Different Types Of Concrete Research Articles

Eco-Friendly Concrete Solutions: The Role of Titanium Dioxide Nanoparticles in Enhancing Durability and Reducing Environmental Pollutants - A Review

Concrete is one of the key components of construction, which ensures durability and aesthetics of the building. In recent days, nanoparticles are playing an essential role in civil engineering research. The binding of nanoparticles into concrete significantly improves the mechanical and durable properties due to the nanostructure of the cementitious materials. This review paper represents the existing research data on titanium dioxide nanoparticles, when applied in the different types of concrete. The data influenced by the different research papers are presented in terms of strength and durable parameters. The most important property of titanium dioxide nanoparticle is its self-cleaning effect because of the photocatalytic reaction is also discussed. The inference from the papers shows the effect of titanium dioxide nanoparticles on correct proportion enhances the production of new material with good strength and durable properties in the construction industry. The photocatalytic action of nano titanium dioxide leads to the manufacture of self-cleaning concrete which shields the surface from environmental pollutants.

Monitoring of interface separation damage in buckling-restrained steel plate shear walls using piezoelectric based smart aggregates under cyclic loading

Interface debonding damage is a critical issue for many prefabricated concrete components. Various studies have employed different methods to detect debonding behaviors and provided quantitative damage indexes. In this paper, we propose a novel monitoring approach for detecting interface debonding damage in Engineered Cementitious Composite (ECC) panel-restrained composite steel plate shear walls (SPSWs) using piezoelectric ceramics (PZT). Four SPSWs were designed with different types of concrete, steel plate thicknesses, and bolt arrangements for the cyclic loading experiment. Energy data was collected for time-domain and wavelet packet analysis. The root mean square deviation (RMSD) was then calculated to provide a quantitative damage index for the specimens. The highest damage indices for each specimen were 0.770, 0.963, 0.988, and 1, respectively, which corresponded well with the actual damage scenarios. The experiments verified that using PZT can accurately monitor debonding damage in SPSWs.

Investigation Of Strength Development In Conventional And High Strength Concrete Under Different Curing Conditions

The composite material obtained by blending cement, aggregate, water and, when necessary, an additive, placing a mixture with carefully adjusted proportions into molds of the desired shape and size without gaps and hardening under appropriate maintenance conditions, is called concrete or traditional concrete. In the 1960s, concretes with compressive strengths of 41 MPa and 52 MPa were used on the market in the USA. In the recent past, concretes with compressive strengths varying between 80 MPa and 100 MPa have been commercially applied in structures made with in-situ concrete and prestressed concrete structural elements. Strength developments of traditional and high-strength concretes under different curing conditions will be examined. For this purpose, central pressure tests were carried out on cube samples produced. For concrete production; For each aggregate class, cement, saturation water, mixed water and high strength concretes; It was prepared by weighing silica fume and superplasticizer. The prepared samples were stored in standard or cold water for 3 days, 7 days, 28 days and 90 days. In this study, the strength development of traditional and high-strength concretes under different curing conditions was examined experimentally. In accordance with the experimental work plan determined for this investigation, concrete cube samples were produced and these samples were subjected to the central pressure test. The concretes produced are in C55, C20 and C12 classes. As a result, although similar behaviors were observed in high-strength and conventional concretes cured in different environments, it was determined that the difference in curing temperature was more effective on the strength development than the inadequacy of curing in water. It should be noted here that it would be beneficial to conduct similar studies on different types of concrete.

Systematic literature review on the application of machine learning for the prediction of properties of different types of concrete

