Concrete in reinforced concrete structure (RC) is generally under significant compressive stress load. To guarantee required quality and ductility, various tests have to be conducted to measure the concrete’s compres...Concrete in reinforced concrete structure (RC) is generally under significant compressive stress load. To guarantee required quality and ductility, various tests have to be conducted to measure the concrete’s compressive strength based on ACI (American Concrete Institute) code. Investigations of recent devastating collapses of structures around the world showed that some of the collapses directly resulted from the poor quality of the concrete. The lesson learned from these tragedies is that guaranteeing high quality of concrete is one of the most important factors ensuring the safety of the reinforced concrete structure. In order to ensure high quality of concrete, a new method for analyzing and evaluating the concrete production process is called for. In this paper, the indices of fit and stable degree are proposed as basis to evaluate the fitness and stability of concrete’s compressive strength. These two indices are combined to define and evaluate the quality index of the compressive strength of concrete. Prin-ciples of statistics are used to derive the best estimators of these indices. Based on the outcome of the study, a concrete compres-sive strength quality control chart is proposed as a tool to help the evaluation process. Finally, a new evaluation procedure to assess the quality control capability of the individual concrete manufacturer is also proposed.展开更多
Failure of concrete structures leading to collapse of buildings has initiated various researches on the quality of construction materials. Collapse of buildings resulting to injuries, loss of lives and investments has...Failure of concrete structures leading to collapse of buildings has initiated various researches on the quality of construction materials. Collapse of buildings resulting to injuries, loss of lives and investments has been largely attributed to use of poor quality concrete ingredients. Information on the effect of silt and clay content and organic impurities present in building sand being supplied in Nairobi County and its environs as well as their effect to the compressive strength of concrete was lacking. The objective of this research was to establish level of silt, clay and organic impurities present in building sand and its effect on compressive strength of concrete. This paper presents the findings on the quality of building sand as sourced from eight supply points in Nairobi County and its environs and the effects of these sand impurities to the compressive strength of concrete. 27 sand samples were tested for silt and clay contents and organic impurities in accordance with BS 882 and ASTM C40 respectively after which 13 sand samples with varying level of impurities were selected for casting of concrete cubes. 150 mm × 150 mm × 150 mm concrete cubes were cast using concrete mix of 1:1.5:3:0.57 (cement:sand:coarse aggregates:water) and were tested for compressive strength at the age of 7, 14 and 28 days. The investigation used cement, coarse aggregates (crushed stones) and water of similar characteristics while sand used had varying levels of impurities and particle shapes and texture. The results of the investigations showed that 86.2% of the sand samples tested exceeded the allowable limit of silt and clay content while 77% exceeded the organic content limit. The level of silt and clay content ranged from 42% to 3.3% for while organic impurities ranged from 0.029 to 0.738 photometric ohms for the unwashed sand samples. With regard to compressive strength, 38% of the concrete cubes made from sand with varying sand impurities failed to meet the design strength of 25 Mpa at the age of 28 days. A combined regression equation of with R2 = 0.444 was generated predicting compressive strength varying levels of silt and clay impurities (SCI), and organic impurities (ORG) in sand. This implies that 44% of concrete’s compressive strength is contributed by combination of silt and clay content and organic impurities in sand. Other factors such as particle shapes, texture, workability and mode of sand formation also play a key role in determination of concrete strength. It is concluded that sand found in Nairobi County and its environs contain silt and clay content and organic impurities that exceed the allowable limits and these impurities result in significant reduction in concrete’s compressive strength. It is recommended that the concrete design mix should always consider the strength reduction due to presence of these impurities to ensure that target strength of the resultant concrete is achieved. Formulation of policies governing monitoring of quality of building sand in Kenya and other developed countries is recommended.展开更多
Compressive strength of concrete is a significant factor to assess building structure health and safety.Therefore,various methods have been developed to evaluate the compressive strength of concrete structures.However...Compressive strength of concrete is a significant factor to assess building structure health and safety.Therefore,various methods have been developed to evaluate the compressive strength of concrete structures.However,previous methods have several challenges in costly,time-consuming,and unsafety.To address these drawbacks,this paper proposed a digital vision based concrete compressive strength evaluating model using deep convolutional neural network(DCNN).The proposed model presented an alternative approach to evaluating the concrete strength and contributed to improving efficiency and accuracy.The model was developed with 4,000 digital images and 61,996 images extracted from video recordings collected from concrete samples.The experimental results indicated a root mean square error(RMSE)value of 3.56(MPa),demonstrating a strong feasibility that the proposed model can be utilized to predict the concrete strength with digital images of their surfaces and advantages to overcome the previous limitations.This experiment contributed to provide the basis that could be extended to future research with image analysis technique and artificial neural network in the diagnosis of concrete building structures.展开更多
This paper presents an investigation on strength of cement deep mixing （CDM） mixture. Four typical works of offshore or land-based projects are introduced. With samples from these projects and laboratory tests, stat...This paper presents an investigation on strength of cement deep mixing （CDM） mixture. Four typical works of offshore or land-based projects are introduced. With samples from these projects and laboratory tests, statistical analysis is made on the increment law of the strength of cement-soil mixture with different amount of cement, and strengths under different working conditions are compared. It is found that the amount of cement in the cement-soil mixture is closely related to the unconfined compressive strength of the mixture. At the age of 90 d,the unconfined compressive strength of the cement-soil mixture increased by 0.054 MPa—0.124 MPa with each cement increasing 10 kg/m3 in the cement-soil mixture, averagely increased by 0.085 MPa, while that at the age of 120 d increased by 1100 in comparison.The quality of the cement-soil mixture should be comprehensively evaluated in accordance with the trimmed average of strength, coefficient of variation and rock quality designation （RQD） indicators of sampling ratio.展开更多
基金Project (No. NSC92-2213-e-167-001) supported by the National Science Council, Taiwan, China
文摘Concrete in reinforced concrete structure (RC) is generally under significant compressive stress load. To guarantee required quality and ductility, various tests have to be conducted to measure the concrete’s compressive strength based on ACI (American Concrete Institute) code. Investigations of recent devastating collapses of structures around the world showed that some of the collapses directly resulted from the poor quality of the concrete. The lesson learned from these tragedies is that guaranteeing high quality of concrete is one of the most important factors ensuring the safety of the reinforced concrete structure. In order to ensure high quality of concrete, a new method for analyzing and evaluating the concrete production process is called for. In this paper, the indices of fit and stable degree are proposed as basis to evaluate the fitness and stability of concrete’s compressive strength. These two indices are combined to define and evaluate the quality index of the compressive strength of concrete. Prin-ciples of statistics are used to derive the best estimators of these indices. Based on the outcome of the study, a concrete compres-sive strength quality control chart is proposed as a tool to help the evaluation process. Finally, a new evaluation procedure to assess the quality control capability of the individual concrete manufacturer is also proposed.
