Special Issue "Performance Prediction, Durability and Modelling of Concrete Materials and Structures"

A special issue of Crystals (ISSN 2073-4352). This special issue belongs to the section "Inorganic Crystalline Materials".

Deadline for manuscript submissions: 28 January 2022.

Special Issue Editors

Dr. Yang Yu
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Guest Editor
School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia
Interests: concrete structures; structural damage detection; structural helath monitoring; non-destructive evaluation
Dr. Weiqiang Wang
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Guest Editor
School of Architecture, Building and Civil Engineering, Loughborough University, Loughborough LE11 3TU, UK
Interests: Fibre reinforced polymer; Ultra high performancce concrete; Blast and impact engineering; 3D concrete printing
Dr. Rafael Shehu
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Guest Editor
Department of Civil and Environmental Engineering (DICA), Politecnico Di Milano, 20133 Milan, Italy
Interests: masonry materials; concrete materials; composite materials; strengthening materials; masonry structures; reinforced concrete; composite structures; steel structures; structural design; structural analysis
Dr. Beatrice Pomaro
E-Mail Website
Guest Editor
Department of Civil, Environmental and Architectural Engineering, University of Padova, Padova, Italy
Interests: finite element method; computational mechanics; constitutive modeling; dynamic stability; concrete; damage; concrete durability; nuclear radiation; radiation damage

Special Issue Information

Dear Colleagues, 

Concrete is one of the most important and commonly used construction materials, and it plays a significant role in supporting the global economy and human activities. To date, a large number of studies have been conducted in the fields of concrete materials and concrete structures to promote the practical applications. However, challenges still exist in the analysis of material and structural behaviours due to ageing, external loads and environmental factors. Accordingly, this Special Issue aims to present the up-to-date advances and developments regarding the durability, structural performance, service life prediction and modelling of concrete materials and structures. The interest topics of this Special Issue include, but are not limited to:

  • Concrete, reinforced concrete and composite concrete structures;
  • Structural behaviours under various types of loading;
  • Non-destructive evaluation and damage identification of concrete structures;
  • Numerical investigation for the performance and life cycle assessment of concrete materials and structures;
  • Durability of concrete materials and structures exposed to invasive environments;
  • Optimal design of concrete structures against external hazard loads.

Dr. Yang Yu
Dr. Weiqiang Wang
Dr. Rafael Shehu
Dr. Beatrice Pomaro
Guest Editors

Manuscript Submission Information

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Keywords

  • Concrete
  • Durability
  • Modeling
  • Composite structures
  • Structural behavior

Published Papers (12 papers)

