This dissertation presents an analysis of two aspects of the chromatographic separation process known as Simulated Moving Bed (SMB) chromatography. The first aspect is system design, and the second is improving computer simulations to generate heuristics for choosing operational modes. For the past 15-20 years, there has been a surge of interest in the use of Simulated Moving Bed systems for the chromatographic separation of chemicals¹. A wide variety of methods, nomenclatures, and conventions have been adopted over the years²⁻⁴, as teams from different backgrounds adopt and improve on the SMB technology. This work presents a unifying discussion of the two major design methods, Triangle Theory and Standing Wave Design, used in the SMB field. We provide the complete computer code required to execute both design methods. A sample problem is worked, which demonstrates the novelty and ease of use that such tools provide. Mathematica was chosen for the implementation of these design methods, because of its strong symbolic analysis capabilities, and simplicity of creating interfaces for new users. We present derivations of the classic Langmuir results in Mathematica, and proceed to extend those implementations. When analytic solutions are impossible, we use Mathematica's numerical methods. This work also develops a distributed computing tool known as ChromRunner which allows large numbers of detailed numerical simulations to be run simultaneously. The motivations and benefits of this approach are discussed alongside implementation details. We apply the distributed computing system to two separate SMB separations in order to optimize them, as well as determine heuristics governing their operational modes. We wrote ChromRunner in C#, and took advantage of Visual Studio's Entity Framework to create the database backend. The user interface for this software was created using Microsoft's "Windows Presentation Foundation" (WPF) technologies. / Ph. D.

The cost of pretreatment process for saccharification from biomass and the cost of dilute ethanol purification are significant components of the overall cost for fuel grade ethanol production through fermentation or other biological routes. This work focuses on developing optimal designs of dilute ethanol purification process and the new acid hydrolysis technology for the production of fermentable sugars from biomass where the overarching goal is to reduce the cost of ethanol production from biomass. In this thesis, the ethanol separation process with the reverse osmosis membrane pretreatment is developed to reduce separation cost and energy consumption especially when the feed is dilute. In addition, the new solid phase reactive separation system for biomass saccharification via acid hydrolysis is proposed. This new process is applied for both dilute and concentrated acid hydrolysis where the goal is to increase sugar yield and to reduce byproduct formation. The reaction kinetics of the concentrated acid hydrolysis is investigated through batch experiment. All of these use optimization approaches for seeking the best process designs and for parameter estimations.

Simulated Moving Bed (SMB) chromatography is a separation process where the components are separated due to their varying affinity towards the stationary phase. Over the past decade, many modifications have been proposed in SMB chromatography in order to effectively separate a binary mixture. However, the separation of multi-component mixtures using SMB is still one of the major challenges. Although many different strategies have been proposed, previous studies have rarely performed comprehensive investigations for finding the best ternary separation strategy from various possible alternatives. Furthermore, the concept of combining reaction with SMB has been proposed in the past for driving the equilibrium limited reactions to completion by separating the products from the reaction zone. However, the design of such systems is still challenging due to the complex dynamics of simultaneous reaction and adsorption. The first objective of the study is to find the best ternary separation strategy among various alternatives design of SMB. The performance of several ternary SMB operating schemes, that are proposed in the literature, are compared in terms of the optimal productivity obtained and the amount of solvent consumed. A multi- objective optimization problem is formulated which maximizes the SMB productivity and purity of intermediate eluting component at the same time. Furthermore, the concept of optimizing a superstructure formulation is proposed, where numerous SMB operating schemes can be incorporated into a single formulation. This superstructure approach has a potential to find more advantageous operating scheme compared to existing operating schemes in the literature. The second objective of the study is to demonstrate the Generalized Full Cycle (GFC) operation experimentally for the first time, and compare its performance to the JO process. A Semba OctaveTM chromatography system is used as an experimental SMB unit to implement the optimal operating schemes. In addition, a simultaneous optimization and model correction (SOMC) scheme is used to resolve the model mismatch in a systematic way. We also show a systematic comparison of both JO and GFC operations by presenting a Pareto plot of the productivity achieved against the desired purity of the intermediate eluting component experimentally. The third objective of the study is to develop an simulated moving bed reactor (SMBR) process for an industrial-scale application, and demonstrate the potential of the ModiCon operation for improving the performance of the SMBR compared to the conventional operating strategy. A novel industrial application involving the esterification of acetic acid and 1-methoxy-2-propanol is considered to produce propylene glycol methyl ether (PMA) as the product. A multi-objective optimization study is presented to find the best reactive separation strategy for the production of the PMA product. We also present a Pareto plot that compares the ModiCon operation, which allows periodical change of the feed composition and the conventional operating strategy for the optimal production rate of PMA that can be achieved against the desired conversion of acetic acid.

This dissertation describes the simulation and optimization of adsorptive and chromatographic separation processes. The first part focus on the simulation and comparison of operational modes in simulated moving bed (SMB) chromatography for separation and purification in bioprocesses. The second part includes the simulation of gas-phase adsorptive processes by pressure swing adsorption and temperature swing adsorption technologies. The applications of SMB chromatography are popular in separating and purifying enantiomers, petrochemicals, pharmaceuticals and biochemicals with higher yield and lower solvent consumption. We simulate and compare several operational modes of simulated moving bed (SMB) for a binary and a ternary bioprocess using Aspen Chromatography. These operational modes are able to improve the separation efficiency of the basic SMB process by our simulation and optimization. We compare their separation performances and identify heuristics that will guide the selection of operational modes across a variety of systems. Pressure swing adsorption (PSA) and temperature swing adsorption (TSA) are two of the main technologies for gas-phase adsorption separation processes. We simulate and demonstrate a PSA model for air separation system and a TSA model for CO2 capture system in Aspen Adsorption. We present their separation performance plots to provide the physical insights of these two systems. / Ph. D.

