Experimental analysis of the natural vibrations and stability of cylindrical shells reinforced with rectangular plates

The paper presents experimental results on the effect of reinforcing cylindrical shells with rectangular plates on the axial compressive critical loads and the natural frequencies and modes of two sets of shells __________ Translated from Prikladnaya Mekhanika, Vol. 44, No. 5, pp. 100–103, May 2008.     

边坡变形的分布式光纤监测模拟试验研究

布里渊散射光时域反射测量技术(BOTDR)作为一项新型光电传感监测技术,因其具有良好的抗干扰、长距离、可植入性和分布式监测的特点而被广泛应用于结构工程健康监测中。而直接将光纤布设在土体中则存在变形协调性差、易折断及空间定位难等问题。本次研究通过室内小比例尺模型试验,分别将光纤植入土工布和土工格栅等柔性复合材料中并一起铺设在边坡模型不同深度处,利用BOTDR监测边坡在外荷作用下的变形特征。试验结果表明,布设在土工格栅中的光纤稳定性最好; 土工布中的光纤变形协调性和敏感性优于土工格栅; 通过合理布置光纤能够对异常应变进行较为准确的识别和定位。试验初步验证了该方法应用于土质边坡变形监测的可行性。     

钢筋混凝土平面构件的配筋优化

钢筋混凝土D区构件由于不满足平截面假定,以往多采用试验加经验的方法进行配筋设计,误差较大,结果多偏于保守。由于钢筋混凝土构件是由钢筋和混凝土两种材料组成的复合构件,它的工作本质可抽象为由混凝土压杆和钢筋拉杆构成的、形状自由的拉压杆模型。引入一种新的结构优化方法遗传演化算法建立反映构件最实质工作机理的拉压杆模型,在所获拉压杆模型的指导下,拉杆位置布置受拉钢筋,压杆位置认为由混凝土承担,完成钢筋混凝土D区构件的配筋设计。首先以一根钢筋混凝土简支深受弯构件为例证明这种方法的可行性,根据所求得的拉压杆模型配置的钢筋数量少于现行规范用量。另外这种方法还被证明能方便地找到包括钢筋混凝土简支深受弯构件、牛腿、框架节点等典型D区构件的拉压杆模型,并据此给出相应的配筋指导。     

A Novel Conflict Management Method Based on Uncertainty of Evidence and Reinforcement Learning for Multi-Sensor Information Fusion

Dempster–Shafer theory (DST), which is widely used in information fusion, can process uncertain information without prior information; however, when the evidence to combine is highly conflicting, it may lead to counter-intuitive results. Moreover, the existing methods are not strong enough to process real-time and online conflicting evidence. In order to solve the above problems, a novel information fusion method is proposed in this paper. The proposed method combines the uncertainty of evidence and reinforcement learning (RL). Specifically, we consider two uncertainty degrees: the uncertainty of the original basic probability assignment (BPA) and the uncertainty of its negation. Then, Deng entropy is used to measure the uncertainty of BPAs. Two uncertainty degrees are considered as the condition of measuring information quality. Then, the adaptive conflict processing is performed by RL and the combination two uncertainty degrees. The next step is to compute Dempster’s combination rule (DCR) to achieve multi-sensor information fusion. Finally, a decision scheme based on correlation coefficient is used to make the decision. The proposed method not only realizes adaptive conflict evidence management, but also improves the accuracy of multi-sensor information fusion and reduces information loss. Numerical examples verify the effectiveness of the proposed method.     

Circular Delaminations - the Effect of Thermal Strains on the Strain Energy Release Rate

The analysis presented focuses on the extent to which the thermal loading resulting from a difference between the curing and service temperatures and from variations in the thermal-expansion coefficients from layer to layer can affect the growth of delaminations. Square laminate plates containing circular delaminations are examined. The reinforcement combinations for the delaminated layer and the core plate considered are [0°]/[90°], [90°]/[0°], [0°]/[±45°] _s , and [±45°] _s /[0°]. The analysis is carried out using the FEM. The strain energy release rate components are calculated using the modified crack-closure integral method. The results obtained show that, for all the reinforcement combinations studied, with the exception of [±45°] _s /[0°], a temperature drop considerably reduces all the strain energy release rate components, but only minor changes in their proportion occur. In the case of the [±45°] _s /[0°] plates, all these components increase, and noticeable changes in their proportion are also observed.     

