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Computer Simulation of Pitting Corrosion of Stainless Steels

机译:不锈钢点蚀的计算机模拟

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Stainless steels and other corrosion resistant alloys are generally protected from the environment by ultra-thin layers of surface oxides, also called passive films. Unfortunately, these films are not perfect and their Achilles' heel is a propensity to catastrophic local breakdown, which leads to rapid corrosion of the metallic substructure (see Fig. 1). Aside from the safety and environmental hazards associated with these events, the economic impact is enormous.1 In the oil and gas and petrochemical industries, it is of course usually possible to select from experience a corrosion-resistant alloy that will perform acceptably in a given service environment. This knowledge is to a large extent captured in industry or company-specific standards, such as Norsok M1. However, these selections are typically very conservative because the limits tend to be driven by particular incidents or test results, rather than by fundamental understanding. Decision-making can be very challenging, especially in today's mega-facilities, where the cost of production downtime is often staggeringly large. Thus significant practical benefits could be gained from reliable quantitative models for pitting corrosion of stainless steels. There have been several attempts to develop purely stochastic models of pitting corrosion. On the other hand, purely deterministic models have also been proposed.
机译:不锈钢和其他耐腐蚀合金通常通过超薄表面氧化物层(也称为钝化膜)来保护其免受环境污染。不幸的是,这些薄膜并不完美,其致命弱点是易于发生灾难性的局部击穿,从而导致金属亚结构的快速腐蚀(见图1)。除了与这些事件相关的安全和环境危害外,经济影响是巨大的。1在油气和石化行业中,通常当然可以从经验中选择在给定条件下性能可接受的耐腐蚀合金。服务环境。这种知识在很大程度上被行业或公司特定的标准(例如Norsok M1)所捕获。但是,这些选择通常非常保守,因为限制往往是由特定的事件或测试结果驱动的,而不是基本的了解。决策可能非常具有挑战性,尤其是在当今的大型工厂中,那里的生产停机时间成本通常非常惊人。因此,通过可靠的定量模型对不锈钢进行点蚀,可以获得明显的实际好处。已经进行了数种尝试来开发点蚀的纯随机模型。另一方面,还提出了纯粹的确定性模型。

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