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Development of a General Modelling Methodology or Vacuum Residue Hydroconversion

机译:通用建模方法或减压渣油加氢转化的开发

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This work concerns the development of a methodology for kinetic modelling of refining processes, and more specifically for vacuum residue conversion. The proposed approach allows to overcome the lack of molecular detail of the petroleum fractions and to simulate the transformation of the feedstock molecules into effluent molecules by means of a two-step procedure. In the first step, a synthetic mixture of molecules representing the feedstock for the process is generated via a molecular reconstruction method, termed SR-REM molecular reconstruction. In the second step, a kinetic Monte-Carlo method (kMC) is used to simulate the conversion reactions on this mixture of molecules. The molecular reconstruction was applied to several petroleum residues and is illustrated for an Athabasca (Canada) vacuum residue. The kinetic Monte-Carlo method is then described in detail. In order to validate this stochastic approach, a lumped deterministic model for vacuum residue conversion was simulated using Gillespie's Stochastic Simulation Algorithm. Despite the fact that both approaches are based on very different hypotheses, the stochastic simulation algorithm simulates the conversion reactions with the same accuracy as the deterministic approach. The full-scale stochastic simulation approach using molecular-level reaction pathways provides high amounts of detail on the effluent composition and is briefly illustrated for Athabasca VR hydrocr aching.
机译:这项工作涉及精炼过程动力学建模方法的发展,尤其是真空残渣转化的方法。所提出的方法允许克服石油馏分的分子细节的缺乏,并且通过两步程序来模拟原料分子向废水分子的转化。第一步,通过称为SR-REM分子重构的分子重构方法,生成代表该工艺原料的分子合成混合物。第二步,使用动力学蒙特卡洛方法(kMC)模拟这种分子混合物上的转化反应。将分子重建应用于几种石油残留物,并举例说明了阿萨巴斯卡(加拿大)的真空残留物。然后详细描述动力学蒙特卡洛方法。为了验证这种随机方法,使用吉莱斯皮的随机模拟算法对真空残渣转化的集总确定性模型进行了模拟。尽管这两种方法都基于非常不同的假设,但随机模拟算法以与确定性方法相同的精度模拟转换反应。使用分子级反应途径的全面随机模拟方法提供了有关废水成分的大量详细信息,并简要说明了Athabasca VR水力缓冲技术。

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