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首页> 外文期刊>Catalysis Today >Simulating vacuum residue hydroconversion by means of Monte-Carlo techniques
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Simulating vacuum residue hydroconversion by means of Monte-Carlo techniques

机译：利用蒙特卡洛技术模拟真空渣油加氢转化

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The present work focuses on the development of a novel methodology for the kinetic modeling of heavy oil conversion processes. The methodology models both the feedstock composition and the process reactions at a molecular level. The composition modeling consists of generating a set of molecules whose properties are close to those of the process feedstock analyses. This synthetic mixture of molecules is generated by a two-step molecular reconstruction algorithm. In its first step, an equimolar set of molecules is built by assembling structural blocks in a stochastic manner. In the second step, the mole fractions of the molecules are adjusted by maximizing an information entropy criterion. Once the composition of the feedstock is represented, the conversion process is simulated by applying, event by event, its main reactions to the set of molecules by means of a kinetic Monte Carlo (kMC) method. The methodology has been applied to hydroconversion of Ural vacuum residue and both the feed and the predicted effluents were favorably compared to the experimental yield pattern.
机译：目前的工作集中在重油转化过程动力学建模的新方法的发展。该方法学在分子水平上对原料组成和过程反应进行建模。组成建模包括生成一组分子，这些分子的性质与过程原料分析的性质接近。这种合成的分子混合物是通过两步分子重构算法生成的。在第一步中，通过以随机方式组装结构块来构建分子的等摩尔组。在第二步中，通过最大化信息熵标准来调整分子的摩尔分数。一旦表示了原料的组成，就可以通过动力学蒙特卡罗（kMC）方法逐事件地将其主要反应应用于一组分子来模拟转化过程。该方法已应用于乌拉尔减压渣油的加氢转化，与实验的产量模式相比，进料和预计的出水均得到了有利的评价。

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