•The fire behavior of reinforced concrete tunnel slabs during both the heating and cooling phases are simulated.•Three modeling strategies are investigated using beam, shell, and solid elements.•Five ...recent fire tests on loaded and restrained large-scale tunnel slabs, with varying concrete strengths, restraint levels, and fire scenarios, are selected to verify the models.•Temperature and displacement evolutions during heating and cooling obtained from the numerical models are compared with the experimental test data.•Shell elements perform the best by achieving a balance between model accuracy and efficiency.
This paper examines different modeling approaches to simulate the behavior of reinforced concrete (RC) tunnel slabs under fire during both the heating and cooling phases. Three modeling strategies are investigated by using beam, shell, and solid elements in addition to different methods to capture the effect of axial restraint on the slabs. The models consider temperature-induced plastic deformations and irrecoverable degradation of materials. The models also utilize distinct concrete properties for heating and cooling as well as account for the transient creep strain explicitly in the calculations. The results obtained from different modeling strategies are compared to five recent fire tests on loaded and restrained large-scale RC tunnel slabs, with varying concrete strengths, restraint levels, and fire scenarios. Temperature and displacement evolutions during heating and cooling obtained from the numerical models are compared with the experimental test data. When considering model accuracy and efficiency as the primary performance metrics, using shell elements to analyze the fire performance of reinforced concrete tunnel segments resulted in the best balance between the two. The numerical models and techniques developed in this paper will enable practicing engineers to reliably and rapidly assess fire damage to reinforced concrete tunnel linings, and to explore cost-effective designs of tunnels for fire.
Fiber reinforced polymer (FRP)-reinforced concrete slabs, an extension of reinforced concrete (RC) slabs leveraged for resisting environment corrosion, are susceptible to punching shear failure due ...to the lower elasticity modulus of FRP reinforcement. To estimate the punching shear resistance accurately, there are two types of models (e.g., white box and black-box models) proposed based on theoretical derivations and machine learning methods. However, these two types of models are considered as independent of each other. In this study, a hybrid model (e.g., grey-box model) derived from modified compression field theory (MCFT) is proposed by this paper, in which the performance is improved by a machine-learning-aided approach (genetic programming). In order to exploit the performance of machine learning, a database containing 154 experimental data is established and used for fitting the correction equations. Iterating the population containing 300 tree-based individuals in 300 times, a correction equation with simple format is obtained, which performs well in performance improvement of the basic model derived from MCFT. Herein, the influential factors involved in the correction equation comply with the sorting in order of the importance quantified by extreme gradient boosting (XGBoost) and shapley additive explanation (SHAP). Combining the correction equation with the basic model derived from MCFT, a symbolic regression MCFT (SR-MCFT) model is established, which performs better prediction performance than other five empirical models.
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•A hybrid machine-learning aided MCFT model for punching shear resistance of FRP-reinforced concrete slabs is developed.•The selection of influential factors is quantified by machine learning methods of XGBoost and SHAP interpretation.•A correction equation with simple format and favorable improvement performance is obtained by genetic programming.•Machine learning aided hybrid models exhibit higher prediction accuracy than 5 empirical models.
Fire hazards are a major threat to tunnel structures; however, the existing understanding of the behavior of tunnel linings under fire is limited, which restricts cost-effective and safe design of ...tunnels for fire. The research work in this paper aims to experimentally evaluate and quantify fire damage to tunnel linings considering a combination of influencing factors. The effects of three parameters on fire damage to the ceiling (typically the most damaged area) of a tunnel lining are studied through five furnace tests on large-scale reinforced concrete slabs. The parameters include: (1) concrete composition - presence/absence of polypropylene fibers, (2) the level of structural restraint (induced using post-tensioned strands), and (3) the fire intensity and duration. These parameters are selected to reflect realistic scenarios and provide a rational basis for evaluating tunnel damage, in terms of crack pattern, spalling, discoloration, non-destructive testing, and deflections during fire and after cooling. This research provides vital experimental data for fire damage assessment of reinforced concrete tunnel linings, and assists in verifying numerical models for analyzing structural performance during both the heating and cooling phases of fire.
