The relative stability of chip‐underfill composite materials was modeled as a function of glass filler concentration between 10 and 70 wt.‐%, filler particle size (between 5 and 25 microns), and the curing temperature of the resin (150 vs. 180 °C), yielding different dynamic viscosity profiles. The stability was gauged using a modified sigmoidal chemorheology model for the dynamic viscosity, and incorporating the time‐dependent viscosity into a model for Stokes' law of sedimentation. We also incorporated a hindered sedimentation term, due to filler concentration due to the higher loadings. Several important findings were observed. First, it appears to be the high concentration of filler that is maintaining the stability of these dispersions during cure. Smaller concentrations of the same particles were predicted to have a larger sedimentation velocity leading to stratification in the resin with time. Second, higher cure temperatures led to a shorter period of sedimentation in a pre‐cured state and resulted in less sedimentation, even though there was probably a slightly smaller viscosity in the pre‐cured condition. While these process models adequately describe the physics of the competitive processes of cure and sedimentation, a full picture may be incomplete without a larger determination of how this also affects polymerization shrinkage and residual shear stress upon cure.
Prior rheology results on chip‐underfill epoxy resins have been re‐analyzed by a sigmoidal model that contains three variable physical parameters, including the terminal cured viscosity of the gel, an induction or dwell time and a time factor associated with the speed of conversion as viscosity undergoes large dynamic changes during rapid crosslinking. The analyses were conducted with resins that were originally cured between 150 and 180 °C and show obvious non‐linearity, even on a semi‐log plot of dynamic viscosity. The sigmoidal models more accurately represent a wider range of dynamic viscosity than power‐law‐based rheological models, which are both more common and more generally accepted for practical application. If total flow is the critical design parameter in terms of chip underfill, perhaps these alternative sigmoidal models need to be more thoroughly evaluated to gauge their practical use and validity.
This article is aimed at studying the design and implementation of a football player training management system based on smart images. Based on the analysis of the importance of informatization for scientific football training, system performance requirements and intelligent image detection technology, the football player training management is designed. The overall architecture of the system, and the detailed design of each functional module of the system. It mainly includes football player information management module, football player training plan viewing module, training goal formulation module and training information feedback module. The realization of the training management system relies on intelligent image technology to detect and track athletes. Finally, the performance of the system was tested. The test results show that the expected response time of each module of the system when different numbers of users are accessed is within 3 seconds. The longest actual time is 2.64 s, and the actual shortest time is 1.18 s. It can be seen that the response time of the system meets the demand. At the same time, the system throughput rate meets the requirements of this article, and the user pass rate is also above 95%, indicating that the performance of the football player training management system designed in this article is better.
In order to actively respond to the government’s call to scientifically create campus football culture, combine the characteristics of football sports, and improve people’s understanding of the mental and intellectual functions of football, this article focuses on the impact of football training on physical function and football technology. Based on the understanding of related theories, the experiment on the impact of football training on physical function and football technology was carried out. The experimental results showed that the weight, height, and BMI increased significantly during the period of football training ( P < 0.05 ). The independent sample T test showed that there were no significant differences in height, weight, and BMI between the two groups before and after training; the standing long jump performance of the control group after training showed an upward trend, but the significance level was not statistically significant. Three months later, the time for the experimental team to complete the eight-character dribble test in football training was reduced from 20.51 seconds to 15.57 seconds. The independent sample T test found that there was no significant difference in the physical fitness of the two groups before training and the changes in football skills of the subjects before and after training. Then, the clustering algorithm in the big data was used to analyze the data of the experimental group. The standing long jump has the highest performance; the second category belongs to the third level, and the third category belongs to the second level.
The path planning of mobile robot is to find an optimal collision-free path in time distance or space from the starting point to the target point in a given environment. With the popularization and application of mobile robots, if the efficiency of mobile robots path is not high, the working quality will be seriously affected. How to quickly plan an effective safe path is of great research significance and practical application value. Therefore, we propose a novel A* algorithm based on Bioinspired algorithm for mobile robot path planning. Firstly, the synchronous bidirectional A* algorithm is used to optimize the pheromone of ant colony algorithm, and the transition probability and pheromone update mechanism of ant colony algorithm are improved, so that the global optimization speed of the algorithm is faster and the path length of mobile robot is shortened. Furthermore, the static path is used to initialize the pigeon algorithm. Then, the improved pigeon algorithm is utilized to plan the local path of the mobile robot, and the simulated annealing criterion is introduced to solve the local optimal problem. The logarithmic S-type transfer function is adopted to optimize the step size of the pigeon number, so that the collision with the dynamic obstacles can be better avoided. Finally, a modified B-spline curve is used to smooth and re-plan the path. The simulation results show that the proposed method can realize path planning more effectively in complex dynamic environment.
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