Particulate Matter Characterization and Coating Microstructure Investigation from a Laser - Paint Removal - System

激光除漆系统的颗粒物表征和涂层微观结构研究

• 批准号: 533143-2018
• 负责人: Huang, Xiao
• 金额: $ 1.82万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=654015
• 关键词: Particulate; Matter; Characterization; Coating; Microstructure

Besnovo (Ajax, ON) is currently using a laser-integrated robotic arm to effectively remove paint by ablation**from a variety of aerospace materials. This process relies on the conversion of laser light into thermal energy**within the coating layer. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) will**be used to evaluate the presence, thickness, and condition of adhesion promoting coatings such that the**interaction between laser light and the coating can be evaluated. The ablation process also generates fine**micron-sized particulate matter (PM). Besnovo would like to further investigate the optimal method of PM**waste extraction. Aiming at better extraction, particulate matter will be characterized experimentally using a**particle size distribution analyzer and numerical simulation of PM dispersion will be performed using**Reynolds Averaged Navier-Stokes (RANS) equations for the air (primary flow) and Lagrangian random-walk**models for the particulate phase.

Besnovo（Ajax，ON）目前正在使用激光集成机械臂，通过烧蚀 ** 有效地去除各种航空航天材料上的油漆。该过程依赖于激光在涂层内转化为热能 **。将使用扫描电子显微镜（SEM）和能量色散光谱（EDS）** 来评价粘附促进涂层的存在、厚度和状况，从而可以评价激光和涂层之间的 ** 相互作用。烧蚀过程还产生细 ** 微米尺寸的颗粒物（PM）。Besnovo希望进一步研究PM** 废物提取的最佳方法。为了更好地提取，将使用 ** 粒度分布分析仪对颗粒物进行实验表征，并使用 ** 雷诺平均纳维尔-斯托克斯（RANS）方程（用于空气（主流））和拉格朗日随机行走 ** 模型（用于颗粒相）对PM扩散进行数值模拟。