reinforced concrete structures under seismic effects. With the aid of finite element (FE) software Abaqus, the RCCV structure was initially modeled and analyzed to obtain preliminary structural acceleration and displacement results. To enhance the accuracy of these simulations, a nonlinear FE model updating framework was developed by integrating Abaqus software with Python. The model updating of RCCV was conducted subsequently based on the shake table measured data to obtain results with significantly improved accuracy. It is shown that the FE simulations and the nonlinear FE model updating algorithm are highly effective for the high-fidelity simulation of large and complex structures. Furthermore, a Fourier neural operator (FNO) model is used to learn the FE simulation database and predict the FE simulation results. It is observed that FNO has an excellent performance in predicting the structural responses with various material and damping parameters and accomplished speedup over 5000 times compared to the FE simulations. The findings provide a basis for the application of nonlinear model updating algorithms at the structure system level through the high-performance GPU-based parallel computing and underscore that the strategy of FE analysis combined with artificial intelligence (AI) has great potential in the field of digital twins for large and complex structures.

Improving Concrete Structures with Engineered Cementitious Composites and Kevlar Sheets: An Affordable Retrofitting Solution for Earthquake Resistance

Improving Concrete Structures with Engineered Cementitious Composites and Kevlar Sheets: An Affordable Retrofitting Solution for Earthquake Resistance

Development of structures and production technologies of reinforcing wire with a screw profile

Reinforcing wire is the main structural element in reinforced concrete structures, widely used in the construction of buildings and structures for various purposes. The type of profile is important factor which determines the consumer properties of fittings. This indicator directly affects the quality of reinforcement adhesion to concrete and the properties of the wire. Currently a periodic profile is the most common type, but a screw profile is the most promising form of the profile. Two methods are used in the production of cold-formed screw profiles: applying a screw profile and torsion process. The first is carried out by rotating the profiling element, and the second by torsion of the workpiece of the shaped section. The patent and literature review of methods for obtaining cold-formed screw profiles has shown that the most effective way to obtain reinforcing wire with a screw profile is torsion, which provides, in addition to profiling, an increase in the mechanical and operational properties of the wire. With the help of the Deform-3D software package we identified impact of the profile, namely the shape of the cross section on the tension. By choosing rational torsion parameters, it is possible to achieve a favorable stress-strain state and respectively the properties of the product. One of the promising areas of development is the combination of a periodic and a screw profile, and it is necessary to obtain a screw profile using torsion deformation as a method of intense plastic deformation in order to form a uniform structure in metal with a minimum stress state in addition to the profile. We justified the application of radial shear broaching, an analogue of the radial shear rolling process, which allows to obtain a screw profile reinforcing wire with high mechanical properties due to the production of a finely dispersed structure. This method is implemented on standard drawing equipment and provides an increase in the productivity of wire production by torsion compared to other methods

Steel stresses and shear forces in reinforcing bars due to dowel action

AbstractReinforcing bars in structural concrete are typically designed to carry axial forces. Nevertheless, due to their bending stiffness, the bars can also carry transverse forces, that are associated with the localized bending mechanism (dowel action) resulting from the relative displacements (or slip) wherever a crack interface or a discontinuity interface (between two concrete parts cast at different times) intercept the bar. Such localized bending induces stress concentrations in both the bars and the concrete. The relative displacement can occur at interfaces either perpendicular to the bar or inclined with respect to its axis. Thanks to steel ductility, the bending stresses in the bars due to dowel action do not impair the sectional capacity at the ultimate limit state. Fatigue verifications, however, require an accurate evaluation of these stresses under imposed transverse displacements or shear forces. As well known, dowel action can be described by means of the traditional unidimensional Winkler's model (beam on an elastic foundation), where the bearing stiffness of the concrete embedment is typically introduced through a couple of parameters, namely the bar diameter and the concrete strength in compression. The actual behavior of a dowel, however, is definitely more complex and for such a reason, improvements are needed for the Winkler's model to introduce other parameters typical of actual structures. Hence, a new formulation is introduced in this study for the bearing stiffness, that is calibrated based on mechanical considerations and measurements with optical fibers. The proposed formulation also accounts for the following parameters: angle between the crack and the bar, concrete‐cover thickness, number of load cycles and the softening effect caused by the local secondary cracks radiating from bar ribs during the pull‐out process. The predictions of the model—implemented with the proposed bearing stiffness—fit fairly well the test results under both monotonic and cyclic loads, in terms of shear force–transverse displacement response and peak stress in the reinforcing bars.

