scholarly journals Mechanical Performance Prediction for Sustainable High-Strength Concrete Using Bio-Inspired Neural Network

Buildings ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 65
Author(s):  
Junbo Sun ◽  
Jiaqing Wang ◽  
Zhaoyue Zhu ◽  
Rui He ◽  
Cheng Peng ◽  
...  
Keyword(s):  
Neural Network ◽  
High Strength Concrete ◽  
Prediction Accuracy ◽  
Mechanical Performance ◽  
Back Propagation ◽  
High Strength ◽  
Mix Design ◽  
Strength Concrete ◽  
Laboratory Test Results ◽  
Bpnn Model

High-strength concrete (HSC) is a functional material possessing superior mechanical performance and considerable durability, which has been widely used in long-span bridges and high-rise buildings. Unconfined compressive strength (UCS) is one of the most crucial parameters for evaluating HSC performance. Previously, the mix design of HSC is based on the laboratory test results which is time and money consuming. Nowadays, the UCS can be predicted based on the existing database to guide the mix design with the development of machine learning (ML) such as back-propagation neural network (BPNN). However, the BPNN’s hyperparameters (the number of hidden layers, the number of neurons in each layer), which is commonly adjusted by the traditional trial and error method, usually influence the prediction accuracy. Therefore, in this study, BPNN is utilised to predict the UCS of HSC with the hyperparameters tuned by a bio-inspired beetle antennae search (BAS) algorithm. The database is established based on the results of 324 HSC samples from previous literature. The established BAS-BPNN model possesses excellent prediction reliability and accuracy as shown in the high correlation coefficient (R = 0.9893) and low Root-mean-square error (RMSE = 1.5158 MPa). By introducing the BAS algorithm, the prediction process can be totally automatical since the optimal hyperparameters of BPNN are obtained automatically. The established BPNN model has the benefit of being applied in practice to support the HSC mix design. In addition, sensitivity analysis is conducted to investigate the significance of input variables. Cement content is proved to influence the UCS most significantly while superplasticizer content has the least significance. However, owing to the dataset limitation and limited performance of ML models which affect the UCS prediction accuracy, further data collection and model update must be implemented.

Application of Inorganic Cohesive Glue in Concrete Repair

2010 ◽  
Vol 168-170 ◽  
pp. 945-948
Author(s):  
Shu Hua Liu
Keyword(s):  
High Strength Concrete ◽  
Mechanical Performance ◽  
High Strength ◽  
Concrete Repair ◽  
Repair Work ◽  
Strength Concrete ◽  
Original Specimen ◽  
Better Than

The properties of inorganic cohesive glue and its appliance to repairing ordinary and high strength concrete were studied in this paper. Inorganic cohesive glue not only has high strength, but also has equivalent coefficient of expansion with that of concrete and steel. The mechanical performance of inorganic cohesive glue is better than that of concrete, and other performances are similar to those of concrete. In the concrete repair work, it can mend the ruinate concrete well, and the strength of the repaired concrete is as high as or higher than that of original specimen.

scholarly journals Evaluation and Mix Design for Ternary Blended High Strength Concrete

2013 ◽  
Vol 51 ◽  
pp. 65-74 ◽  
Author(s):  
R. Rathan Raj ◽  
E.B. Perumal Pillai ◽  
A.R. Santhakumar
Keyword(s):  
High Strength Concrete ◽  
High Strength ◽  
Mix Design ◽  
Strength Concrete

scholarly journals Effect of Carbon Pricing on Optimal Mix Design of Sustainable High-Strength Concrete

2019 ◽  
Vol 11 (20) ◽  
pp. 5827 ◽  
Author(s):  
Xiao-Yong Wang
Keyword(s):  
Co2 Emissions ◽  
High Strength Concrete ◽  
Cement Content ◽  
Gene Expression Programming ◽  
High Strength ◽  
Material Design ◽  
Mix Design ◽  
Carbon Pricing ◽  
Strength Concrete ◽  
Material Cost

