Abstract
Publisher Summary This chapter discusses the dynamic optimization for air separation plants (ASPs). Linde's process simulation and optimization tool have been extended with optimization features for the formulation and solution of optimal control and dynamic parameter estimation problems. The optimization problem is solved with state-of-the-art sequential quadratic programming (SQP) methods. Sensitivity calculations and appropriate discontinuity handling are essential parts of the algorithm. Computation of optimal load change policies for ASP and parameter identification for a gas bottle filling process shows the applicability of the chosen approach. An ASP consists of three major parts: feed air preparation, cooling, and rectification. A standard configuration of ASP is given. To accelerate the filling process, the heat balance of the bottle system must be investigated. To determine the heat flows in the system, coefficients for gas-bottle heat transfer need to be known. The newly implemented algorithms are applied to a model tuning problem where constant heat transfer coefficients are identified based on data from experiments.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
