Surface Cracking and Fractal Characteristics of Cement Paste after Exposure to High Temperatures

Li, Li; Zhang, Yang; Yuqiong, Shi; Xue, Zhigang; Cao, Mingcui

doi:10.3390/fractalfract6090465

Cited by 24 publications

(10 citation statements)

References 41 publications

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“…The effectiveness of the fractal dimension in evaluating the high-temperature resistance performance of CCs stems from its reduced susceptibility to variations in material shape and size under high-temperature conditions. Li et al [132] conducted an analysis on the cracking characteristics of concrete materials at elevated temperatures, examining parameters such as crack area, total length, average width, and c D . They prepared two sizes of concrete material specimens: cube specimens (70 × 70 × 70 mm 3 ) and prism specimens (40 × 40 × 40 mm 3 ).…”

Section: Correlation Between Pore Structure and High-temperature Resi...mentioning

confidence: 99%

Fractal Analysis of Cement-Based Composite Microstructure and Its Application in Evaluation of Macroscopic Performance of Cement-Based Composites: A Review

Zhang,

Ding,

Guo

et al. 2024

Fractal Fract

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Cement-based composites’, as the most widely used building material, macroscopic performance significantly influences the safety of engineering structures. Meanwhile, the macroscopic properties of cement-based composites are tightly related to their microscopic structure. The complexity of cement-based composites’ microscopic structure is challenging to describe geometrically, so fractal theory is extensively applied to quantify the microscopic structure of cement-based composites. However, existing studies have not clearly defined the quantification methods for various microscopic structures in CCs, nor have they provided a comprehensive evaluation of the correlation between the fractal dimensions of different microscopic structures and macroscopic performance. So, this study categorizes the commonly used testing methods in fractal theory into three categories: particle distribution (laser granulometry, etc.), pore structure (mercury intrusion porosity, etc.), and fracture (computed tomography, etc.). It systematically establishes a detailed process for the application of testing methods, the processing of test results, model building, and fractal dimension calculation. The applicability of different fractal dimension calculation models and the range of the same fractal dimension established by different models are compared and discussed, and the advantages and disadvantages of different models are analyzed. Finally, the research delves into an in-depth analysis of the relationship between the fractal dimension of cement-based composites’ microscopic structure and its macroscopic properties, such as compressive strength, corrosion resistance, impermeability, and high-temperature resistance. The principle that affects the positive and negative correlation between fractal dimension and macroscopic performance is discussed and revealed in this study. The comprehensive review in this paper provides scholars with methods and models for quantitative research on the microscopic structural parameters of cement-based composites and offers a pathway for the non-destructive assessment of the macroscopic performance of cement-based composites.

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Section: Correlation Between Pore Structure and High-temperature Resi...mentioning

confidence: 99%

Fractal Analysis of Cement-Based Composite Microstructure and Its Application in Evaluation of Macroscopic Performance of Cement-Based Composites: A Review

Zhang,

Ding,

Guo

et al. 2024

Fractal Fract

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“…These research results show that convolutional neural networks can accurately model numerous complex systems relying on big data. Li et al accurately identified concrete surface cracks using a semantic segmentation algorithm based on convolutional neural networks [38,39]. According to the semantic recognition results, they extracted the crack parameters and analyzed the fractal characteristics of the surface cracks from different specimens using image processing techniques.…”

Section: Introductionmentioning

confidence: 99%

Dynamic displacement estimation of structures using one-dimensional convolutional neural network

Zhou,

2023

Front. Phys.

