Multicolor photometry of the nearby galaxy cluster A119

This paper presents multicolor optical photometry of the nearby galaxy cluster Abell 119 （z = 0.0442） with the Beijing-Arizona-Taiwan-Connecticut system of 15 intermediate bands. Within the BATC field of view of 58＇× 58＇, there are 368 galaxies with known spectroscopic redshifts, including 238 member galaxies （called sample I）. Based on the spectral energy distributions of 1376 galaxies brighter than iBATC ---- 19.5, the photometric redshift technique and the color-magnitude relation of early-type galaxies are applied to select faint member galaxies. As a result, 117 faint galaxies were selected as new member galaxies. Combined with sample I, an enlarged sample （called sample II） of 355 member galaxies is obtained. Spatial distribution and localized velocity structure for two samples demonstrate that A119 is a dynami- cally complex cluster with at least three prominent substructures in the central region within 1 Mpc. A large velocity dispersion for the central clump indicates a merging along the line of sight. No significant evidence for morphology or luminosity segrega- tions is found in either sample. With the PEGASE evolutionary synthesis model, the environmental effect on the properties of star formation is confirmed. Faint galaxies in the low-density region tend to have longer time scales of star formation, smaller mean stellar ages, and lower metallicities in their interstellar medium, which is in agreement with the context of the hierarchical cosmological scenario.

Stifness modeling and analysis of a novel 4-DOF PKM for manufacturing large components

Faster response to orientation varying is one of the outstanding abilities of a parallel kinematic machine（PKM）.It enables such a system to act as a reconfgurable module employed to machine large components effciently.The stiffness formulation and analysis are the beforehand key tasks for its parameters design.A novel PKM with four degrees of freedom（DOFs）is proposed in this paper.The topology behind it is 2PUS-2PRS parallel mechanism.Its semianalytical stiffness model is frstly obtained,where the generalized Jacobian matrix of 2PUS-2PRS is formulated with the help of the screw theory and the stiffness coeffcients of complicated components are estimated by integrating fnite element analysis and numerical ftting.Under the help of the model,it is predicted that the property of system stiffness distributes within the given workspace,which features symmetry about a certain plane and is also verifed by performing fnite element analysis of the virtual prototype.Furthermore,key parameters affecting the system stiffness are identifed through sensitivity analysis.These provide insights for further optimization design of this PKM.

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.