CFRP Shear Strengthening of Reinforced-Concrete T-Beams with Corroded Shear Links
- Qin, Shunde, Dirar, Samir, Yang, Jian, Chan, Andrew, Elshafie, Mohammed
- Authors: Qin, Shunde , Dirar, Samir , Yang, Jian , Chan, Andrew , Elshafie, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Composites for Construction Vol. 19, no. 5 (2015), p.
- Full Text:
- Reviewed:
- Description: This paper investigates the structural behavior of uncorroded as well as corroded RC T-beams strengthened in shear with either externally bonded (EB) carbon fiber-reinforced polymer (CFRP) sheets or embedded CFRP rods. Nine tests were carried out on RC T-beams having an effective depth of 295 mm and a shear span to effective depth ratio of 3.05. The investigated parameters are the shear link corrosion level (uncorroded, 7% corroded, or 12% corroded) and type of CFRP strengthening system (EB CFRP sheets or embedded CFRP rods). The unstrengthened beams with shear link corrosion levels of 7 and 12% had shear strengths that were 11 and 14%, respectively, less than the shear strength of the uncorroded unstrengthened beam. Both the embedded CFRP rods and EB CFRP sheets were effective in enhancing the shear strength of tested beams but the effectiveness of both strengthening systems decreased with increasing shear link corrosion level. The shear strength enhancement provided by the embedded CFRP rods and EB CFRP sheets decreased from 19 and 15%, respectively, to 12 and 11%, respectively, with an increase in shear link corrosion level from 7 to 12%. Corrosion of the shear links did not have a significant effect on the beam stiffness. Premature debonding limited the effectiveness of the EB CFRP sheets whereas the embedded CFRP rods did not exhibit signs of debonding and therefore showed higher effectiveness.
- Authors: Qin, Shunde , Dirar, Samir , Yang, Jian , Chan, Andrew , Elshafie, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Composites for Construction Vol. 19, no. 5 (2015), p.
- Full Text:
- Reviewed:
- Description: This paper investigates the structural behavior of uncorroded as well as corroded RC T-beams strengthened in shear with either externally bonded (EB) carbon fiber-reinforced polymer (CFRP) sheets or embedded CFRP rods. Nine tests were carried out on RC T-beams having an effective depth of 295 mm and a shear span to effective depth ratio of 3.05. The investigated parameters are the shear link corrosion level (uncorroded, 7% corroded, or 12% corroded) and type of CFRP strengthening system (EB CFRP sheets or embedded CFRP rods). The unstrengthened beams with shear link corrosion levels of 7 and 12% had shear strengths that were 11 and 14%, respectively, less than the shear strength of the uncorroded unstrengthened beam. Both the embedded CFRP rods and EB CFRP sheets were effective in enhancing the shear strength of tested beams but the effectiveness of both strengthening systems decreased with increasing shear link corrosion level. The shear strength enhancement provided by the embedded CFRP rods and EB CFRP sheets decreased from 19 and 15%, respectively, to 12 and 11%, respectively, with an increase in shear link corrosion level from 7 to 12%. Corrosion of the shear links did not have a significant effect on the beam stiffness. Premature debonding limited the effectiveness of the EB CFRP sheets whereas the embedded CFRP rods did not exhibit signs of debonding and therefore showed higher effectiveness.
Effects of a proper feature selection on prediction and optimization of drilling rate using intelligent techniques
- Liao, Xiufeng, Khandelwal, Manoj, Yang, Haiqing, Koopialipoor, Mohammadreza, Murlidhar, Bhatawdekar
- Authors: Liao, Xiufeng , Khandelwal, Manoj , Yang, Haiqing , Koopialipoor, Mohammadreza , Murlidhar, Bhatawdekar
- Date: 2020
- Type: Text , Journal article
- Relation: Engineering with Computers Vol. 36, no. 2 (Apr 2020), p. 499-510
- Full Text:
- Reviewed:
- Description: One of the important factors during drilling times is the rate of penetration (ROP), which is controlled based on different variables. Factors affecting different drillings are of paramount importance. In the current research, an attempt was made to better recognize drilling parameters and optimize them based on an optimization algorithm. For this purpose, 618 data sets, including RPM, flushing media, and compressive strength parameters, were measured and collected. After an initial investigation, the compressive strength feature of samples, which is an important parameter from the rocks, was used as a proper criterion for classification. Then using intelligent systems, three different levels of the rock strength and all data were modeled. The results showed that systems which were classified based on compressive strength showed a better performance for ROP assessment due to the proximity of features. Therefore, these three levels were used for classification. A new artificial bee colony algorithm was used to solve this problem. Optimizations were applied to the selected models under different optimization conditions, and optimal states were determined. As determining drilling machine parameters is important, these parameters were determined based on optimal conditions. The obtained results showed that this intelligent system can well improve drilling conditions and increase the ROP value for three strength levels of the rocks. This modeling system can be used in different drilling operations.
- Authors: Liao, Xiufeng , Khandelwal, Manoj , Yang, Haiqing , Koopialipoor, Mohammadreza , Murlidhar, Bhatawdekar
- Date: 2020
- Type: Text , Journal article
- Relation: Engineering with Computers Vol. 36, no. 2 (Apr 2020), p. 499-510
- Full Text:
- Reviewed:
- Description: One of the important factors during drilling times is the rate of penetration (ROP), which is controlled based on different variables. Factors affecting different drillings are of paramount importance. In the current research, an attempt was made to better recognize drilling parameters and optimize them based on an optimization algorithm. For this purpose, 618 data sets, including RPM, flushing media, and compressive strength parameters, were measured and collected. After an initial investigation, the compressive strength feature of samples, which is an important parameter from the rocks, was used as a proper criterion for classification. Then using intelligent systems, three different levels of the rock strength and all data were modeled. The results showed that systems which were classified based on compressive strength showed a better performance for ROP assessment due to the proximity of features. Therefore, these three levels were used for classification. A new artificial bee colony algorithm was used to solve this problem. Optimizations were applied to the selected models under different optimization conditions, and optimal states were determined. As determining drilling machine parameters is important, these parameters were determined based on optimal conditions. The obtained results showed that this intelligent system can well improve drilling conditions and increase the ROP value for three strength levels of the rocks. This modeling system can be used in different drilling operations.
- «
- ‹
- 1
- ›
- »