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For large infrastructures, dynamic displacement measurement in structures is an essential topic. However, limitations imposed by the installation location of the displacement sensor can lead to measurement difficulties. Accelerometers are characterized by easy installation, good stability and high sensitivity. For this regard, this paper proposes a structural dynamic displacement estimation method based on a one-dimensional convolutional neural network and acceleration data. It models the complex relationship between acceleration signals and dynamic displacement information. In order to verify the reliability of the proposed method, a finite element-based frame structure was created. Accelerations and displacements were collected for each node of the frame model under seismic response. Then, a dynamic displacement estimation dataset is constructed using the acceleration time series signal as features and the displacement signal at a certain moment as target. In addition, a typical neural network was used for a comparative study. The results indicated that the error of the neural network model in the dynamic displacement estimation task was 9.52 times higher than that of the one-dimensional convolutional neural network model. Meanwhile, the proposed modelling scheme has stronger noise immunity. In order to validate the utility of the proposed method, data from a real frame structure was collected. The test results showed that the proposed method has a mean square error of only 5.097 in the real dynamic displacement estimation task, which meets the engineering needs. Afterwards, the outputs of each layer in the dynamic displacement estimation model are visualized to emphasize the displacement calculation process of the convolutional neural network.

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“…As a kind of reinforcement material, fiber is incorporated into cement-based materials, which can prevent the generation and propagation of cracks, improve the strength and toughness of cement-based materials [14], prevent their fatigue, improve impact resistance [15] and heat resistance [16][17][18][19][20][21][22][23][24][25], etc., which is one of the main means to improve the performance of cement-based materials and extend their service life. At present, there are many varieties of fiber, often used in concrete, such as steel fiber [26,27], glass fiber, basalt fiber [28], polyvinyl alcohol fiber [29][30][31][32], polypropylene fiber [33] and hybrid fiber [34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Impact of Nano-CaCO3 and PVA Fiber on Properties of Fresh and Hardened Geopolymer Mortar

et al. 2023

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Geopolymer is a green substitute for Portland cement but has low tensile strength, high brittleness and easy cracking. Therefore, fibers and nanomaterials are used to strengthen and toughen geopolymer composites. The influence of nano-calcium carbonate and PVA fiber on the properties of fresh and hardened geopolymer mortar were studied herein. The hybrid of long and short fibers with small content (0.8 vol.%) is conducive to flowability, while the hybrid with large content (1.6 vol.%) and nano-calcium carbonate is conducive to flowability. The slump flow and flow rate of geopolymer mortars with low fiber factor (product of fiber volume fraction and length-diameter ratio) decrease with the growth in nano-calcium carbonate content. As the PVA fiber factor reaches 464.8%, the slump flow and flow rate values of mortars with 0, 1 wt.% and 2 wt.% nano-calcium carbonate are close to each other. About 450% is the density packing threshold of PVA fiber in geopolymer composites. The combination of 0.8 vol.% 12 mm + 0.4 vol.% 6 mm fiber + 1 wt.% nano-calcium carbonate presents the highest flexural strength and flexural to compressive strength ratio, with a compressive strength of about 36 MPa. The optimal fiber factor range of PVA fiber in cement and geopolymer mortar is about 400% and higher than 600%, respectively. PVA fibers show more effective enhancement of flexural strength and toughness in geopolymer than cement mortar. The ultrasonic wave velocity and apparent density of geopolymer mortar show a downward trend as a whole with the increase in fiber factor. The intensity rise of the hump between 17° and 38° (2 θ) in the XRD pattern is observed. The SEM indicates that the surface of PVA fiber in geopolymer mortar with nano-calcium carbonate is heavily scratched, and the fiber filaments are rolled up, demonstrating improved bonding between PVA fiber and geopolymer mortar.

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Surface Cracking and Fractal Characteristics of Cement Paste after Exposure to High Temperatures

Cited by 24 publications

References 41 publications

Fractal Analysis of Cement-Based Composite Microstructure and Its Application in Evaluation of Macroscopic Performance of Cement-Based Composites: A Review

Fractal Analysis of Cement-Based Composite Microstructure and Its Application in Evaluation of Macroscopic Performance of Cement-Based Composites: A Review

Dynamic displacement estimation of structures using one-dimensional convolutional neural network

Impact of Nano-CaCO3 and PVA Fiber on Properties of Fresh and Hardened Geopolymer Mortar

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