在天然气压力调节器中,对降噪孔板的高效优化,基于自适应式多尺度采样-模模型
Huan Xie1, Tiantian Wang1, Dongrong Meng1
1School of Mechanical Engineering, Xijing University, Xi'an, China.
Scientific reports
|January 21, 2026
概括
本研究介绍了一种自适应的多尺度采样Kriging (AMSS-KG) 模型,用于优化降噪孔板. 新方法显著提高了工程噪音控制应用中的效率和准确性.
科学领域:
- 工程 工程师 工程师 工程师
- 声学 声学 在声学方面
- 计算科学 计算科学
背景情况:
- 降噪孔板的结构优化对于天然气压力调节来说至关重要.
- 传统的方法面临效率和高计算成本的挑战.
研究的目的:
- 开发一种有效的优化方法,用于降噪孔板.
- 在速度和成本方面解决传统优化技术的局限性.
主要方法:
- 提出了一个可适应的多尺度采样Kriging (AMSS-KG) 模型.
- 采用动态抽样调整策略,以提供高效的模型培训.
- 在优化过程中平衡勘探和开发.
主要成果:
- AMSS-KG模型大约提高了2.7%的优化准确度.
- 与传统方法相比,实现了54%的计算成本降低.
- 与传统的Kriging模型和并行q-EI策略相比,表现出优越的性能.
结论:
- AMSS-KG方法提供了一种高效且具有成本效益的解决方案,用于优化降噪孔板.
- 提供一个可通用的适应性采样框架,适用于其他基于代理的优化问题.
- 在天然气应用中促进定制设计和工程噪声控制.
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