基于概率分析的锈蚀钢筋混凝土结构寿命预测

钢筋锈蚀是导致混凝土结构破坏的主要原因,合理预测锈蚀钢筋混凝土结构的使用寿命对减少工程的经济损失、保证结构的安全运行具有重要意义。针对锈蚀钢筋混凝土结构在不同寿命评估准则下的使用寿命预测问题,基于混凝土结构耐久性现状检测结果,采用概率分析可靠度方法,通过抗力和荷载效应的统计特征求得结构的时变可靠指标,从而对结构的裂缝宽度寿命和承载力寿命进行分析预测。以拱坝孔口和水电站厂房吊车梁为例进行计算,研究结果表明：结构的动态可靠指标随着服役时间的增加呈下降趋势,概率分析法的寿命预测结果在合理的预测区间内。研究成果可在实际工程中为钢筋混凝土结构的维修和加固提供决策依据。     

基于健康指数法的水电站延寿评估效益研究

中华人民共和国成立之后建设的第一批水电站已逐步到达国家规定的发电许可年限,但随着水电工程技术的成熟,各水电站的设备管理水平也有了质的飞跃,在机组经历了数次大修,并且对设备进行升级改造后,至今仍然保持着良好的运行能力。本文以EA公司的健康指数算法为基础对发电机组各设备当前健康情况进行评价,然后结合木桶原理,进行发电机组今后可运行寿命的综合评估。本文以广西西津水电站为例进行计算和评估,证明了在进行水电站延寿评估时该方法是合理的,并且通过延寿评估后,可以使清洁能源更加合理的利用,也优化了水电资源的配置效率。     

聚丙烯玄武岩混杂纤维混凝土氯盐侵蚀耐久性试验研究

玄武岩纤维和聚丙烯纤维可在混凝土中产生互补和协同作用,大幅提升混凝土性能.文章通过试验研究的方法,探讨了玄武岩聚丙烯纤维混凝土的抗氯盐侵蚀性能.从试验结果来看,纤维混掺有助于提高混凝土的抗氯盐侵蚀性能,而玄武岩纤维掺量0.15％、聚丙烯纤维掺量0.5％的混杂纤维混凝土抗氯盐侵蚀性能最佳,建议在工程设计和施工中采用.     

Instability of diatomic deuterium in fcc palladium

To clarify some of the solid-state aspects of cold fusion in deuterated transition metal electrodes, we have carried out first-principles self-consistent total energy calculations for various configurations of atomic and diatomic deuterium inside fcc palladium. We find that the stability of the Pd+D system is controlled by the relative position of the deuterium-inducedantibonding level with respect to the Fermi energy. The equilibrium D-D distance in dense PdD up to =3 is found to be much larger than the free space value. The calculated Born-Oppenheimer energy surface of diatomic D₂ in crystalline palladiuim is shown to have but metastable local minima whose internuclear separation is at least 0.2 Ålarger than that of the isolated D₂ molecule. We conclude that D₂ incrystalline Pd will have a substantially lower tunneling probability than hitherto thought and that explanation for fusion mechanisms should be sought elsewhere.     

Data stream classification with novel class detection: a review,comparison and challenges

Knowledge and Information Systems - Developing effective and efficient data stream classifiers is challenging for the machine learning community because of the dynamic nature of data streams. As a...     

Predicting the blast-induced vibration velocity using a bagged support vector regression optimized with firefly algorithm

Ground vibration is the most detrimental effect induced by blasting in surface mines. This study presents an improved bagged support vector regression (BSVR) combined with the firefly algorithm (FA) to predict ground vibration. In other words, the FA was used to modify the weights of the SVR model. To verify the validity of the BSVR–FA, the back-propagation neural network (BPNN) and radial basis function network (RBFN) were also applied. The BSVR–FA, BPNN and RBFN models were constructed using a comprehensive database collected from Shur River dam region, in Iran. The proposed models were then evaluated by means of several statistical indicators such as root mean square error (RMSE) and symmetric mean absolute percentage error. Comparing the results, the BSVR–FA model was found to be the most accurate to predict ground vibration in comparison to the BPNN and RBFN models. This study indicates the successful application of the BSVR–FA model as a suitable and effective tool for the prediction of ground vibration.

     

轻量级密码算法Piccolo的统计故障分析

Piccolo算法是于2011年CHES会议上提出的一种轻量级分组密码算法,用于物联网环境中保护RFID、传感器、智能卡等电子设备的通信安全.目前国内外安全性分析研究集中在该算法的已知明文攻击和选择明文攻击,在攻击者能力最弱条件下的唯密文攻击尚无相关研究.文中提出了统计故障分析下Piccolo密码的安全性,即在唯密文条件下,使用SEI、HW、ML、GF、MAP、GF-SEI、GF-ML、ML-SEI、ML-MAP、MM-HW及MM-HW-ML等一系列区分器,恢复Piccolo密码的主密钥.实验结果表明,Piccolo算法不能抵御统计故障分析的攻击,文中提出的新型区分器ML-MAP、MM-HW和MM-HW-ML仅需164和262个故障,可以分别恢复出80比特和128比特主密钥,有效地减少了故障数,并提升了攻击效率.该结果为物联网环境中轻量级密码的安全设计与实现提供有价值的参考.     

Layout Optimization for Greenhouse WSN Based on Path Loss Analysis

When wireless sensor networks (WSN) are deployed in the vegetable greenhouse with dynamic connectivity and interference environment, it is necessary to increase the node transmit power to ensure the communication quality, which leads to serious network interference. To offset the negative impact, the transmit power of other nodes must also be increased. The result is that the network becomes worse and worse, and node energy is wasted a lot. Taking into account the irregular connection range in the cucumber greenhouse WSN, we measured the transmission characteristics of wireless signals under the 2.4 Ghz operating frequency. For improving network layout in the greenhouse, a semi-empirical prediction model of signal loss is then studied based on the measured data. Compared with other models, the average relative error of this semi-empirical signal loss model is only 2.3%. Finally, by combining the improved network topology algorithm and tabu search, this paper studies a greenhouse WSN layout that can reduce path loss, save energy, and ensure communication quality. Given the limitation of node-degree constraint in traditional network layout algorithms, the improved algorithm applies the forwarding constraint to balance network energy consumption and constructs asymmetric network communication links. Experimental results show that this research can realize the energy consumption optimization of WSN layout in the greenhouse.     

Parallel optimization of three-dimensional wedge-shaped underwater acoustic propagation based on MPI+OpenMP hybrid programming model

The three-dimensional wedge-shaped underwater acoustic propagation model exists analytical solution, which provides verification for models like FOR3D propagation model under certain situation. However, the solving process of a three-dimensional complex underwater sound field problem is hindered by intensive computing and long calculation times. In this paper, we exploit a hybrid parallel programing model, such as MPI and OpenMP, to accelerate the computation, design various optimization methods to improve the overall performance, and then carry out the performance and optimization analysis on the Tianhe-2 platform. Experiments show that the optimized implementation of the three-dimensional wedge-shaped underwater acoustic propagation model achieves a 46.5 speedup compared to the original serial program, thereby illustrating a substantial performance improvement. We also carried out scalability tests and parallel optimization experiments for large-scale practical examples.

     

Entity-level sentiment prediction in Danmaku video interaction

The Journal of Supercomputing - Sentiment analysis in Danmaku video interaction aims at measuring public mood in respect of the video, which is helpful for the potential applications in behavioral...