SBIR Phase II: Vacuum Arc Control using Arc Position Sensing and Induced Magnetic Fields

这个小型企业创新研究(SBIR)第二阶段项目将在真空电弧重熔(VAR)过程中基于反馈控制电弧行为的规模上提供商业验证。这将改善VAR在特殊金属生产中的性能，从而在降低电耗的同时提高钢锭质量。特殊金属，如钛和镍合金，用于航空航天、能源和医药等行业的关键高性能部件，这些部件的故障可能导致灾难性的系统故障和潜在的生命危险情况。在VAR炉中，熔化电极和钢锭之间持续的收缩和/或扩散弧产生的极端温度梯度可能会导致非均匀材料和夹杂物缺陷，导致每个钢锭的成品率损失高达8%，在整个国内行业造成10.24亿美元的损失。改善对这些金属熔化过程中的电弧分布的控制，预计将减少最终产品中的缺陷频率，并提高该工艺的总成品率。通过应用弧光动态的主动反馈控制，该项目有望将这些损失减少高达50%。这种类型的控制有望提高产量，降低能源需求，并提高整个制造过程行业的安全性。该项目将产生一个能够检测和操纵VAR处理过程中使用的电弧分布的系统。第一阶段的工作表明，使用电磁线圈实时检测电极上的电弧位置并影响其运动是可能的。在第二阶段，电弧测量将通过反馈耦合，以控制工业规模研究VAR中的电弧分布，提供工业规模的概念证明。在这样做的过程中，将识别和构建用于驱动大规模电弧运动的最佳电磁线圈几何形状、硬件和材料。为了验证该控制系统，计划进行一系列工业实验。在受控和非受控条件下生产的钢锭的化学成分将被表征，以将缺陷与观察到的电弧行为相关联，并确定最佳控制参数。同样，测量的电弧分布将用于验证计算凝固模型，该模型将用于识别可能的缺陷区域。实验数据和经过验证的模拟结果的组合将被用于向VAR反馈控制系统提供关于最佳电弧分布的信息，从而产生用于定制熔化过程和提高钢锭质量的改进控制策略。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This Small Business Innovation Research (SBIR) Phase II project will provide commercial validation at scale of feedback-based control of arc behavior within the vacuum arc remelting (VAR) process. This will improve VAR performance in the production of specialty metals, resulting in improvements to ingot quality while reducing electricity consumption. Specialty metals, such as titanium and nickel alloys, are used in critical high-performance parts in industries such as aerospace, energy, and medicine, where the failure of these parts may lead to catastrophic systems failures and potentially life-threatening situations. In a VAR furnace, extreme temperature gradients from constricted and/or diffuse arcs sustained between the melting electrode and ingot can cause non-homogeneous material and inclusion defects, resulting in up to 8% yield loss per ingot, representing $1.024 billion in losses across the domestic industry. Improved control over the arc distributions during the melting of these metals is expected to decrease the frequency of defects in the final product and increase overall yield from the process. The proposed project is expected to reduce these loses by up to 50% through the application of active, feedback control of the arc dynamics. This type of control is expected to increase yield, decrease energy requirements, and increase safety of the manufacturing process industry-wide.This project will result in a system capable of detecting and manipulating the distribution of the arcs utilized during VAR processing. The Phase I effort showed that it is possible to simultaneously detect arc locations on the electrode and influence their movements, using electromagnetic coils, in real time. In Phase II, the arc measurements will be coupled through feedback to control the arc distribution in an industrial-scale research VAR, providing proof of concept at industrial scale. In so doing, the optimal electromagnetic coil geometry, hardware, and materials for driving the arc motion at scale will be identified and constructed. A series of industrial experiments are planned to validate the control system. The chemical composition of the ingots produced during controlled and uncontrolled conditions will be characterized to correlate defects with observed arc behaviors and to identify optimal control parameters. Similarly, the measured arc distributions will be used to validate the computational solidification modeling, which will be used to identify probable defect regions. The combination of experimental data and validated simulation results will be used to inform the VAR feedback control system regarding optimal arc distribution, yielding an improved control strategy for tailoring the melt process and improving ingot quality.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.