Material cost and CO2 emissions are among the vital issues related to the sustainability of high-strength concrete. This research proposes a calculation procedure for the mix design of silica fume-blended high-strength concrete with an optimal total cost considering various carbon pricings. First, the material cost and CO2 emission cost are determined using concrete mixture and unit prices. Gene expression programming (GEP) is used to evaluate concrete mechanical and workability properties. Second, a genetic algorithm (GA) is used to search the optimal mixture, considering various constraints, such as design compressive strength constraint, design workability constraint, range constraints, ratio constraints, and concrete volume constraint. The optimization objective of the GA is the sum of the material cost and the cost of CO2 emissions. Third, illustrative examples are shown for designing various kinds of concrete. Five strength levels (from 95 to 115 MPa with steps of 5 MPa) and four carbon pricings (normal carbon pricing, zero carbon pricing, five-fold carbon pricings, and ten-fold carbon pricings) are considered. A total of 20 optimal mixtures are calculated. The optimal mixtures were found the same for the cases of normal CO2 pricing and zero CO2 pricing. Optimal mixtures with higher strengths are more sensitive to variation in carbon pricing. For five-fold CO2 pricing, the cement content of mixtures with higher strengths (105, 110, and 115 MPa) are lower than those of normal CO2 pricing. As the CO2 pricing increases from five-fold to ten-fold, for mixtures with a strength of 110 MPa, the cement content becomes lower. Summarily, the proposed method can be applied to the material design of sustainable high-strength concrete with low material cost and CO2 emissions.

Experimental Research on Physical and Mechanical Properties of Steel Fiber High-Strength Concrete

2010 ◽  
Vol 168-170 ◽  
pp. 1061-1064 ◽  
Author(s):  
Yu Dong Wang ◽  
Xiao Chun Fan
Keyword(s):  
High Strength Concrete ◽  
Bending Strength ◽  
Steel Fiber ◽  
Mechanical Performance ◽  
Physical And Mechanical Properties ◽  
Drying Shrinkage ◽  
High Strength ◽  
Engineering Practice ◽  
Strength Concrete ◽  
Mix Proportion

Based on experiment, the mix proportion matching with the design and construction requirements is obtained. It meets with the requirement of pump structure on the basis of meeting the strength requirement. On this basis, the basic physical and mechanical performance is studied and the conclusion is that steel fiber high-strength concrete has excellent resistance to splitting, bending and drying shrinkage. The splitting strength and bending strength of steel fiber high-strength concrete named CF60-2 is respectively 38.7% and 56.8% higher than that of plane concrete named C60. The drying shrinkage rate of CF60-2 is 45.5% lower than that of C60 in three days. The results have an important guiding significance to steel fiber high-strength concrete in theoretical and engineering practice.

Predicting the compressive strength and slump of high strength concrete using neural network

2006 ◽  
Vol 20 (9) ◽  
pp. 769-775 ◽  
Author(s):  
Ahmet Öztaş ◽  
Murat Pala ◽  
Erdogˇan Özbay ◽  
Erdogˇan Kanca ◽  
Naci Çagˇlar ◽  
...  
Keyword(s):  
Neural Network ◽  
Compressive Strength ◽  
High Strength Concrete ◽  
High Strength ◽  
Strength Concrete

scholarly journals Study on Mix Proportion Optimization of C50 High Strength Concrete

2021 ◽  
Vol 2101 (1) ◽  
pp. 012068
Author(s):  
Yunhua Wang ◽  
Fanji Cai ◽  
Qiong Wang ◽  
Dongfeng Li ◽  
Pan Guo
Keyword(s):  
Fly Ash ◽  
High Strength Concrete ◽  
Mechanical Performance ◽  
High Strength ◽  
Economic Costs ◽  
Engineering Technology ◽  
Strength Concrete ◽  
Mix Proportion ◽  
C 50 ◽  
Selection Of

Abstract With the progress of engineering technology, C50 high-strength coagulation came into being for the needs of actual engineering. This research mainly focuses on the selection of cement varieties and admixtures of C 50 high-strength concrete, so as to realize the optimization research of the mix ratio of C 50 high-strength concrete. The results show that ordinary P.O 42.5 and fly ash admixture can increase the mechanical performance of concrete. However, the concrete compressive strength with the mixed admixture of fly ash and mineral powder is even lower than that without any admixture. On the premise of meeting actual engineering needs, the optimization of the mix ratio of high-strength concrete can not only achieve sustainable development, but also save investment in project economic costs.

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