Compressive Strength of Basic Magnesium Sulfate Cement Coral Aggregate Concrete(MCAC)on Non-Destructive Testing

Basic magnesium sulfate cement coral aggregate concrete(MCAC)is a new type of concrete consisting of basic magnesium sulfate cement,coarse coral aggregate,coral reef sand and seawater.The rebound hammer(RH),the ultrasonic pulse velocity(UPV)and the compressive strength(fcu)tests of 14 sets of cube specimens of the MCAC after 28 d of aging were conducted.The impact of the content and length of sisal fiber on the relationship between the fcu-RH and the fcu-UPV was determined.A mathematical model was established to predict the strength of the MCAC using the UPV,RH,and comprehensive UPV/RH methods and to obtain the curves of test strength.The applicability of the test strength curves of ordinary portland concrete(OPC),light-weight aggregate concrete(LAC),and coral aggregate concrete(CAC)to MCAC was assessed.The results showed that the test strength curves of OPC,LAC and CAC were inappropriate to determine the strength of MCAC using non-destructive method.The relative standard error of the curves of test strength of the RH method and the comprehensive method met the specifications,whereas that of the UPV method did not.

Experimental study on the shear behavior of the interface between cushion materials and the concrete raft

Cushion is a layer of granular materials between the raft and the ground. The shear behavior of the interface between the cushion and the raft may influence the seismic performance of the superstructure. In order to quantify such influences, horizontal shear tests on the interfaces between different cushion materials and concrete raft under monotonic and cyclic loading were carried out. The vertical pressure P_v, material type and cushion thickness h_c were taken as variables. Conclusions include： 1） under monotonic loading, P_v is the most significant factor; the shear resistance P_（hmax） increases as P_v increases, but the normalized factor of resistance μ_n has an opposite tendency; 2） for the materials used in this study, μ_n varies from 0.40 to 0.70, the interface friction angle δ_s varies from 20° to 35°, while u_（max） varies from 3 mm to 15 mm; 3） under cyclic loading, the interface behavior can be abstracted as a ＂three-segment＂ back-bone curve, the main parameters include μ_n, the displacement u_1 and stiffness K_1 of the elastic stage, the displacement u_2 and stiffness K_2 of the plastic stage; 4） by observation and statistical analysis, the significance of different factors, together with values of K_1, K_2 and μ_n have been obtained.

Automated pavement horizontal curve measurement methods based on inertial measurement unit and 3D profiling data

Pavement horizontal curve is designed to serve as a transition between straight segments, and its presence may cause a series of driving-related safety issues to motorists and drivers. As is recognized that traditional methods for curve geometry investigation are time consuming, labor intensive, and inaccurate, this study attempts to develop a method that can automatically conduct horizontal curve identification and measurement at network level. The digital highway data vehicle （DHDV） was utilized for data collection, in which three Euler angles, driving speed, and acceleration of survey vehicle were measured with an inertial measurement unit （IMU）. The 3D profiling data used for cross slope calibration was obtained with PaveVision3D Ultra technology at 1 mm resolution. In this study, the curve identification was based on the variation of heading angle, and the curve radius was calculated with ki- nematic method, geometry method, and lateral acceleration method. In order to verify the accuracy of the three methods, the analysis of variance （ANOVA） test was applied by using the control variable of curve radius measured by field test. Based on the measured curve radius, a curve safety analysis model was used to predict the crash rates and safe driving speeds at horizontal curves. Finally, a case study on 4.35 km road segment demonstrated that the proposed method could efficiently conduct network level analysis.