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Experimental Tests and Numerical Analysis of Construction Materials

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Construction and Building Materials".

Deadline for manuscript submissions: 10 June 2024 | Viewed by 5928

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Guest Editor
Department of Civil Engineering, Chosun University, Gwangju, Republic of Korea
Interests: soil improvement; foundation engineering; dynamic behaviour of soil
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Construction materials are crucial to safely maintaining structures and buildings. In recent years, significant advances in the field of construction materials have been made. We invite you to contribute high-quality research or review papers to this Special Issue of Materials on  ‘Experimental Tests and Numerical Analysis on Construction Materials’, with an emphasis on innovative, novel and emerging materials, as well as traditional construction materials. We welcome the submission of papers that attend to areas including, but not limited to, soil, geomaterials, cements, concretes, steels, grouting materials, and novel and emerging construction materials. Papers will be accepted for this Special Issue once they have undergone a rigorous peer-review procedure.

Prof. Dr. Daehyeon Kim
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • experimental research
  • load test
  • numerical analysis
  • construction materials
  • concretes
  • cements
  • geomaterials
  • grouting materials
  • steels
  • rock and rock-like materials
  • civil structures
  • infrastructures
  • foundation engineering

Published Papers (9 papers)

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24 pages, 8637 KiB  
Article
Effective Prediction of Concrete Constitutive Models for Reinforced Concrete Shear Walls under Cyclic Loading
by Quoc Bao To, Jiuk Shin, Sung Jig Kim, Hye-Won Kim and Kihak Lee
Materials 2024, 17(8), 1877; https://doi.org/10.3390/ma17081877 - 18 Apr 2024
Viewed by 215
Abstract
One of the most challenging elements of modeling the behaviour of reinforced concrete (RC) walls is combining realistic material models that can capture the observable behaviour of the physical system. Experiments with realistic loading rates and pressures reveal that steel and concrete display [...] Read more.
One of the most challenging elements of modeling the behaviour of reinforced concrete (RC) walls is combining realistic material models that can capture the observable behaviour of the physical system. Experiments with realistic loading rates and pressures reveal that steel and concrete display complicated nonlinear behaviour that is challenging to represent in a single constitutive model. To investigate the response of a reinforced concrete structure subjected to dynamic loads, this paper’s study is based on many different material models to assess the advantages and disadvantages of the models on 2D and 3D RC walls using the LS-DYNA program. The models consisted of the KCC model and the CDP model, which represented plasticity and distinct tensile/compressive damage models, and the Winfrith model, which represented plasticity and the smeared crack model. Subsequently, the models’ performances were assessed by comparing them to experimental data from reinforced concrete structures, in order to validate the accuracy of the overall behaviour prediction. The Winfrith model demonstrated satisfactory results in predicting the behaviour of 2D and 3D walls, including maximum strength, stiffness deterioration, and energy dissipation. The method accurately predicted the maximum strength of the Winfrith concrete model for the 2D wall with an error of 9.24% and for the 3D wall with errors of 3.28% in the X direction and 5.02% in the Y direction. The Winfrith model demonstrated higher precision in predicting dissipation energy for the 3D wall in both the X and Y directions, with errors of 6.84% and 6.62%, correspondingly. Additional parametric analyses were carried out to investigate structural behaviour, taking into account variables such as concrete strength, strain rate, mesh size, and the influence of the element type. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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24 pages, 8833 KiB  
Article
An Integrated Framework for Image Acquisition, Processing, and Analysis Procedures for Automated Damage Evaluation of Concrete Surfaces
by Haixu Zhang, Cassandra Trottier, Leandro F. M. Sanchez and Anthony Allard
Materials 2024, 17(4), 813; https://doi.org/10.3390/ma17040813 - 08 Feb 2024
Viewed by 737
Abstract
Concrete surface cracks serve as early indicators of potential structural threats. Visual inspection, a commonly used and versatile concrete condition assessment technique, is employed to assess concrete degradation by observing signs of damage on the surface level. However, the method tends to be [...] Read more.
