Study on Preparation of Construction Waste Paving Brick

2013 ◽  
Vol 712-715 ◽  
pp. 913-916
Author(s):  
Lan Xi Wang ◽  
Guang Hui Pan ◽  
Fu Yong Li ◽  
Hai Ming Wang ◽  
Guo Zhong Li
Keyword(s):  
Compressive Strength ◽  
Mass Fraction ◽  
Raw Material ◽  
Recycled Aggregate ◽  
Analysis Method ◽  
Mass Ratio ◽  
Construction Waste ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Orthogonal Analysis

The construction waste was processed into recycled aggregate to produce paving brick with grade of Cc40. The influences of raw material ratio on the compressive strength of construction waste paving brick were studied with orthogonal analysis method. The results show that the optimum raw material ratio are as follows: mass ratio of recycled aggregate to cement is 3.0, water cement ratio 0.30, compound activator 1.1% (mass fraction of cement, the same below), interfacial agent 0.6%, and water reducing agent of 0.5%. In addition, mechanisms of the admixtures were further studied by SEM and EDS.

Study on Preparation of Solid Concrete Brick with Recycled Aggregate

2013 ◽  
Vol 648 ◽  
pp. 108-111
Author(s):  
Qi Jin Li ◽  
Guo Zhong Li
Keyword(s):  
Compressive Strength ◽  
Mass Fraction ◽  
Recycled Aggregate ◽  
Preparation Process ◽  
Mass Ratio ◽  
Construction Waste ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Optimal Value

The construction waste was processed into recycled aggregate to produce solid construction waste brick with grade of MU20. The preparation process of recycled aggregate and the optimal value of mass ratio of water to cement (water cement ratio) and mass ratio of recycled aggregate to cement was studied. The results shows that when the water cement ratio is 0.86 and the mass ratio of recycled aggregate to cement is 5.5 and the dosage of activator is 0.25% (mass fraction with recycled aggregate), the compressive strength of sample is 22.5MPa and can be satisfied with the requirement of MU20 solid concrete brick.

scholarly journals Synthesis of Geopolymer from Inorganic Construction Waste

2013 ◽  
Vol 30 ◽  
pp. 45-51 ◽  
Author(s):  
Arbind Pathak ◽  
Vinay Kumar Jha
Keyword(s):  
Compressive Strength ◽  
Coal Fly Ash ◽  
Chemical Society ◽  
Raw Material ◽  
Curing Temperature ◽  
Alkali Concentration ◽  
Curing Time ◽  
Mass Ratio ◽  
Construction Waste ◽  
Alumino Silicate

Recently, the demolition of old houses and the construction of new buildings in Kathmandu valley are in the peak which in turn generates a huge amount of construction waste. There are two major types of construction wastes which are burden for disposal namely cement-sand-waste (CSW) and the coal fly ash (CFA). These construction wastes are rich source of alumino-silicate and thus used as raw material for the synthesis of geopolymer in this study. Geopolymers have been synthesized from CSW and CFA using NaOH-KOH and Na2SiO3 as activators. Some parameters like alkali concentration, amount of Na2SiO3 and curing time have been varied in order to improve the quality of geopolymeric product. The geopolymerization process has been carried out using 3-8M KOH/NaOH solutions, Na2SiO3 to CFA and CSW mass ratio of 0.25-2.00 and curing time variation from 5-28 days. The curing temperature was fixed at 40ºC in all the cases. 6M NaOH and 7M KOH solutions were found appropriate alkali concentrations while the ratio of sodium silicate to CSW and CFA of 0.5 and 1.75 respectively were found suitable mass ratio for the process of geopolymer synthesis. The maximum compressive strength of only 7.3 MPa after 15 days curing time with CSW raw material was achieved while with CFA, the compressive strength was found to be 41.9 MPa with increasing the curing time up to 28 days.DOI: http://dx.doi.org/10.3126/jncs.v30i0.9334Journal of Nepal Chemical Society Vol. 30, 2012 Page:  45-51 Uploaded date: 12/16/2013    

Research on Simulation Test of Coal Similar Material

2013 ◽  
Vol 850-851 ◽  
pp. 847-850 ◽  
Author(s):  
Lin Chao Dai
Keyword(s):  
Compressive Strength ◽  
Raw Materials ◽  
Similarity Theory ◽  
Design Method ◽  
Uniform Design ◽  
Physical And Mechanical Properties ◽  
Raw Material ◽  
Similar Material ◽  
Cement Ratio ◽  
Water Cement Ratio

In order to study the coal and gas outburst similar simulation experiment, coal similar material was made up based on the similarity theory. Based on the previous similar material study, the cement, sand, water, activated carbon and coal powder was selected as the raw material of similar material. Meanwhile similar material matching program with 5 factors and 6 levels was designed by using Uniform Design Method. And the physical and mechanical properties of the similar material compressive strength was measured under different proportions circumstances. The relationship between similar material and the raw materials was analyzed. The results show that choosing different materials can compound different similar materials with different requirements. And the water-cement ratio plays a decisive influence on the compressive strength of similar material. The compressive strength of similar material decreases linearly when the water-cement ratio increases.

