Investigation of liquid water heterogeneities in large area proton exchange membrane fuel cells using a Darcy two-phase flow model in a multiphysics code

Proper management of the liquid water and heat produced in proton exchange membrane (PEM) fuel cells remains crucial to increase both its performance and durability. In this study, a two-phase flow and multicomponent model, called two-fluid model, is developed in the commercial COMSOL Multiphysics® software to investigate the liquid water heterogeneities in large area PEM fuel cells, considering the real flow fields in the bipolar plate. A macroscopic pseudo-3D multi-layers approach has been chosen and generalized Darcy's relation is used both in the membrane-electrode assembly (MEA) and in the channel. The model considers two-phase flow and gas convection and diffusion coupled with electrochemistry and water transport through the membrane. The numerical results are compared to one-fluid model results and liquid water measurements obtained by neutron imaging for several operating conditions. Finally, according to the good agreement between the two-fluid and experimentation results, the numerical water distribution is examined in each component of the cell, exhibiting very heterogeneous water thickness over the cell surface.     

A model of PEMFC-battery system to evaluate inner operating status and energy consumption under different energy management strategies

A hybrid system with jointed battery and PEMFC is popular and of great potential in New Energy Vehicle (NEV) application. However, reliability and efficiency remain to be improved for commercial products. To reflect the complicated physics inside the proton exchange membrane fuel cell (PEMFC), the PEMFC model consisting of inner muti-physics process and other accessories was built, then a complete hybrid system was established when a matched battery, DC/DC, regenerative braking were taken into consideration. Based on the above model, the stack state and system performance under standard cycle for heavy duty vehicle-CWTVC were obtained. According to the simulation results, fuel cell states such as pressure, water content and voltage suffers severe oscillation with external load, especially in the highway cycle. Membrane electrode assembly (MEA) suffers from pressure impact with average value of more than 24 kPa in highway cycle. In the aspect of relative humidity, the PEMFC stack is most threatened in road cycle. As for the hybrid system, its efficiency and state of charge (SOC) fluctuation perform worst in urban cycle and road cycle respectively, while its highest efficiency occurs in road test. Operating mode of fuel cell has influence on hybrid system. When 3-level mode of fuel cell output was applied, the efficiency increased to its peak value at medium level of 28 kW and then declined gradually. H₂ consumption had an opposite trend compared to efficiency. In the aspect of battery SOC, it declines in operating process and its fluctuations decreases when medium level got bigger. The 3-level mode and 4-level mode were compared using this model. It can be concluded that although 3-level mode performs slightly better in hybrid system efficiency, H₂ consumption, pressure impact, it does not have absolute advantage over 4-level mode in other indicators.     

学生参与电气人才创新能力培养的探索

基于“以学生为本”的OBE教育理念，本文对电气人才创新能力培养进行了探索。整个过程将专业课程体系契合学业规划以明确学生学习目标；学生参与理论、实践教学和平台搭建，在夯实其理论知识的同时丰富教学资源；在创新考核中采用“螺旋递进式”的师生互动模式，全程培养学生自主的创新能力。多年实践探索表明学生在课程实践、学科竞赛、论文发表和申报专利等方面的创新能力得到显著提升。     

“电工学”国家级一流课程建设与实践

根据新时代新工科人才需求特点和电工学课程特点,分析非电专业学生的电类实践需求,提出构建电工学课程为核心的电工电子实践创新能力培养新体系。通过优化教学内容、开展教学模式和考核模式改革、构建教学资源体系和进行教师队伍建设,使我校电工学课程教学质量提升、学生工程实践和创新能力提高、学生满意度增加、一流课程建设成效显著。     

科研管理项目管理系统设计与开发

信息化时代推动了我国科研水平飞速增长,为各行业、各领域提供先进的技术与设备支持,以此提升我国整体的GDP水平。文章认为在提升科研水平的过程中,科研项目管理系统起到举足轻重的作用,为科研活动的规范性、合理性与可行性提供了参考标准。     