Background Concrete, a fundamental construction material, stands as a significant consumer of virgin resources, including sand, gravel, crushed stone, and fresh water. It exerts an immense demand, accounting for approximately 1.6 billion metric tons of Portland and modified Portland cement annually. Moreover, addressing extreme conditions with exceptionally nonlinear behavior necessitates a laborious calibration procedure in structural analysis and design methodologies. These methods are also difficult to execute in practice. To reduce time and effort, ML might be a viable option. Material and Methods A set of keywords are designed to perform the search PubMed search engine with filters to not search the studies below the year 2015. Furthermore, using PRISMA guidelines, studies were selected and after screening, a total of 42 studies were summarized. The PRISMA guidelines provide a structured framework to ensure transparency, accuracy, and completeness in reporting the methods and results of systematic reviews and meta-analyses. The ability to methodically and accurately connect disparate parts of the literature is often lacking in review research. Some of the trickiest parts of original research include knowledge mapping, co-citation, and co-occurrence. Using this data, we were able to determine which locations were most active in researching machine learning applications for concrete, where the most influential authors were in terms of both output and citations and which articles garnered the most citations overall. Conclusion ML has become a viable prediction method for a wide variety of structural industrial applications, and hence it may serve as a potential successor for routinely used empirical model in the design of concrete structures. The non-ML structural engineering community may use this overview of ML methods, fundamental principles, access codes, ML libraries, and gathered datasets to construct their own ML models for useful uses. Structural engineering practitioners and researchers may benefit from this article’s incorporation of concrete ML studies as well as structural engineering datasets. The construction industry stands to benefit from the use of machine learning in terms of cost savings, time savings, and labor intensity. The statistical and graphical representation of contributing authors and participants in this work might facilitate future collaborations and the sharing of novel ideas and approaches among researchers and industry professionals. The limitation of this systematic review is that it is only PubMed based which means it includes studies included in the PubMed database.

Lap-slip model of rebar-to-concrete in RC/ECC/UHPC based on GA-BP neural network

Rebar lap splicing is a widely used method of reinforcement connection in precast concrete structures, and the lap-slip model serves as an important prerequisite for conducting detailed mechanical calculations of reinforced concrete lap splice members. Most traditional bond-slip mechanical models are semi-empirical and semi-theoretical formulas derived from experimental data; they do not consider the effect of reinforcement lap spacing, which prevents them from accurately reflecting the force transfer characteristics of lap reinforcement in concrete. In this paper, a Back Propagation (BP) neural network based on a Genetic Algorithm (GA) is used to establish a lap-slip model of reinforced concrete considering rebar spacing, which improves on the current bond-slip mechanical model. Several sets of rebar lap tests based on RC/ECC/UHPC were designed, and full-sample parameter sensitivity analyses were carried out using the lap length, the thickness of the concrete cover, the rebar spacing and the stirrup ratio as test parameters. The results showed that rebar lap spacing was an important influencing factor in the proposed lap-slip model, with a sensitivity coefficient reaching 0.471. The lap-slip model, based on the GA-BP neural network, was developed and compared with existing models; the predictive ability of the model was verified by the ten-fold crossover method. The generalizability of the GA-BP model was verified by randomly selecting non-training test data as well as lap test data of rebar in different types of concrete. The results indicated that the model exhibits high predictive and generalization abilities, with most correlation coefficients exceeding 0.95. The proposed model was compared with a mechanical model established using the traditional fitting formula method, and the results showed that the prediction accuracy of the lap-slip model established based on the GA-BP neural network is slightly lower than that of the mechanical model obtained using the fitting formula method, but it still offers high prediction accuracy, and the prediction results are more objective and realistic, which is of guiding significance for practical applications and related research.

The industrial SO2-induced corrosion: Investigation of the corrosion onset

The stability of the passivation film on reinforcing steel is significantly influenced by the internal chemical environment of concrete under industrial sulfur dioxide (SO2) corrosion. This study aimed to investigate the electrochemical state of the reinforcing steel and the internal chemical environment (corrosion products, phase composition, and pore structure) of concrete by conducting indoor simulations of reinforced concrete specimens exposed to industrial SO2 environment. The results indicated a consistent trend in open circuit potential (OCP) and corrosion current density (icorr) of steel rebar in different types of concrete. A sudden reduction in OCP is accompanied by a significant increase in icorr when the rebars reach an active state. At this time, the ratio of sulphation depth to protective layer thickness ranges from 0.47 to 0.63. The main sulphation products were gypsum and ettringite, with their content decreasing as the cover layer depth, water-to-binder ratio, and fly ash content increased. Due to crystallization pressure and expansion, the impact of SO2 corrosion on the capillary pores of concrete was the most significant, followed by its effect on larger pores. After 96 days of corrosion, there was an increase of 191.7 % and 116.2 % in the quantity of pore sizes, respectively. Furthermore, the porosity growth rate in concrete with the incorporation of fly ash is lower than that of Portland concrete. This suggests that the rational use of fly ash to partially replace Portland cement is beneficial for enhancing the resistance of concrete to SO2 corrosion.

