Effect of vinyl acetate content on the photovoltaic-encapsulation performance of ethylene vinyl acetate under accelerated ultra-violet aging

The vinyl acetate (VA) content in ethylene vinyl acetate (EVA) can significantly affect its performance as an encapsulant in photovoltaic modules under field conditions. EVA films of varying VA content (18, 24, 33, and 40%) have been prepared using twin screw extruder with the necessary additives and subsequently cured at 150 °C. All the EVA films have been subjected to UV radiation at a wavelength of 340 nm for 1000 and 2000 h to simulate accelerated field aging. The effects of accelerated aging on the gel content, mechanical properties, transmittance, Fourier transform infra-red (FTIR) spectra, thermal stability, degree of crystallinity, and yellowness have been studied. The observations made in this study of UV aging up to 2000 h suggests that the optimum range of VA content in EVA should be between 18 and 33% by weight. VA content beyond 40% degrades almost all properties needed for an encapsulate material after aging of only 2000 h. VA content of around 18% is the most stable under UV aging conditions but has a slightly lower value of transmittance for the unaged sample although the difference in transmittance between different specimens decreases with UV aging. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48268.     

数字化射线检测技术在船舶领域的应用

随着数字射线检测技术的不断发展,CR与DR数字射线检测技术以其检测灵敏度高、检测速度快及底片数据电子化存储等优势越来越广泛地应用于各行业中。针对船舶行业射线检测的主要检测对象(钢板对接焊缝、管路对接焊缝),开展了CR数字射线检测技术等价性评价、典型裂纹试验,以及基于不同种类射线装置的DR数字射线检测工艺试验,验证了数字化射线检测技术在船舶领域应用的适用性。     

专业认证背景下铸造工艺课程设计教学改革的探讨

工程教育专业认证是保证、改进教育质量的重要途经,是以专业全体学生的学习结果为认证的主要目标。铸造工艺课程设计是综合性较强的专业核心课程,对于学生综合能力培养具有重要作用。本文基于对重庆大学材料成型及控制工程专业铸造工艺课程设计课程目标达成情况的分析,对课程教学的教学设计、组织形式、实施方法以及学业成绩评价等方面进行了改进,突出"以学生为中心"的工程应用水平和创新能力的培养。     

基于模糊数和AHP的数控机床可靠性分配方法

针对层次分析法(AHP)处理可靠性分配问题时存在的局限性,将直觉梯形模糊数与层次分析法相结合,提出了一种新的数控机床可靠性分配方法。在确定影响机床可靠性分配的重要因素种类及分配原则后,利用层次分析法确定数控机床可靠性分配问题的层次模型和可靠性分配中影响因素的重要性权重。运用直觉梯形模糊数准确表达出模糊信息和专家意见,最终确定子系统在可靠性分配中的分配比例。以一数控机床为例,通过和层次分析法进行对比,证明了该方法的有效性。     

Quantitative analysis of fuel-saving potential for waste heat recovery system integrated with hybrid electric vehicle

Hybrid electric vehicles (HEVs) with low fuel consumption, low emissions, and long driving range are the ideal transition models between conventional fuel vehicles and pure electric vehicles. The growing demand for increased vehicle efficiency has motivated the introduction of waste heat recovery (WHR) technology in the automotive industry, with the organic Rankine cycle (ORC) as the most promising measure for recycling waste energy. Currently, only a few studies have been conducted to couple HEV and WHR systems. These studies have mainly focused on the hybrid powertrain control strategy, but lack quantitative methods to comprehensively analyze the fuel-saving potential due to the WHR system. In this study, an HEV-WHR integrated system that includes a mechanism-based dynamic model of ORC and a hybrid diesel-electric truck model is established. Further, a quantitative evaluation method that simultaneously considers the negative integrated effects (increased vehicle weight and increased exhaust back pressure) and the positive impact values of the engine, motor, and WHR system on the fuel-saving potential is proposed. Finally, the influence of two environmental factors (wind speed and ambient temperature) on the fuel-saving performance is analyzed. The results reveal that under the standard highway driving cycle (HWY), the negative integrated effects reduce the ideal fuel-saving potential of the HEV-WHR system from 6.10% to 5.42%. However, the optimized performances of the engine, motor, and WHR system improve the fuel-saving rate by 0.39%, 1.81%, and 3.22%, respectively. The results also indicate that the fuel-saving potential increases from 1.62% to 8.60% with increasing wind speed and decreases from 6.70% to 4.25% with increasing ambient temperature.     

