CAE技术在汽轮机高温强度计算中的应用

为分析某百万千瓦超超临界汽轮机高压缸旋转部件在高温以及高离心力载荷下的强度状况,建立高压缸第一级动叶片的模型.根据蠕变试验数据,采用最小二乘法拟合幂蠕变方程中的各个参数,并详细介绍各参数的拟合、优化和验算过程;用CFD分析软件计算流体域内的对流传热系数并插值到有限元计算程序中,分析叶根倒角处危险区域的蠕变应力状况.数据验算结果表明,利用拟合数据计算得到的蠕变应力值与试验值比较接近,证明该方法可靠;CAE计算结果表明,叶根倒角处危险区域蠕变应力考核合格,并且有充足的安全裕量.     

反应堆堆芯围筒结构热流固耦合热变形分析

针对反应堆堆芯围筒热流固耦合问题,采用三维有限元法研究堆芯围筒的热变形.考察ANSYS的三维实体热单元SOLID 70,三维实体单元SOLID 45,三维表面热效应单元SURF 152和三维热-流耦合管单元FLUID 116等单元类型的特点和实用性.建立堆芯围筒、吊篮和冷却剂的温度分析有限元模型：堆芯围筒和吊篮采用SOLID 70,结构表面与冷却剂的对流传热表面采用SURF152,堆芯围筒与吊篮之间冷却剂采用FLUID 116.采用SOLID 45建立堆芯围筒有限元模型,根据得到的堆芯围筒、吊篮和冷却剂的温度场结果分析堆芯围筒热变形.结果表明,在考虑堆芯围筒及吊篮固体和流体的交叉耦合的基础上,采用三维有限元法能比较客观地模拟反应堆堆芯处的复杂运行环境.     

基于VFP的艺术类专业报名考试系统的设计与实现

结合高校艺术类专业招生工作实际情况,针对当前艺术类专业报名考试的特点和要求,借助VFP强大的数据管理功能,构建基于VFP的艺术类专业报名考试系统,实现报名信息管理、考场安排、准考证打印和成绩统计的一体化管理,提高了招生工作效率。     

欠驱动机器人控制策略综述

欠驱动机器人是指独立控制输人量少于系统自由度的一类机器人,具有重量轻、成本低、能耗低等众多优点,目前已引起学者们的广泛关注,介绍了欠驱动机器人控制器设计的六类策略,分析了各类策略的应用及效果,如何将鲁棒控制与其它控制策略相结合,开发出更实用、性能更优越的控制策略,有待于进一步研究.     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.     

Double Medical Images Zero-Watermarking Algorithm Based on the Chaotic System and Ternary Accurate Polar Complex Exponential Transform

Journal of Mathematical Imaging and Vision - Different from the traditional watermarking schemes, zero-watermarking schemes are lossless embedding methods, which are applicable to be used in...     

A conditional classification recurrent RBM for improved series mid-term forecasting

In the context of human-robot and robot-robot interactions, the better cooperation can be achieved by predicting the other party’s subsequent actions based on the current action of the other party. The time duration for adjustment is not sufficient provided by short term forecasting models to robots. A longer duration can by achieved by mid-term forecasting. But the mid-term forecasting models introduce the previous errors into the follow-up forecasting and amplified gradually, eventually invalidating the forecasting. A new mid-term forecasting with error suppression based on restricted Boltzmann machine(RBM) is proposed in this paper. The proposed model can suppress the error amplification by replacing the previous inputs with their features, which are retrieved by a deep belief network(DBN). Furthermore, a new mechanism is proposed to decide whether the forecasting result is accepted or not. The model is evaluated with several datasets. The reported experiments demonstrate the superior performance of the proposed model compared to the state-of-the-art approaches.

     

GRU-based capsule network with an improved loss for personnel performance prediction

Applied Intelligence - Personnel performance is a key factor to maintain core competitive advantages. Thus, predicting personnel future performance is a significant research domain in human...     

A graph-based QoS prediction approach for web service recommendation

Applied Intelligence - With the development of the Internet, the recommendation based on Quality of Service(QoS) is proven to be an efficient way to deal with the ever-increasing web services in...     

AES算法的硬件实现分析与设计

分析了AES算法的结构特点,对算法的不同硬件实现方式进行了对比分析,分析结果表明,不同的实现方式在算法应用模式支持、运行频率、资源占用、吞吐量方面各有优缺点,需要根据具体应用需求采用合适的实现方式。对AES算法不同实现方式的分析以及提出的设计结构对于其他类似的分组密码算法实现也具有参考价值。