蠕墨铸铁中性盐雾腐蚀行为及机理研究

目的揭示蠕墨铸铁的大气腐蚀行为,阐明其腐蚀规律及腐蚀机理。方法采用室内加速中性盐雾腐蚀实验,并用失重法、SEM\EDS、XRD、电化学的方法来表征实验现象。结果蠕墨铸铁在中性盐雾环境中锈层截面具有明显的分层现象,前期腐蚀速率为0.53 mg/(cm~2·h),后期腐蚀速率在波动中总体趋于稳定,为0.36mg/(cm~2·h)。蠕墨铸铁带锈试样的自腐蚀电位(Ecorr)在-680～-600mV之间先减小后增大,极化电阻(Rp)变化趋势与自腐蚀电位(Ecorr)一致,自腐蚀电流(Icorr)大小在整个腐蚀周期内具有明显的波动。蠕墨铸铁在中性盐雾环境中的腐蚀产物为Fe(OH)_3、Fe_2O_3、FeOOH及少量Fe_3O_4和金属碳化物Fe_2C。结论蠕墨铸铁在中性盐雾环境中腐蚀84 h后发展为全面腐蚀,形貌呈沟壑状,腐蚀产物微观形貌呈团簇状和片层状。腐蚀早期,基体表面发生电化学腐蚀形成一层氧化膜,腐蚀介质沿石墨侵蚀基体从而产生内应力,导致外部锈层断裂,同时蠕虫状石墨处腐蚀产物呈疏松团簇状,二者共同构成介质传质通道,使腐蚀更容易发展。     

LY12铝合金摩擦点焊工艺及力学性能

摩擦点焊是在搅拌摩擦焊基础上开发的一种新型固态连接技术.针对2 mm厚的LY12铝合金,研究了摩擦点焊过程中的焊接工艺参数对焊点成形及力学性能的影响.结果表明,当焊接时间一定,搅拌头旋转速度较高时,焊点的表面成形较好;随着搅拌头旋转速度的降低,焊点的表面成形逐渐变差.焊点的抗剪载荷随搅拌头旋转速度增加呈现出先增大后减小的趋势,当搅拌头旋转速度为950 r/min、焊接时间为8 s时,焊点的抗剪载荷达到最大值,为9.33 kN/点.焊点横截面的显微硬度测试结果表明,显微硬度沿匙孔中心呈高-低-较高-低-高的"W"形分布,最小值出现在热影响区,塑性区的显微硬度较高,但略小于母材.     

小型航拍直升机造型设计

为了解决传统小型航拍直升机拍摄效果不稳定的问题,运用工业设计方法整合直升机结构布局,提出了三轴精确定向云台的方案,并将云台放置在机头部位。直升机外形设计不仅着重考虑飞行稳定性、负载能力、拆卸简洁性以及航空拍摄的功能和结构要求,还在符合空气动力学要求的前提下,借鉴仿生设计理念进行外形设计,兼顾视觉美观与特色并存,力求在静态及飞行状态下都能达到较好的视觉识别性。     

加工中心造型的宜人性设计

通过对加工中心结构与外观的研究，分析了数控加工中心的造型宜人性，并完成了其造型的改良没计，从而为企业提高产品的竞争力，作了有实际意义的工作。     

女士皮鞋外观设计需求驱动方式建构

目的 为了科学评价并划分女士皮鞋外观要素的需求类型,将用户需求要素量化分析得出其权重值,从而指导女士皮鞋外观设计,进而提升用户满意度,并构建出以用户需求为驱动方式的女士皮鞋外观设计模型。方法 首先,通过多渠道调研将女士皮鞋及其外观设计要素进行合理分类;其次,制作李克特量表以调研用户外观需求评价,应用Kano模型划分用户外观需求属性类别;最后,借助AHP层次分析法建构女士皮鞋外观要素需求分析模型,计算归纳出不同种类皮鞋各层级外观需求权重,并通过国内外优秀案例检验方法的合理性。结论 建立Kano-AHP的用户需求驱动方式,针对女士皮鞋外观设计要素对其重要度分类进行量化排序,得出女式皮鞋各外观要素在设计评价中的相对权重值,对鞋靴类产品外观设计有现实意义。     

