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

该小型企业创新研究（SBIR）第二阶段项目将在真空电弧重熔（VAR）过程中提供基于反馈的电弧行为控制规模的商业验证。 这将提高特种金属生产中的VAR性能，从而提高铸锭质量，同时降低电力消耗。 钛和镍合金等特种金属用于航空航天、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危及生命的情况。在VAR炉中，熔化电极和铸锭之间持续的收缩和/或扩散电弧产生的极端温度梯度可能导致非均匀材料和夹杂物缺陷，导致每个铸锭高达8%的产量损失，在整个国内行业中造成10.24亿美元的损失。 在这些金属的熔化过程中，对电弧分布的改进控制有望降低最终产品中的缺陷频率，并提高工艺的总产量。拟议的项目预计将减少这些损失高达50%，通过应用主动，反馈控制的电弧动力学。这种类型的控制预计将提高产量，降低能源需求，并提高整个行业的制造过程的安全性。该项目将导致一个系统，能够检测和操纵VAR处理过程中使用的电弧分布。第一阶段的努力表明，它是可能的，同时检测电弧位置的电极和影响他们的运动，使用电磁线圈，在真实的时间。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验证。在这样做的过程中，将确定和构造用于以比例驱动电弧运动的最佳电磁线圈几何形状、硬件和材料。一系列的工业实验计划，以验证控制系统。在受控和非受控条件下生产的铸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。 类似地，测量的弧分布将用于验证计算凝固建模，其将用于识别可能的缺陷区域。实验数据和验证的模拟结果的结合将被用来通知VAR反馈控制系统关于最佳电弧分布，产生一个改进的控制策略，以定制熔化过程和提高铸锭质量。该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

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.