一种X煤在首钢的应用实践

针对当前优质炼焦煤资源越来越少，而高炉生产对焦炭质量指标要求越来越高的情况下，对具有低灰、高硫特点的X煤进行了系统的炼焦试验研究。结果发现，在炼焦生产中合理配加5%～8%的X煤不会造成焦炭硫分升高的不利影响，焦炭灰分下降明显，强度保持稳定。该研究成果成功应用于首钢炼焦生产，焦炭各项指标均达标，这不仅扩大了炼焦煤的使用范围，而且在资源使用方面为公司焦炭灰分的降低提供了支持。     

A hierarchical simple particle swarm optimization with mean dimensional information

To reduce the negative influence of the overemphasis of gbest the dimensional information of particle is introduced to be a new example. This additional information source is incorporated into simple PSO to establish a simpler position model. Another two simpler position updating models, cognition only model and social only model, based on the simple PSO algorithm are presented as well. Time hierarchy strategy is extended from probability hierarchy, both aiming to make full use of advantages of three models. Three models are used with time or probability hierarchy to update each particle’s position. Thus, two proposed algorithms THSPSO and PHSPSO are finally obtained. Experiments are conducted on fifteen benchmark functions. The results demonstrate the two proposed algorithms both have excellent performances for basic functions compared with other popular PSO variants. Probability hierarchy strategy is more effective than time hierarchy strategy in general.     

基于区块链应用模式的铁路旅客身份认证系统

采用“区块链技术+不对称加密+生物识别+身份认证”应用模式，依托智能手机客户端设计与开发一套铁路旅客身份认证系统.基于Ethereum开发平台，应用truffle开发框架，实现铁路旅客身份认证系统智能合约的编写与部署.系统针对传统铁路身份认证模式的不足，将旅客身份数据分布式存储，弱化中心化服务器的压力，提升旅客身份数据的安全性和鲁棒性；进行生物信息认证确保旅客对身份信息的所有权；利用非对称加密技术在保护旅客隐私、实现实名制的前提下增强数据的透明性.基于区块链应用模式的铁路旅客身份认证系统能够让用户身份实现本地存储、信息摘要链上校验，实现铁路旅客身份信息数据访问的细粒度控制，保障铁路旅客身份信息安全，提升铁路旅客的乘车体验.     

Porous Si3N4 ceramics prepared by aqueous gelcasting using low–toxicity DMAA system: Regulatable microstructure and properties by monomer content

In this study, the low–toxicity monomer N, N–dimethylacrylamide (DMAA), serving as both gelling agent and pore–forming agent, was adopted to fabricate porous Si₃N₄ ceramics with a regulatable microstructure and property by aqueous gelcasting. Results indicate that monomer content played an important role in regulating and optimizing the properties of sintered bodies. With increasing monomer content (5.94–30.69?wt%), both slurry viscosity (maximum 0.14?Pa?s at 95.40 s^?1) and green body strength (11.35–49.23?MPa) exhibited monotonic increasing trends, demonstrating superior mechanical properties to those obtained using the neurovirulent acrylamide (AM) gelling system. The increased monomer content not only improved porosity, but also promoted α→β–Si₃N₄ transformation as well as β–Si₃N₄ grain growth through enhancing the connectivity of interlocking pores and accelerating the vapor phase transport during liquid–phase sintering. These variations in phase composition and microstructure derived from the varied monomer content further resulted in monotonic changes in porosity (40.32–51.50%), mean pore size (0.27–0.38?μm), flexural strength (202.77–132.15?MPa), fracture toughness (2.93–2.32?MPa?m^1/2), dielectric constant (3.48–2.78) and loss (3.52–3.09?×?10^?3) at 10?GHz for sintered bodies, displaying an excellent comprehensive properties. This study suggests a promising prospect for DMAA in preparation of high–performance porous Si₃N₄ ceramics by aqueous gelcasting.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

Reliability-based fault analysis models with industrial applications: A systematic literature review