Early age bond-slip behavior of reinforcing steel bars in concrete subjected to uniaxial lateral pressure: An experimental study

The bond between reinforcing bars and concrete is a crucial factor concerning the serviceability of reinforced concrete structures, particularly for those during construction in some developing areas where plain bars were still used as reinforcements. Despite numerous studies on early age bond behavior between steel bars and concrete, little research has been conducted to quantify the effect of uniaxial lateral pressures on this bond. This study involved testing a total of 378 pullout specimens to evaluate the early age bond-slip behavior of plain bars in concrete under uniaxial lateral pressure. The main test parameters included the concrete ages (1, 3, 7, 14 and 28 days), lateral pressures (0, 0.1, 0.2, 0.4 and 0.6 times the compressive strengths of concrete), concrete strength grades (C20, C35 and C45), and bar diameters (12, 16 and 20 mm). Based on the experimental results, a series of analytical expressions were developed for bond strength, maximum bond slip and residual bond stress predictions considering the effects of early age and lateral pressure. The results demonstrate that degradation of bond strength at early ages can be effectively mitigated by uniaxial lateral pressures. As the age decreases from 28 to 1 days, the bond strength exhibits a significant decrease of up to 51.59 %, while this adverse effect can be reduced by around 10 % in the presence of lateral pressures. Increasing the pressure level from 0 to 0.4 results in a significant increased early age bond strength by 112.6 % to 199.0 % for different bar diameters. However, the residual-to-maximum bond stress ratio remains nearly constant at 0.49 regardless of age and lateral pressure, as the pressure primarily contributes to frictional forces at the bar-concrete interface. An age-dependent bond-slip constitutive model considering the effect of uniaxial lateral pressures was finally proposed and verified with the test results. The paper concludes that given the concrete compressive strength at 28 days, the proposed bond strength and bond stress-slip models can predict the early age bond responses of plain bars in concrete under uniaxial lateral pressures with reasonable accuracy.

Performance comparison of several explainable hybrid ensemble models for predicting carbonation depth in fly ash concrete

The carbonation of fly ash concrete critically impacts the lifespan of structures, necessitating precise prediction of carbonation depth for the construction industry. This study establishes an original database comprising 883 cases, which are divided into training and testing sets in a 4:1 ratio. The Sand Cat Swarm Algorithm (SCSO) was developed to optimize the hyperparameters of three ensemble models: Gradient Boosting Decision Trees (GBDT), Light Gradient Boosting Machine (LGBM), and Categorical Boosting (CatBoost), resulting in the development of three hybrid ensemble models: SCSO-GBDT, SCSO-LGBM, and SCSO-CatBoost. Five classic models were included in the comparison, and all models used five-fold cross validation. Models’ performance was rigorously evaluated using Correlation coefficient (R2), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Variance Accounted For (VAF), with VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method and Taylor diagrams utilized for optimal model selection. The SCSO-CatBoost model demonstrated superior performance, with R2 = 0.9657, MAE = 2.0062, RMSE = 8.2147, and VAF = 96.6177. Shapley additive explanations (SHAP) analysis of the SCSO-CatBoost model identified time of exposure as the most significant factor influencing carbonation depth, followed by fly ash content and carbon dioxide concentration. To facilitate practical application by non-algorithm engineers, an intelligent program was developed, allowing for straightforward testing with the three hybrid ensemble models. This study presents three precise models for predicting the carbonation depth of fly ash concrete. These models serve as valuable tools for estimating the service life of concrete structures and can be utilized as simulation instruments in durability engineering.

Exploration of Teaching Reform in the Course of Concrete Structure Design Principles in the Context of the New Era

In response to the requirements for cultivating applied talents in civil engineering under the background of the new era, and addressing the practical problems existing in the teaching of the course on concrete structure design principles in higher education institutions, this paper conducts an analysis of the current situation and challenges of the course teaching. It focuses on issues such as the abstract difficulty of teaching content, the singularity of teaching methods, and the lack of practical teaching. Combining the characteristics of the course and the industry’s demand for talent capabilities, the paper explores and outlines reform measures, including optimizing course content, transforming the roles of teachers and students, and integrating theory with practice. The aim is to provide insights and inspiration for the teaching of related courses.