文摘Failure of concrete structures leading to collapse of buildings has initiated various researches on the quality of construction materials. Collapse of buildings resulting to injuries, loss of lives and investments has been largely attributed to use of poor quality concrete ingredients. Information on the effect of silt and clay content and organic impurities present in building sand being supplied in Nairobi County and its environs as well as their effect to the compressive strength of concrete was lacking. The objective of this research was to establish level of silt, clay and organic impurities present in building sand and its effect on compressive strength of concrete. This paper presents the findings on the quality of building sand as sourced from eight supply points in Nairobi County and its environs and the effects of these sand impurities to the compressive strength of concrete. 27 sand samples were tested for silt and clay contents and organic impurities in accordance with BS 882 and ASTM C40 respectively after which 13 sand samples with varying level of impurities were selected for casting of concrete cubes. 150 mm × 150 mm × 150 mm concrete cubes were cast using concrete mix of 1:1.5:3:0.57 (cement:sand:coarse aggregates:water) and were tested for compressive strength at the age of 7, 14 and 28 days. The investigation used cement, coarse aggregates (crushed stones) and water of similar characteristics while sand used had varying levels of impurities and particle shapes and texture. The results of the investigations showed that 86.2% of the sand samples tested exceeded the allowable limit of silt and clay content while 77% exceeded the organic content limit. The level of silt and clay content ranged from 42% to 3.3% for while organic impurities ranged from 0.029 to 0.738 photometric ohms for the unwashed sand samples. With regard to compressive strength, 38% of the concrete cubes made from sand with varying sand impurities failed to meet the design strength of 25 Mpa at the age of 28 days. A combined regression equation of with R2 = 0.444 was generated predicting compressive strength varying levels of silt and clay impurities (SCI), and organic impurities (ORG) in sand. This implies that 44% of concrete’s compressive strength is contributed by combination of silt and clay content and organic impurities in sand. Other factors such as particle shapes, texture, workability and mode of sand formation also play a key role in determination of concrete strength. It is concluded that sand found in Nairobi County and its environs contain silt and clay content and organic impurities that exceed the allowable limits and these impurities result in significant reduction in concrete’s compressive strength. It is recommended that the concrete design mix should always consider the strength reduction due to presence of these impurities to ensure that target strength of the resultant concrete is achieved. Formulation of policies governing monitoring of quality of building sand in Kenya and other developed countries is recommended.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(NRF-2018R1A2B6007333).
文摘Compressive strength of concrete is a significant factor to assess building structure health and safety.Therefore,various methods have been developed to evaluate the compressive strength of concrete structures.However,previous methods have several challenges in costly,time-consuming,and unsafety.To address these drawbacks,this paper proposed a digital vision based concrete compressive strength evaluating model using deep convolutional neural network(DCNN).The proposed model presented an alternative approach to evaluating the concrete strength and contributed to improving efficiency and accuracy.The model was developed with 4,000 digital images and 61,996 images extracted from video recordings collected from concrete samples.The experimental results indicated a root mean square error(RMSE)value of 3.56(MPa),demonstrating a strong feasibility that the proposed model can be utilized to predict the concrete strength with digital images of their surfaces and advantages to overcome the previous limitations.This experiment contributed to provide the basis that could be extended to future research with image analysis technique and artificial neural network in the diagnosis of concrete building structures.
文摘This paper presents an investigation on strength of cement deep mixing （CDM） mixture. Four typical works of offshore or land-based projects are introduced. With samples from these projects and laboratory tests, statistical analysis is made on the increment law of the strength of cement-soil mixture with different amount of cement, and strengths under different working conditions are compared. It is found that the amount of cement in the cement-soil mixture is closely related to the unconfined compressive strength of the mixture. At the age of 90 d,the unconfined compressive strength of the cement-soil mixture increased by 0.054 MPa—0.124 MPa with each cement increasing 10 kg/m3 in the cement-soil mixture, averagely increased by 0.085 MPa, while that at the age of 120 d increased by 1100 in comparison.The quality of the cement-soil mixture should be comprehensively evaluated in accordance with the trimmed average of strength, coefficient of variation and rock quality designation （RQD） indicators of sampling ratio.