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets-intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their applications, and benefits to the industry. This paper presents a contemporary state-of-the-art systematic literature survey focusing on a comprehensive review of the models for fault detection and their industrial applications. This study uses advanced tools from bibliometric analysis to systematically analyze over 500 peer-reviewed articles on focus areas published since 2010. We first present an exploratory analysis and identify the influential contributions to the field, authors, and countries, among other key indicators.  A network analysis is presented to unveil and visualize the clusters of the distinguishable areas using a co-citation network analysis. Later, a detailed content analysis of the top-100 most-cited papers is carried out to understand the progression of fault detection and artificial intelligence–based algorithms in different industrial applications. The findings of this paper allow us to comprehend the development of reliability-based fault analysis techniques over time, and the use of smart algorithms and their success. This work helps to make a unique contribution toward revealing the future avenues and setting up a prospective research road map for asset-intensive industry, researchers, and policymakers.     

Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology

This work intends to develop an online experimental system for screening of deoxynivalenol (DON) contamination in whole wheat meals by visible/near-infrared (Vis/NIR) spectroscopy and computer vision coupling technology. Spectral and image information of samples with various DON levels was collected at speed of 0.15 m s⁻¹ on a conveyor belt. The two-type data were then integrated and subjected to chemometric analysis. Discriminant analysis showed that samples could be classified by setting 1000 μg kg⁻¹ as the cut-off value. The best correct classified rate obtained in prediction was 93.55% based on fusion of spectral and image features, with reduced prediction uncertainty as compared to single feature. However, quantification of DON by quantitative analysis was not successful due to poor model performance. These results indicate that, although not accurate enough to provide conclusive result, this coupling technology could be adopted for rapid screening of DON contamination in cereals and feeds during processing.     

The effects of porosity,asphalt content and fiberglass incorporation on the tensile strength and resilient modulus of asphalt concrete blends

Asphalt concrete is the prevailing material used for road surface construction. Its adequate characteristics in providing stability, durability and driving safety are controlled by complex interactions between its components. Thus, it is important to estimate the sensitivity of asphalt concrete mechanical properties as a function of its volumetrics. For this study, different combinations between asphalt content (3.5, 5 and 7.5%) and porosity values (above 4%) were used in order to disassociate these properties. The influence of mixing in fiberglass (0.5%) was also analyzed. It was found that porosity is significantly more relevant than the asphalt content in the prediction of tensile strength and resilient modulus of fiber-free asphalt concretes. In fiber-reinforced mixtures, the mechanical properties are improved by increasing the asphalt content, which suggests a better bonding between fibers and aggregates. For both cases, decreasing porosity is beneficial. By grouping both sets of results, it was possible to create a unique theoretical curve for both the tensile strength (q_t) and the resilient modulus (RM). The RM/q_t ratio was 5800 for the fiber-free group, and 3900 for the fiber-reinforced group - suggesting a better fatigue life indicator for asphalt concretes when fibers are added.     

TSL:predicting popularity of Facebook content based on tie strength

The rapid development of online social networks leads to an explosion of information,however,there are great differences in the popularity of different messages,and accurate prediction is always a great difficulty is the current study.Popularity prediction of online content aims to predict the popularity in the future based on its early diffusion status.Existing models for popularity prediction were mostly based on discovering network features or fitting the equation into a varying time function that the accuracy of current popularity prediction model was not high enough.Therefore,with the help of the weak ties theory in sociology,the concept of tie strength was introduced and a multilinear regression equation was constructed combined with the early popularity.A TSL model to predict the popularity of Facebook’s well-known pages was proposed.The main contribution of this article was to solve the problem and few or no work based on sociology.A high linear correlation between the proportion of faithful fans was existed in Facebook homepage with frequent shares in the early and the future popularity.Compared with other baseline models,an experimental study of Facebook (including 1.54 million shares) illustrates the effectiveness of the proposed TSL model,and the performance is better than the existing similar methods.