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Research

Article
Applying Artificial Intelligence to Improve On-Site Non-Destructive Concrete Compressive Strength Tests
Crystals 2021, 11(10), 1157; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11101157 - 23 Sep 2021
Viewed by 418
Abstract
In the construction industry, non–destructive testing (NDT) methods are often used in the field to inspect the compressive strength of concrete. NDT methods do not cause damage to the existing structure and are relatively economical. Two popular NDT methods are the rebound hammer [...] Read more.
In the construction industry, non–destructive testing (NDT) methods are often used in the field to inspect the compressive strength of concrete. NDT methods do not cause damage to the existing structure and are relatively economical. Two popular NDT methods are the rebound hammer (RH) test and the ultrasonic pulse velocity (UPV) test. One major drawback of the RH test and UPV test is that the concrete compressive strength estimations are not very accurate when comparing them to the results obtained from the destructive tests. To improve concrete strength estimation, the researchers applied artificial intelligence prediction models to explore the relationships between the input values (results from the two NDT tests) and the output values (concrete strength). In-situ NDT data from a total of 98 samples were collected in collaboration with a material testing laboratory and the Professional Civil Engineer Association. In-situ NDT data were used to develop and validate the prediction models (both traditional statistical models and AI models). The analysis results showed that AI prediction models provide more accurate estimations when compared to statistical regression models. The research results show significant improvement when AI techniques (ANNs, SVM and ANFIS) are applied to estimate concrete compressive strength in RH and UPV tests. Full article
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Article
Performance Test for Sulfate Resistance of Concrete by Tensile Strength Measurements: Determination of Test Criteria
Crystals 2021, 11(9), 1018; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11091018 - 25 Aug 2021
Cited by 1 | Viewed by 554
Abstract
The European standard EN 206-1 contains descriptive requirements for concrete to withstand sulfate attack in the field. This approach limits the use of feasible concrete mixtures that don’t comply with these requirements. A performance approach based on the residual tensile strength of concrete [...] Read more.
The European standard EN 206-1 contains descriptive requirements for concrete to withstand sulfate attack in the field. This approach limits the use of feasible concrete mixtures that don’t comply with these requirements. A performance approach based on the residual tensile strength of concrete briquet specimen according to ASTM C307 after storage in sodium sulfate solution close to field conditions is suggested by the authors. The newly developed test method is verified on a variety of 23 binders. Threshold values for the determination of the sulfate resistance of concrete after nine months of storage in 6000 mg SO42−/L sulfate solution at 5 °C are proposed. A first repeatability test as well as thermodynamic calculations prove the suitability of the method to test the performance of concrete during sulfate attack under practical conditions. Full article
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Article
Development of a Sulfate Resistance Performance Test for Concrete by Tensile Strength Measurements: Determination of Test Conditions
Crystals 2021, 11(8), 1001; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11081001 - 22 Aug 2021
Cited by 2 | Viewed by 518
Abstract
Assessing the sulfate resistance of concrete is essential for the use of concrete in sulfate rich environments. A multitude of test methods exists worldwide, showing the relevance of the problem and the difficulty to find a suitable test setup. Testing the relative tensile [...] Read more.
Assessing the sulfate resistance of concrete is essential for the use of concrete in sulfate rich environments. A multitude of test methods exists worldwide, showing the relevance of the problem and the difficulty to find a suitable test setup. Testing the relative tensile strength of ASTM C307 concrete briquette specimens after exposure to a sulfate solution is a new direct method to assess the degree of deterioration. The aim of this study is to develop a new performance test, which considers both the chemical and physical resistance of a specific concrete mix against sulfate attack. In the experimental investigations, the binder type, storage temperature, type and concentration of sulfate solution, and concrete composition were varied, and the remaining tensile strength evaluated to define the test parameters. To gain significantly distinguishable data within nine months of storage, the use of sodium sulfate solution with 6000 mg SO42−/L at 5 °C is proposed. Full article
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Article
Experimental Analysis of Changes in Cement Mortar Containing Oil Palm Boiler Clinker Waste at Elevated Temperatures in Different Cooling Conditions
Crystals 2021, 11(8), 988; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11080988 - 20 Aug 2021
Viewed by 358
Abstract