Research on the Performance of Plaster Material by Chemical Foaming Method

2013 ◽  
Vol 830 ◽  
pp. 435-438
Author(s):  
Hong Xia Wang ◽  
Bo Liu ◽  
Kuang Ping Yuan ◽  
Wu Biao Duan ◽  
Fei Hua Yang ◽  
...  
Keyword(s):  
Compressive Strength ◽  
Flexural Strength ◽  
Water Temperature ◽  
Chemical Reaction ◽  
Raw Material ◽  
Foaming Agent ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Chemical Foaming

The paper introduces a kind of foaming plaster with main raw material of α- gypsum, which is produced by utilizing the chemical reaction principles H2O2 was decomposed. Meanwhile，study the changes of density，flexural strength and compressive strength of plaster material performance with the additives in different ratio. The result showed that water-cement ratio, H2O2 foaming agent and water temperature all affect the performance of the foaming plaster.

Effect of Admixed Recycled Aggregate on Properties of Recycled Concrete

2012 ◽  
Vol 174-177 ◽  
pp. 743-746
Author(s):  
Ya Jun Zhao ◽  
Ying Gao ◽  
Li Li He
Keyword(s):  
Compressive Strength ◽  
Design Method ◽  
Orthogonal Design ◽  
Plain Concrete ◽  
Recycled Concrete ◽  
Recycled Aggregate ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Influence Of Water ◽  
The Impact

The mixture proportion of recycled concrete was discussed by orthogonal design method. The influence of water-cement ratio, recycled aggregate quantity on workability, cube compressive strength of recycled concrete was analyzed. The experimental results indicated that，Recycled concrete mix proportion design should consider the impact of the water absorption of recycled aggregate. Unit water amount of recycled concrete should be plain concrete unit water consumption and recycled aggregate additional amount of water. Sand ratio should increase in the corresponding ordinary aggregate concrete sand ratio on the basis of 1 to 3 percent. When the water-cement ratio is 0.36 and construction waste content of 40% slag content of 20%, 28d compressive strength of concrete is 48.1MPa, slightly higher than the reference concrete (48.0MPa).

scholarly journals Study on the Permeability of Recycled Aggregate Pervious Concrete with Fibers

Materials ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 321 ◽  
Author(s):  
Haitang Zhu ◽  
Chengcheng Wen ◽  
Zhanqiao Wang ◽  
Lan Li
Keyword(s):  
Compressive Strength ◽  
Permeability Coefficient ◽  
Polypropylene Fiber ◽  
Volumetric Analysis ◽  
Pervious Concrete ◽  
Recycled Aggregate ◽  
Fiber Types ◽  
Cross Sectional ◽  
Cement Ratio ◽  
Water Cement Ratio

Pervious concrete is considered to be porous concrete because of its pore structure and excellent permeability. In general, larger porosity will increase the permeability coefficient, but will significantly decrease the compressive strength. The effects of water-cement ratio, fiber types, and fiber content on the permeability coefficient, porosity, compressive strength, and flexural strength were investigated. The pore tortuosity of the pervious concrete was determined by volumetric analysis and two-dimensional cross-sectional image analysis. The concept and calculation method of porosity tortuosity were further proposed. Results show that the permeability coefficient of the pervious concrete is the most suitable with a water-cement ratio of 0.30; the water permeability of the pervious concrete is influenced by fiber diameter. The permeability coefficient of pervious concrete with polypropylene thick fiber (PPTF) is greater than that with copper coated steel fiber (CCF) and the polypropylene fiber (PPF). The permeability coefficient is related to tortuosity and porosity, but when porosity is the same, the permeability coefficient may be different. Finally, general relations between the permeability coefficient and porosity tortuosity are constructed.

scholarly journals Experimental and Statistical Evaluation of the Interaction Effect of Recycled Aggregate and Water/Cement Ratio on Concrete Compressive Strength

