Optimization problem of complex system under uncertainty

In industrial practice, conceptual process design is typically conducted by repetitive simulation studies, which require detailed design specifications in an early design phase. Guided by heuristics, these iterative solution procedures result in high manual effort and, in addition, no guarantee concerning the quality of the solution can be given. Optimization-based design methods provide a tremendous potential to accelerate and improve conceptual process design. For this purpose, a synthesis framework for the optimization-based design of chemical processes is presented in this thesis. Powerful shortcut and rigorous evaluation methods for reaction and distillation are presented. These methods are computationally efficient in order to allow an optimization-based design of large-scale chemical processes. Various industrial case studies illustrate the application of the novel approaches and highlight their benefits. ...

Integration of Design and Control Using Efficient PSE Approximations

Research work has emphasized the importance of reliability and maintenance in chemical process operation and the benefits from achieving high process availability levels by optimizing the trade-offs between maintenance costs and plant production volumes. This has motivated the need for the development of contemporary techniques and tools for availability assessment of process systems, which go beyond traditional practices, by focussing on the interactions of reliability and maintenance optimization with the detailed process operation and its dynamic, continuously changing environment. Furthermore, at the design stage of chemical plants, operability considerations accounting for the plant's life cycle, such as flexibility, reliability and maintainability are not typically included. The main reason for this is that there is a lack of an integrated design framework enabling process engineers to look at the various operability factors in conjuction with cost in a systematic and quantified way during process design development. This work presents theoretical and computational developments aiming at the integration of maintenance optimization in optimal life-cycle process design and development under uncertainty. In particular, the impact of uncertainty upon determining the optimal balance between maintenance costs and benefits as well as the interactions of process design and maintainability in the presence of uncertainty are clearly shown and quantified.

The design and scheduling of chemical batch processes: Computational complexity studies

One of the priority issues in green chemistry is to devise of greener and sustainable chemical strategies and processes to reduce or eliminated the use of hazardous substances. The development of bio-based materials has been constantly increasing, and there is a global effort in agreement with the demands of sustainable management for reducing reliance of fossil resources. In this sense there are green polymerization systems improved to reach increased yields and produce polymers with high molar mass and with specific microstructure characteristics. In the same way, biocatalysis in green chemistry reactions are performer under mild conditions of temperature, pressure and pH. However, along with new materials, chemical processes and reactors must be redesign and developed to guarantee the requirements and meet the demand for green chemical products. Substantial differences with traditional chemical process are based on the synthesis of materials changing the solvents selections and the implementation of continuous reactors, as well as in evaluating the effectiveness of the process through factors such as atom economy, environmental factor, and process mass intensity to implement an industrial green process. This chapter is a review of the processes that have been design and developed to achieve to maximize efficiency and reduce waste.

A hybrid global optimization method for design of batch chemical processes

The optimal design of large complex chemical processes: Development of the max-sensitive method

The constant tightening of environmental regulations and the ongoing need to reduce operating costs have posed a challenge for the design of any chemical process. Process engineers use process simulators to help them perform calculations that will, ultimately, result in design parameters or operating conditions for a plant or process. Exergy is a potential indicator that can aid in the design of energy efficient chemical processes and plants. The exergy concept has been increasingly used as a tool to locate the critical energy use in many industrial processes, both chemical and non‐chemical. However, currently most process simulators in the market do not offer the capability of calculating the exergy of a process. An open‐source exergy calculator has been created by embedding the calculation procedure in an open‐source chemical process simulator. This improves process simulation by including a potential tool for design teams to quickly evaluate several process options in detail in order to understand their energy utilisation. A simple exergy analysis for a gas processing facility is used to demonstrate the capabilities of the tool. The analysis shows where the largest quantities of exergy are being consumed within the plant, thus pointing to areas where improvement in energy usage can be made. The use of exergy as a potential design and retrofit tool is also discussed. Copyright © 2007 Curtin University of Technology and John Wiley & Sons, Ltd.

A process design framework for considering the stability of steady state operating points and Hopf singularity points in chemical processes

Computer tool supported process design methodology

Over the years, the design of chemical vapor deposition processes has relied on accumulated empirical ability. It is now well established that the properties of films grown by this chemical process are strongly determined by both transport phenomena and homogeneous and heterogeneous reactions in the reactor. Thermodynamic calculations and mass transport modeling provide a possible approach to delineate the general features of a given process. The application of this concept to the deposition of Si 1-x Ge x alloys has led to a better knowledge of the physicochemical phenomena involved in the growth of these materials

Modern chemical industrial processes are becoming more and more integrated and consist of multiple interconnected nonlinear process units. These strong interactions profoundly complicate a system's inherent properties and further alter the plant‐wide process dynamics. This may lead to a poor control performance and cause plant‐wide operability problems. To ensure entire processes run robustly and safely, with considerable profitability, it is crucial to recognize the inherent characteristics that can jeopardize controllability and process behavior at the early design stage. With a focus on inherently safer designs, from a plant‐wide perspective, a systematic method for chemical processes controllability analysis is addressed in this study. In the proposed framework, based on open‐loop stability/instability and minimum/nonminimum‐phase behavior, the entire operating zone of the process can be categorized into distinct subregions with different inherent properties. Variations in the inherent characteristics of a plant‐wide process with the operation and design conditions, over the feasible operation region, can be probed and analyzed. An attempt of this framework is made to illustrate how to clarify the roots of the poor controllability that arise in the design and operation of a large scale chemical process, and the results can provide guidance for both deciding the optimal operation conditions and selecting the most suitable control structure. Singularity theory is also applied in the framework to improve the computational efficiency. The framework is illustrated with two case studies. One involves a reactor‐external heat exchanger network and the other a more complex plant‐wide process, comprising a reactor, an extractor, and a distillation column. © 2012 American Institute of Chemical Engineers AIChE J, 58: 3096–3109, 2012

Optimal design and sensitivity analysis of post-combustion CO2 capture process by chemical absorption with amines

The paper presents a stochastic methodology for handling uncertainty in process development as part of a general framework for batch and continuous process models. The method combines systematic modelling procedures with Hammersley sampling based uncertainty analysis and a range of sample-based sensitivity analysis techniques which are used to quantify predicted performance uncertainty and identify key uncertainty contributions. The methodology was implemented on a batch chemical reactor process and some clear recommendations as to how to reduce the uncertainty in the main output variables are obtained.

Multi-criteria screening of carbon dioxide utilization products combined with process optimization and evaluation