A superstructure representation, generation, and modeling framework for chemical process synthesis

Advanced Modeling and Optimization Strategies for Process Synthesis

This article provides a systematic review of recent progress in optimization-based process synthesis. First, we discuss multiscale modeling frameworks featuring targeting approaches, phenomena-based modeling, unit operation-based modeling, and hybrid modeling. Next, we present the expanded scope of process synthesis objectives, highlighting the considerations of sustainability and operability to assure cost-competitive production in an increasingly dynamic market with growing environmental awareness. Then, we review advances in optimization algorithms and tools, including emerging machine learning-and quantum computing-assisted approaches. We conclude by summarizing the advances in and perspectives for process synthesis strategies.

Modern Modeling Paradigms Using Generalized Disjunctive Programming

Models involving decision variables in both discrete and continuous domain spaces are prevalent in process design. Generalized Disjunctive Programming (GDP) has emerged as a modeling framework to explicitly represent the relationship between algebraic descriptions and the logical structure of a design problem. However, fewer formulation examples exist for GDP compared to the traditional Mixed-Integer Nonlinear Programming (MINLP) modeling approach. In this paper, we propose the use of GDP as a modeling tool to organize model variants that arise due to characterization of different sections of an end-to-end process at different detail levels. We present an illustrative case study to demonstrate GDP usage for the generation of model variants catered to process synthesis integrated with purchasing and sales decisions in a techno-economic analysis. We also show how this GDP model can be used as part of a hierarchical decomposition scheme. These examples demonstrate how GDP can serve as a useful model abstraction layer for simplifying model development and upkeep, in addition to its traditional usage as a platform for advanced solution strategies.

Recent Developments and Challenges in Optimization-Based Process Synthesis

This article first reviews recent developments in process synthesis and discusses some of the major challenges in the theory and practice in this area. Next, the article reviews key concepts in optimization-based conceptual design, namely superstructure representations, multilevel models, optimization methods, and modeling environments. A brief review of the synthesis of major subsystems and flowsheets is presented. Finally, the article closes with a critical assessment and future research challenges for the process synthesis area.

A roadmap for the synthesis of separation networks for the recovery of bio-based chemicals: Matching biological and process feasibility

Microbial conversion of renewable feedstocks to high-value chemicals is an attractive alternative to current petrochemical processes because it offers the potential to reduce net CO₂ emissions and integrate with bioremediation objectives. Microbes have been genetically engineered to produce a growing number of high-value chemicals in sufficient titer, rate, and yield from renewable feedstocks. However, high-yield bioconversion is only one aspect of an economically viable process. Separation of biologically synthesized chemicals from process streams is a major challenge that can contribute to >70% of the total production costs. Thus, process feasibility is dependent upon the efficient selection of separation technologies. This selection is dependent on upstream processing or biological parameters, such as microbial species, product titer and yield, and localization. Our goal is to present a roadmap for selection of appropriate technologies and generation of separation schemes for efficient recovery of bio-based chemicals by utilizing information from upstream processing, separation science and commercial requirements. To achieve this, we use a separation system comprising of three stages: (I) cell and product isolation, (II) product concentration, and (III) product purification and refinement. In each stage, we review the technology alternatives available for different tasks in terms of separation principles, important operating conditions, performance parameters, advantages and disadvantages. We generate separation schemes based on product localization and its solubility in water, the two most distinguishing properties. Subsequently, we present ideas for simplification of these schemes based on additional properties, such as physical state, density, volatility, and intended use. This simplification selectively narrows down the technology options and can be used for systematic process synthesis and optimal recovery of bio-based chemicals.