On second order asymptotic solutions of axial symmetrical problems ofr>0 thin uniform circular toroidal shells with a large parametera 2/R0h

According to the classical shell theory based on the Love-Kirchhoff assumptions, the basic differential equations for the axial symmetrical problems of r>0 thin uniform circular toroidal shells in bending are derived, and the second order asymptotic solutions are given for r>0 thin uniform circular toroidal shells with a large parameter a²/R₀h. In the resent paper, the second order asymptotic solutions of the edge problems far from the apex of toroidal shells are given, too. Their errors are within the margins allowed in the classical theory based on the Love-Kirchhoff assumptions.     

Shear-sensitive chain extension of dissolved poly(ethylene oxide) by aluminate ions

The phase behavior of poly(ethylene oxide) (PEO) in aqueous salt solutions has been studied many times but rarely for solution conditions relevant to the hydration process of cement, where PEO's interactions with surrounding ions modulate its application as both plasticizer and strength-building additive. Here, the conformation, that is, coil size, of PEO was examined in aqueous solutions in the presence of sodium-, calcium- and aluminum-containing salts. Ion-induced conformational changes for a model linear PEO were mostly unremarkable and consistent with past reports. However, trends for aluminum-containing ions, which predominantly occur in water at neutral and basic pH as the monovalent hydroxo-aluminate anion Al(OH)₄⁻, were different: either present as the sodium or calcium salt, PEO's hydrodynamic radius determined by dynamic light scattering was approximately 30% larger than determined by intrinsic viscosity. The intrinsic viscosity was similar to that measured in the presence of simpler monovalent anions. We hypothesize that aluminum containing ions weakly couple the model polymer's hydroxyl end groups (present at just one chain end), creating polymeric aggregates sensitive to disruption by shearing. Supporting our argument, the hydrodynamic radius determined by dynamic light scattering dropped to the intrinsic viscosity value after hydroxyl groups were converted to methoxy groups.     

建筑垃圾再生混凝土的性价比研究

为了能够有效进行材料力学性能及成本耗费的比较研究, 提出了价格-强度比和价格-模量比两个衡量指标. 在再生混凝土材料体系设计方面, 骨料取自建筑垃圾混凝土, 选取了砂率分别为30%、37%和39%的3种材料体系. 通过添加不同比例的矿物掺合料, 形成了不同的材料配合比. 通过一维应力压缩实验, 得到了材料的模量和强度. 通过比较价格-强度比和价格-模量比的定量结果, 得到了性价比最优的材料配合比设计. 研究结果对于合理利用建筑垃圾形成力学性能优良的再生混凝土具有参考意义.     

A multi-channel and multi-user dynamic spectrum access algorithm based on deep reinforcement learning in Cognitive Vehicular Networks with sensing error

In this paper, a spectrum access problem is proposed to improve the spectrum access rates of secondary vehicles in Cognitive Vehicular Networks, where the channel capacity mathematic model is established under the conditions of spectrum sensing errors rates and the dynamic occupancy spectrum rates. Meanwhile, an improved Q-learning method is proposed to conform the dynamic communication under the different conditions of the reward functions. In this function, a Deep Q Network method with a modified reward function (IDQN) is proposed to deal with the situation of multi-vehicle in multi-channel. In order to verify the effectiveness of the IDQN method, the Myopic method, the improved Q-learning method, and the traditional DQN method are compared on Python. The simulation results shown that the proposed IDQN method not only outperforms the compared methods in terms of channel utilization and channel capacity but also improves the ability that the vehicle adapts to the dynamic communication environment.     

Task offloading for vehicular edge computing with imperfect CSI: A deep reinforcement approach

This article examines a multi-user mobile edge computing (MEC) system for the Internet of Vehicle (IoV), where one edge point (EP) nearby the vehicles can help assist in processing the compute-intensive tasks. For the MEC networks, the majority of existing works concentrate on the minimization of system cost of task offloading under the perfect channel estimation, which however fails to consider the practical limitation of imperfect channel estimation (CSI) because of vehicles’ high-mobility. Therefore, the goal of our study is to reduce the delay as well as energy consumption (EC) of computation and communication with imperfect CSI, which are the two significant performance metrics of MEC network. With this aim, we first express the system cost as a form of the linear combination of the delay and EC, and then formulate the optimization problem for the system cost. Moreover, a novel deep approach is proposed, which is integrated by deep reinforcement learning (DRL) with the Lagrange multiplier to jointly minimize the system cost. In particular, the DRL algorithm is employed to obtain the capable offloading strategy, while the Lagrange multiplier is used to obtain the bandwidth allocation. The simulated results are finally presented to show that the devised approach outperforms the traditional ones.     

