Applied Thermodynamics for Process Modeling
Chau-Chyun Chen and Paul M. Mathias
Aspen Technology, Inc., Cambridge, MA 02141
mental data are available and accurate description is essential and feasible. Highly parameterized models are accepted and useful if they represent available data within experimental accuhe process industries spend an estimated $500 billionannualracy. These reference quality models suffer the disadvantage, ly worldwide in conceptual design, process engineering, however, of not easily allowing incorporation of additional detailed engineering, construction, startup, plant operations, components into the system being modeled. and maintenance for chemical, refining, polymer and power plants. • Engineers frequently lack either In order forchemical engineers to experimental data or expertise successfully execute these process to develop and validate models. and product studies, they perform As a result, they often rely on process modeling and capture estimation techniques such as knowledge of the thermodynamic group-contribution methods. properties and phase behavior of the • Engineers need databanks that chemical systems they work with.are compilations of validated Process modeling is a key experimental data and model enabling technology for process parameters for pure compodevelopment and design, equipnent and mixture properties. ment sizing and rating, and process (a) Databanks and correlations of debottlenecking and optimization. known accuracy play key roles More recently, process modeling in engineering calculations. hasenabled offline dynamic simu• The value of thermodynamic lation for controllability studies, models is especially evident in operator training simulators, online “flash” calculations. Robust model-based process sensors, stateand computationally efficient estimation, look-ahead predictors, flash algorithms for a variety of and online process control and optiphase equilibrium and chemimization.Success in process modcal equilibrium conditions are eling is critically dependent upon an integral part of the practice accurate descriptions of the thermoof applied thermodynamics. dynamic properties and phase (b) Practicing engineers prefer behavior of the concerned chemical “simple and intuitive” thermodysystems. A perspective is offered Figure 1. Modeling sulfuric acid with chemistry and namicmodels that can be applied here on applied thermodynamics Electrolyte NRTL model (Mathias et al., 2001) easily. Models that are constantly from an industrial viewpoint. (a) Vapor pressure of sulfuric acid and oleum being revised, sophisticated theoat 100°C Industry Uses Thermories requiring expert users, models (b) Liquid-phase compositions in saturated with excessive computational load, dynamicInnovations sulfuric acid and oleum at 100°C or models requiring extensive Industry uses a wide array of parameterization (i.e., ternary parathermodynamic innovations: engineering correlations, reference meters), have limited industrial applications. quality models, estimation methods, databanks, and flash algorithms. • Chemical engineers benefit most from models and correlaThermodynamic ModelingDeliver Value in tions that capture the dominant physical and chemical behavIndustrial Practice ior of chemical systems. Engineers use these correlative modExample 1. A number of process licensors and manufacturers are els within a thermodynamic modeling framework to describe concerned with designing, optimizing, and troubleshooting sulfuric and validate available data and to extrapolate withreasonable acid plants. Sulfuric acid is the largest volume chemical produced, confidence outside the range of available data. and certain aspects of it make the development of accurate and reli• For commonly encountered systems such as water and steam, able process models difficult and challenging. Figure 1a demonair, ammonia, and light hydrocarbons, comprehensive experi-
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