Excited State Modulation for Organic Afterglow: Materials and Applications

Organic afterglow materials, developed recently by breaking through the difficulties in modulating ultrafast‐decayed excited states, exhibit ultralong‐lived emission for persistent luminescence with lifetimes of several orders of magnitude longer than traditional fluorescent and phosphorescent emissions at room temperature. Their exceptional properties, namely ultralong luminescent lifetime, large Stokes shifts, facile excited state transformation, and environmentally sensitive emission, have led to a diverse range of advanced optoelectronic applications. Here, the organic afterglow is reviewed from the perspective of fundamental concepts on both phenomenon and mechanism, examining the technical challenges in relation to excited state tuning and lifetime elongation. In particular, the advances in material design strategies that afford a large variety of organic afterglow materials for a broad utility in optoelectronics including lighting and displays, anti‐counterfeiting, optical recording, chemical sensors and bio‐imaging are highlighted.     

基于RadFET的宽范围电离总剂量效应监测系统及试验研究

设计了一种基于辐射剂量传感器(RadFET)的辐射总剂量监测系统,并利用60Co-γ射线和电子加速器对金属氧化物半导体(MOS)结构的RadFET进行了电离总剂量效应模拟试验,得到了器件阈值电压随辐照剂量的变化情况.结果表明,该器件具有良好的抗辐射能力,累积剂量可达到1.0 ×105 Gy,同时,在空间应用时需重点考虑阈值电压、环境温度以及击穿电压等敏感参数.     

负梯度声速下特征声线与传播时间快速求解方法

求解特征声线最直接的方法是采用"扫描-插值-迭代"的声线跟踪法,过程较复杂,计算速度较慢。将负梯度声速环境下特征声线的起始掠射角表示为声速、海水深度、声源与接收点相对位置的方程,通过采用量子粒子群算法求解方程直接获得掠射角,进而确定特征声线和传播时间。与声线跟踪法相比,所提出的方法由于不存在数值累计误差和角度插值误差,因此精度更高,另外速度也更快,适合浅海负梯度环境下特征声线与传播时间的快速求解。     

提升交互过程时间体验的实验研究

目的通过设计手段来提升交互过程中的用户时间体验。方法以时间心理学为理论基础分析和总结影响人们时间体验的主要因素;以设计和心理学实验挖掘实验载体和进行效果测试。结果提出了设计提升时间体验的策略和原则并以交通灯红灯信号为对象建立假设和实验。基于时距估计的策略和人的时间信号读取习惯对红灯的2个变量——形状和速度进行考察,发现各样本2个变量的不同水平能够引起的时距估计和情绪状况变化。结论验证了时间信号的传达形式可以影响人的时距认知过程从而对提升时间体验具备实际的效果。     

LS-DYNA模拟爆破中时间步长对计算结果影响探讨

为减小LS-DYNA软件模拟工程爆破时产生的误差,探讨了不同输出时间步长Δt对计算结果的影响。通过三个经典算例,数值比较不同时间步长Δt下相应的单元压力、质点速度与加速度的时程曲线的形状与峰值变化规律,并结合实例进行验证。结果表明:Δt值设置越小,绘制出的曲线越平滑,Δt值取1、2或3时的曲线几乎重合;Δt值不为1时,输出的坐标点都包含在Δt值为1的坐标点内;随Δt值增大,结果误差有增大的趋势,但并非严格递增;Δt值等于1时模拟的精确度较高,但求解时间长,且输出数据存储空间大。采用LS-DYNA模拟工程爆破中,Δt值取3~5是比较合理的。     

基于能量自采集的无线传感器网络网关切换机制研究

针对野外传感网系统中采用太阳能供电的网关因天气变化而产生能量供给失效的问题,研究了基于历史能量采集信息和实时气象信息的多网关切换方法。首先基于气象信息决定需要切换的网关和网关切换的时机;其次提出了一种网关选择算法(Easi GS),根据候选网关剩余工作时间让节点先验式选择网关接入,以避免网关失效带来的数据丢失问题,并通过最优网关接入方法降低系统中采集节点的整体能耗;最后根据实际应用关注的数据发送频率、网关恢复时间、节点与候选网关之间的传输距离等信息,通过概率统计的方法对Easi GS的计算开销进行了进一步优化。仿真实验表明,Easi GS能使系统整体能耗达到最优,并且优化后的Easi GS能够有效降低节点上的计算量。     

面向海量NetFlow数据的存储和查询处理方法研究

针对全国骨干网高速海量Net Flow数据到来速度快、数据量大以及对所存数据进行频繁多维查询操作的特点,提出了一种多维属性聚簇存储(MACS)模型。该模型根据实际应用环境中查询的特点对数据进行空间分片,以并行加流水的方式对数据进行存储。此外,为Net Flow提出了一种超多面体的查询模式。真实环境实验结果表明,运用MACS模型实现的系统单点数据实时存储速度达到270万条/s,远远快于其他的数据分析系统,并且多维属性查询的速度优于Hive和Impala。     

Structural damage identification via time domain response and Markov Chain Monte Carlo method

The present work addresses the problem of structural damage identification built on the statistical inversion approach. Here, the damage state of the structure is continuously described by a cohesion parameter, which is spatially discretized by the finite element method. The inverse problem of damage identification is then posed as the determination of the posterior probability densities of the nodal cohesion parameters. The Markov Chain Monte Carlo method, implemented with the Metropolis–Hastings algorithm, is considered in order to approximate the posterior probabilities by drawing samples from the desired joint posterior probability density function. With this approach, prior information on the sought parameters can be used and the uncertainty concerning the known values of the material properties can be quantified in the estimation of the cohesion parameters. The assessment of the proposed approach has been performed by means of numerical simulations on a simply supported Euler–Bernoulli beam. The damage identification and assessment are performed considering time domain response data. Different damage scenarios and noise levels were addressed, demonstrating the feasibility of the proposed approach.     

Analytical study for the estimation of thermal properties of processed meat based on hyperbolic heat conduction model

This study proposes an analytical method in conjunction with existing experimental temperature to estimate the unknown relaxation time and thermal diffusivity of processed meat based on the hyperbolic heat conduction model. This analytical method is a combination of the Laplace transform and least squares methods. The thermal contact resistance at the interface between adjacent samples at different temperatures is assumed to be negligible. The relaxation time is estimated from the temperature jump at a specific measurement location. The thermal diffusivity is determined from the definition of the dimensionless spatial coordinate and the resulting relaxation time. The results show that the relaxation time and thermal diffusivity obtained are in good agreement with the existing results. The obtained dimensionless temperature history at a specific measurement location is close to the experimental temperature data. This means that the Cattaneo–Vernottee (CV) model can be suitable for this study. The proposed analytical inverse method can be applied to determine a more accurate estimate of such problems. A comparison of the estimate obtained from CV and dual phase lag models is made.