油品运输中减少能耗的精细化管理措施分析

油品具有两个基本的物理特性,第一个是挥发性,第二个是易燃性。这些物理特性使得油品在运输过程中的能耗现象非常常见,有时候还会引发安全事故。为了让油品在运输过程里面的能耗得到更加有效的控制,就应该对油品消耗管理体系加以改进,使能源能耗控制管理模式的层次不断提升。此外还要对水电气能源进行多层次管理,从而提升企业整体效益并实现节约能源的目标。本文主要对油品运输中优品损耗的精细化管理措施加以研究。     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Historical and contemporary movement and survival rates of walleye (Sander vitreus) in Lake Winnipeg,Canada

Understanding patterns of fish movement in large lake ecosystems is essential for determining appropriate management actions as differences in movement behaviour can influence life history traits such as growth and survival. Lake Winnipeg in Manitoba, Canada supports the 2nd largest walleye (Sander vitreus) commercial fishery in North America. We used mark-recapture models to determine movement and estimate survival of walleye between basins of Lake Winnipeg in historical and contemporary contexts, comparing a tag-recovery study completed historically during 1974–1977 with a contemporary (2017–2019) acoustic telemetry study. Mark-recapture models revealed comparably low but detectable annual transitions between basins from historical (0.3–1.2%) and contemporary datasets (7–8.5%). Historically, fish > 300 mm more frequently moved in a south to north direction. Contemporary estimates suggest similar length-based directionality in that fish > 350 mm were always more likely to move in a south-north direction. Contemporary annual survival derived from mark-recapture models ranged between 27 and 45% and 64.3% when derived from catch curve analysis, while independently derived annual historical survival estimates ranged between 50 and 69% and 45.5% from catch curve analysis. Using the contemporary dataset, we also observed seasonal variation in movement and survival between basins, with the greatest movement across the lake occurring during the fall. Our results demonstrate a persisting pattern of low but measurable movement, suggesting between basin movement is not unusual for Lake Winnipeg. Further, low walleye survival rates reported here for the two time periods studied, support recent management actions to reduce fishing pressure across the lake.     

A survey of dairy goat kid-rearing practices on Canadian farms and their associations with self-reported farm performance

Although future production of dairy goats is influenced by kid-rearing practices, little is known regarding which practices maximize kid growth, welfare, and future production success. The objectives of this survey study were to (1) identify common rearing practices of Canadian commercial dairy goat farms and evaluate their associations with 6 farm performance indicators and (2) determine if farms could be grouped by management style on the basis of the 6 performance indicators and compare rearing practices common across the different groups. A survey was sent by post or electronic media to reach dairy goat producers across Canada. The questionnaire contained 70 questions on the following areas of kid rearing: kidding management, care of newborn, colostrum management, milk and solid feeding in the preweaning period, health management, disbudding, housing conditions, weaning strategies, record keeping and growth monitoring, and farm performance data. Performance indicators, calculated on self-reported data, were 305-d milk production, preweaning mortality rate, diarrhea and respiratory disease prevalence, average daily gain from birth to weaning, herd milk production, and replacement rate. A total of 175 questionnaires were returned. After applying inclusion criteria, including herd size (≥40 goats) and completeness of surveys, 104 respondents from Ontario (n = 72, 69%), Québec (n = 23, 22%), and the Western provinces (n = 9, 9%) were retained for analysis, representing 29% of all Canadian producers. Farm sizes ranged from 42 to 2,500 (median = 190) goats. A large amount of variation in rearing practices and farm performance was found between farms. Colostrum and milk feeding management were found to be associated with all performance indicators except for kid respiratory disease prevalence, with timing of colostrum delivery and feeding method accounting for most the associations within each of the 2 areas. Replacement rate was mostly affected by whether or not kids were reared with their dam. Herds surveyed in the study could successfully be divided into 3 distinct groups (production-focused, longevity-focused, and low performance), representing different management styles on the basis of farm self-reported performance levels. Rearing practices found to be associated with higher farm performance could be targeted by advisory services to help improve management practices on Canadian dairy goat farms.