Details

Refinery Engineering

Integrated Process Modeling and Optimization
1. Aufl.

von: Ai-Fu Chang, Kiran Pashikanti, Y. A. Liu
106,99 €
Verlag:	Wiley-VCH
Format:	EPUB
Veröffentl.:	01.03.2013
ISBN/EAN:	9783527666850
Sprache:	englisch
Anzahl Seiten:	522

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Beschreibungen

Titelbeschreibung

A pioneering and comprehensive introduction to the complex subject of integrated refinery process simulation, using many of the tools and techniques currently employed in modern refineries. Adopting a systematic and practical approach, the authors include the theory, case studies and hands-on workshops, explaining how to work with real data. As a result, senior-level undergraduate and graduate students, as well as industrial engineers learn how to develop and use the latest computer models for the predictive modeling and optimization of integrated refinery processes. Additional material is available online providing relevant spreadsheets and simulation files for all the models and examples presented in the book.

Inhaltsverzeichnis

PREFACE CHARACTERIZATION, PHYSICAL AND THERMODYNAMIC PROPERTIES OF OIL FRACTIONS Crude Assay Pseudocomponent Generation Based on Boiling-Point Ranges Workshop 1.1 - Interconvert Distillation Curves Workshop 1.2 - Extrapolate an Incomplete Distillation Curve Workshop 1.3 - Calculate MeABP of a Given Assay Workshop 1.4 - Duplicate the Oil Fraction in Aspen HYSYS/Refining Property Requirements for Refinery Process Models Physical Properties Process Thermodynamics Miscellaneous Physical Properties for Refinery Modeling Conclusions Nomenclature References ATMOSPHERIC DISTILLATION UNIT Introduction Scope of the Chapter Process Overview Model Development Feed Characterization Data Requirements and Validation Representative Atmospheric Distillation Unit Building the Model in Aspen HYSYS Results Model Applications to Process Optimization Workshop 2.1 - Rebuild Model Using "Backblending" Procedure Workshop 2.2 - Investigate Changes in Product Profiles with New Product Demands Conclusions Nomenclature References VACUUM DISTILLATION UNIT Process Description Data Reconciliation Model Implementation Model Applications toProcess Optimization - VDU Deep-Cut Operation Workshop - Using Aspen HYSYS/Refining to Implement Deep-Cut Operation References PREDICTIVE MODELING OF THE FLUID CATALYTIC CRACKING (FCC) PROCESS Introduction Process Description Process Chemistry Literature Review Aspen HYSYS/Petroleum Refining FCC Model Calibrating the Aspen HYSYS/Petroleum Refining FCC Model Fractionation Mapping Feed Information to Kinetic Lumps Overall Modeling Strategy Results Model Applications to Process Optimization Model Application to Refinery Production Planning Workshop 4.1: Guide for Modeling FCC Units in Aspen HYSYS/Petroleum Refining Workshop 4.2: Calibrating Basic FCC Model Workshop 4.3: Build Main Fractionator and Gas Plant System Workshop 4.4: Model Applications to Process Optimization -Perform Case Study to Identify Different Gasoline Production Scenarios Workshop 4.5: Model Application to Production Planning- Generate DELTA-BASE Vectors for Linear-Programming (LP)-Based Production Planning Conclusions Nomenclature References PREDICTIVE MODELING OF THE CONTINUOUS CATALYST REGENERATION (CCR) REFORMING PROCESS Introduction Process Overview Process Chemistry Literature Review Aspen HYSYS/Petroleum Refining Catalytic Reformer Model Thermophysical Properties Fractionation System Feed Characterization Model Implementation Overall Modeling Strategy Results Model Applications to Process Optimization Model Applications to Refinery Production Planning Workshop 5.1: Guide for Modeling CCR Units in Aspen HYSYS/Petroleum Refining Workshop 5.2: Model Calibration Workshop 5.3: Build a Downstream Fractionation Workshop 5.4: Case Study to Vary RON and Product Distribution Profile Conclusions Nomenclature References PREDICTIVE MODELING OF THE HYDROPROCESSING UNITS Introduction Aspen HYSYS/Refining HCR Modeling Tool Process Description Model Development Modeling Results of MP HCR Process Modeling Results of HP HCR Process Model Applications to Process Optimization Model Application - Delta-Base Vector Generation Conclusion Workshop 6.1 - Build Preliminary Reactor Model of HCR Process Workshop 6.2 - Calibrate Preliminary Reactor Model to Match Plant Data Workshop 6.3 - Model Applications to Process Optimization Workshop 6.4 - Connect Reactor Model to Fractionator Simulation Nomenclature References

Autorenportrait

Ai-Fu Chang received his Ph.D. in the Department of Chemical Engineering at Virginia Polytechnic Institute and State University in September, 2011. He received his B.S. in chemical engineering from National Taiwan University in 2001. He completed his doctoral dissertation on integrated process modeling and product design of biodiesel manufacturing, and refinery reaction and fractionation systems. The latter was the basis of this textbook. He has worked on several industrial modeling projects, including poly(acrylonitrile-vinyl acetate), hydrocracking, and biodiesel. These projects were collaborative efforts between Virginia Tech, Aspen Technology, and industrial manufacturers. He is currently employed by Chevron Phillips Chemical Company. Kiran Pashikanti was a PhD student in the Department of Chemical Engineering at Virginia Tech. He received his B.S. in chemical engineering from Virginia Commonwealth University in 2005, and his Ph.D. in chemical engineering from Virginia Tech in September, 2011. He has worked on several industrial modeling projects on integrated modeling of reaction and fractionation systems, and of carbon-dioxide capture processes. This textbook grows out of his doctoral dissertation on the predictive modeling of fluid catalytic cracking and catalytic reforming processes. He is currently employed by Chevron Phillips Chemical Company. Prof. Y.A. Liu is the Frank C. Vilbrandt Endowed Professor of Chemical Engineering at Virginia Polytechnic Institute and State University. He received his B.S. (1967), M.S. (1970), and Ph.D. (1974) degrees from National Taiwan University, Tufts University and Princeton University, respectively. He has published numerous papers and eight books, including four pioneering chemical engineering textbooks on artificial intelligence in chemical engineering (with Thomas E. Quantrille) and on neural networks in bioprocessing and chemical engineering (with D. Richard Baughman). Professor Liu's contributions to chemical engineering teaching and research have been recognized by university, national and international awards and he is a Fellow of the American Institute of Chemical Engineers. For his contributions to teaching, research and industrial outreach, he received the Virginia Outstanding Faculty Award from Governor Jim Gilmore in 2000. He also received the National Friendship Award from China's Premier Zhu Ronjie in 2000.

Back cover copy

Petroleum refining is one of the most important yet challenging industries, and continues to be a major contributor in the production of transportation fuels and chemicals. Current economic, regulatory and environmental concerns place significant pressure on refiners to upgrade and optimize the refining process. At the same time, new product demands are urging refiners to explore alternative processing units and feedstocks. This textbook represents a pioneering and comprehensive introduction to this complex subject, using many of the tools and techniques currently employed in modern refinery process simulation. Adopting a systematic and practical approach, the authors include the theory, case studies and hands-on workshops, explaining how to work with real data. As a result, senior-level undergraduate and graduate students, as well as industrial engineers learn how to develop and use the latest computer models for the predictive modeling and optimization of integrated refinery processes. Additional material is available online providing relevant spreadsheets and simulation files for all the models and examples presented in the book.