共查询到18条相似文献,搜索用时 78 毫秒
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针对燃气活塞弹射装置,采用加质源项法,通过UDF(用户自定义函数)编译,向高压室注入火药燃气的质量、动量、能量,实现了复杂燃烧化学反应的数值模拟,得到了高压室压力和速度分布及变化规律,分析了压力和速度对弹射装置的影响。计算结果表明,装药燃烧数值模拟与理论计算基本吻合,能够较好地仿真弹射装置高压室燃气流场的特性,为弹射装置进一步优化设计和装药设计提供理论参考。 相似文献
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由于中厚板在冲压成型过程中的应力分布特点与常规薄板冲压有所不同,因此以JSTAMP/NV提供的解决方案为例,探讨中厚板回弹分析中单元类型和材料模型等关键参数的设定.利用JSTAMP/NV提供的解决方案对料厚为7 mm的某铁路货车梁进行回弹仿真,并使用专用于中厚板回弹分析的参数设定,结果表明仿真结果与试验结果吻合良好。 相似文献
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张福玲 《数字社区&智能家居》2007,3(7):290-291
利用MATLAB的数值计算功能和图形用户界面,设计了一个在MATLAB环境下的数值分析教学与数值实验系统,解决了数值分析教学过程中存在的实时计算和图形问题。 相似文献
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基于Fluent的全机数值模拟及并行计算 总被引:3,自引:0,他引:3
利用CFD商用软件Fluent对亚声速飞行飞机的三维绕流流场进行了数值模拟以及并行计算,得到了飞机附近的流场,实现了此软件在高性能并行计算机上的并行;并且通过对不同数量网格在不同结点数目机群上的计算结果进行分析比较,验证了此商用软件在并行平台上应用的有效性,也为进行大规模科学工程计算提供了技术参照。 相似文献
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张福玲 《数字社区&智能家居》2007,(13)
利用MATLAB的数值计算功能和图形用户界面,设计了一个在MATLAB环境下的数值分析教学与数值实验系统,解决了数值分析教学过程中存在的实时计算和图形问题. 相似文献
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以铁路货车某类零件为例,结合铁路货车冲压件的特点,从建立回弹分析的数学模型入手,用JSTAMP/NV研究回弹的有限元求解过程,找出影响回弹的主要因素.结合实际模具设计,从坯料的网格划分、成型速度和自适应设置等方面论述提高回弹仿真分析精度的若干要点. 相似文献
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本文阐述高级语言程序设计中数值量的数值范围问题。本文对数值量数值范围的定义、控制、选择、预测和测定等进行分析,并说明处理方法。 相似文献
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During the winding process of stranded wire helical springs (SWHSs), uneven wire tension always results in high rejection rate and non-compliance service life of SWHSs. Combining the proportion integral neural network (PINN) with a simplified actuator model, this paper presents a new control scheme for the SWHS CNC machine to keep the wire tension uniform. The PINN is improved by introducing an error variance ratio, accounting for the interaction between wires, as a modifying factor in the second hidden layer. The actuator model is simplified based on the analysis of the dynamic characteristics of the actuator. The output value of the improved PINN is transferred into control voltage value by the simplified model. The tension of each wire is controlled by an improved PINN. In order to enhance the control performance, the network parameters are updated using the gradient-based back-propagation method. The validity and consistency of the improved PINN are verified by experiments. The results indicate that (1) the computation load is slight; (2) the rising time of the step response is within 1 s; (3) 89%-96% of tension deviation values of the wire 1 and wire 3 under different process parameters are within 10% of the reference tension value; (4) the standard deviation of the wire 2 with large disturbance is 8.24 N. Compared with other algorithms (incremental PI, multiple PIDNN, PI based particle swarm optimization), the control scheme based on the improved PINN has less computation load, faster response speed and better performance in the time-varying and nonlinear system with larger disturbance. 相似文献
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Optimal process design of sheet metal forming for minimum springback via an integrated neural network evolutionary algorithm 总被引:3,自引:1,他引:3
K.M. Liew H. Tan T. Ray M.J. Tan 《Structural and Multidisciplinary Optimization》2004,26(3-4):284-294
The process of sheet metal forming is characterized by various process parameters. Accurate prediction of springback is essential for the design of tools used in sheet metal forming operations. In this paper, an evolutionary algorithm is presented that is capable of handling single/multiobjective, unconstrained and constrained formulations of optimal process design problems. To illustrate the use of the algorithm, a relatively simple springback minimization problem (hemispherical cup-drawing) is solved in this paper, and complete formulations of the algorithm are provided to deal with the constraints and multiple objectives. The algorithm is capable of generating multiple optimal solutions in a single run. The evolutionary algorithm is combined with the finite element method for springback computation, in order to arrive at the set of optimal process parameters. To reduce the computational time required by the evolutionary algorithm due to actual springback computations via the finite element method, a neural network model is developed and integrated within the evolutionary algorithm as an approximator. The results clearly show the viability of the use of the evolutionary algorithm and the use of approximators to derive optimal process parameters for metal forming operations. 相似文献
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热轧带钢卷取温度是影响成品带钢性能指标的重要工艺参数之一,其层流冷却控制系统具有高度非线性。影响卷取温度的因素多而且复杂,采用传统的温度预报模型难以达到较高的精度要求。为了满足卷取温度高精度的要求,提出了一种基于数据挖掘技术的遗传神经网络方法。充分发挥数据挖掘的关联分析能力、神经网络的泛化映射能力和遗传算法的全局搜索能力,将三者结合起来,建立了卷取温度预测模型。运用实际现场数据进行测试表明:它能准确地预报卷取温度,具有在线应用的前景。 相似文献
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