(585w) Chemical Product Design Using a Novel Computer-Aided Model-Based Tool

Authors: 
Kalakul, S., Auburn University
Eden, M. R., Auburn University
Gani, R., Technical University of Denmark
In chemical product design, the application of model-based methodologies can help to design/improve products so as to reach the market faster by reducing costly and time-consuming experiments at the early stages of design [1]. That is, experiments are only performed during the last stage as a verification step. Since product candidates involve thousands of mixtures/blends of chemicals that need to be evaluated, a huge amount of data on physico-chemical properties of chemicals and their mixtures and/or models that can reliably predict them are needed for tailor-made design of products. This is a challenging task requiring data acquisition, data testing, model development, model-based design method development, etc, that needs to be integrated within a computer-aided framework so that chemicals based products can be designed, analyzed and verified in a fast, efficient and systematic manner [2].

In this work, the development of a systematic model-based framework for product design and evaluation, implemented in a new product design simulator called ProCAPD is presented. The chemical product simulator works in the same way as a chemical process simulator, but has additional features. Like a process simulator, the chemical product simulator is able to perform calculations on the specified product. Instead of the process flowsheet, the product molecular structure (in the case of a single molecule) or a mixture of molecules is given as input. Analogous to the process conditions, the product application conditions are specified and similar to the mass and energy balance calculations in the process simulator, the properties-functions of the product are calculated. Like the contents of the process simulator, the product simulator needs a database of chemicals and properties, a library of models, numerical routines to solve mathematical problems as well as various calculation options. Also, like the process simulator, the product simulator comes with a user-interface to describe the problems and to obtain the simulation results.

In order to make the chemical product simulator versatile with a wide range of applications, it includes a suite of a built-in knowledge base that has a suit of databases containing properties of different classes of chemicals (lipids, solvents, aroma, polymers, cosmetics, etc.) and blended products (gasoline, jet-fuels, lubricants, hair spray, etc.). It can calculate 55 pure component properties (such as critical properties, acentric factor and solubility parameter) and 10 functional properties (such as vapor pressure, liquid viscosity, and surface tension) and includes databases covering more than 24,000 compounds. Also, it has models for phase equilibria predictions such as UNIQUAC, UNIFAC, NRTL and PC-SAFT. It has special model parameters and data for lipids and ionic liquids. Transport related properties and new interaction parameters for a UNIFAC model for lipids systems have also been incorporated. These features together allow the design of a very wide range chemical-based products. The large amount of data, models and calculation-algorithms are managed through a specially developed ontology. All these capabilities are based on the prototype tool developed by Kalakul et al. (2017) [3].

The presentation will highlight the software architecture, the implemented computer aided methods-tools and the scope-significance will be illustrated through new chemical product design-evaluation applications.

 

References

[1] M. Hill, 2009. Chemical Product Engineering – The third paradigm, Computer & Chemical Engineering, 33(5), 947-953.

[2] R. Gani, 2004, Chemical Product Design: Challenges & Opportunities, Computers and Chemical Engineering, 28, 2441-2457.

[3] S. Kalakul, S. Cignitti, L. Zhang, R. Gani, 2017, Chapter 3 – VPPD-Lab: The Chemical Product Simulator, Tools For Chemical Product Design, Computer Aided Chemical Engineering, 39, 61-94

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