环量控制翼型非定常气动力建模
Journal of Beijing University of Aeronautics and Astronautics（2021）
Abstract
针对目前环量控制技术中射流参数与迎角对翼型气动特性的影响高度耦合,对应非定常气动力模型精度较差的研究现状,基于环量控制翼型强迫俯仰振动数值模拟数据,借助Kriging模型实现环量控制翼型的定常气动力插值,借助微分方程模型完成了适用于环量控制翼型的线性微分方程建模,采用两步线性回归参数辨识方法辨识线性微分方程模型中特征时间常数等参数,对高动量系数大振幅流动状态下的非线性影响进行修正.研究结果表明:基于Kriging模型实现的环量控制翼型定常气动力插值精度较传统气动导数模型高,建立的环量控制翼型非定常气动力模型能够精确预测不同流动状态下的气动力和力矩系数变化情况.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined