The strength curves of lightweight aggregate concrete （LWAC） were tested based on detecting LWAC with density of 1 400-1 900 kg/m3 and LWAC with strength grade of LC15-LC50 by rebound method and ultrasonic-rebound c...The strength curves of lightweight aggregate concrete （LWAC） were tested based on detecting LWAC with density of 1 400-1 900 kg/m3 and LWAC with strength grade of LC15-LC50 by rebound method and ultrasonic-rebound combined method.The results show that the common measured strength curves tested by above two methods can not satisfy the required accuracy of LWAC strength test.In addition,specified compressive strength curves of testing LWAC by rebound method and ultrasonic-rebound combined method are obtained,respectively.展开更多
The Sonreb and Core (SRC) combined method is proposed to assess the concrete compression strength of mass concrete structures.Artificial neural network is employed together with the SRC combined method to obtain the o...The Sonreb and Core (SRC) combined method is proposed to assess the concrete compression strength of mass concrete structures.Artificial neural network is employed together with the SRC combined method to obtain the optimal core number.The artificial neural network is trained based on data from different testing methods.The procedure of using artificial neural network to assess the concrete strength is described.It proves that the SRC combined method is superior in many aspects and artificial the presented neural network has a high efficiency and reliability.The combined method using artificial intelligence is promising in the strength assessment of mass concrete structures such as the dam,the anchor of the suspension bridge,etc.展开更多
Ultrasonic pulse velocity (UPV) and rebound hammer (RH) tests are often used for assessing the quality of concrete and estimation of its compressive strength. Several parameters influence this property of concrete as ...Ultrasonic pulse velocity (UPV) and rebound hammer (RH) tests are often used for assessing the quality of concrete and estimation of its compressive strength. Several parameters influence this property of concrete as the type and size of aggregates, cement content, the implementation of concrete, etc. To account for these factors, both of the two tests are combined and their measurements are calibrated with the results of mechanical tests on cylindrical specimens cast on site and on cores taken from the existing structure in work progress at the new-city Massinissa El-Khroub Constantine in Algeria. In this study;the two tests cited above have been used to determine the concrete quality by applying regression analysis models between compressive strength of in situ concrete on existing structure and the nondestructive tests values, the combined method is used, equations are derived using statistical analysis (simple and multiple regression) to estimate compressive strength of concrete on site and the reliability of the technique for prediction of the strength is discussed for this case study.展开更多
文摘The strength curves of lightweight aggregate concrete （LWAC） were tested based on detecting LWAC with density of 1 400-1 900 kg/m3 and LWAC with strength grade of LC15-LC50 by rebound method and ultrasonic-rebound combined method.The results show that the common measured strength curves tested by above two methods can not satisfy the required accuracy of LWAC strength test.In addition,specified compressive strength curves of testing LWAC by rebound method and ultrasonic-rebound combined method are obtained,respectively.
基金Sponsored by the Priority Academic Program Development Foundation of Jiangsu Higher Education Institute(Grant No. CE01-3)the NSFC for Outstanding Youth Fund (Grant No. 50725828),the NSFC for Young Scholars (Grant No. 50908046)+1 种基金the Ph. D. Programs Foundation of Ministry of Education of China (Grant No. 200802861012)the Basic Scientific & Research Fund of Southeast University (Grant No. Seucx201106)
文摘The Sonreb and Core (SRC) combined method is proposed to assess the concrete compression strength of mass concrete structures.Artificial neural network is employed together with the SRC combined method to obtain the optimal core number.The artificial neural network is trained based on data from different testing methods.The procedure of using artificial neural network to assess the concrete strength is described.It proves that the SRC combined method is superior in many aspects and artificial the presented neural network has a high efficiency and reliability.The combined method using artificial intelligence is promising in the strength assessment of mass concrete structures such as the dam,the anchor of the suspension bridge,etc.
文摘Ultrasonic pulse velocity (UPV) and rebound hammer (RH) tests are often used for assessing the quality of concrete and estimation of its compressive strength. Several parameters influence this property of concrete as the type and size of aggregates, cement content, the implementation of concrete, etc. To account for these factors, both of the two tests are combined and their measurements are calibrated with the results of mechanical tests on cylindrical specimens cast on site and on cores taken from the existing structure in work progress at the new-city Massinissa El-Khroub Constantine in Algeria. In this study;the two tests cited above have been used to determine the concrete quality by applying regression analysis models between compressive strength of in situ concrete on existing structure and the nondestructive tests values, the combined method is used, equations are derived using statistical analysis (simple and multiple regression) to estimate compressive strength of concrete on site and the reliability of the technique for prediction of the strength is discussed for this case study.
