Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process. 相似文献
The technique of imaging a target with a complicated motion using an Inverse Synthetic Aperture Radar (ISAR) system is an effective tool in the field of radar signal processing. After the translational compensation, the received signal reflected from the target can take the form of a multi-component Polynomial Phase Signal (m-PPS), and the high quality ISAR image can be provided via the combination between the estimated parameters of the m-PPS and the Range Instantaneous-Doppler technique (RID). For a target with a high maneuvrability, the occurrence of scatterers Migration Through Resolution Cell (MTRC), caused by the rotational movement could be appearing. That is why the variation in the amplitude of the echo during the time of observation cannot be neglected. The purpose of this study is the parameters estimation of the m-PPS signal with order three in the case of the Time Varying Amplitude (TVA). The Improved-version of the Product High-order Ambiguity Function (IPHAF) with TVA is proposed to improve the quality of the ISAR image compared with traditional techniques based on a constant amplitude; the experimental outcomes confirm that the new IPHAF-TVA method presented in this study is an effective technique to make the ISAR image very clear. 相似文献
Swirl-Loop Scavenging (SLS) improves the performance of 2-stroke aircraft diesel engine because the involved swirl may not only benefit the scavenging process, but also facilitate the fuel atomization and combustion. The arrangement of scavenge port angles greatly influences in-cylinder flow distribution and swirl intensity, as well as the performance of the SLS engine. However, the mechanism of the effect and visualization experiment are rarely mentioned in the literature. To further investigate the SLS, Particle Image Velocimetry (PIV) experiment and Computational Fluid Dynamics (CFD) simulation are adopted to obtain its swirl distribution characteristics, and the effect of port angles on scavenging performance is discussed based on engine fired cycle simulation. The results illustrate that Reynolds Stress Turbulence model is accurate enough for in-cylinder flow simulation. Tangential and axial velocity distribution of the flow, as well as the scavenging performance, are mainly determined by geometric scavenge port angles αgeom and βgeom. For reinforcement of scavenging on cross-sections and meridian planes, αgeom value of 27° and βgeom value of 60° are preferred, under which the scavenging efficiency reaches as high as 73.7%. Excessive swirl intensity has a negative effect on SLS performance, which should be controlled to a proper extent. 相似文献