技术
- 传感器 - 流量计
- 传感器 - 液体检测传感器
适用行业
- 生命科学
- 矿业
适用功能
- 物流运输
- 产品研发
用例
- 数字孪生
- 虚拟现实
服务
- 系统集成
关于客户
安赛乐米塔尔是世界领先的钢铁和采矿公司,业务遍及 60 个国家,并在 17 个国家设有主要炼钢设施。公司拥有员工超过 190,000 名。在最近的一个项目中,该公司的研发团队的任务是优化滨海福斯烧结冷却厂的大型装料溜槽。目标是通过确定一种更好的设计来改善颗粒偏析、磨损和机械阻力,从而提高该设备的可靠性和效率。
挑战
安赛乐米塔尔是世界领先的钢铁和采矿公司,在优化滨海福斯烧结冷却厂的大型装料溜槽时面临挑战。目的是通过确定可增强颗粒偏析、磨损和机械阻力的更好设计来提高设备的可靠性和效率。将热材料装入烧结冷却机的过程经常会导致颗粒分离,从而导致严重的问题,例如传送带上的火灾问题和烧结矿质量问题。研发团队需要研究这些偏析模式,特别是颗粒尺寸的影响以及填充率对烧结流台车中偏析模式的影响。然而,与颗粒尺寸相比,模拟大型系统中的颗粒流是复杂且耗时的。该团队需要一种平衡计算效率和物理真实性的建模策略。
解决方案
安赛乐米塔尔研发团队使用高性能颗粒材料模拟软件 Altair® EDEM™ 来模拟和分析装料溜槽中的颗粒流。 EDEM 提供了预校准的材料模型,使工程师能够创建和校准他们的模型以匹配物理实验。工程师首先分析了烧结流台车中的偏析模式,这与工厂的实验测量结果非常吻合。然后,他们使用不同的颗粒尺寸进行了敏感性研究,以确定更细的材料是否会改变偏析模式。结果表明,颗粒尺寸对偏析模式没有影响。研究小组还研究了填充率对颗粒流动模式的影响,发现大填充率会导致均匀分布,而低填充率则会产生负面影响。利用这些结果,工程师对不同的充电槽场景进行了虚拟测试,以找到满足容量和机械阻力所有要求的设计。
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