Blade thickness is an essential parameter of the impeller, which has significant effects on the pump performance. The plastic pump generally adopts thick blade due to low strength of plastic. The effects of blade thickness on the internal flow and performance of a plastic centrifugal pump were discussed based on the numerical methods. Two kinds of blade profile, the constant thickness blade (CTB) and the variable thickness blade (VTB), were investigated. The results indicated that, for the CTB, when the blade thickness was less than 6 mm, the pump performance did not change significantly. When the blade thickness exceeded 6 mm, the pump head and efficiency decreased rapidly. The pump head and efficiency of CTB 10 decreased by 42.2% and 30% compared with CTB 4, respectively. For the VTB, with blade thickness in a certain range (6 mm–14 mm), the pump performance changed slightly with the increased of trailing edge thickness. The minimum blade thickness of the plastic centrifugal pump should be 4 mm based on the finite element analysis. A variable thickness blade (VTB 4-8-4) with the maximum thickness located at 60% chord length was proposed to improve the pump performance, and its efficiency was 1.67% higher than that of the CTB 4 impeller.

In the present study, Moldflow® software is applied to simulate the injection molding of automobile instrument light guide bracket and optimize the injection gate position. In this regard, Taguchi orthogonal experimental design is adopted, and five processing parameters, the mold temperature, melt temperature, cooling time, packing pressure, and packing time, are considered as the test factors. Moreover, volume shrinkage and warping amount are considered as quality evaluation indices. Then range analysis and variance analysis are carried out to obtain the optimal combination of molding parameters with the volume shrinkage rate and the warpage amount. The grey correlation analysis was used to analyze the test results and obtain the optimal combination of volume shrinkage rate and amount of warping. Based on the performed simulations, it is found that the maximum volume shrinkage rate and the maximum amount of warping in the optimal design are 6.753% and 1.999 mm, respectively. According to the optimal process parameters, the injection molding of the automobile instrument light guide bracket meets the quality requirements.

In order to obtain the optimum technological parameters of fender forming, the finite element analysis software DYNAFORM is used to simulate the drawing process of fender in this paper. The orthogonal test is designed and completed. On the basis of the orthogonal test, Taguchi method is used to design the orthogonal inner table, and the SNR of each factor at each level is calculated. The results of Taguchi method are analyzed with variance analysis, and the adjustable influencing variables and influence factors on quality stability that affect the forming quality of the fender are obtained. Experimental optimization of the adjustable variables is carried out again to obtain the optimal combination of process parameters that affect the shaping quality of the fender. The optimal combination of process parameters is as follows: blank holder force is 120 kN, model clearance is 1.0 t (t represents sheet thickness), friction coefficient is 0.11, and radius of die is 6 mm. Finally, the experimental results show that the fender manufactured with this combination of process parameters has better performance.

Numerical simulation of the injection molding of the inner panel of the car door and the optimization of its process parameters were completed. The inner panel and its injection mold were designed by UG software and simulated by the filling and cooling module of the Moldflow software. Different gate schemes were selected to compare quality indicators such as filling time, air pockets, and weld lines to obtain the optimal number of gates. We established the objective function model with gate position as the independent variable, and used a multi-population genetic algorithm to solve the optimal position of the function model to get the best gate position. The mold temperature, melt temperature, cooling time, holding pressure, and holding time were selected as the influencing factors, and volume shrinkage and warpage deformation were selected as the evaluation indicators to design and complete the orthogonal test. The test data were simulated by Moldflow, and the optimal combination of process parameters was determined by range and variance analysis. The BP neural network model related to the molding process parameters, volume shrinkage, and warpage deformation was built, and the trained network model was optimized with the ant colony algorithm. The optimal parameter combination was: mold temperature 76, melt temperature 205, cooling time 23.8s, holding pressure 54.7Mpa, and holding time 22.1s. The simulation results showed that volume shrinkage was 13.32% and warpage deformation was 4.315 mm. The design of an injection mold for the car door inner panel was completed and its molding process parameters were optimized.

In order to put forward the theoretical calculation formula for the compression force of the compression mold of the trunk trim panel, obtain the influence trend of the process parameters on the molding quality of the trunk trim panel, and obtain the optimal process parameters combination for the compression molding of the trunk trim panel, four process parameters, the heating temperature, time, compression pressure, and holding time, which affected the compression molding, were selected as the level factors; the maximum thinning rate, maximum thickening rate, and shrinkage rate of the trunk trim panel were selected as evaluation indicators and orthogonal experiments were designed and completed; the comprehensive weighted scoring method was used to obtain the comprehensive score results and obtain the comprehensive evaluation indicators of the best combination of process parameters of trunk trim panel; BP neural network and genetic algorithm were used to study the change trend of the evaluation indicators of trunk trim panel with the changes of process parameters; based on the optimal process parameter combination and the established neural network’s prediction function, the maximum thinning rate, maximum thickening rate, and shrinkage rate under a single process parameter change could be predicted, and the influence of a single process parameter on the maximum thinning rate, maximum thickening rate, and shrinkage rate could be obtained; the process parameters were optimized, and a maximum thinning rate of 28%, a maximum thickening rate of 4.3%, and a shrinkage rate of 0.8% were obtained; the optimal molding process parameters of the trunk trim panel were heating temperature of 209°C, heating time of 62 s, molding pressure of 14 kPa, and holding pressure time of 49 s; after optimization, the maximum shrinkage rate was 28.0880%, the maximum thickening rate was 44.3264%, and the shrinkage rate was 0.8901%; according to the optimal process parameters, the quality of the trunk trim panel was very good, which met the production quality requirements.

Based on the oil quality of diesel oil, the thermal efficiency and fuel consumption of the fuel‐burning submersible hot water machine were calculated. The structure of the fuel‐burning submersible hot water machine was designed. The heat transfer calculation of the flame tube and convection surface of the high‐efficiency fuel submersible hot water machine was carried out, and the overall heat balance of the system was checked. ANSYS was used to analyze and study the mechanical and thermodynamic properties of the fuel‐based submersible hot water machine, and the simulation results were compared with the theoretical calculation results. The thermal field of the flame tube and the threaded tube was simulated, and the influence of the temperature field on the flame tube was analyzed. The changes in the total deformation and strength of the flame tube under the thermal structure coupling were studied. The thermal efficiency of oil‐fired submersible hot water machine was studied, and the relevant factors affecting the thermal efficiency of oil‐fired submersible hot water machine were put forward. The main factors affecting thermal efficiency were analyzed and mathematically modeled. The air supply model and the convective heat transfer model of the threaded tube were established. The main parameters that affected the thermal efficiency of the threaded tube were optimized. In the end, the design scheme of a high‐efficiency fuel‐type submersible hot water machine was obtained.