The increasingly strict emission regulations in combustion engines are raising high requirements for the engine valve train system. In this paper, a novel multifunctional wear apparatus is designed to study the performance of engine valve train components. The apparatus employs a mechanical loading system, which consists of a special eccentric wheel and disc springs that apply the combustion loads, and the contact configurations and loading conditions of valve train components are simulated. It has three test functions for different components through specifically designed fixtures. The first function aims to evaluate the interaction between the valve seating face and the seat insert at high temperatures and loads. The second function is used to study the friction and wear properties of the valve stem and the valve guide. The third function is designed to evaluate the performance of the valve seals. At last, a verification test was carried out by the proposed experimental method. A pair of new exhaust valve and seat insert is tested for the performance evaluation of the first function. The wear mechanisms acting on the pairs interface are shown to be a combination of oxidative wear, adhesive wear, as well as fatigue flaking.
The miniaturization of the scrubber used in vessel flue gas desulphurization is a critical issue. In this study, the structure optimization of the vessel desulphurization scrubber based on CFD (computational fluid dynamics) and the SVM‐GA (support vector machine and genetic algorithm) is performed and a miniaturized scrubber design with the same desulphurization efficiency as large scrubbers is obtained. First, the seawater SO2 absorption process in a vessel desulphurization scrubber is investigated using the CFD‐DPM method, and the effects of the operating and structural parameters on the desulphurization efficiency η are discussed in detail. Results show that η is positively correlated to the absorption area height, H2, and the spray level number, N, and η first increases and then decreases with an increase in the scrubber diameter, D1, as well as the inlet flue angle, θ. Then, a prediction model of η considering D1, H2, θ, and N is established and validated using the SVM with the simulation data. Finally, D1, H2, θ, and N are optimized using the GA method based on the SVM model. The results show that the volume of the absorption area, Vab, can be reduced by 30 % while maintaining the same η through the use of this optimization method.
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