Characterization of residual stresses from cold expansion using spatial statistics

Residual stress fields from cold expansion have been widely used to extend the fatigue life of aircraft structures. However, the spatial statistical character of these residual stress fields has not been established and has not been incorporated in current analysis methods. The objective of this study was to establish a spatial statistical method to quantify the residual stress field around a cold expanded hole. A framework called the Spatial Analysis of Residual Stress (SpARS) was developed utilizing spatial correlation, response surface modelling techniques and statistical resampling methods to characterize the residual stress field. Our results showed that tolerance bounds on residual stress can be quantified using this method. We also demonstrated the SpARS method using recently published round robin case studies. The newly developed model will be useful for aircraft structural fatigue crack growth analyses to incorporate residual stress fields for extending inspection intervals for fatigue and fracture critical structures.     

Development of single drive electrode electrical resistance tomography system

A new electrical resistance tomography system has been designed using the single drive electrode method. The bidirectional pulse current is adopted in this system as the exciting current. The model of this new method has been set up in ANSYS and validated by simulation and actual measured data. Based on this model, the influence of medium resistivity and connected resistance as well as the influence of medium distribution on the measured data is studied. The experimental results and the reconstructed images are presented at last to testify to the reliability of the new system and the feasibility of the new method.     

解决无线传感器网络能量洞问题的贪婪算法

无线传感器网络中的能量洞问题是影响网络寿命的关键因素之一。在基于环模型的多跳传感器网络中,通过优化所有环的传输距离可以有效地延长网络寿命。提出了一种近似的贪婪算法（ASGT）,该算法将最优传输距离序列问题转化为最优生成树问题,在降低搜索（算法）复杂度的同时得到与最优解近似的结果。模拟实验证明了采用ASGT算法的网络寿命逼近于理想最优序列下的网络生命时间,并且与已有的文献算法相比,ASGT可以延长网络寿命两倍以上。     

基于密度加权的粗糙K-均值聚类改进算法

针对粗糙K-均值聚类算法中类均值计算式的特点,提出了一种改进的粗糙K-均值算法.改进后的算法基于数据对象所在区域的密度,在类的均值计算过程中对每个对象赋以不同的权重.不同测试数据集的实验结果表明,改进后的粗糙K-均值算法提高了聚类的准确性,降低了迭代次数,并且可以有效地减小孤立点对聚类的影响.     

低临界胶束浓度PEGMA-b-PCL的制备及其 药物缓释性能

以ε-己内酯（ε-CL）为疏水链段,聚乙二醇甲醚甲基丙烯酸酯（PEGMA）为亲水链段,4-氰基-4-[(十二烷基硫基硫羰基)硫基]戊酸（CDPA）为可逆加成-断裂链转移（RAFT）试剂,在以甲苯为溶剂、N2氛围、80 ℃、反应24 h的条件下,通过RAFT聚合法制备了两嵌段聚合物PEGMA-b-PCL。将其自组装为胶束用作纳米药物载体,并以姜黄素（Cur）为胶束负载药物。考察了两嵌段聚合物结构、分子量及分布,表征了胶束载体粒径、形貌,测试了胶束载体的载药和释药性能。结果表明,不同嵌段聚合物相对分子质量范围为478~7318,此类聚合物具有较低的临界胶束浓度（CMC）,在常规条件下（pH=7.4）其范围为0.920~1.600 μg/mL。胶束载体粒径范围为:68.34~186.30 nm。当n(CDPA)∶n(ε-CL)=1∶200时,胶束载药量和包封率最高,可达12.05%和75.26%。在不同pH值环境下,药物缓释性能可达15 d,其中pH=5.0时释药量可达35.38%。     

基于渐进式分解架构的风电时间序列预测

准确预测风电机组各项指标对准确管控机组和调控电网的供需有着重要意义. 预测指标任务可抽象为风电时间序列预测任务. 目前时间序列预测模型主要采用深度学习模型, 但是风电时间序列具有较强的波动性和随机性, 导致绝大部分模型不能较好挖掘风电时间序列的复杂演化特性. 为解决上述问题, 提出了一种基于渐进式分解架构的风电时间序列预测方法, 该方法首先应用神经网络池化分解方法将复杂的依赖关系简化并应用注意力机制学习长期趋势, 然后运用多变量融合捕捉模块增强了网络整体的多变量关联挖掘能力, 最后, 融合趋势项和周期项对风电时间序列做出准确的预测. 实验结果表明, 该方法在风电时间序列的多步预测中均方误差相比基线模型至高可提升24%, 在多尺度预测长度下表现出预测性能稳定提升的同时, 计算效率显著优于同类模型.     

Unsourced Multiple Access for 6G Massive Machine Type Communications

Unsourced multiple access(UMA) is a multi-access technology for massive, low-power, uncoordinated, and unsourced Machine Type Communication(MTC) networks. It ensures transmission reliability under the premise of high energy efficiency.Based on the analysis of the 6G MTC key performance indicators(KPIs) and scenario characteristics,this paper summarizes its requirements for radio access networks. Following this, the existing multiple access models are analyzed under these standards to determine U...     

天广直流输电系统过负荷功能研究

直流输电系统的快速响应和过负荷能力有利于提高整个电网的稳定性,基于天广直流输电系统的控制策略,介绍了其过负荷功能的计算和实现方法,并结合实例进行说明,最后还讨论了运行中应引起重视的相关问题。