【摘 要】
:
Deep learning has been probed for the airfoil performance prediction in recent years.Compared with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper means.Neverth
【机 构】
:
MHIT Key Laboratory of Pattern Analysis and Machine Intelligence,College of Computer Science and Tec
论文部分内容阅读
Deep learning has been probed for the airfoil performance prediction in recent years.Compared with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper means.Nevertheless,effective training of the data-driven models in deep learning severely hinges on the data in diversity and quantity.In this paper,we present a novel data augmented Generative Adversarial Network(GAN),daGAN,for rapid and accurate flow filed prediction,allowing the adaption to the task with sparse data.The presented approach consists of two modules,pre-training module and fine-tuning module.The pre-training module utilizes a conditional GAN(cGAN)to preliminarily estimate the distribution of the training data.In the fine-tuning module,we propose a novel adversarial archi-tecture with two generators one of which fulfils a promising data augmentation operation,so that the complement data is adequately incorporated to boost the generalization of the model.We use numerical simulation data to verify the generalization of daGAN on airfoils and flow conditions with sparse training data.The results show that daGAN is a promising tool for rapid and accurate evaluation of detailed flow field without the requirement for big training data.
其他文献
The features of carrier-based aircraft\'s navigation systems during the approach and land-ing phases are investigated.A new adaptive Kalman filter with unknown state noise statistics is pro-posed to improve the accuracy of the INS/GNSS integrated naviga
The shape approximation method has been proven to be rapid and practicable in resolv-ing low-thrust trajectory;however,it still faces the challenges of large deviation from the optimal solution and inability to satisfy the specific flight time and fuel ma
高坊水库是一座以灌溉为主,兼顾防洪、发电等综合利用的中型水库,其地理位置非常重要,故水库安全鉴定工作中,防洪能力复核是非常重要的环节.文章采用江西省水文总局2010年编制的《江西省暴雨洪水查算手册》,按暴雨洪水查算法复核坝址设计洪水,经过调洪演算,抗洪能力复核计算,评价高坊水库大坝防洪安全性为A级.
坝体防冻害维护管理和库区水资源管理必须经常应用水库水体温度预测和计算,文章运用一维水体温度模型对水电站水库全年水体温度构造进行算例分析探究,其计算形式及所揭示的库水温度分布规律,可为同类水库水体温度预测工程应用提供研究和技术参考.
Ballistic Missile Trajectory Prediction(BMTP)is critical to air defense systems.Most Trajectory Prediction(TP)methods focus on the coast and reentry phases,in which the Ballistic Missile(BM)trajectories are modeled as ellipses or the state components are
桥上水库位于新余市渝水区下村镇花堆村境内,控制流域面积6.98km2,属赣江流域袁河支流蒙河水.水库运行数年来,为水库下游农业生产发展和经济建设做了一定得贡献,但大坝存在渗漏等质量问题,限制低水位运行,工程效益难以发挥,文章针对桥上水库现状存在的问题,选取了合理的除险加固设计方案.
Deep Learning(DL)has important applications to both commercial and military com-munications,such as software-defined radio,cognitive radio and spectrum surveillance.While DL has been intensively studied for modulation recognition,there are very few invest
以北方寒冷地区猴山水库为例,考虑到混凝土预埋冷却水管、不设纵缝而只设横缝,采取间歇式的施工方法和常态混凝土筑坝技术等工程特点,其温度应力问题比较突出,做好大坝防裂措施和温度控制相关工作极为重要.通过大量的计算分析和理论研究,并结合相关资料与实践经验,经积极探索提出合理的温控标准和有效的温控措施,设计了有效完整的混凝土防裂技术,可为大坝的温控防裂和设计施工提供一定参考.
以五华县五华河左岸某局部段防洪堤工程为例,分析了堤防工程建设中的相关技术要点,包括堤线布置、堤型断面选择、冲刷深度计算及护脚分析、堤岸结构稳定计算和地基加固处理等.结果表明防洪堤布置可沿原批复堤线走向,堤防结构稳定满足要求,局部段地基经换填处理后可满足地基承载力要求.
通过制备、加载和超声检测混凝土试件,揭示了不同含水量和频率下试件超声波速,以及超声波速随荷载增加的变化规律.试验表明:混凝土超声波速随着检测频率及含水量的增加而增大,不同频率下的超声波速随混凝土损伤的增加均显著降低.然后考虑微观损伤演化规律,深入分析了混凝土损伤超声检测受含水量及频率的影响机理,可为损伤分析及无损检测混凝土技术的发展提供一定指导.