Concrete surface cracks serve as early indicators of potential structural threats. Visual inspection, a commonly used and versatile concrete condition assessment technique, is employed to assess concrete degradation by observing signs of damage on the surface level. However, the method tends to be qualitative and needs to be more comprehensive in providing accurate information regarding the extent of damage and its evolution, notwithstanding its time-consuming and environment-sensitive nature. As such, the integration of image analysis techniques with artificial intelligence (AI) has been increasingly proven efficient as a tool to capture damage signs on concrete surfaces. However, to improve the performance of automated crack detection, it is imperative to intensively train a machine learning model, and questions remain regarding the required image quality and image collection methodology needed to ensure the model’s accuracy and reliability in damage quantitative analysis. This study aims to establish a procedure for image acquisition and processing through the application of an image-based measurement approach to explore the capabilities of concrete surface damage diagnosis. Digitizing crack intensity measurements were found to be feasible; however, larger datasets are required. Due to the anisotropic behavior of the damage, the model’s ability to capture crack directionality was developed, presenting no statistically significant differences between the observed and predicted values used in this study with correlation coefficients of 0.79 and 0.82. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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0 pages, 8205 KiB  
Article
Numerical Study on the Axial Compressive Behavior of Steel-Tube-Confined Concrete-Filled Steel Tubes
by Xiaozhong Li, Sumei Zhang, Yu Tao and Bing Zhang
Materials 2024, 17(1), 155; https://doi.org/10.3390/ma17010155 - 27 Dec 2023
Cited by 1 | Viewed by 488 | Correction
Abstract
To improve the concrete confinement and mechanical properties of concrete-filled steel tube (CFST) columns, a new configuration of steel-tube-confined concrete-filled steel tube (T-CFST) columns has recently been developed, in which an outer steel tube is employed externally, and the additional tube does not [...] Read more.
To improve the concrete confinement and mechanical properties of concrete-filled steel tube (CFST) columns, a new configuration of steel-tube-confined concrete-filled steel tube (T-CFST) columns has recently been developed, in which an outer steel tube is employed externally, and the additional tube does not sustain the axial load directly. This preliminary experimental study revealed that, due to the effective concrete confinement by the outer steel tube, the T-CFST column achieves higher compressive strength and more ductile deformation compared to the CFST columns of the same steel ratio. In this study, two finite element (FE) models were developed for the T-CFST cross-section and stub column, respectively. The numerical study results revealed that the concrete can be constrained by the outer steel tube at the beginning of loading and the outer steel tube hoop stress can reach its yield strength at the column’s compressive strength, showing its effective confinement to the concrete. Numerous data were generated by the developed FE model to cover a wide range of parameters. Based on that, the calculation methods for the stress components of the inner and outer steel tubes are proposed. Finally, a suitable prediction method is proposed, utilizing the superposition method to determine the compressive strength of the T-CFST stub column, and the results of the calculation method and FE model agree well with each other. This research is the basis for promoting further research of T-CFST columns. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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15 pages, 6197 KiB  
Article
Influence of Fines Content and Pile Surface Characteristics on the Pullout Resistance Performance of Piles
by Seungkyong You, Kwangwu Lee and Gigwon Hong
Materials 2024, 17(1), 124; https://doi.org/10.3390/ma17010124 - 26 Dec 2023
Viewed by 572
Abstract
In this study, the direct shear test and model pullout test results are presented to assess the impact of soil fines content and shear resistance characteristics of the pile–soil interface on the pullout resistance of drilled shafts. The direct shear test on the [...] Read more.
