Juyong Zhang

The Tianlai Cylinder Pathfinder Array consists of three adjacent cylindrical reflectors fixed on the ground, each 40 m long and 15 m wide, with the cylinder axis oriented along the North–South (N–S) direction. Dual linear polarization feeds are distributed along the focus line, parallel to the cylinder axis. Measurement of the primary beam profile of these cylindrical reflectors is difficult, as they are too large to be placed in an anechoic chamber. While the beam profile along the East–West (E–W) direction can be measured with the transit observations of bright astronomical radio sources, the beam profile along the N–S direction remains very uncertain. We present a preliminary measurement of the beam profile of the Tianlai cylindrical antenna along both the N–S direction and E–W direction in the frequency range of 700–800 MHz, using a calibrator source carried by an unmanned aerial vehicle (UAV) flying in the far field. The beam profile of the Tianlai cylindrical antenna is determined from the analysis of the auto-correlation signals from the cylinder array correlator, taking into account the emitter antenna beam profile, itself measured with a dipole antenna on the ground. The accuracy of the UAV-based determination of the cylinder beam profiles is validated by comparing the results with the one derived from bright astronomical source transits, and with simulated beams.

The welding and construction processes for H-type thick-plate bridge steel involve complex multi-pass welding processes, which make it difficult to ensure its welding performance. Accordingly, it is crucial to explore the inherent correlations between the welding process parameters and welding quality, and apply them to welding robots, eliminating the instability in manual welding. In order to improve welding quality, the GMAW (gas metal arc welding) welding process parameters are simulated, using the Q345qD bridge steel flat joint model. Four welds with X-shaped grooves are designed to optimize the parameters of the welding current, welding voltage, and welding speed. The optimal welding process parameters are investigated through thermal–elastic–plastic simulation analysis and experimental verification. The results indicate that, when the welding current is set to 230 A, the welding voltage to 32 V, and the welding speed to 0.003 m/s, the maximum deformation of the welded plate is 0.52 mm, with a maximum welding residual stress of 345 MPa. Both the simulation results of multi-pass welding, and the experimental tests meet the welding requirements, as they show no excessive stress or strain. These parameters can be applied to building large steel-frame bridges using welding robots, improving the quality of welded joints.

The welding and construction processes of H-type thick-plate-bridge steel involve complex multi-pass welding processes, which is difficulty to ensure its welding performance. Accordingly, it is crucial to explore the inherent correlation among the welding processes parameters and welding quality, and applied it into the welding robots, eliminating the instability from manual welding. In order to improve the welding quality, the GMAW (Gas Metal Arc Welding) welding process parameters are simulated using the Q345qD bridge steel flat joint model. Four welds with X-shaped grooves are designed to optimize the parameters of welding current, welding voltage, and welding speed. The optimal welding process parameters are investigated through thermal-elastic-plastic simulation analysis and experimental verification. The results indicate that when the welding current is set to 230A, the welding voltage to 32V, and the welding speed to 0.003m/s, the maximum deformation of the welded plate is 0.52mm, with a maximum welding residual stress of 345MPa. Both the simulation results of multi-pass welding and experimental tests meet the welding requirements, as they show no excessive stress or strain. These parameters can be applied into building large steel frame bridges with welding robots, improving the quality of welded joints.

(1) Background: Personalized product customization is an important direction in the development of the chair industry. This paper studies an intelligent design method for the rapid realization of personalized office chair customization; (2) Methods: based on the case-based reasoning (CBR) method, the characteristic attributes of office chair patterns are analyzed, and an attribute model is established. According to office chair data and customer demand, an intelligent design model using multi-layer weighted k-nearest neighbor (K-NN) for chair patterns is developed using the entropy weight method and an analytic hierarchy process. In addition, an example is employed for verification of the K-NN and multi-layer weighted K-NN retrieval models; (3) Results: both models are able to effectively retrieve chair type cases that meet the target requirements from the office chair pattern base; the case matching similarity of the multi-layer weighted K-NN retrieval model was higher, with an average increase of about 3.9%, and the chair pattern case results obtained by setting different customer needs are different, indicating that the case can be selected according to different customer preferences, which is more conducive to personalized product customization design; (4) Conclusions: The multi-layer weighted K-NN model for intelligent chair pattern design proposed in this paper is more conducive to personalized product customization design.

Based on the idea of maximizing variances, a weight optimization method is proposed in this research to improve railway transportation safety evaluation. Firstly, the main evaluation indicators that can reflect the safety of railway transportation are selected as the independent variables. Secondly, in order to avoid the influence of experts’ empowerment on the evaluation results of railway transport safety, fuzzy set theory is introduced to generate the variation range of the weights of each evaluation index, which is used as the constraint of weight optimization model. Then, the weight optimization model for railway transportation safety performance measurement is established based on the principle of maximum variance. The structure of the optimization model shows the characteristics of the quadratic programming model. Therefore, the optimal weight is calculated by using the branch bounded algorithm, which is one of the quadratic programming model solution algorithms. Finally, the empirical analysis of the safety performance measurement for 18 railway bureaus shows that using the optimized index weight for safety performance measurement can not only make full use of prior information but also ensure that 18 railway bureaus can be distinguished to the maximum extent.