Preparation and characterization of glass fiber–reinforced polyethylene terephthalate/linear low density polyethylene (GF‐PET/LLDPE) composites

Polyethylene terephthalate (PET) was melt blended with linear low density polyethylene (LLDPE) and subsequently compounded with glass fibers (GF) as reinforcements at percentages ranging from 15 to 45 wt% of LLDPE and 5 to 30 wt% of GF. Thermal, morphological, and mechanical properties of the prepared composites were investigated. It was found that compounding PET/LLDPE blends with GF would be beneficial in producing composites that are thermally stable with good mechanical properties. For example, the impact strength of the composites containing 85/15 wt% (PET/LLDPE) at relatively high loading of GF, ie, from 15 to 30 wt%, was higher than that of the GF‐reinforced neat PET. When increasing the percentage of LLDPE in the composites, the impact strength increased with increasing GF content, and this was also better than that of GF‐reinforced PET whose impact strength drastically decreased upon increasing the GF%. The improvement in mechanical properties of the composite, we suggest, should be correlated with the morphologies of the composites where the visualized interface adhesion tended to be better at higher loadings of both LLDPE and GF.     

Ortho lithiation-in situ borylation of substituted morpholine benzamides

Morpholine amides are cheap and safe alternative to Weinreb amides as acylating agents of organometallic species. Herein, the in-situ lithiation/borylation of 18 ortho- meta- and para-substituted morpholine benzamides has been investigated. 10 of the 18 substrates provided the desired boronic esters as the major isomer (>90% regioselectivity) in crude isolated yields ranging from 68 to 93%. The synthetic usability of such building blocks was subsequently illustrated via the synthesis of a kinase inhibitor.     

Opinion strength influences the spatial dynamics of opinion formation

Opinions are rarely binary; they can be held with different degrees of conviction, and this expanded attitude spectrum can affect the influence one opinion has on others. Our goal is to understand how different aspects of influence lead to recognizable spatio-temporal patterns of opinions and their strengths. To do this, we introduce a stochastic spatial agent-based model of opinion dynamics that includes a spectrum of opinion strengths and various possible rules for how the opinion strength of one individual affects the influence that this individual has on others. Through simulations, we find that even a small amount of amplification of opinion strength through interaction with like-minded neighbors can tip the scales in favor of polarization and deadlock.     

A fractal model of reinforcement of elastoplastic nanocomposites

Within the framework of fractal analysis and percolation theory, an alternative model of reinforcement of filled polymers is offered. Practically, this model can be used only to describe the reinforcement of nanocomposites, because, according to the treatment considered, a pronounced reinforcement can be reached only at ratios of filler particle diameter to the statistical segment length of about 10 and less. A theoretical calculation showed a good qualitative and quantitative agreement with experiments. The type of reinforcement mechanism of composites is determined by the type of the space (fractal or Euclidean) in which the structure of the polymeric matrix is formed. __________ Translated from Mekhanika Kompozitnykh Materialov, Vol. 42, No. 6, pp. 797–802, November–Decem ber, 2006.     

带时间窗的车间搬运机器人路径优化建模及算法研究

本文以车间搬运机器人为研究对象,在考虑时间窗的前提下,求解机器人进行物料配送和成品回收场景下的路径优化问题。提出一种强化学习遗传蚁群算法,首先利用扫描法求解初始搬运机器人的数量,并将子路径节点的几何中心设置为虚拟节点,利用嵌入遗传算子的蚁群算法求解连接虚拟节点的最优路径,再利用强化学习算法求解子路径的最优结果;最后将基本成本、运输成本和时间惩罚成本的加权和作为目标解,并最终求出满足约束条件的最优解。通过与基准问题求解结果对比,验证了强化学习遗传蚁群算法的优越性。     

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。     

对岩体加固工程的水文地质条件分析

裂隙岩体的透水性各向异性和透水率大小的随机性,决定着渗控 (加固 )工程钻孔方位、倾角的多样性。它说明渗控工程设计中把裂隙岩体透水性假定成各向同性是不合实际的。应根据岩体的水文地质条件,寻找出裂隙隙宽、透水性和透水率相对较大的方位和倾角作为渗控工程钻孔的矢量。     

Action learning versus strategy learning

This article seeks to ascertain whether the strategy‐learning model of Hanaki, Sethi, Erev, and Peterhansl (2003) better accounts for observed behavior than do the various action‐learning models. It does so by measuring the goodness‐of‐fit of the models' predictions against published experimental results for such games as Coordination, Prisoner's Dilemma, and Chicken. The fit is measured via the mean squared deviation (MSD) between the observed behavior and the one predicted by the model. The results show that, for Chicken, the strategy‐learning model fits the observed data much better than do the action‐learning models. The best action‐learning model, on the other hand, fits the observed data well in Coordination. Overall, the strength of the strategy‐learning model is best shown in games where alternations between the two stage‐game Nash equilibria are often observed in the laboratory experiments. © 2004 Wiley Periodicals, Inc. Complexity 9: 41–50, 2004     

ChatGPT在计算结构力学领域的应用初探与浅析

OpenAI开发的人工智能聊天机器人ChatGPT自发布以来,受到了社会各界的广泛关注。凭借卓越的分析计算能力和良好的开放性,该模型已作为一种全新服务信息检索和问题解决的助手。平面桁架结构作为结构力学中的常见结构,在工程实践中通常采用刚度法编写计算程序;然而,初学者或缺乏力学背景的研究人员难以高质量地快速完成编程任务。本文首先简要介绍了ChatGPT的原理及应用,然后以使用ChatGPT快速生成平面桁架计算程序为例,探索并展示了ChatGPT辅助完成计算结构力学程序编制的卓越性能与具体使用方法,最后讨论了以ChatGPT为代表的生成式人工智能在计算结构力学程序开发中的应用和挑战。     

集中载荷作用下FRP布加固带裂缝木梁的弯曲

将FRP布视为正交各向异性材料,考虑其拉伸与压缩时的双弹性模量性质,给出了四周粘贴FRP布加固带裂缝木梁四点弯曲的边值问题,得到了FRP布加固木梁挠度的解析解,并验证了其有效性和适用性.参数分析表明:相比于侧面粘贴CFRP布,在木梁受拉侧沿轴向粘贴CFRP布的刚度加固效果更加显著;CFRP布加固木梁的挠度随CFRP加固布厚度和弹性模量的增加而减小,但当侧贴CFRP布厚度增加到某一值时,继续增加厚度对木梁挠度的减少效果已不明显;当受拉侧CFRP布厚度较小时,木梁挠度随CFRP布厚度的增加非线性减小,而当受拉侧CFRP布厚度较大时,木梁挠度随CFRP布厚度几乎呈线性减小.同时,当侧贴CFRP布的剪切模量很大时,此时,CFRP布加固带裂缝木梁的挠度趋于CFRP布加固完整无裂缝木梁的挠度,此时,CFRP加固完全消除了裂缝因素.