Collaborative Research: Investigation of Ion Currents in the Oxyfuel Cutting Flame and their Links to Critical Process Parameters

合作研究:火焰切割火焰中的离子电流及其与关键工艺参数的关系的研究

基本信息

项目摘要

The award seeks to address serious persistent challenges in providing process feedback to better control and fully automate the oxyfuel cutting process. Though it is more than a century old, oxyfuel's (or 'flame-cutting's') unparalleled performance on thick steel has rendered it an enduring favorite in shipyards, building construction, rail, defense, and countless other heavy industries. The harsh operating environment (open flames, extreme heat) limit the ability of contemporary sensor suites to provide reliable data essential for process feedback control and automation. A potential solution to this problem is motivated by preliminary measurements demonstrating that electrical events called 'ion currents' associated with the flame itself can reliably indicate vital process states. The research will probe the underlying physics of the flame via modeling and experimental efforts. If successful the work could realize reliable cost-effective control and automation of the oxyfuel cutting process, a capability of great interest to many core US industries involved in construction, and major equipment manufacture for defense and energy applications. This is a collaborative research, whereby the experimental work will be undertaken at a predominantly undergraduate institute, while most of the modeling efforts will be conducted at the partner university. Engaging undergraduate students in industrially relevant research projects will hopefully encourage and promote advanced manufacturing beyond those immediately involved, and encourage broader participation. Collaboration with the partner university and the industrial partner, IHT-Automation, will also increase the workforce preparedness of both the graduate student and undergraduate students working on this project. This work tests the validity of a reduced-order ion transport model that considers standoff distance, work-surface/kerf chemical activity, and flame chemical activity with respect to the resulting current-voltage characteristic between the oxyfuel cutting torch and the workpiece. A novel spinning disc Langmuir probe technique will establish a spatially resolved map for the ion densities in the flame. Using these data as a reference, a multi-dimensional computational fluid dynamics simulation will be built on recently developed reduced chemical kinetic models to fully resolve the formation and transport of charged species throughout the flow. Subsequent analysis of the modeling and experimental results will validate or reject a highly simplified one-dimensional transport model relating the current-voltage characteristic of the flame to critical events. These include drift in standoff, ready-to-pierce, pierce success/failure, loss-of-cut prediction, drift in fuel/oxygen ratio, flameout, and potentially others.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
该奖项旨在解决在提供过程反馈以更好地控制和完全自动化氧气切割过程方面的严重持续挑战。 虽然它已经有超过世纪的历史,但氧燃料(或“火焰切割”)在厚钢上无与伦比的性能使其成为造船厂,建筑,铁路,国防和无数其他重工业的持久最爱。 恶劣的操作环境(明火、极热)限制了现代传感器套件提供过程反馈控制和自动化所必需的可靠数据的能力。 这个问题的一个潜在的解决方案是由初步的测量表明,与火焰本身相关的称为“离子电流”的电事件可以可靠地指示重要的过程状态。 该研究将通过建模和实验努力探索火焰的基本物理学。如果成功的话,这项工作可以实现对氧燃料切割过程的可靠的成本效益控制和自动化,这对美国许多涉及建筑业的核心行业以及国防和能源应用的主要设备制造业都具有极大的兴趣。这是一项合作研究,实验工作将在一个以本科为主的研究所进行,而大部分建模工作将在合作大学进行。让本科生参与工业相关的研究项目,有望鼓励和促进先进制造业超越那些直接参与,并鼓励更广泛的参与。与合作伙伴大学和工业合作伙伴IHT-Automation的合作也将增加研究生和本科生在该项目中工作的劳动力准备。 这项工作测试的有效性降阶离子传输模型,考虑间距,工作表面/切口的化学活性,和火焰化学活性相对于所产生的电流-电压特性之间的氧燃料割炬和工件。 一种新的旋转圆盘朗缪尔探针技术将建立一个空间分辨的火焰中的离子密度的地图。 使用这些数据作为参考,一个多维的计算流体动力学模拟将建立在最近开发的减少化学动力学模型,以充分解决整个流动的带电物种的形成和运输。 随后的建模和实验结果的分析将验证或拒绝一个高度简化的一维传输模型有关的火焰的电流-电压特性的关键事件。 这些包括偏离、准备穿孔、穿孔成功/失败、切割损失预测、燃料/氧气比漂移、熄火和潜在的其他。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Spatially Resolved Ion Density Measurements in an Oxyfuel Cutting Flame
  • DOI:
    10.1080/00102202.2020.1792458
  • 发表时间:
    2020-07
  • 期刊:
  • 影响因子:
    1.9
  • 作者:
    C. Martin;A. Untaroiu;K. Xu
  • 通讯作者:
    C. Martin;A. Untaroiu;K. Xu
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Alexandrina Untaroiu其他文献

Progress in oxyfuel cutting automation using ion current sensing

Alexandrina Untaroiu的其他文献

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