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Simulation of amine plants: fundamental models and limitations

By: Description: 17 pOnline resources: In: Summary: Transcripción del resumen del autor. Computer simulation models are indispensable tools for designing and revamping amine plants. Accurate predictions allow engineers to properly design equipment to meet the target treating or capacity requirements, as well as operate the plant with high reliability over the life of the project. Many simulation programs allow users to quickly and accurately design and rate equipment, to predict equipment deficiencies, and to recognize process limitations. However, not all simulation models perform equally well. This paper will review the basic fundamental theories and models that are used in amine simulation programs. We will discuss some areas of shortcomings and areas of advantages of these models and simulation approaches. Finally, we will examine some operating plant data to provide insight into how these models can be used to predict amine plant performance and the pitfalls of missing key design points.
Item type: Congresos (trabajos presentados)
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Transcripción del resumen del autor. Computer simulation models are indispensable tools for designing and revamping amine plants. Accurate predictions allow engineers to properly design equipment to meet the target treating or capacity requirements, as well as operate the plant with high reliability over the life of the project. Many simulation programs allow users to quickly and accurately design and rate equipment, to predict equipment deficiencies, and to recognize process limitations. However, not all simulation models perform equally well. This paper will review the basic fundamental theories and models that are used in amine simulation programs. We will discuss some areas of shortcomings and areas of advantages of these models and simulation approaches. Finally, we will examine some operating plant data to provide insight into how these models can be used to predict amine plant performance and the pitfalls of missing key design points.



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