Prediction of the Deformation of Aluminum Alloy Drill Pipes in Thermal Assembly Based on a BP Neural Network

The connection between the steel joint and aluminum alloy pipe is the weak part of the aluminum alloy drill pipe. Practically, the interference connection between the aluminum alloy rod and the steel joint is usually realized by thermal assembly. In this paper, the relationship between the cooling water flow rate, initial heating temperature and the thermal deformation of the steel joint in interference thermal assembly was studied and predicted. Firstly, the temperature data of each measuring point of the steel joint were obtained by a thermal assembly experiment. Based on the theory of thermoelasticity, the analytical solution of the thermal deformation of the steel joint was studied. The temperature function was fitted by the least square method, and the calculated value of radial thermal deformation of the section was finally obtained. Based on the BP neural network algorithm, the thermal deformation of steel joint section was predicted. Besides, a prediction model was established, which was about the relationship between cooling water flow rate, initial heating temperature and interference. The magnitude of interference fit of steel joint was predicted. The magnitude of the interference fit of the steel joint was predicted. A polynomial model, exponential model and Gaussian model were adopted to predict the sectional deformation so as to compare and analyze the predictive performance of a BP neural network, among which the polynomial model was used to predict the magnitude of the interference fit. Through a comparative analysis of the fitting residual (RE) and sum of squares of the error (SSE), it can be known that a BP neural network has good prediction accuracy. The predicted results showed that the error of the prediction model increases with the increase of the heating temperature in the prediction model of the steel node interference and related factors. When the cooling water velocity hit 0.038 m/s, the prediction accuracy was the highest. The prediction error increases with the increase or decrease of the velocity. Especially when the velocity increases, the trend of error increasing became more obvious. The analysis shows that this method has better prediction accuracy.

Optimization of nano coating to reduce the thermal deformation of ball screws

To reduce the thermal deformation of ball screws, the process of nano coating preparation for coating on ball screws to reduce temperature rise and thereby thermal deformation was discussed in this article. Simultaneously, the cooling mechanism was presented. The thermal channels and the relatively even distribution of graphene in the nano coating were observed in scanning electron microscopic images. In terms of the preparation of nano coating, optimization design was carried out to obtain the optimized material ratio and nozzle flow through orthogonal experiment. The influence of design parameters of nano coating on reducing thermal deformation was also discussed. The experimental results show that the maximum temperature rise, thermal deformation, and time to reach thermal balance decreased by 12.5, 69.1, and 46.3%, respectively. The effectiveness of nano coating in reducing thermal deformation was validated experimentally.

Structural material with designed thermal twist for a simple actuation

Materials with desired thermal deformation are very important for various engineering applications. Here, a material with the combination of chiral structure and TiNi shape memory alloy (SMA) sheets that performs a twist during heating is proposed. The thermo-mechanical properties of these materials are experimentally investigated. Inspired by this, a car-like material performing translational and rotational motion is designed, which illustrates the potential applications for the next-generation soft robotic devices. Based on this method, one can design remotely manipulated artificial muscles, nanorobots, revolute pairs, and thermal sensors or actuators in a noncontact fashion.

THERMAL DRILLING OPTIMIZATION IN MULTI HOLE PLATES

The article presents the results of simulation of thermal deformations by the finite element method for round multi-hole plates used in heat exchangers. The heat generated when drilling holes causes thermal deformation of these objects, which contributes to errors in the location of the holes. Obtained results of simulation were compared for different drilling strategies (the studies considered 24 different strategies). It was found that the maximum drilling temperatures according to different strategies may differ by up to 100%. Similar conclusions can be drawn for thermal deformations. The general conclusion that results from the conducted research indicates the need to choose a strategy that ensures the symmetry of the drilled holes in relation to the axis of symmetry of the object. Then, both thermal deformation and maximum temperature are the smallest. The thus identified thermal deformations can form the basis for the correction of the coordinates of the holes on a CNC multi-spindle drilling machine.