非结构混合网格自适应并行技术

计算流体力学（CFD）模拟实际工程问题所采用的网格规模可达千万量级，并行技术是减少计算时间的有效方法。耦合流场信息的网格自适应技术能有效动态优化计算网格，被NASA视为一项亟待发展的CFD关键技术。混合网格自适应系统包含网格分布优化、表面网格投影和空间网格匹配等关键技术。针对以上3项关键技术分别建立了高效的并行算法。首先，提出了"先唯一后同一"的两步法策略实现了网格单元分布优化过程的并行相容性；其次，基于局部曲面拟合思想，实现了曲面重构和新增物理网格点投影的完全并行；再次，提出了空间网格匹配技术的半并行算法，快速解决了网格单元交错问题。为了提高后续流场计算的并行效率，发展了基于并行重分区-网格数据迁移方法的动态负载平衡技术，并采用圆柱激波流场自适应模拟对动态负载平衡技术进行初步验证。最后，采用三角翼自适应加密测试了自适应系统的并行效率。结果表明，建立的混合网格自适应系统并行效率较高，且相比流场求解耗费总时间的比例低于1%。     

Regression model for civil aero-engine gas path parameter deviation based on deep domain-adaptation with Res-BP neural network

The variations in gas path parameter deviations can fully reflect the healthy state of aero-engine gas path components and units; therefore, airlines usually take them as key parameters for monitoring the aero-engine gas path performance state and conducting fault diagnosis. In the past, the airlines could not obtain deviations autonomously. At present, a data-driven method based on an aero-engine dataset with a large sample size can be utilized to obtain the deviations. However, it is still difficult to utilize aero-engine datasets with small sample sizes to establish regression models for deviations based on deep neural networks. To obtain monitoring autonomy of each aero-engine model, it is crucial to transfer and reuse the relevant knowledge of deviation modelling learned from different aero-engine models. This paper adopts the Residual-Back Propagation Neural Network (Res-BPNN) to deeply extract high-level features and stacks multi-layer Multi-Kernel Maximum Mean Discrepancy (MK-MMD) adaptation layers to map the extracted high-level features to the Reproduce Kernel Hilbert Space (RKHS) for discrepancy measurement. To further reduce the distribution discrepancy of each aero-engine model, the method of maximizing domain-confusion loss based on an adversarial mechanism is introduced to make the features learned from different domains as close as possible, and then the learned features can be confused. Through the above methods, domain-invariant features can be extracted, and the optimal adaptation effect can be achieved. Finally, the effectiveness of the proposed method is verified by using cruise data from different civil aero-engine models and compared with other transfer learning algorithms.     

一种三维并行自适应计算方法

基于串行网格划分软件METIS与并行化消息传递编程接口（ MPICH2）对现有串行自适应程序进行简单的并行化改造,给出了一种三维可压缩无粘流数值模拟的并行自适应方法。首先利用单个进程调用METIS,串行划分网格;然后对所有进程并行计算以获得初始网格下的流场解;再次利用单个进程对整个流场运用自适应方法进行局部网格加密并调用METIS串行划分网格;最后全部进程在流场初始解的基础上继续并行计算,以获得自适应网格下的流场解。数值模拟算例验证了此方法的可靠性与高效性。     

非结构混合网格鲁棒自适应技术

数值格式、湍流模型和计算网格是影响CFD数值模拟精度的3个主要因素。结合流场信息的网格自适应技术具备动态优化计算网格的能力,被NASA列为未来CFD发展的一项关键技术。本文针对非结构混合网格,发展了网格单元分布优化、表面网格几何投影和空间网格协调匹配3项关键技术,建立了高鲁棒性几何保真的网格自适应系统。首先,为了提高自适应方法的鲁棒性和通用性,发展了基于标准面网格的多面体网格单元分布优化方法。其次,发展了仅依赖表面网格信息的局部曲面重构技术,采用参数点映射方法实现了新增表面网格点的几何投影,消除了自适应系统对几何CAD系统的依赖。再次,采用改进的距离函数方法实现了空间网格与投影后表面网格的快速匹配。最后,结合基于流场特征的自适应探测器,采用二阶格式的有限体积方法,开展了30P30N三段翼绕流和三角翼大迎角绕流的网格自适应数值模拟。结果表明,通过网格自适应对网格单元的分布进行优化后,流场求解的收敛性和模拟精度都得到了显著提高。     

规划未来 塑造自我

通过对有关大学生心理困惑方面的问卷调查分析,笔者发现目前大学生在学习生活中存在着很大的盲目性,解决问题的出路之一是把握学年特点,根据自己的实际情况,作出合理规划,并付诸实践。     

F-22未能成为舰载战斗机原因浅析

从经济可承受性、进度、海上作战需求和航母适配性等方面，论述F-22未能成为舰载战斗机的原因。     

A mesh optimization method using machine learning technique and variational mesh adaptation

Computational mesh is an important ingredient that affects the accuracy and efficiency of CFD numerical simulation. In light of the introduced large amount of computational costs for many adaptive mesh methods, moving mesh methods keep the number of nodes and topology of a mesh unchanged and do not increase CFD computational expense. As the state-of-the-art moving mesh method, the variational mesh adaptation approach has been introduced to CFD calculation. However, quickly estimating the flow fi...     

舰—机适配条件对舰载机滑跃起飞性能的影响

针对不同舰-机适配条件下舰载机起飞安全性的问题,建立了飞机滑跃起飞动力学分析模型,用数值方法分析了飞机起飞质量、甲板参数、舰船航行速度等因素对飞机滑跃起飞性能的影响。仿真结果表明：舰载机起飞质量增大会减小其离舰爬升率;平直甲板越长或斜甲板出口倾角越大,离舰爬升率越大;但是出口倾角太大时,会使飞机离舰迎角超出限制;增大舰船的行驶速度,可以缩短舰载机起飞所需甲板的长度。     

一种改进的适应性超媒体学习单元模型

在netUniversité这一平台上,结合IMS LD标准建立学习单元模型,并以此标准根据新的教学需求对已有模型进行改进.将HBDI 全脑模型结合入学习内容管理工具,利用设计时工具Reload Editor和运行时工具CopperCore Player构造学习单元模型.     

Evaluation of Turbulence Models in Predicting Hypersonic and Subsonic Base Flows Using Grid Adaptation Techniques

The flows behind the base of a generic rocket, at both hypersonic and subsonic flow conditions, are numerically studied. The main concerns are addressed to the evaluation of turbulence models and the using of grid adaptation techniques. The investiga- tion focuses on two configurations, related to hypersonic and subsonic experiments. The applicability tests of different turbulence models are conducted on the level of two-equation models calculating the steady state solution of the Reynolds-averaged Navier-Stokes(RANS) equations. All used models, the original Wilcox k-ω, the Menter shear-stress transport (SST) and the explicit algebraic Reynolds stress model(EARSM) formulation, predict an asymmetric base flow in both cases caused by the support of the models. A comparison with preliminary experimental results indicates a preference for the SST and EARSM results over the results from the older k-ω model. Sensitivity studies show no significant influence of the grid topology or the location of the laminar to turbulent transition on the base flow field, but a strong influence of even small angles of attack is reported from the related experiments.