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Optimization of the direct synthesis of dimethyl ether from CO2 rich synthesis gas: closing the loop between experimental investigations and model-based reactor design

机译:CO2富合成气中二甲醚直接合成的优化:关闭实验研究与模型基反应器设计的环

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摘要

Reaction kinetic modeling, model-based optimization and experimental validation are performed for the direct synthesis of dimethyl ether from CO2 rich synthesis gas. Among these disciplines, experimental methods and models are aligned in a stringent way of action, , the same setup and models are applied throughout the whole contribution. First, a lumped reaction kinetic model from the literature is modified and parametrized to fit a vast array of 240 data points measured in a laboratory fixed bed reactor. The data were acquired using a mechanical mixture of the commercial catalysts CuO/ZnO/Al2O3 and γ-Al2O3.For this setup, a predictive model is derived and applied within dynamic model-based optimization. Here, the single-pass CO conversion serves as objective function while the operating conditions and composition of the mixed catalyst bed are the optimization variables. Finally, the optimization results obtained numerically are validated experimentally verifying the identified performance enhancement qualitatively. The remaining quantitative deviations yield valuable insights into model and methodological weaknesses or inaccuracies, closing the loop between kinetic investigations, model-based optimization and experimental validation.
机译:反应动力学建模,基于模型的优化和实验验证,用于直接合成二甲醚来自CO 2富含合成气。在这些学科中,实验方法和模型以严格的作用方式对齐,在整个贡献中应用相同的设置和模型。首先,改变文献的集总反应动力学模型和参数化,以适合在实验室固定床反应器中测量的大量240个数据点。使用商业催化剂CuO / ZnO / Al2O3和γ-Al2O3的机械混合物获得数据。对于该设置,导出并应用于基于动态模型的优化内的预测模型。这里,单通过CO转化物用作目标函数,而混合催化剂床的操作条件和组合物是优化变量。最后,在数值上获得的优化结果经过实际验证确定的性能增强定性。剩余的定量偏差将有价值的见解,以模型和方法论弱点或不准确性,关闭动力学调查,基于模型的优化和实验验证之间的环路。

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