In this study, the direct shear test and model pullout test results are presented to assess the impact of soil fines content and shear resistance characteristics of the pile–soil interface on the pullout resistance of drilled shafts. The direct shear test on the soil–pile interface was conducted based on the pile surface simulated using sandpaper with three roughness types (#24, #40, and #400) and varying fines content. The direct shear test results of soil showed that the internal friction angle decreased by about 29% and the cohesion increased by about 110% when the fine powder content increased from 5% to 30%. Specifically, in the case of soil–sandpaper (#24), the interface friction angle decreased by about 31%, and the adhesion increased by about 16%. The sandpaper with a roughness of #40 and #400 also showed a similar trend. Normalizing the shear strength parameters from the direct shear test demonstrated an intersection between the normalized curves of the friction angle and cohesion (or adhesion) within a specific fines content range. This suggests that shear strength parameters play a significant role based on fines content. Analyzing the normalized index using model pullout test results indicated the necessity to evaluate the contribution of friction angle and cohesion (or adhesion) of the shear surface, taking into account the fines content of the soil for predicting pile pullout resistance. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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28 pages, 6664 KiB  
Article
Robust Machine Learning Framework for Modeling the Compressive Strength of SFRC: Database Compilation, Predictive Analysis, and Empirical Verification
by Yassir M. Abbas and Mohammad Iqbal Khan
Materials 2023, 16(22), 7178; https://doi.org/10.3390/ma16227178 - 15 Nov 2023
Cited by 2 | Viewed by 919
Abstract
In recent years, the field of construction engineering has experienced a significant paradigm shift, embracing the integration of machine learning (ML) methodologies, with a particular emphasis on forecasting the characteristics of steel-fiber-reinforced concrete (SFRC). Despite the theoretical sophistication of existing models, persistent challenges [...] Read more.
In recent years, the field of construction engineering has experienced a significant paradigm shift, embracing the integration of machine learning (ML) methodologies, with a particular emphasis on forecasting the characteristics of steel-fiber-reinforced concrete (SFRC). Despite the theoretical sophistication of existing models, persistent challenges remain—their opacity, lack of transparency, and real-world relevance for practitioners. To address this gap and advance our current understanding, this study employs the extra gradient (XG) boosting algorithm, crafting a comprehensive approach. Grounded in a meticulously curated database drawn from 43 seminal publications, encompassing 420 distinct records, this research focuses predominantly on three primary fiber types: crimped, hooked, and mil-cut. Complemented by hands-on experimentation involving 20 diverse SFRC mixtures, this empirical campaign is further illuminated through the strategic use of partial dependence plots (PDPs), revealing intricate relationships between input parameters and consequent compressive strength. A pivotal revelation of this research lies in the identification of optimal SFRC formulations, offering tangible insights for real-world applications. The developed ML model stands out not only for its sophistication but also its tangible accuracy, evidenced by exemplary performance against independent datasets, boasting a commendable mean target-prediction ratio of 99%. To bridge the theory–practice gap, we introduce a user-friendly digital interface, thoroughly designed to guide professionals in optimizing and accurately predicting the compressive strength of SFRC. This research thus contributes to the construction and civil engineering sectors by enhancing predictive capabilities and refining mix designs, fostering innovation, and addressing the evolving needs of the industry. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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17 pages, 3701 KiB  
Article
Analysis of Resistance to Wind Suction of Flat Roof Coverings Glued with Polyurethane Adhesives
by Barbara Francke, Jarosław Szulc, Jan Sieczkowski, Artur Piekarczuk, Joanna Witkowska Dobrev and Krzysztof Schabowicz
Materials 2023, 16(22), 7135; https://doi.org/10.3390/ma16227135 - 12 Nov 2023
Viewed by 713
Abstract
The article analyses the impact of wind suction on roof coverings glued with polyurethane adhesives to flat roofs, i.e., roofs with an up to 20% slope. The impact of the cyclical wind was simulated in fatigue tests, gradually increasing the test pressure in [...] Read more.
