用神经网络建模和进化优化支持重质原油精炼的碳钢概念设计

L. Torres-Treviño, A. Reyes-Valdes
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引用次数: 3

摘要

整个世界,特别是墨西哥的石油工业一直具有重要的相关性。这个行业面临着两大挑战。一是深海原油的勘探和利用,二是轻质原油的稀缺,实际产量报告重质原油的增加,在开采和精炼过程中产生腐蚀钢。本文提出了一种综合考虑原油的某些特性和精炼过程的温度来设计概念钢的智能系统。结果为在每个细化阶段选择正确的钢材提供了信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Conceptual Design of Carbon Steels to Support Heavy Crude Refinement Using Neural Network Modeling and Evolutionary Optimization
The oil industries in the entire World and particularly in Mexico, have been taking an important relevance. There are two major challenges in this industry. The first one is the exploration and utilization of crude oil in deep sea, the second one is the scarce of light crude, the actual production report an increment of heavy crude, generating corrosion steel in the extraction and refinement processes. This paper presents an intelligent system to design conceptual steels considering its properties, taking into account some properties of oil crude and the temperature of the refinement process. The results provide information to choice the correct steel for every refinement phase.
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