基于深度学习的高压油泵可靠性试验故障分析方法研究

介绍了船用柴油机高压油泵可靠性试验平台的系统架构,开展了对试验数据的清洗处理和基于机器学习的试验典型故障的研究。利用TensorFlow平台对试验中两种典型故障进行原因分析和模式识别,建立高压油泵可靠性试验故障诊断模型。结合柴油机高压油泵可靠性试验中大量反复出现的故障数据进行训练,大大提高了故障诊断模型的准确度,为高压油泵生产研制部门提供应急故障处理方案提供了依据,为实现船舶动力行业智能诊断提供了新的思路。     

Analytical framework for ex-post evaluation of transport projects: Lessons learnt on retrospective CBA

This study deals with the ex-post evaluation of ten major transport projects which were co-financed by the European Regional Development Fund and the Cohesion Fund in the period 2000–2013 and located across nine EU Member States. The original contribution of this study is represented by the combination of the traditional ex-post Cost–Benefit approach with a qualitative analysis. Specifically, a retrospective Cost–Benefit analysis is used to quantify the benefits and costs of the projects, then interviews to relevant stakeholders were carried out. Ex-post CBA, when appropriately implemented and integrated with qualitative evidence, represents a powerful tool for supporting decision-making processes and for policy lessons.     

基于双谱特征的行星齿轮箱故障诊断方法

为了研究行星齿轮箱齿面磨损全生命周期实验的退化过程,使用了可以抑制高斯噪声和对信号中产生的频率耦合进行解耦的双谱方法去进行故障特征提取,提出了两个基于双谱的特征指标,双谱熵以及非高斯强度,并通过特征指标评价方法去检验其指标性能。结果表明基于双谱熵具有良好的指标性能,而且对于行星齿轮箱齿面磨损的早期微弱故障十分敏感,适用于行星齿轮箱齿面磨损的故障诊断。     

Multi-stage intelligent operation optimization for a hydrocracking fractionation system with a multi-fractionator series-parallel structure

A fractionation system is an essential unit in the hydrocracking process. Its optimal operation is challenging because of the complexity in the structure of the distillation tower and composition of the stream. In addition, the series-parallel structure between the distillation towers of different techniques aggravates the coupling and complexity of the hydrocracking fractionation system (HFS). This, in turn, increases the time complexity of the optimization problem. In this paper, a rigorous mechanism model of an actual HFS is first applied to describe the operating conditions of the HFS. Then, an improved state transition algorithm (STA) with a staged evaluation strategy is proposed to solve the above problem. To overcome problems caused by the series-parallel structure of HFS, the model is divided into multiple stages for evaluation by mechanism analysis. Furthermore, several typical convergence estimation criteria are introduced to reduce unnecessary model calculations. To solve time-consuming problems associated with HFS optimization, the adaptive change operator is used to improve the search function of the original algorithm and two performance criteria are presented to reduce the optimization time. The proposed algorithm is successfully applied to the operational parameter optimization problem of HFS with a multi-fractionator series-parallel structure. The experimental results indicated that the staged evaluation strategy improved the fast convergence probability of the HFS mechanism model and reduced unnecessary calculations, whereas the improved algorithm increased accuracy and significantly decreased optimization time.     

基于RBF神经网络的露天矿爆破效果预测研究

露天矿爆破是一个受诸多因素共同影响的系统工程,是露天开采的重要环节之一,其爆破效果的优劣直接影响后续工序的完成。提高爆破技术水平和爆破质量,对矿山安全和生产具有重要的意义。本文通过随机森林选择影响爆破效果的主要参数,结合模糊评价确定爆破综合效果,建立了RBF神经网络爆破效果预测模型。将该模型应用于矿山爆破效果预测中,并将爆破现场实测的11组数据作为模型训练样本,另外5组现场数据作为预测样本进行测试,通过与BP神经网络比较,发现RBF神经网络的预测性能更为优越,可广泛应用于现场实践中。