The article analyses the impact of wind suction on roof coverings glued with polyurethane adhesives to flat roofs, i.e., roofs with an up to 20% slope. The impact of the cyclical wind was simulated in fatigue tests, gradually increasing the test pressure in repeated sequences until the first delamination occurred. The tests were carried out for eight test sets, with concrete and trapezoidal sheets used as a construction substrate, on whose surface thermal insulation layers were glued with polyurethane adhesive; the thermal insulation layers were EPS (expanded polystyrene) and PIR (polymer mainly of polyisocyanurate groups), respectively, followed by flexible sheets, i.e., a laminated PVC membrane (polyvinylchloride) and an EPDM (terpolymer of ethylene, propylene and a diene with a residual unsaturated portion of diene in the side chain)-type rubber-based membrane. The test results were compared with the functional requirements determined with computational simulation methods for the maximum wind load values on the example of wind loads for Poland. The tests confirmed that some polyurethane adhesives could ensure the operation of flexible sheets used as flat roof coverings that are failure-free from the point of view of resistance to wind suction. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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18 pages, 9207 KiB  
Article
Prediction of Dynamic Behavior of Large-Scale Ground Using 1 g Shaking Table Test and Numerical Analysis
by Yong Jin, Sugeun Jeong and Daehyeon Kim
Materials 2023, 16(18), 6093; https://doi.org/10.3390/ma16186093 - 06 Sep 2023
Viewed by 581
Abstract
Earthquake disasters can threaten human life and cause property damage. The dynamic analysis of the ground performance of the seismic field is essential. In this study, numerical analysis is used to predict the dynamic behavior and response analysis of large-scale models under different [...] Read more.
Earthquake disasters can threaten human life and cause property damage. The dynamic analysis of the ground performance of the seismic field is essential. In this study, numerical analysis is used to predict the dynamic behavior and response analysis of large-scale models under different seismic waves. Firstly, the accuracy of numerical analysis is verified by a 1 g shaking table test under the same size. Then, according to the similarity law, numerical analysis is used to obtain the dynamic behavior of the model at different scales. The results show that the 1 g shaking table test results are in good agreement with the numerical analysis results and that the numerical analysis can predict the dynamic behavior of the scale model. The 1 g shaking table test provides a valuable method for evaluating the numerical analysis, which captures the complex behavior and resolves uncertainties, ultimately leading to more robust and reliable analyses. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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16 pages, 7674 KiB  
Article
Two-Dimensional Microstructure-Based Model for Evaluating the Permeability Coefficient of Heterogeneous Construction Materials
by Jiaqi Chen, Shujun Yu, Wei Huang and Hao Wang
Materials 2023, 16(17), 5892; https://doi.org/10.3390/ma16175892 - 28 Aug 2023
Cited by 1 | Viewed by 782
Abstract
The permeability coefficient of construction materials plays a crucial role in engineering quality and durability. In this study, a microstructure model based on real aggregate shape and digital image technology is proposed to predict the permeability coefficient of concrete. A two-dimensional, three-component finite [...] Read more.
The permeability coefficient of construction materials plays a crucial role in engineering quality and durability. In this study, a microstructure model based on real aggregate shape and digital image technology is proposed to predict the permeability coefficient of concrete. A two-dimensional, three-component finite element model of cement concrete was established considering the interfacial transition zone (ITZ) between aggregate and mortar. The permeability coefficient prediction model was developed by the finite element method. The accuracy of the model was verified by experimental data, and the influence of the water−cement ratio on the permeability coefficient of concrete was analyzed. The results show that this method has good prediction accuracy with a relative error of 1.73%. According to the verified model, the influences of aggregate content, aggregate characteristics, aggregate location, ITZ thickness, and other factors on the permeability of concrete were explored. The higher the water−cement ratio, the higher the permeability coefficient. With the increase in aggregate content, the permeability coefficient decreases. Aggregate permeability has a significant influence on the effective permeability coefficient of concrete within a certain range. The greater the roundness of aggregate, the greater the permeability of concrete. On the contrary, the larger aggregate size causes lower permeability. The permeability coefficient of concrete with segregation is lower than that with uniform distribution. At the same time, the permeability increases with the increase of ITZ thickness. Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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2 pages, 638 KiB  
Correction
Correction: Li et al. Numerical Study on the Axial Compressive Behavior of Steel-Tube-Confined Concrete-Filled Steel Tubes. Materials 2024, 17, 155
by Xiaozhong Li, Sumei Zhang, Yu Tao and Bing Zhang
Materials 2024, 17(5), 1132; https://doi.org/10.3390/ma17051132 - 29 Feb 2024
Viewed by 369
Abstract
In the original publication [...] Full article
(This article belongs to the Special Issue Experimental Tests and Numerical Analysis of Construction Materials)
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