Development of a Computational Tool for Solvent Recovery from Process Waste Streams | AIChE

Development of a Computational Tool for Solvent Recovery from Process Waste Streams

The global chemical industry is rapidly growing as production increases to meet the growing demand. In the United States, the amount of solvent waste from processes in the chemical industry is increasing annually, shown by the US EPA (Environmental Protection Agency) Toxic Release Inventory database. A widely used disposal method of solvent waste is incineration, but it is unfavorable due to its negative impact on the environment by releasing pollutants and greenhouse gases. In an aim to improve the overall greenness and sustainability of chemical processes, a solvent recovery computational tool is proposed.

In this work, the programs MATLAB and GAMS (General Algebraic Modeling Software) are used together to build the solvent recovery tool. The role of MATLAB is for ease of use on the user’s side, therefore it is used to develop a Graphical User Interface (GUI). This GUI will allow a user to specify input parameters for a specific process or solvent waste stream and receive the solution. The role of GAMS is to perform an optimization using a superstructure-based approach. The optimization method is a superstructure-based approach and is presented as a pathway of separation units to achieve the desired separation of the solvent waste stream, while also providing economic and environmental outputs. This superstructure consists of mathematical models of separation technologies, made of mass, energy balance, design and cost equations. The superstructure considers desired recovery or purity and the process is analyzed as a multi-objective optimization problem. Using specified desired outputs, the GAMS code will optimize the recovery of solvent while minimizing economic and environmental impacts. Using GAMS as the computational tool, a case study for the recycling of Polyethylene terephthalate (PET) using ethyl benzoate as the solvent to provide proof of concept. This case study will serve as a strong example of the broad impacts that the implementation of solvent recovery can have across multiple industries.