Changes in cement-based materials containing waste after exposure to elevated temperatures are an important aspect that should be studied in developing sustainable construction materials. Modified cement-based materials obtained using the industrial waste present robust engineering properties can lead to sustainable development. This work [...] Read more.
Changes in cement-based materials containing waste after exposure to elevated temperatures are an important aspect that should be studied in developing sustainable construction materials. Modified cement-based materials obtained using the industrial waste present robust engineering properties can lead to sustainable development. This work evaluated the capacity of oil palm boiler clinker (OPBC) waste that had been produced during the palm oil extraction process as partial and full substitutions for natural sand to produce cement mortar. The mortar materials were cured under three different curing conditions and were then tested at a room temperature of approximately 27 °C and elevated temperatures of 200 °C to 1000 °C using an electric furnace. The specimens were maintained in the electric furnace under maximum temperatures for 2 h and were then cooled down with water or under ambient temperature. The changes in the forms of colour, weight, compressive strength, microstructure, mineralogical composition, and thermal conductivity were investigated. Test results showed that the compressive strength of OPBC mortars was generally higher than the strength of the control mortar after heat exposure. Water cooling exerted less damage to samples compared to air cooling. The results from field emission scanning electron microscopy–energy-dispersive X-ray spectroscopy demonstrated that the mineral composition varied at different temperatures. In conclusion, this work provides an extensive report and can be used as a guide in utilising OPBC as cementitious materials for future cement-based applications. Full article
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Article
Study on Flexural Performance of Concrete Beams Reinforced by Steel Fiber and Nano–SiO2 Materials
Crystals 2021, 11(8), 927; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11080927 - 10 Aug 2021
Viewed by 367
Abstract
Steel fiber and Nano–SiO2 reinforced concrete is a novel material of concrete which has great potential to be used in practical engineering. However, there is relatively little literature available on the flexural behavior of steel fiber and Nano–SiO2 materials reinforced concrete [...] Read more.
Steel fiber and Nano–SiO2 reinforced concrete is a novel material of concrete which has great potential to be used in practical engineering. However, there is relatively little literature available on the flexural behavior of steel fiber and Nano–SiO2 materials reinforced concrete (SFNMRC) beams. Hence, the main objective of this paper is to investigate the flexural performance of SFNMRC beams through combined experimental and theoretical studies. A total of 10 specimens were tested to investigate the flexural behavior and the effect of some key parameters, including concrete strength, the volume fraction of steel fiber, and the amount of Nano–SiO2. The load vs. deflection curves of SFNMRC beams during the whole loading process were analyzed in detail. The failure mode was discussed in detail, and the specimens all behaved in a very ductile manner. Furthermore, the test results indicated that bending cracks and concrete crushing were formed in the compression zone of all specimens. With the increase in concrete strength and the volume fraction of steel fiber, both the cracking load and ultimate load of beams increased. The amount of Nano–SiO2 had a limited effect on the flexure performance. Finally, the calculation formula for predicting the flexural bearing capacity of SFNMRC beams was derived with consideration of the effect of steel fiber on the cracked sections after beam cracking. The predicted results show satisfactory agreement with both experimental results. The studies may provide a considerable reference for designing this type of structure in engineering practice. Full article
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Article
Local Buckling Behavior of Buckling-Restrained Braces with Longitudinally Profiled Steel Core
Crystals 2021, 11(8), 914; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11080914 - 05 Aug 2021
Viewed by 429
Abstract
One of the most important requirements for a well-designed buckling restrained brace (BRB) under severe earthquake loading is to ensure its stability until the brace achieves sufficient elasto-plastic deformation. This study presents the finite element analysis results of the proposed buckling restrained brace [...] Read more.
One of the most important requirements for a well-designed buckling restrained brace (BRB) under severe earthquake loading is to ensure its stability until the brace achieves sufficient elasto-plastic deformation. This study presents the finite element analysis results of the proposed buckling restrained brace with a longitudinally profiled steel core (LPBRB). The objective of the analyses is to conduct a performance evaluation of the proposed LPBRBs, and to perform a parameter study with different clearance, width:thickness ratio, mortar strength, and friction coefficient for investigating the local buckling behavior of the LPBRBs. Numerical analyses results demonstrate that the LPBRBs exhibited good ductile performance and stable hysteretic behavior. The local buckling failure can be predicted by the demand:capacity ratio formula. The friction coefficient has little influence on the hysteretic behavior of LPBRBs. The local stability can be improved by adopting the mortar with higher compression strength or the LP core with lower width:thickness ratio. The proposed LPBRBs have a similar hysteretic response to the conventional BRBs. Full article