高强钢筋混凝土单向板在非接触爆炸下的抗爆性能研究

钢筋混凝土(RC)单向板是桥梁建设的重要组成部分. 对6块高强RC单向板进行非接触爆炸试验, 研究HRB400、HRB500和HTRB600高强RC单向板的抗爆性能, 分析爆炸后试件的破坏形态和参数. 结果表明 非接触爆炸下, 3种类型高强钢筋混凝土单向板的破坏形态相似, 单向板整体响应后出现弯曲破坏, 侧表面出现多条弯曲破坏裂缝; 在2.5kgTNT作用下的HTRB600高强RC单向板的裂缝数量和裂缝类型与2.1kgTNT作用下的HRB500高强RC单向板和1.7 kgTNT作用下的HRB400高强RC单向板差别不大, 相差范围在1条裂缝以内; HTRB600高强RC单向板在承受更大载荷时, 其平均加速度峰值比低载荷下HRB500、HRB400高强RC单向板分别增加45.1%和88.6%, 其抗弯承载力更好, 刚度更大.     

钢筋混凝土圆形截面非均匀配筋的图算法

圆形截面是工程中常使用的截面形式之一,但圆形截面的配筋计算较为困难,存在双重非线性(材料和截面宽度变化的非线性),《混凝土结构设计规范》给出了计算均匀配筋的超越方程组,且须迭代求解,无法手算.另外,一些圆形截面构件(如桥墩、桩基的预制桩和灌注桩等)的截面尺寸大,构件长,钢筋用量大,若采用均匀布置的配筋方式,中性轴附近的...     

钢筋混凝土旧工业厂房结构加固方案优选

当前人们选择旧工业厂房结构加固方案效率低下,且所考虑的因素较为片面,为了全面、高效地解决这一问题,通过综合考虑安全性、经济性、时间性、可行性和适用性等因素,以加固效果显著的工程案例为标准,以全面的18个参数为评价指标,构建了一种基于蛛网面积相似和形状相似的结构加固方案优选模型。该模型中首先运用熵权法确定18个指标权重,并将参数值归一化处理,随后运用Python计算蛛网结构相似度,检索出与目标范例最为相似的源范例。最后以结构加固效果显著的工程为例,验证了该模型能有效减少主观误差,具有较强的实用性,并以此模型优选出了某轧钢厂房结构加固方案。     

Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning

Mobile crowdsensing (MCS) is attracting considerable attention in the past few years as a new paradigm for large-scale information sensing. Unmanned aerial vehicles (UAVs) have played a significant role in MCS tasks and served as crucial nodes in the newly-proposed space-air-ground integrated network (SAGIN). In this paper, we incorporate SAGIN into MCS task and present a Space-Air-Ground integrated Mobile CrowdSensing (SAG-MCS) problem. Based on multi-source observations from embedded sensors and satellites, an aerial UAV swarm is required to carry out energy-efficient data collection and recharging tasks. Up to date, few studies have explored such multi-task MCS problem with the cooperation of UAV swarm and satellites. To address this multi-agent problem, we propose a novel deep reinforcement learning (DRL) based method called Multi-Scale Soft Deep Recurrent Graph Network (ms-SDRGN). Our ms-SDRGN approach incorporates a multi-scale convolutional encoder to process multi-source raw observations for better feature exploitation. We also use a graph attention mechanism to model inter-UAV communications and aggregate extra neighboring information, and utilize a gated recurrent unit for long-term performance. In addition, a stochastic policy can be learned through a maximum-entropy method with an adjustable temperature parameter. Specifically, we design a heuristic reward function to encourage the agents to achieve global cooperation under partial observability. We train the model to convergence and conduct a series of case studies. Evaluation results show statistical significance and that ms-SDRGN outperforms three state-of-the-art DRL baselines in SAG-MCS. Compared with the best-performing baseline, ms-SDRGN improves 29.0% reward and 3.8% CFE score. We also investigate the scalability and robustness of ms-SDRGN towards DRL environments with diverse observation scales or demanding communication conditions.     

An Application of Inverse Reinforcement Learning to Estimate Interference in Drone Swarms

Despite the increasing applications, demands, and capabilities of drones, in practice they have only limited autonomy for accomplishing complex missions, resulting in slow and vulnerable operations and difficulty adapting to dynamic environments. To lessen these weaknesses, we present a computational framework for deducing the original intent of drone swarms by monitoring their movements. We focus on interference, a phenomenon that is not initially anticipated by drones but results in complicated operations due to its significant impact on performance and its challenging nature. We infer interference from predictability by first applying various machine learning methods, including deep learning, and then computing entropy to compare against interference. Our computational framework begins by building a set of computational models called double transition models from the drone movements and revealing reward distributions using inverse reinforcement learning. These reward distributions are then used to compute the entropy and interference across a variety of drone scenarios specified by combining multiple combat strategies and command styles. Our analysis confirmed that drone scenarios experienced more interference, higher performance, and higher entropy as they became more heterogeneous. However, the direction of interference (positive vs. negative) was more dependent on combinations of combat strategies and command styles than homogeneity.