解决3号喷气燃料悬浮物问题采取的措施

针对中国石油某石化公司3号喷气燃料生产中遇到外观不合格等问题进行分析,采取必要的整改措施,从源头抓起,确实改善3号喷气燃料的质量,确保3号喷气燃料生产正常.     

某汽车高光格栅注塑缺陷分析与成型优化

基于Moldflow软件,针对具有复杂曲面的免喷涂高光注塑格栅可能出现缺料、困气和泛白等的外观缺陷,通过局部优化渐变壁厚、优化布置顺序阀热流道系统、改变局部熔体流动方向的设计方法,进而消除产品外观缺陷。经过实际生产验证,制备的高光格栅产品外观品质较优,可实现量产,且大幅降低了产品的报废率,节约了制造成本。     

A mathematical model for simulating heat and moisture transfer within porous cotton fabric drying inside the domestic air-vented drum dryer

A mathematical model was developed to describe the processes of coupled heat and mass and momentum transfer occurring in convective drying of 100% porous cotton fabric. In this model, the variation in both air and fabric properties were expressed as a function of temperature and moisture content. The resulting systems of transient non-linear partial differential equations in the space-time domain together with the set of initial values and boundary conditions were numerically solved by utilizing the finite difference method. A series of laboratory drying experiments were performed using a computer-controlled dehydration system, which was developed to obtain data of drying kinetics under varying operating conditions for the validation of the predicted results from the proposed model. The experimental results has shown a very good agreement with the predictions of the model, which indicates that the proposed numerical model can be used with confidence as a tool in optimizing the design and operation of the fabric drying system. A parametric study was performed using the modeling tool has demonstrated the impact of key operational parameters on the drying kinetics, which has significant meaning on improving fabric’s appearance smoothness and decreasing the damage. It is expected that the model can be applied for other fiber products and processes involving similar phenomena.     

Automated prediction of sensory scores for color and appearance in canned black beans (Phaseolus vulgaris L.) using machine vision

Evaluation of canning quality of beans is commonly carried out by simple visual inspection that is time-consuming, resource intensive, and biased by the experience of the panelist. Moreover, there is not a standard scale to rate visual quality traits of canned beans. In this research, a machine vision system was implemented and tested for automatic inspection of color (COL) and appearance (APP) in canned black beans. Various color and textural image features (average, standard deviation, contrast, correlation, energy, and homogeneity from red, green, blue, lightness, red/green, yellow/blue, hue, saturation and value color scales) were extracted from beans and brine images, and evaluated to predict the quality rates for COL and APP of a group of bean panelists using multivariate statistics. Sixty-nine commercial canned black bean samples from different brands and markets were used for analysis. In spite of the “fair” agreement among the sensory panelists for COL and APP, as determined by multi-rater Kappa analysis, machine vision data based on partial least squares regression model showed high predictive performance for both COL and APP with correlation coefficients of 0.937 and 0.871, and standard errors of 0.26 and 0.38, respectively. When a classification was performed based on both COL and APP traits, a support vector machine model was able to sort the samples into two sensory quality categories of “acceptable” and “unacceptable” with an accuracy of 89.7%. Using simple color and texture image data, a machine vision system showed potential for the automatic evaluation of canned black beans by COL and/or appearance as a professional visual inspection.     

A model of seam pucker and its applications Part I: theoretical

Abstract

This article considers a simple model of the lock stitch (301) seam, and uses it to derive a measure of the severity of puckering in the seam. The numerical value of the measure depends on the bending properties of the fabrics and thread in the seam, together with the tensions in the threads. How the latter may be estimated is discussed.