Development of correlation equations on hydrogen properties for hydrogen refueling process by machine learning approach

The energy transition which refers to shift of the energy system from fossil-based resources to renewable and sustainable energy sources becomes a global issue to mitigate the progression of climate change. Hydrogen can play an important role in long-term decarbonization of energy system and achievement of carbon neutrality. Currently, the utilization of hydrogen in the energy system is focused on a road transportation sector as a fuel in a vehicle fleet.Compressing gaseous hydrogen is the most well-established technology for storage in hydrogen-fueled vehicles. The refueling hydrogen requires short filling time while ensuring the safety of storage tanks in a vehicle. However, a fast filling of hydrogen in high pressure leads to a rapid temperature rise of hydrogen stored in tank. Therefore, many numerical and experimental studies have been carried out to analyze the filling process. Various thermo-physical properties of gaseous hydrogen such as density, viscosity, and thermal conductivity are required for the numerical studies and the accurate hydrogen properties are essential to obtain reliable results.In this work, a polynomial equation is proposed with respect to temperature and pressure in ranges of 223.15 K < T < 373.15 K and 0.1 MPa < P < 100.1 MPa to present various hydrogen thermo-physical properties by adopting different coefficients. The coefficients are determined by a machine learning method to regress the equation using a great number of reference data. The equation is trained, tested, and validated using different datasets for each property. The order of the equation has been changed from 2 to 5. Then, the accuracies are estimated and compared with respect to the order. The average relative errors (REs) of the 5th order equation are assessed to lower than 0.3% except for molar volume and entropy. The accuracy of the equation is also examined with experimental data and other correlation equations for density, viscosity, and thermal conductivity which are required for numerical simulations of hydrogen refueling. The proposed equation presents better accuracy for viscosity and thermal conductivity than literature equations. In density calculation, a literature equation shows better performance than the proposed equation, but the difference between their accuracies is not so significant. In calculation time comparison, it is revealed that the proposed equation rapidly responses adequate to computational fluid dynamics (CFD) simulations.Results of the study can provide accurate and reliable hydrogen property values in a fast and robust means specifically for simulation of hydrogen refueling process, but not restricted only to the process. Correlation equations proposed in the present work can aid in optimizing a hydrogen value chain including production, storage, and utilization by providing accurate hydrogen property.     

A tutorial on the segmentation of metallographic images: Taxonomy,new MetalDAM dataset,deep learning-based ensemble model,experimental analysis and challenges

Image segmentation is an important issue in many industrial processes, with high potential to enhance the manufacturing process derived from raw material imaging. For example, metal phases contained in microstructures yield information on the physical properties of the steel. Existing prior literature has been devoted to develop specific computer vision techniques able to tackle a single problem involving a particular type of metallographic image. However, the field lacks a comprehensive tutorial on the different types of techniques, methodologies, their generalizations and the algorithms that can be applied in each scenario. This paper aims to fill this gap. First, the typologies of computer vision techniques to perform the segmentation of metallographic images are reviewed and categorized in a taxonomy. Second, the potential utilization of pixel similarity is discussed by introducing novel deep learning-based ensemble techniques that exploit this information. Third, a thorough comparison of the reviewed techniques is carried out in two openly available real-world datasets, one of them being a newly published dataset directly provided by ArcelorMittal, which opens up the discussion on the strengths and weaknesses of each technique and the appropriate application framework for each one. Finally, the open challenges in the topic are discussed, aiming to provide guidance in future research to cover the existing gaps.     

机械故障诊断技术及其应用

机械一旦发生故障，轻则停工，影响生产的正常进行，重则造成人身伤亡和财产损失的灾难。因此，为了防患于未然，对机械故障诊断技术进行研究并使其付诸应用，有着重要的现实意义。本文论述了机械故障诊断技术的一般理论、研究方法、应用实例以及它的发展动向。     

CAT777自卸车速度控制计算机译码及信号采集

为了获得最佳功率,CATERPILLAR777型工程自卸车采用前后2套发电机和变速箱系统,2台发电机系统的速度同步,是自卸车取得最大功率和效益的关键,对美国CATERPILLAR777型工程自卸车自动变速控制总成电路进行了剖析和改造。     

沥青路面摊铺不平整的机械性原因分析及对策

分析了机械造成沥青路面摊铺不平整的原因，探讨了处理措施。     

砖混结构住宅楼群整体移动工程的设计与施工

砖混结构具有自重大和抗裂性差等特点。在整体移动的过程中,由于行走基础与老基础以及在建筑物移动方向的前部和后部沉降量的差异,容易导致建筑物在移动过程中开裂甚至破坏。结合郑州某小区7栋砖混结构住宅楼整体移动工程,对其设计与施工中的主要问题开展了讨论。工程每栋建筑物需经历纵向平移、旋转、横向平移和提升过程,克服了该工程建筑体量大、移动距离远、工艺复杂和地质条件差等困难,并根据其受力和变形特点,提出了行走梁和基础设计的原则。     

世亚行贷款公路工程项目投标文件的翻译要点

针对近年来世行、亚行贷款公路项目的增加，山西省各路桥公司亦不断参与的现状，从专业术语、选词、选语态、句子处理等方面阐述了工程项目投标文件的翻译要点，归纳总结了标书翻译的语言特点及汉译英翻译技巧。     

基于空间图解及基础转译的山居空间 模式探析

"山居玖式"以"行望居游"分类山居的方式引发了"将身体运动与山居空间建立转译关系"的思考。基于此启发及园林调研,将"行望居游"的山居方式与典型的山居基本空间建立转译关系,并以空间图解的方法解析归纳出螺旋式、取景式、山房式、回环式、山梯式、并联式、穿越式、点景式8种典型的复合山居空间模式,旨在以"空间"视角深化对园林的认识,并提供园林设计的相关参考。     

城市污水处理过程中壬基酚的迁移转化途径研究

采用GC—Ms法对北京市某污水处理厂各处理单元的壬基酚（NP）分布状况进行了检测，探讨了城市污水处理过程中壬基酚的迁移转化途径。结果表明，城市污水处理厂进水NP平均浓度为19．26μg／L，出水NP平均浓度为4．57μg／L。由于泥区回流液中NP浓度较高，导致NP浓度随水处理流程有先升高后降低的趋势，沉砂池出水NP浓度最高，为进水浓度的1．5倍。在污水处理流程中，除原水外，泥区回流液是NP的一个重要来源；NP的迁出与去除途径包括：初沉池生污泥和二沉池活性污泥的吸附作用，曝气池内的生物降解作用以及随处理出水的排放。     

一种新型动力施加方式在建筑物平移工程中的应用

通过介绍建筑物整体平移工程的几种常用动力施加方法及其存在的一些缺点,介绍了一种新型的动力施加方式。