成分配比对稀土钨电极材料组织及力学性能影响

通过固液掺杂、等静压压制、中频烧结的方法，制备了不同的氧化镧、氧化钇、氧化锆三元掺杂成分比例的钨电极材料烧结棒材，探究了不同成分配比对样品显微组织、第二相粒子分布以及宏观力学性能的影响。结果表明，氧化镧、氧化钇、氧化锆三元复合添加能够有效改善第二相粒子在钨基体中的分布形态，降低第二相在晶界的过度富集，提高钨电极材料的综合力学性能。并且当添加成分镧、钇、锆质量比为3:1:1时，材料具有最好的综合力学性能，致密度可达96.04%，显微硬度可达549.37HV0.3，抗压强度可达3785MPa，原因是此配比下第二相粒子最为细小均匀，弥散程度最高，对基体晶粒的细化作用最好，该配比下钨基体平均晶粒尺寸达到10.3μm。     

Data fusion and transfer learning empowered granular trust evaluation for Internet of Things

In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability.     

Influence of accelerated curing on the compressive strength of polymer-modified concrete

In recent building practice, rapid construction is one of the principal requisites. Furthermore, in designing concrete structures, compressive strength is the most significant of all parameters. While 3-d and 7-d compressive strength reflects the strengths at early phases, the ultimate strength is paramount. An effort has been made in this study to develop mathematical models for predicting compressive strength of concrete incorporating ethylene vinyl acetate (EVA) at the later phases. Kolmogorov-Smirnov (KS) goodness-of-fit test was used to examine distribution of the data. The compressive strength of EVA-modified concrete was studied by incorporating various concentrations of EVA as an admixture and by testing at ages of 28, 56, 90, 120, 210, and 365 d. An accelerated compressive strength at 3.5 hours was considered as a reference strength on the basis of which all the specified strengths were predicted by means of linear regression fit. Based on the results of KS goodness-of-fit test, it was concluded that KS test statistics value (D) in each case was lower than the critical value 0.521 for a significance level of 0.05, which demonstrated that the data was normally distributed. Based on the results of compressive strength test, it was concluded that the strength of EVA-modified specimens increased at all ages and the optimum dosage of EVA was achieved at 16% concentration. Furthermore, it was concluded that predicted compressive strength values lies within a 6% difference from the actual strength values for all the mixes, which indicates the practicability of the regression equations. This research work may help in understanding the role of EVA as a viable material in polymer-based cement composites.     

Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.     

Performance evaluation of structural concrete using controlled quality coarse and fine recycled concrete aggregate

This paper presents the fresh, mechanical, and durability performance, of a structural concrete mix classified as C-1, by the Canadian Standards Association (CSA) made with controlled quality Recycled Concrete Aggregate (RCA). Five mixes with water-to-cementing material (w/cm) ratio of 0.40 were produced with various RCA contents and tested against two 0% RCA control mixes made with General Use (GU) cement, and General Use Limestone cement (GUL). The RCA contents in the mixes were 10%, 20%, and 30% by coarse aggregate volume replacement, as well as 10% and 20% fine and coarse (granular) aggregate volume replacement. All evaluated mixes met the specifications from the CSA for fresh, mechanical, and durability properties. The coarse RCA mixes performed better than the granular RCA mixes in terms of flexural and splitting tensile strengths, linear drying shrinkage, water sorptivity, and rapid chloride-ion permeability, where the test results were significantly affected by the ultra fines present in the granular RCA.     

大宗粉煤灰的综合利用及提质方案

对于大宗粉煤灰原灰进行分选加球磨机粉磨，同时添加合适的激发剂进行提质，可以生产出不同细度和活性的粉煤灰产品，提升粉煤灰在水泥及商品砼中的用量。介绍了某发电公司的粉煤灰处置现状，在此基础上，对商品砼的粉煤灰性能要求进行了大量市场调研，针对性地给出了该公司粉煤灰的提质方案，最后进行了提质粉煤灰的应用市场和产品竞争力分析。     

Stress distribution in thick-walled cylinder due to non-uniform radial pressure on the example of reinforcement corrosion in concrete

This paper presents an analytical solution to the non-uniform pressure on thick-walled cylinder. The formulation is based on the linear elasticity theory (plain strain) and stress function method. As an example, the proposed solution is used to model the stress distribution due to non-uniform steel reinforcement corrosion in concrete. The model is formulated considering different scenarios of corrosion pressure distribution. It is validated against the finite element model for different cases of non-uniform pressure distributions. The results show that the corrosion-induced cracks are likely to start just beyond the anodic zone. This is confirmed by the experimental tests on concrete cylinder exposed to non-uniform accelerated corrosion of steel reinforcement. The model can be effectively used to calculate the distribution of corrosion-induced stresses in concrete.     

Effect of steel slag on 3D concrete printing of geopolymer with quaternary binders

A new type of 3D-printable ‘one-part’ geopolymer was synthesized with fly ash (FA), granulated blast furnace slag (GBFS), steel slag (SS) and flue gas desulfurization gypsum (FGD). The effects of SS content (0–40%) on the rheological properties, 3D-printability, mechanical anisotropy and reaction kinetics of geopolymer were investigated. The yield stress and plastic viscosity monotonically decreased with the increasing SS content. Contrarily, the geopolymer with 10% of SS presented better extrudability, buildability and mechanical strength than those with 0, 20%, 30% and 40% of SS. This was mainly attributed to the conflicting influence of SS on geopolymerization, of which the OH^? produced by hydration of SS raised the alkalinity of the reaction system and accelerated the dissolution of SiO₄^4? and AlO₄^5?, while the low reactivity prohibited the following polymerization process. Furthermore, the 3D-printed geopolymer presented more compact microstructure and less mechanical anisotropy thanks to the crosslinking of morphologically complementary products, including N(C)-A-S-H, C–S–H, AFt and CH, formed via synergistic reaction of FA-GBFS-SS-FGD system.     

When Does Communication Learning Need Hierarchical Multi-Agent Deep Reinforcement Learning

Abstract

Multi-agent systems need to communicate to coordinate a shared task. We show that a recurrent neural network (RNN) can learn a communication protocol for coordination, even if the actions to coordinate are performed steps after the communication phase. We show that a separation of tasks with different temporal scale is necessary for successful learning. We contribute a hierarchical deep reinforcement learning model for multi-agent systems that separates the communication and coordination task from the action picking through a hierarchical policy. We further on show, that a separation of concerns in communication is beneficial but not necessary. As a testbed, we propose the Dungeon Lever Game and we extend the Differentiable Inter-Agent Learning (DIAL) framework. We present and compare results from different model variations on the Dungeon Lever Game.     

混凝土结构的压电声波检测分析

本文介绍了混凝土结构的压电体波和表面波检测的主要进展,对两种压电声波检测的优缺点进行了总结。体波检测设备一般埋入混凝土内部,需要选择合理的检测部位,检测结果较为精确;声表面波检测无需选择特定的部位,但是检测深度有限。在实际检测工作过程中,可以联合两种方法相互验证。