Study on corrosion characteristics of reinforcing bars in concrete under industrial SO2 environment

Sulfur dioxide (SO2) is the primary pollutant in industrial atmospheres, leading to significant damage to industrial buildings. The corrosion caused by SO2 in concrete, including neutralization and solid phase volume expansion, poses particular concerns. However, there is a lack of research on the electrochemical behaviour and corrosion mechanisms of reinforcing bars embedded in concrete. This study conducted indoor simulations of reinforced concrete specimens exposed to industrial SO2 corrosion utilizing an SO2 testing chamber. The corrosion behavior of the reinforcing bars was monitored through half-cell potential, weak polarization, and electrochemical impedance spectroscopy (EIS). Additionally, the corrosion mechanisms of the reinforcing bars under SO2 exposure were investigated using scanning electron microscopy with energy dispersive spectroscopy (SEM/EDS), X-ray diffraction (XRD), and Raman spectra. The results demonstrated a consistent correlation between variations in corrosion potential (Ecorr) and corrosion current density (icorr) of steel rebars in different types of concrete. The corrosion rates of the reinforcing steel in C1 (w/b=0.57), C2 (w/b=0.47), and C3 (w/b=0.37) concrete exceeds 0.1 μA/cm2 after 42, 72, and 90 days of SO2 corrosion, respectively. At this time, the ratio of the depth of neutralization to the thickness of the protective layer is 0.51–0.65. The rust exhibits a layered structure with a presence of S elements adsorbed and deposited on the surface of the rust layer. Moreover, the research has identified the accumulation of S elements within corrosion pits, which can be attributed to localized acidification reactions. The rust products identified include iron hydroxide (FeOOH), and iron oxide (Fe2O3), rozenite (FeSO4·4 H2O). The formation of FeSO4·4 H2O in corrosion pits suggests that significant localized corrosion on the surface of reinforcing bars in concrete under the impact of SO2.

Modelling Water Absorption Index and Compressive Strength of Paving Stone Composites with Polyethylene Terephthalate (PET) as Total Binder Replacement

Packing density method of mix design of concrete is new method to design different types of concrete. The mix design obtained from the packing density method has suitable workability, maximum packing density and minimum voids ratio. The geometrical characteristics like shape, size and proportion of fine aggregate and coarse aggregate affect packing density. The objective of this research is to study the mix design of concrete using packing density method and develop the correlation between bulk density, packing density and voids ratio. In this work large number of trail to decide the proportion of aggregate for that optimum bulk density and packing density calculated for different varying proportion of 20 mm: 12.5 mm coarse aggregate (i.e. 90:10, 80:20,70:30, 65:35, 60:40 and 50:50) and for varying proportion coarse aggregate: fine aggregate (i.e. 90:10, 80:20, 70:30, 60:40, 55:45 and 50:50). To finalize the mix design using packing density method also varies the percentage of excess cement paste (i.e. 5%, 7%, 9%, 10%, 11% and 12%). Tests were performed for the properties of fresh concrete like workability test (Slump cone) and hardened concrete like compressive strength, split- tensile strength, pull-out test, rebound hammer and flexural Test etc. tests were determined at 7, 14 and 28 days. The obtained results for above mentioned test using packing density method at 9% of excess cement paste are satisfying the standard results.

Design of Fibre-Reinforced Concrete Structures

Different types of concrete are invented in the past years, in order to improve it`s behaviour for different loading and environmental situations. Among them, fibre reinforced concrete (FRC) is one of the most recently developed concrete types. Design procedures for the FRC elements are included in only a few existing code provisions. Among them, fib Model Code 2010 (MC 2010) provides the biggest amount of necessary information and recommendations in order to design FRC elements. Yet, a lack of the guidelines for the design of elements loaded with different combinations of bending moment and axial force is noticed in the existing code provisions. Therefore, in the scope of this paper, interaction curves for FRC are developed. The interaction curves are developed for both, ultimate limit state (ULS) and serviceability limit state (SLS). Furthermore, example of the use of such interaction curves is given. Comparison in the design of reservoir made of reinforced concrete (RC) and FRC is performed. It is shown that the use of FRC especial benefits design according to SLS, as FRC provides better behaviour regarding crack spacing and crack width of element, while developed interaction curves for SLS significantly decrease the time necessary for such a design.