•A total of five fire tests on large-scale reinforced tunnel concrete slabs are conducted.•The considered test parameters are concrete composition, level of restraint, fire intensity, and fire duration.•Fire damage to the slabs is evaluated from multiple aspects.•The lack of active or passive fire protection may lead to irrecoverable damage under moderate railway tunnel fires.•Moderate railway tunnel fires result in an average reduction of 15–20% in concrete strength.
Piezoelectric lead zirconate titanate (PZT) is being gradually applied into practice as a new intelligent material for structural health monitoring. In order to study the damage detection properties ...of PZT on concrete slabs, simply supported reinforced concrete slabs with piezoelectric patches attached to their surfaces were chosen as the research objects and the Electromechanical Impedance method (EMI) was adopted for research. Five kinds of damage condition were designed to test the impedance values at different frequency bands. Consistent rules are found by calculation and analysis. Both the root mean square deviation (RMSD) and the correlation coefficient deviation (CCD) damage indices are capable of detecting the structural damage. The newly proposed damage index Ry/Rx can also predict the changes well. The numerical and experimental studies verify that the Electromechanical Impedance method can accurately predict changes in the amount of damage in reinforced concrete slabs. The damage index changes regularly with the distance of damages to the sensor. This relationship can be used to determine the damage location. The newly proposed damage index Ry/Rx is accurate in determining the damage location.
This paper aims to develop a practical artificial neural network (ANN) model for predicting the punching shear strength (PSS) of two-way reinforced concrete slabs. In this regard, a total of 218 test ...results collected from the literature were used to develop the ANN models. Accordingly, the slab thickness, the width of the column section, the effective depth of the slab, the reinforcement ratio, the compressive strength of concrete, and the yield strength of reinforcement were considered as input variables. Meanwhile, the PSS was considered as the output variable. Several ANN models were developed, but the best model with the highest coefficient of determination (
R
2
) and the smallest root mean square errors was retained. The performance of the best ANN model was compared with multiple linear regression and existing design code equations. The comparative results showed that the proposed ANN model was provided the most accurate prediction of PSS of two-way reinforced concrete slabs. The parametric study was carried out using the proposed ANN model to assess the effect of each input parameter on the PSS of two-way reinforced concrete slabs. Finally, a graphical user interface was developed to apply for practical design of PSS of two-way reinforced concrete slabs.
To reveal the anti-explosion capacity of polyisocyanate oxazodone (POZD)-coated steel RC composite structural slabs, a explosion test was carried out for 2 test models. Using ANSYS/LS-DYNA, the ...damage mode and maximum mid-span deflection of steel plate-RC plate and POZD coated steel plate-RC plate were explored, and the experimental results were compared. Parametric analysis of the charge, POZD, steel plate and concrete slab thickness on the anti-explosion performance of the POZD-steel plate-RC slab. The results show that increasing the thickness of POZD, steel plate and RC slab can effectively reduce the POZD-steel – RC slab mid-span deflection. The POZD coating and steel plates increased the tensile area of concrete and improved the flexural and load carrying ability of the concrete slabs.
Concrete structures are essential for shelters, storage, transportation, and defense systems. However, they are vulnerable to terrorist attacks and explosions. The most exposed component of these ...structures is the reinforced concrete slab, which is also the primary force-transferring member. Therefore, the present study utilizes machine learning techniques to predict the maximum vertical displacement of reinforced concrete slabs subjected to air-blast loading. This can be achieved using 11 input parameters of the slab and TNT blast to predict the maximum displacement. The dataset comprises 146 samples from various experimental and numerical blast studies on reinforced concrete slabs in the open literature. Rather than presenting the data in a tabular format, each individual data sample is transformed into an image using distinct techniques: one uses a self-similarity matrix, and the other utilizes an image generator for the tabular data. Image generation transforms tabular data into images by assigning features to pixel positions. This results in spatial dependency of the input features. Using these images, various convolutional neural networks were adopted (ResNet-18, ResNet-50, ResNet-101, EfficentNet-b0, ShuffleNet, Xception, DarkNet-53, and DenseNet-20) and trained to predict the slab maximum displacement. Most models demonstrated promising results. The performance of the models was predicted based on the root mean squared error, mean absolute error, and coefficient of determination, and the impact of input features on the maximum displacement was examined. Along with this, the initial study of the blast damage assessment on reinforced concrete slabs is explained for future work to be performed based on the proposed method.
