Systematic optimisation technology for high-level screening and scoping of complex distillation systems |
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| Affiliation: | 1. From the Division of Endocrinology, Boston Children''s Hospital, Boston, Massachusetts;2. Institutional Centers for Clinical and Translational Research, Boston Children''s Hospital, Boston, Massachusetts;3. Harvard Medical School, Boston, Massachusetts;4. Division of Pediatric Endocrinology, Riley Hospital for Children at Indiana University Health, Indianapolis, Indiana;5. Division of Endocrinology, Seattle Children''s Hospital, Seattle, Washington;6. Division of Endocrinology and Center for Biobehavioral Health, Nationwide Children''s Hospital, Columbus, Ohio;7. Division of Pediatric Endocrinology, Cook Children''s Medical Center, Fort Worth, Texas.;1. Departamento de Teoría de la Señal y Comunicaciones, Escuela Politécnica Alcalá de Henares, Spain Campus Universitario Ctra. Madrid-Barcelona, Km 33.600, 28871 Alcalá de Henares, Madrid, Spain;2. LARM: Laboratory of Robotics and Mechatronics, DICeM, University of Cassino and Southern Lazio, Via Di Biasio 43, 03043 Cassino (Fr), Italy;3. División de Ingeniería de Máquinas, Universidad Politécnica de Madrid, Spain CJosé Gutiérrez Abascal 2, 28002 Madrid, Spain |
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| Abstract: | Established procedures for complex distillation synthesis employ detailed models that are unable to function for high-level screening. In this article, a new approach is presented in the form of Conceptual Programming for the preliminary screening of complex distillation systems. Conceptual Programming employs a generic supertask representation that replaces the need of superstructures. Tasks stand for simple distillation columns and hybrids represent complex distillation arrangements. A supertask accounts for all possible configurations without introducing representation and modelling difficulties. The basic tasks are then modelled using appropriate shortcut or semi-rigorous methods. A mixed integer linear programming (MILP) problem is formulated to obtain the optimum structure and performance targets. The strengths of the approach are highlighted with a light alcohol separation problem. |
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