Achieving sustainable performance: synergistic effects of nano-silica and recycled expanded polystyrene in lightweight structural concrete

Lightweight concrete, particularly polystyrene concrete, has been extensively utilized in civil engineering for decades. The incorporation of waste expanded polystyrene (EPS) as a filler material in the production of lightweight concrete presents significant advantages from a circular economy perspective. Prior research indicates that increasing the proportion of lightweight aggregates, such as EPS, typically results in reductions in strength and bulk density. The utilization of substantial amounts of EPS waste in the formulation of structural polystyrene concrete is crucial for advancing sustainable construction practices. This study investigates the effects of varying nano-silica content on the bulk density, compressive strength, flexural strength, splitting tensile strength, and water penetration depth of structural polystyrene concrete. Concrete specimens were prepared by substituting 25%, 50%, 75%, and 100% of sand with EPS waste, while evaluating nano-silica contents of 0.75%, 1%, and 1.25%. The findings reveal that increasing the volume fraction of EPS corresponds to a decrease in the concrete’s bulk density. This research provides critical insights into optimizing structural lightweight concrete, thereby promoting advancements in sustainable construction applications.

Effective Concrete Failure Area for SC Structures Using Stud and Tie Bar Under Performance Tests.

Nuclear power plants, where steel-plate concrete (SC) structures are commonly adopted, require large-scale components to withstand significant loads, such as those caused by sudden explosions. As a result, SC modular members used in nuclear power plants must have thicker walls filled with concrete compared to standard-sized ones. These large walls also require additional components, such as tie bars and H-shaped steel sections, to reinforce adhesion and resist shear stresses. This study focuses on tie bars placed adjacent to studs and evaluates their influence on the tensile strength of wall structures. To investigate this, we conducted experimental tests using full-scale specimens, including various combinations ranging from single stud to combined stud-tie configurations. Based on the results of these performance tests, we propose a design recommendation for estimating the tensile capacity of SC structures, considering the influence of tie bars.

Numerical modeling of the transfer length of 17.8 mm (0.7 in) diameter prestressing strands in pretensioned members

The bond between concrete and reinforcing steel bars in reinforced concrete structures is crucial. Prestressing strands with a diameter of 17.8 mm (0.7 in) transfer higher compression per unit area than smaller strands, improving moment capacity and shear strength and extending the girder span. However, limited research on the bond performance of these 17.8 mm diameter prestressing strands has restricted their widespread use despite their advantages. This study presents a methodology to determine the transfer length of pretensioned members numerically. The influence of pretension force and bond strength on a 17.8 mm diameter strand was assessed through the validation of a finite element model using experimental results from a standardized pretensioned pull-out test. Analytical calculations using different code formulas were also conducted, encompassing strands of varying diameters. Our finite element analysis suggests that a 50.8 mm spacing between adjacent 17.8 mm diameter strands is applicable, ensuring there is no stress overlap in the transfer zones, which can lead to concrete cracking and reduced structural integrity. Existing code formulas, such as ACI 318–19 and AASHTO LRFD 9th edition, require longer transfer lengths when compared with the numerical results. The fib MC 2010 and EC2 formulas offer closer results to numerical results of smaller diameter strands but underestimate the transfer length for the 17.8 mm diameter strand. Therefore, improvements to code formulations may be necessary for more accurate transfer length predictions for this specific strand size.

Exploring Ultimate Flexural Strengths of Ultra-High-Performance Concrete (UHPC) Samples through Experimental Analysis in Comparison with Ordinary Concrete Structures

Exploring Ultimate Flexural Strengths of Ultra-High-Performance Concrete (UHPC) Samples through Experimental Analysis in Comparison with Ordinary Concrete Structures

Robotic destructive and nondestructive testing of concrete structures

Structural elements may develop defects due to severe environmental conditions. Nondestructive testing is a common method for structural evaluations; however, these structures may be inaccessible or located in unsafe areas. In this paper, a Sawyer robot was employed to carry nondestructive testing (NDT) sensors such as Ground Penetration Radar (GPR) and Impact Echo (IE). The experiment comprised twelve reinforced concrete beams divided into four groups: Control (without defects), Void, Corrosion, and Debonding. The beams underwent three-point bending tests, with loads distributed across three levels: 50 %, 75 %, and 100 % of the failure load. Robotic and handheld IE and GPR tests were conducted, with IE performed before the actual test and GPR conducted before, during, and after the tests. Load-displacement diagrams were subsequently generated. The comparison between robotic and handheld tests demonstrated the high accuracy of the robotic NDT and indicated that the defects led to reduced load capacity and increased crack propagation.