Adsorption separation processes are extremely important to the chemical industry, especially in the manufacturing of food, pharmaceutical, and fine chemical products. This work addresses three main topics: first, systematic decision-making between rival gas phase adsorption processes for the same separation problem; second, process development for liquid phase simulated moving bed chromatography (SMB); third, accelerated startup for SMB units. All of the work in this thesis uses model-based optimization to answer complicated questions about process selection, process development, and control of transient operation. It is shown in this thesis that there is a trade-off between productivity and product recovery in the gaseous separation of enantiomers using SMB and pressure swing adsorption (PSA). These processes are considered as rivals for the same separation problem and it is found that each process has a particular advantage that may be exploited depending on the production goals and economics. The processes are compared on a fair basis of equal capitol investment and the same multi-objective optimization problem is solved with equal constraints on the operating parameters. Secondly, this thesis demonstrates by experiment a systematic algorithm for SMB process development that utilizes dynamic optimization, transient experimental data, and parameter estimation to arrive at optimal operating conditions for a new separation problem in a matter of hours. Comparatively, the conventional process development for SMB relies on careful system characterization using single-column experiments, and manual tuning of operating parameters, that may take days and weeks. The optimal operating conditions that are found by this new method ensure both high purity constraints and optimal productivity are satisfied. The proposed algorithm proceeds until the SMB process is optimized without manual tuning. In some case studies, it is shown with both linear and nonlinear isotherm systems that the optimal performance can be reached in only two changes of operating conditions following the proposed algorithm. Finally, it is shown experimentally that the startup time for a real SMB unit is significantly reduced by solving model-based startup optimization problems using the SMB model developed from the proposed algorithm. The startup acceleration with purity constraints is shown to be successful at reducing the startup time by about 44%, and it is confirmed that the product purities are maintained during the operation. Significant cost savings in terms of decreased processing time and increased average product concentration can be attained using a relatively simple startup acceleration strategy.

Simulated moving bed chromatography process (SMBCP) is the technical realisation of a countercurrent adsorption process through the cyclic port switching. SMB technology reduces the cost of packing material with high loading capacity and provides high purity and high recovery in a very short time. Major commodity applications have been found in the petroleum, food, biotechnology, pharmaceutical and fine chemical industries. The industrial applications bring an emergent demand to improve the SMBCP operation for higher product quality, productivity, efficiency and robustness. However, for this particular process, we encounter several challenges. Firstly, the interplay of the effects of strong nonlinearities, competition of solutes, mass transfer resistance and fluid dynamic dispersion produces steep concentration fronts. Mathematical model accounted for this particular property constitutes a serious difficulty for the solution procedure. Secondly, a dynamic SMB model consists of a set of partial differential, ordinary differential and algebraic equations, which are highly coupled. The large size is a problem due to its intensive computation when on-line optimisation and real-time control are necessary. Thirdly, the SMB unit operation exhibits complex dynamics. Process metrics for design and operation can be determined only when a cyclic steady state is reached after a certain number of switching. Achieving this steady state by solving the PDE models cycle after cycle involves expensive calculation. Studies have been carried out to solve these problems through process analysis, investigation on spatial discretisation techniques, and development of an accelerated integration scheme. / Through a systematic study on the advances of SMB modelling, design and control, a set of functionally equivalent models for SMBCP are identified and summarized for their practical applications. The limitations of the existing modelling techniques in industrial applications are also identified. Furthermore, structural analysis of the existing models is conducted for a better understanding of the functionality and suitability of each model. Suggestions are given on how to choose an appropriate model with sufficient accuracy while keeping the computational demand reasonably low for real time control. / Effort is made on to the systematic investigation of different numerical methods for the solution of PDEs to circumvent the steep gradients encountered in chromatographic separation. Comprehensive studies are conducted on a single column chromatographic process represented by a transport-dispersive-equilibrium linear model. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. It reveals that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. / The advantages and disadvantages of the wavelet based approaches are further investigated through several case studies on real SMBCP system. A glucose-fructose separation process is firstly chosen with its relatively simple isotherm representations. Simulations are conducted using both wavelet collocation and upwind finite difference methods. For more complicated applications, an enantiomers separation process is selected. As the PDEs model exhibit a certain degree of singularity, wavelet collocation and high resolution methods are adopted for spatial discretisation. It is revealed that both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. This is the first time that these two frontier numerical methods are used for such a complex SMB system models and our results are encouraging for the development of model-based online control scheme. / In developing a new scheme to rapidly obtain the solution at steady state for any arbitrary initial condition, the concept of Quasi-Envelope (QE) is adopted under the consideration that a SMBCP can be treated as a pseudo-oscillatory process because of a large number of continuous switching. The scheme allows larger steps to be taken to predict the slow change of starting state within each switching. Combined with previously developed wavelet-based technique, this method is successfully applied to the simulation of a SMB sugar separation process. Investigations are also carried out on the location of proper starting point for the algorithm and on the effect of changing stepsize to the convergence of iteration method. It is found that if the starting state of Quasi-Envelope is chosen to be the same as the original function, the multivalue algorithm would require similar computational effort to achieve the steady state prediction, regardless of the integration stepsize. If using constant stepsize, launching QE later is helpful when quasi-envelope displays steep change at the start-up period. A changing stepsize produces slow convergence compared to the constant stepsize strategy, thus increasing the work load where the stepsize change is occurring. Other iteration method is required to be imposed to achieve faster convergence right from the beginning. Potential applications can be seen for other chemical engineering processes with inherent cyclic behaviour.