Role of adsorbed chain rigidity in reinforcement of polymer nanocomposites

The thermomechanical behavior of polymer nanocomposites is mostly governed by interfacial properties which rely on particle–polymer interactions, particle loading, and dispersion state. We recently showed that poly(methyl methacrylate) (PMMA) adsorbed nanoparticles in poly(ethylene oxide) (PEO) matrices displayed an unusual thermal stiffening response. The molecular origin of this unique stiffening behavior resulted from the enhanced PEO mobility within glassy PMMA chains adsorbed on nanoparticles. In addition, dynamic asymmetry and chemical heterogeneities existing in the interfacial layers around particles were shown to improve the reinforcement of composites as a result of good interchain mixing. Here, the role of chain rigidity in this interfacially controlled reinforcement in PEO composites is investigated. We show that particles adsorbed with less rigid polymers improve the mechanical properties of composites. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 9–14     

A new periodic structure composite material with quasi-phononic crystals

Phononic crystals (PCs) provide a new method for vibration insulation and noise reduction. PCs commonly have small bandgap width, and understanding how to expand this bandgap, including the ultra-low band gap, is crucial for applying PCs to vibration reduction in engineering structures. A new periodic structure composite material quasi-PCs is proposed and the high polymer concrete with quasi-PCs structure is conducted. Vibration measurements for the new periodic structure composite material demonstrate that quasi-PC behavior can open the ultra-low frequency band gap. The new periodic structure composite material can be used to reduce vibrations in engineering field.     

Green Effectively Enhanced Extraction to Produce Yttrium(III) in Slug Flow Microreactor

Process reinforcement research was carried out in Y‐junction slug flow microreactors under variable conditions, using EHEHPA (2‐ethylhexyl phosphonic acid mono‐2‐ethylhexyl) to extract yttrium(III) from hydrochloric acid solution. The influence of pH and flow rate on the extraction‐reaction efficiency, slug size, mass transfer performance was assessed. The experimental results showed that maximum extraction‐reaction efficiency of 91.85% can be achieved in the smallest microreactor (residence time is 11.25 s), which was significantly higher than traditional extraction requiring more than 10 min. The slug length tended to decrease with the increase of pH and flow rate. Volumetric mass transfer coefficients for the slug flow microreactors were found to be in the range of 1.39×10^?1—1.642 s^?1 that is several orders of magnitude higher as compared to traditional extractors, which testified the beneficial effects of Y‐junction slug flow microreactor. Significant mass transfer reinforcement has prompted the use of microreactor as a suitable alternative to traditional extractors, which can advantageously improve the economic and environmental development of mineral processing.     

数字散斑技术在混凝土单轴压缩试验中的应用

数字散斑技术作为一种新兴的测量方法,它具有非接触、全场量测、精度高、操作简单等特点,随着计算机技术的迅猛发展,数字散斑技术得到了广泛的应用与研究。针对混凝土在外荷载作用下具有明显的非均匀变化的特征,借助传统的测量方法很难得到混凝土表面的全场变形结果的问题,结合数字散斑相关方法测量技术,开展了混凝土单轴压缩试验,拍摄了混凝土表面在单轴压缩过程中的位移与应变矢量场,为分析混凝土试件的损伤区域奠定了基础;与电测法测量结果进行了对比,其测量结果表明,这两种测量方法误差相对较小,且数字散斑技术能更早的发现混凝土表面的破坏,验证了数字散斑相关方法的准确性和可靠性。借助数字散斑技术可以更加方便准确的得到材料表面的变形场,这也将在一定程度上促进土木工程领域的发展,具有广阔的应用前景。     

硫酸镁侵蚀环境下玄武岩纤维混凝土耐腐蚀及力学性能劣化研究

为了增强混凝土的抗侵蚀性能,对不同纤维掺量混凝土在硫酸镁侵蚀下的耐久性及力学性能进行了试验研究及分析。采用100mm×100mm×100mm的试块,纤维掺量分别为0%、0.05%、0.1%、0.2%、0.3%,浸泡于浓度为5.0%的硫酸镁溶液中,每30d观测表观裂缝、测试吸水率变化;每90d测定力学性能变化,并进行离子浓度测量。结果表明:玄武岩纤维对混凝土承载力及变形能力有一定的提高;玄武岩纤维混凝土与普通混凝土在硫酸镁溶液环境中相比,孔隙率增加速度较慢;但过量纤维反而对耐久性能产生不利影响;玄武岩掺量在0.1%左右时最为经济、合理。另外,针对玄武岩纤维离散困难的问题,提出了粉体颗粒玄武岩纤维离散法。本文研究可为玄武岩纤维混凝土的工程应用提供一定基础。