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Article
Experiments and Mechanical Simulation on Bubble Concrete: Studies on the Effects of Shape and Position of Hollow Bodies Mixed in Concrete
Crystals 2021, 11(8), 858; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11080858 - 23 Jul 2021
Viewed by 787
Abstract
This paper proposes a new type of lightweight concrete called bubble concrete, which was developed by mixing concrete with high-strength hollow bodies. In the present study, concave and spherical steel hollow bodies were used not only to form multiple cavities in the concrete [...] Read more.
This paper proposes a new type of lightweight concrete called bubble concrete, which was developed by mixing concrete with high-strength hollow bodies. In the present study, concave and spherical steel hollow bodies were used not only to form multiple cavities in the concrete but also to transfer internal stresses. Through compression tests, the shape effects and distribution effects of the hollow bodies on the strength and Young’s modulus of concrete were investigated. In addition, the mechanical characteristics of the bubble concrete were simulated by nonlinear elastoplastic finite element analysis to study the stress distribution and failure mechanism. The results indicate that with the proper combination, bubble concrete can reduce its density to 1.971–2.003 g/cm3 (83.3–84.7%, compared to control concrete) and its strength reaches 27.536–28.954 N/mm2. Full article
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Article
On Modeling Concrete Compressive Strength Data Using Laplace Birnbaum-Saunders Distribution Assuming Contaminated Information
Crystals 2021, 11(7), 830; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11070830 - 17 Jul 2021
Viewed by 494
Abstract
Compressive strength is a well-known measurement to evaluate the endurance of a given concrete mixture to stress factors, such as compressive loads. A suggested approach to assess compressive strength of concrete is to assume that it follows a probability model from which its [...] Read more.
Compressive strength is a well-known measurement to evaluate the endurance of a given concrete mixture to stress factors, such as compressive loads. A suggested approach to assess compressive strength of concrete is to assume that it follows a probability model from which its reliability is calculated. In reliability analysis, a probability distribution’s reliability function is used to calculate the probability of a specimen surviving to a certain threshold without damage. To approximate the reliability of a subject of interest, one must estimate the corresponding parameters of the probability model. Researchers typically formulate an optimization problem, which is often nonlinear, based on the maximum likelihood theory to obtain estimates for the targeted parameters and then estimate the reliability. Nevertheless, there are additional nonlinear optimization problems in practice from which different estimators for the model parameters are obtained once they are solved numerically. Under normal circumstances, these estimators may perform similarly. However, some might become more robust under irregular situations, such as in the case of data contamination. In this paper, nine frequentist estimators are derived for the parameters of the Laplace Birnbaum-Saunders distribution and then applied to a simulated data set and a real data set. Afterwards, they are compared numerically via Monte Carlo comparative simulation study. The resulting estimates for the reliability based on these estimators are also assessed in the latter study. Full article
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Article
Comparison of Machine Learning Approaches with Traditional Methods for Predicting the Compressive Strength of Rice Husk Ash Concrete
Crystals 2021, 11(7), 779; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11070779 - 03 Jul 2021
Cited by 4 | Viewed by 888
Abstract
Efforts are being devoted to reducing the harmful effect of the construction industry around the globe, including the use of rice husk ash as a partial replacement of cement. However, no method is available to date to predict the compressive strength (CS) of [...] Read more.
Efforts are being devoted to reducing the harmful effect of the construction industry around the globe, including the use of rice husk ash as a partial replacement of cement. However, no method is available to date to predict the compressive strength (CS) of rice husk ash blended concrete (RHAC). In this study, advanced machine learning techniques (artificial neural network, artificial neuro-fuzzy inference system) were used to predict the CS of RHAC. Based on the published literature, six inputs, i.e., age of specimen, percentage of rice husk ash, percentage of superplasticizer, aggregates, water, and amount of cement, were selected. Results obtained from machine learning methods were compared with traditional methods such as linear and non-linear regressions. It was observed that the performance of machine learning methods was superior to traditional methods for determining the CS of RHAC. This study will prove beneficial in minimizing the cost and time of executing laboratory experiments for designing the optimum content portions of RHAC. Full article