Anti-blast performance and damage characteristics of reinforced concrete slab with different reinforcement ratios were analyzed in the present study through both blast experiments and numerical ...simulations. Three sets of slabs with different reinforcement ratios under 0.13kg and 0.19kg TNT explosive blast loading were conducted. The experimental and numerical results show that different damage features are observed in the different tests. On the one hand, the increase of explosive charge is shown to gradually change the damage degree of RC slab. The crack diameter and spallation area of larger mass explosive test is greater than that of small mass explosive test. On the other hand, with an increasing reinforcement ratio, the damage degree, deflection and the spall radius all decrease. The results indicate that the reinforcement ratio has great influence on the survivability of RC slabs when subjected to blast loading.
Ten additional simulations with different reinforcement ratios and TNT masses were conducted. The results show the deflection thickness ratio of RC slab is inversely proportional to the scale distance and the reinforcement ratio. Based on the experimental and numerical results, an empirical expression on deflection thickness ratio was obtained which considered both the scale distance and the reinforcement ratio.
•Blast experiments of RC slabs with different reinforcement ratio•3D numerical simulations of RC slabs subjected to blast loading•Damage characteristics of RC slabs under blast•Deflection thickness ratio inversely proportional to the reinforcement ratio•Empirical expression on deflection thickness ratio of RC slab
•The connection of precast plates to one-way reinforced concrete slabs increased their bearing capacity.•The connection of precast plates to one-way reinforced concrete slabs reduced their ...deflection.•The increase in the thickness of the precast plates prevented the slabs and plates from acting in an integrated manner.
This experimental research addressed the reinforcement of one-way concrete slabs using ultra-high-performance fiber-reinforced geopolymer concrete (UHPFRGC) based on ground granulated blast furnace slag (GGBFS) and silica fume. So, five 1000*300*70 mm one-way slabs were fabricated by uniform mix design. One slab was selected as the control specimen, and the other specimens were reinforced by 25-mm and 35-mm thick precast ultra-high-performance fiber-reinforced geopolymer concrete plates (PUHPFRGCP). The precast plates were connected to the tensile zone of the slab once with ultra-high-performance geopolymer concrete (UHPGC) and the other time with epoxy adhesive. The results revealed that the use of 25-mm thick PUHPFRGCS increased their bearing capacity and reduced their deflection significantly. Increasing the plate thickness to 35 mm prevented the slab and plate from acting in an integrated manner and significant debonding was observed in some parts between the slab and the plate, so the bearing capacity did not significantly increase in these specimens. Also, debonding was responsible for failure in none of the specimens. Finally, the specimen that was reinforced with the 25-mm plate and connected to the slab with epoxy adhesive was promising for structural applications.
Semi-precast-reinforced concrete slab system offers more economic method of construction as it minimises the need of formwork at site. The assembly of semi-precast slab system involves two steps: (1) ...casting of semi-precast slab at the yard and (2) overtopping of concrete at the site. One of the main factors that influence the performance of such slab system is the interface bonding between precast and overtopping concrete. Therefore, in order to better understand the performance of this slab system, a research was carried out to investigate the influence of surface treatment methodologies to the overall flexural behaviour through experimental and numerical studies. In total, five representative semi-precast slabs were constructed and tested to assess the flexural performance with different surface preparation methods and concrete overtopping. Further small-scale precast with overtopped concrete couplets and triplets were casted and tested as the representative semi-precast concrete slab types to examine the interface shear and tensile bond strength characteristics with those different surface treatments. The experimental results revealed that the surface treatment methods have influenced the flexural behaviour of the slabs, where the interface shear bond strength exceeds more than 1.0 MPa and the slab system behaves monolithically under flexural action. Moreover, numerical modelling technique for this slab system was developed based on the finite element framework to further analyse the overall flexural behaviour. Subsequently, good agreements between experimental and developed numerical model results were found. Finally, parametric analyses were performed to further assess the influences of concrete strengths, spans and reinforcement ratios on the safe imposed pressure applicable for this slab system.
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