Comparative Analysis of Reinforced Concrete Structure with Traditional and Decoupled Masonry Infill Under Earthquake

Different types of concrete are invented in the past years, in order to improve it`s behavior for different loading and environmental situations. Among them, fibre reinforced concrete (FRC) is one of the most recently developed concrete types. Design procedures for the FRC elements are included in only a few existing code provisions. Among them, fib Model Code 2010 (MC 2010) provides the biggest amount of necessary information and recommendations in order to design FRC elements. Yet, a lack of the guidelines for the design of elements loaded with different combinations of bending moment and axial force is noticed in the existing code provisions. Therefore, in the scope of this paper, interaction curves for FRC are developed. The interaction curves are developed for both, ultimate limit state (ULS) and serviceability limit state (SLS). Furthermore, example of the use of such interaction curves is given. Comparison in the design of reservoir made of reinforced concrete (RC) and FRC is performed. It is shown that the use of FRC especial benefits design according to SLS, as FRC provides better behaviour regarding crack spacing and crack width of element, while developed interaction curves for SLS significantly decrease the time necessary for such a design.

Influence of concrete type on rigid pavement behavior under static loads

It is thought that rigid pavements are more expensive than flexible pavements. However, when taking into account the element of durability, it was found that rigid pavements are less expensive than flexible pavements and have a service life up to 20 years. The flexible pavements are more suitable for the areas with weak subsoil and poor drainage, but it has a negative impact on the environment. This research presents an experimental and numerical study to explore the behavior of rigid pavement made of different types of concrete under the influence of static loads. The recent experimental study consists of six slabs with dimensions of 600 × 600 × 60 mm made of different types of concrete. Such types are normal-strength concrete (NSC), high-strength concrete (HSC) and strain hardening cementitious composites (SHCC). Based on the findings of this study, it is evident that the slab constructed with SHCC exhibits a 76.6% greater bearing capacity compared to the NSC slab. Regarding cost-effectiveness, the HSC slab was identified as the most economically advantageous option. A point to be noted is that the numerical model using the Abaqus program succeeded in modeling the experimental tested slabs.

A Brief Study on Comparison of Properties of Different Types of Concrete

Abstract: The abstract distinction refers to a distinction among concepts, which is typically characterized as follows. Concrete concepts are those who referents can be experienced through perception

STRENGTH AND DURABILITY OF CONCRETES WITH A SUPER ABSORBENT POLYMER ADDITIVE

The article presents an analysis of the results of experimental studies of the effect of different types of a super absorbent polymer additive on the strength of different types of concrete. The study is aimed at the effectiveness of a new type of super absorbent additive in concrete structures. In the course of full-scale experiments, it was possible to identify the optimum dosage of SAP for fine-grained and heavy concretes. In addition, the results showed that the strength of concrete remains unchanged if the dosage of super absorbent polymer additive (SAP) is 0.5% of the weight of cement or less. The possibility of modern intelligent technologies (artificial neural networks) to predict the properties of concrete mixture and hardened concrete at given values of input parameters (SAP dosage and W/C), influence on concrete characteristics (slump of the cone, bending strength, compressive strength) has also been shown.

Phương pháp tính toán kết cấu bê tông cốt thép nhiều lớp chịu uốn

In construction practice, reinforced concrete structures are designed to meet the requirements of not only the load-bearing capacity but also the abilities of sound insulation, heat insulation, fire resistance, etc. A promising and effective solution to meet these requirements is using multi-layer reinforced concrete structures with an internal layer by low thermal conductivity concrete, and external layers by traditional concrete, high-strength concrete, or kezamzit concrete. The different physical-mechanical properties of the material layers affect the structure's performance under load. In this study, the authors have introduced a theoretical method to calculate and analyze the stress-strain states of flexural reinforced concrete structures with cross-sectional sections consisting of layers from different concrete materials under the effect of load. The study's results have shown that in the manufacturing process of multi-layer reinforced concrete structures by different concretes, a contact zone is formed between layers because of aggregate components from different types of concrete. Calculated results by using the proposed model have shown that the values of the moment and deflection of the beam when cracks begin to appear and when the beam is damaged, are closer to the experimental results than by using the previous models. The research results are useful references for the calculation of multi-layer reinforced concrete structures with a middle layer from lightweight concrete.

