Abstract
• Severe cryogenic conditions require high reliability on thermodynamic models. • Reliable models allow to avoid overdesigns and energy dissipations. • Different numerical techniques for bubble/dew problems have been analyzed. • Proposed approach can be generally extended to non-cubic Equations of State. • An improvement in algorithm robustness and efficiency have been proven. High accuracy in Equations of State (EoSs) is becoming a more and more critical aspect for design and operational purposes in different areas of chemical and process engineering. It is well-known that improper predictions of mixture properties provide large deviations in process simulations, process control actions, estimation of operative conditions, assessment of performance indexes and optimal unit/process design. These deviations are strongly emphasized when typical operating conditions appear rather severe. One of the most challenging application sectors is represented by cryogenic separations and especially in case their nominal operating conditions approach the critical point. Air Separation Units (ASUs) are the ideal application field to demonstrate these criticisms. In addition, dedicated EoSs sometimes lacks in implementation details and thermodynamic parameters, making the reliability target impossible to be achieved. The present paper is aimed at bridging the current gaps in the implementation of Bender EoS for the reliable prediction of air mixture properties as well as the reliable simulation of ASU plants. The implementation requires the description of robust and efficient algorithms. At last, a quantitative comparison between the proposed approach and the existing solutions is provided.
Highlights
Accurate thermodynamic modeling is fundamental for a precise prediction of fluid properties, especially in the case of mixtures
The present paper is aimed at bridging the current gaps in the implementation of Bender Equations of State (EoSs) for the reliable prediction of air mixture properties as well as the reliable simulation of Air Separation Units (ASUs) plants
In the 1970s, the request for accurate thermodynamic models was partially satisfied by Cubic Equations of State (CEoS) such as, for example, the Soave-Redlich-Kwong (SRK) CEoS [76], and the PengRobinson (PR) CEoS [62]
Summary
Accurate thermodynamic modeling is fundamental for a precise prediction of fluid properties, especially in the case of mixtures. Process System Engineering could be represented as a series of interconnected layers and in this image, the thermodynamic modelling and consequent robust-efficient properties estimation algorithms are the core of this structure [27] It is well-known that more accurate predictions result in a more reliable process design parameters estimation [11,17,20,23,53,55,67], an optimal operative conditions definition [16,18,35,77,95,97], a better units design, a more clear estimation of investment and operative costs [39], more performing process control and a higher reduction in energy consumption [56,60,71]. In the 1970s, the request for accurate thermodynamic models was partially satisfied by Cubic Equations of State (CEoS) such as, for example, the Soave-Redlich-Kwong (SRK) CEoS [76], and the PengRobinson (PR) CEoS [62] Their developments were originally based on physical principles and they had a theoretical background. They are still considered as best practice in many areas of application given their easiness in numerical implementation (i.e., availability of the analytical solution) and domain application adaptability [3,9,19,61]
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