电化学氧化技术在印染废水处理中的应用

电化学氧化技术因其具有高度灵活性、易于控制、污染少等特点倍受研究者的重视。采用电化学氧化技术处理酸性红4B染料废水，考查溶液pH值、电流密度、电解时间和外加电解质对处理效果的影响。采用该方法处理实际印染废水，废水脱色率完全符合有关排放要求。     

两年制高职机械制造专业课程新体系的构建

针对二年制高职教育的特点和机械制造业的发展，对二年制高职机械制造类专业课程体系的改革的具体内容进行了深入的探讨研究，提出了课程体系改革的原则以及优化和整合现设课程；构建基础素质和专业素质两大模块，建立和加强改革的保障体系等方法，是机制专业培养复合型社会急需人才的有效途径。     

基于层次分析法和模糊综合评判的军用飞机技术风险评估

分析了技术风险的内涵和影响因素;结合我国航空项目管理中风险识别的特点,分析了模糊综合评判和层次分析法在军用飞机技术风险管理中的具体应用,给出了技术风险评估指标体系的构建原则和各指标的量化分析方法,并初步建立了新一代军用飞机技术风险的评估体系.     

从国外典型星载铷原子频标看其技术发展

针对美国在星载频标方面的主要原子频率标准,PerkinElmer公司的RAFS星载铷原子频率标准的结构及性能分析,介绍了目前国外星载铷原子频率标准的技术状况及主要性能指标.与普通商用或军用铷原子频标进行了主要性能指标的比较,就其对空间环境的适应性、可靠性、长短指标的保证等方面进行了论述.分析了该技术的发展趋势.     

规范计量管理与监督 提升航天计量技术保障能力

阐述了规范计量管理与监督的意义和目的,详细说明了计量管理与监督的实施途径,描述了航天计量保证工作的内容、特点和一般要求,通过规范计量管理与监督,不断改进和完善计量保证体系,以进一步提升航天计量技术保障能力。     

以项目任务驱动为特色的机械制造技术课程教改探索

围绕高职机电一体化专业《机械制造技术》课程教学，阐述该课程的项目任务模块，并通过课题1的课程教学设计案例，阐述以项目任务驱动为特色的总体思路和主要内容。     

基于工作过程的《机械制造技术》理实一体化教学研究与应用

提出了基于工作过程《机械制造技术》课程的理实一体化教学新思路及具体实施方案,并通过应用实例证明理实一体化教学相对传统教学方法的优越性。     

Space technology transfer: Spin-off cases from Japan

Government organizations have to justify high expenditure during periods of financial crisis such as the one we are experiencing today. Space agencies have attempted to increase the returns on their investments in space missions by encouraging the commercial use of advanced technologies. This paper describes two technology transfer (TT) cases promoted by JAXA, in order to identify the organizational models and determinants of TT. The development of a TT process from space to Earth not only benefits the aerospace industry but also the network of national companies. The aim of the paper is to investigate who the actors are and the nature of their role, as well as the determinants of the TT process in the Japanese space sector. The case studies confirm the typical path of transfer as ‘Earth–space–Earth’.     

轮椅电机传动机构（中轴,齿轮）热处理工艺设计及改进

高精度齿轮高频淬火，选择合适的材料，增加稳定化处理，改善高频加热方法，可有效降低其热加工变形，保证其精度要求。     

On developing data-driven turbulence model for DG solution of RANS

High-order Discontinuous Galerkin(DG) methods have been receiving more and more attentions in the area of Computational Fluid Dynamics(CFD) because of their high-accuracy property. However, it is still a challenge to obtain converged solution rapidly when solving the Reynolds Averaged Navier–Stokes(RANS) equations since the turbulence models significantly increase the nonlinearity of discretization system. The overall goal of this research is to develop an Artificial Neural Networks(ANNs) model with low complexity acting as an algebraic turbulence model to estimate the turbulence eddy viscosity for RANS. The ANN turbulence model is off-line trained using the training data generated by the widely used Spalart–Allmaras(SA) turbulence model before the Optimal Brain Surgeon(OBS) is employed to determine the relevancy of input features.Using the selected relevant features, a fully connected ANN model is constructed. The performance of the developed ANN model is numerically tested in the framework of DG for RANS, where the‘‘DG+ANN" method provides robust and steady convergence compared to the ‘‘DG+SA" method. The results demonstrate the promising potential to develop a general turbulence model based on artificial intelligence in the future given the training data covering a large rang of flow conditions.