An improved understanding of the influence of w/c ratio and interfacial transition zone on fracture mechanisms in concrete

The interfacial transition zone (ITZ) is significantly influenced by the water/cementitious materials (w/cm) ratio and governs the overall strength and fracture properties of concrete. Even though an ample number of studies on this topic are available in the literature, there is a lack of unified conclusions pertaining to the influence of w/cm ratios on various fracture characteristics and the underlying mechanisms. In this study, an attempt was made to investigate fracture characteristics (such as the size of the fracture process zone (FPZ), fracture energy, traction-free cracks (TFCs), toughening mechanisms) for varying ITZ properties and water/cement (w/c) ratios. Plain concrete beams of size 700 × 150 × 80 mm (l × d × b) with varying w/c ratios were tested under centre-point loading by controlling the crack mouth opening displacement. The acoustic emission (AE) technique was used to assess the internal damage parameters. A novel method was developed for identifying the TFC tip and the FPZ size using AE event location data at different stages of loading. The role of the ITZ on the fracture mechanisms of different types of concrete was also assessed. Evaluation of the fracture energy revealed that its relation with the w/c ratio is affected by the type of concrete.

Efficacy of deltamethrin emulsifiable concentrate against stored-product insects

Stored-product insects are specially adapted to dry conditions and to a diet of grains and grain dust. Under favorable environmental conditions, insect populations multiply rapidly and spread in stored food. Prevention of pests' development can be achieved by a variety of methods, including the use of insecticides. Deltamethrin is a synthetic pyrethroid commonly used as an insecticide in grain storage. In Israel, deltamethrin emulsifiable concentrate (Keshet 2.5% EC) is the only pyrethroid insecticide formulation permitted for use in stored grain. Although deltamethrin is used routinely, insect populations develop consistently in warehouses and newly stored grain is rapidly infested. In the current study, we examined the efficacy of deltamethrin emulsifiable concentrate for the control of adult Sitophilus oryzae (L.) (Coleoptera: Curculionidae), Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) and Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae). The insecticide was sprayed on surfaces including plastic, self-made concrete, two kinds of ready-mix concrete, as well as harvested wheat. When deltamethrin concentrations of 0.2–2.0 ppm was applied to the grain, insect mortality increased with the application rate, with complete mortality observed at 2.0 ppm. A dose of 0.2 ppm was found to be insufficient to protect the grain. Plastic surfaces and surfaces of different types of concrete were sprayed with a 4% aqueous solution of deltamethrin emulsifiable concentrate (deltamethrin concentration 0.1 mg/m2). Deltamethrin emulsifiable formulation was found to be effective on a nonporous surface and when sprayed directly on insects, but was not very effective as a residual insecticide on porous surfaces.

Strength enhancement due to FRP confinement for coarse aggregate-free concretes

Concrete strength can be effectively enhanced by external fiber reinforced polymer (FRP) confinement. However, it is found from the literature that the strength enhancement coefficient (k1) varies significantly, especially for different types of concrete. This paper presents an in-depth investigation of the variety of strength enhancement coefficients with concrete types. First, two state-of-the-art databases for FRP-confined UHPC and FRP-confined ECC specimens are constructed in this paper. From analyzing the databases, although the mechanical performances and components are different for UHPC and ECC, nonetheless, their strength enhancement coefficients are quite similar (k1 = 2.27 and 2.01, respectively). With the validation by an experimental program on FRP-confined mortar specimens, it can be concluded that the similarity of strength enhancement coefficients for FRP-confined UHPC, ECC, and mortar, which are much lower than that for normal concrete, is caused by the lack of coarse aggregates. The reasons are discussed and well explained by a simplified experiment with steel balls and shear-friction mechanism. Based on the research, this paper proposed a unified strength enhancement coefficient, i.e., 2.13, for all coarse aggregate-free concretes. As the existence of coarse aggregates is found to be the main governing factor for the strength enhancement coefficient, this paper provides a fundamental basis for future research on confinement for next-generation coarse aggregate-free cementitious materials, such as lunarcrete and 3D-printed concrete.