2021 ◽  
Vol 03 (03) ◽  
pp. 1-1
Author(s):  
Mônica Batista Leite ◽  
◽  
Paulo Roberto Lopes Lima ◽  
Keyword(s):  
Compressive Strength ◽  
Interaction Model ◽  
Construction And Demolition Waste ◽  
Recycled Aggregate ◽  
Recycled Aggregates ◽  
Demolition Waste ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Aggregate Content ◽  
Factorial Design Experiment

The production of concrete using recycled aggregates, obtained from the processing of construction and demolition waste, is extensively practiced worldwide. However, the effect of simultaneous adding fine recycled aggregate and the recycled coarse aggregate on the mechanical properties of concrete is still unfamiliar. This work aims to evaluate the influence of the water/cement ratio (WC Ratio), the fine recycled aggregate content (%FRA), the coarse recycled aggregate content (%CRA), as well as the interaction between factors on the compressive strength of concrete. Accordingly, a factorial design experiment was developed, analyzing these factors at three levels, which resulted in the production of 27 mixtures. These levels were: WC Ratio (0.50; 0.65 and 0.80); %FRA (0; 50 and 100) and %CRA (0; 50 and 100). Statistical analysis was performed on the response surface, and an enhanced approximation of the two-way interaction model was identified. The results indicate that the substitution of the natural aggregate with recycled aggregate shows a significant influence on the compressive strength, and its effect depends on the water-cement ratio. Furthermore, considering the interaction between the content and type of aggregate and the water-cement ratio is fundamental for obtaining the proper mix design of this type of concrete.

Effect of nanocomposite slurry on strength development of fully recycled aggregate concrete

2021 ◽  
pp. 136943322199248
Author(s):  
Tao Meng ◽  
Song-lin Yu ◽  
Huadong Wei ◽  
Sheng Zhu
Keyword(s):  
Compressive Strength ◽  
Recycled Concrete ◽  
Recycled Aggregate Concrete ◽  
Recycled Aggregate ◽  
Strength Development ◽  
Aggregate Concrete ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Natural Aggregate ◽  
Enhancement Method

Recycled concrete has been widely used in construction because of the gradual shortage of natural aggregate resources and the large amount of construction waste. In this study, concrete with 100% recycled aggregate was prepared, and its properties, microtopography, and potential enhancement method were investigated. The results indicated that the mechanical properties of the fully recycled aggregate concrete (FRC) were significantly inferior to the natural aggregate concrete. The compressive strength of the FRC with a water-cement ratio of 0.6 was noticeably improved by spraying a nanocomposite slurry on recycled aggregate, whereas this had little influence when the water-cement ratio was 0.3. The compressive strength of the FRC with a water-cement ratio of 0.3 could be improved by mixing with strengthening materials. The best improvement in the compressive strength of the concrete was observed at 28 days because a membrane covered the surface of the aggregate, creating a bond between the aggregate and cement, filling the pores between them, and compacting the concrete. This paper reports a prospective method for improving the properties of FRC, which will promote the application of recycled aggregate in industry.

scholarly journals Use of Nondestructive Testing of Ultrasound and Artificial Neural Networks to Estimate Compressive Strength of Concrete

Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 44
Author(s):  
Fernando A. N. Silva ◽  
João M. P. Q. Delgado ◽  
Rosely S. Cavalcanti ◽  
António C. Azevedo ◽  
Ana S. Guimarães ◽  
...  
Keyword(s):  
Neural Networks ◽  
Compressive Strength ◽  
Artificial Neural Networks ◽  
Cross Sections ◽  
Influential Factors ◽  
Average Error ◽  
Ann Model ◽  
Cement Ratio ◽  
Water Cement Ratio ◽  
Artificial Neural

The work presents the results of an experimental campaign carried out on concrete elements in order to investigate the potential of using artificial neural networks (ANNs) to estimate the compressive strength based on relevant parameters, such as the water–cement ratio, aggregate–cement ratio, age of testing, and percentage cement/metakaolin ratios (5% and 10%). We prepared 162 cylindrical concrete specimens with dimensions of 10 cm in diameter and 20 cm in height and 27 prismatic specimens with cross sections measuring 25 and 50 cm in length, with 9 different concrete mixture proportions. A longitudinal transducer with a frequency of 54 kHz was used to measure the ultrasonic velocities. An ANN model was developed, different ANN configurations were tested and compared to identify the best ANN model. Using this model, it was possible to assess the contribution of each input variable to the compressive strength of the tested concretes. The results indicate an excellent performance of the ANN model developed to predict compressive strength from the input parameters studied, with an average error less than 5%. Together, the water–cement ratio and the percentage of metakaolin were shown to be the most influential factors for the compressive strength value predicted by the developed ANN model.

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