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Article
Prediction on Permeability of Engineered Cementitious Composites
Crystals 2021, 11(5), 526; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11050526 - 10 May 2021
Viewed by 509
Abstract
Permeability of concrete is regarded as a basic indicator of its durability. This paper proposed a simple model to predict the permeability of engineered cementitious composites (ECC), which are fiber reinforced cementitious composites with extremely high ductility and toughness. The permeability of cement [...] Read more.
Permeability of concrete is regarded as a basic indicator of its durability. This paper proposed a simple model to predict the permeability of engineered cementitious composites (ECC), which are fiber reinforced cementitious composites with extremely high ductility and toughness. The permeability of cement paste in ECC was firstly determined based on the general effective media theory. The needed microstructure information of cement paste was obtained from a simulated microstructure. Porosity of the interfacial transition zone (ITZ) was obtained with an ITZ porosity model, and then used to calculate the permeability of ITZ. The permeability of the matrix was determined according to the general self-consistent scheme, and the influence of fiber was simplified with its volume fraction. The calculated permeability of ECC was verified with results from water permeability tests and the accuracy of the model was acceptable for cement-based materials. Full article
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Article
Prediction of Neutralization Depth of R.C. Bridges Using Machine Learning Methods
Crystals 2021, 11(2), 210; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11020210 - 20 Feb 2021
Viewed by 497
Abstract
Machine learning techniques have become a popular solution to prediction problems. These approaches show excellent performance without being explicitly programmed. In this paper, 448 sets of data were collected to predict the neutralization depth of concrete bridges in China. Random forest was used [...] Read more.
Machine learning techniques have become a popular solution to prediction problems. These approaches show excellent performance without being explicitly programmed. In this paper, 448 sets of data were collected to predict the neutralization depth of concrete bridges in China. Random forest was used for parameter selection. Besides this, four machine learning methods, such as support vector machine (SVM), k-nearest neighbor (KNN) and XGBoost, were adopted to develop models. The results show that machine learning models obtain a high accuracy (>80%) and an acceptable macro recall rate (>80%) even with only four parameters. For SVM models, the radial basis function has a better performance than other kernel functions. The radial basis kernel SVM method has the highest verification accuracy (91%) and the highest macro recall rate (86%). Besides this, the preference of different methods is revealed in this study. Full article
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Article
Experimental Study and Design of Experiment Using Statistical Analysis for the Development of Geopolymer Matrix for Oil-Well Cementing for Enhancing the Integrity
Crystals 2021, 11(2), 139; https://0-doi-org.brum.beds.ac.uk/10.3390/cryst11020139 - 29 Jan 2021
Cited by 3 | Viewed by 624
Abstract
This paper presents an experimental investigation on geopolymer cement formulations for enhancing oil-well integrity. Fresh slurry properties, mixability, density, free-water, and rheology were determined for possible field applications. The compressive strength and expansion characteristics were studied for the durability and integrity of the [...] Read more.
This paper presents an experimental investigation on geopolymer cement formulations for enhancing oil-well integrity. Fresh slurry properties, mixability, density, free-water, and rheology were determined for possible field applications. The compressive strength and expansion characteristics were studied for the durability and integrity of the well system. Mix formulations complied with the requirements of API RP 10B-2. All formulations showed homogeneous mixability, rheological properties, the plastic viscosity (PV), and yield point (YP) were increased from 48 cP to 104 cP and 3.8 N/m2 12.4 N/m2, respectively, with the increase of the dosage of elastomeric type expandable material (R additive). The highest compressive strength of 15 MPa was obtained using 10% R additive in the mix-blend after 60 days of curing. Increasing the amount of R additive provides the optimum strength at 10.4 MPa with design 2, 3, and 4. The linear expansion was increased to about 1% at 60 days with 20% and 25% of the R additive dosage. Design of Experiment (DOE) was performed for setting three factors: curing time (A), curing temperature (B), and concentration of R additive (C) to optimize the linear expansion (response). Full article
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