Prediction of Concrete Compressive Strength Using Artificial Neural Network

Concrete is the most widely used material by humans after water. Rapid growth in the construction industry, concrete will continue to be the dominant material in the future. Concrete is a composite material like aggregates, water, and admixtures. Destructive testing of concrete to know its strength achieved after the mix design will be an expensive and time-consuming process. With recent advances in soft computing techniques like artificial intelligence, these results can be predicted by feeding the algorithm with a large number of data available to obtain the desired results. In the present research work, it is proposed to use artificial neural networks to predict the strength of different types of concrete. A Multilayer Perceptron has input and output layers, and one or more hidden layers with many neurons stacked together. Data capturing will be done regarding different types of concrete and artificial neural networks are preliminarily trained with various inputs to solve problems with data applica- ble to obtain the desired results. This ANN with captured data helps in minimizing repetitive process and tests involved to obtain the results through experimental procedures which is time, material, and money- consuming with practical difficulties. The advantage of python is that designer can create a customized program for interactive design, Python determination also improve the analytical skill of the student and programs can be converted into executable software. Concrete Cubes are cast to validate the predicted Result of the Software.

Prediction of Mixed-mode I and II effective fracture toughness of several types of concrete using the extreme gradient boosting method and metaheuristic optimization algorithms

Complex sample preparation procedures, the necessity for highly accurate and sensitive instruments, early sample failure, and brittle samples all contribute to the difficulty of measurement of concrete fracture toughness (CFT) in the laboratory. With such limitations on the measuring CFT, it is necessary to develop new and more effective tools. Machine learning (ML) methods are promising tools for non-linear time series prediction. In this study, six extreme gradient boosting (XGBoost)-based meta-heuristic algorithms, including standard XGBoost, XGBoost-particle swarm optimization (PSO), XGBoost-imperialist competitive algorithm (ICA), XGBoost-grey wolf optimization (GWO), XGBoost-shuffled frog leaping algorithm (SFLA), and XGBoost-genetic algorithm (GA) were developed to predict the effective fracture toughness (K_eff) of concrete, utilizing 560 datasets obtained from the central straight notched Brazilian disc (CSNBD) test. Additives of micro silica and powdered stone, which are the most widely used building materials were used in the concrete samples to investigate their effect on the physical and mechanical properties. Therefore, 10 different materials made from a combination of concrete and different percentages of additives, were used in the experiment. The datasets included six input parameters effective on the K_eff, including concrete type (ST), diameter (D), thickness (t), length (L), force (F), and crack angle (α). The XGBoost-based models' performances were compared with those of each other and with four other ML methods of Gaussian process regression (GPR), decision trees (DT), support vector regression (SVR), and K-nearest neighbors (KNN). The ML models’ performance in the prediction of K_eff for both holdout and 5-fold methods from high to low is XGBoost-PSO, XGBoost-ICA, XGBoost-GWO, XGBoost-SFLA, XGBoost-GA, XGBoost, GPR, SVR, DT, and KNN. Considering the datasets utilized in this research, the feature selection method's sensitivity analysis revealed that, except for the parameter D, all other parameters considered in this study, significantly affect the K_eff. By developing the meta-heuristic methods, the ability of the XGBoost-based methods was significantly improved. Finally, this article recommends using the XGBoost-PSO hybrid model to predict the K_eff. This work’s significance is that it allows geotechnical engineers to accurately estimate the K_eff of different types of concrete. In this way, the high time and cost required for the CSNBD test can be eliminated.

Frost resistance performance assessment of concrete structures under multi-factor coupling in cold offshore environment

The offshore reinforced concrete (RC) structures in cold regions are subjected to complex environments that are affected by pore structure, material properties, ion concentration, heat transfer, heat radiation, stress and saturation. However, the existing methods cannot predict the mechanical behavior of RC structures in different environments with different types of concrete. To solve this problem, the performance degradation prediction method under the coupling degradation of ion concentration-heat transfer-heat radiation-stress-water transfer was proposed for the RC structures by considering the environmental characteristics in combination with the seawater freeze-thaw cycles (FTCs) damage behavior of concrete with different mix proportion at different freezing temperatures. Subsequently, the environment in Jinzhou was employed as an example, and the calculation method was proposed for the mechanical performance degradation. The calculation results of the performance degradation prediction suggest that the evaluation prediction method is capable of effectively analyzing the effect of multiple factors on the performance degradation based on the multi-scale method. The distribution of the FTCs damage appeared heterogeneous after over 20 years, and the FTCs damage was largely concentrated in the tidal-splash area. Moreover, the change of temperature distribution originated from the tide along the surface of the pier within 24 h, and the temperature distribution in the RC pier presented a "U" shape, similar to the strength damage. The strength damage degree on the surface of the atmospheric area was significantly higher than that of the tide-splash area, and the damage distribution in the tidal-splash area was deeper than that in the atmospheric area.