Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes

In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer® with an external NLP solver implemented in Matlab®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.

Sorbent design for CO2 capture under different flue gas conditions

CO2 capture by solid sorbents is a physisorption process in which the gas molecules are adsorbed in a different porosity range, depending on the temperature and pressure of the capture conditions. Accordingly, CO2 capture capacities can be enhanced if the sorbent has a proper porosity development and a suitable pore size distribution. Thus, the main objective of this work is to maximize the CO2 capture capacity at ambient temperature, elucidating which is the most suitable porosity that the adsorbent has to have as a function of the emission source conditions. In order to do so, different activated carbons have been selected and their CO2 capture capacities have been measured. The obtained results show that for low CO2 pressures (e.g., conditions similar to post-combustion processes) the sorbent should have the maximum possible volume of micropores smaller than 0.7 nm. However, the sorbent requires the maximum possible total micropore volume when the capture is performed at high pressures (e.g., conditions similar to oxy-combustion or pre-combustion processes). Finally, this study also analyzes the important influence that the sorbent density has on the CO2 capture capacity, since the adsorbent will be confined in a bed with a restricted volume.

Glutaraldehyde in bio-catalysts design: a useful crosslinker and a versatile tool in enzyme immobilization

Glutaraldehyde is one of the most widely used reagents in the design of biocatalysts. It is a powerful crosslinker, able to react with itself, with the advantages that this may bring forth. In this review, we intend to give a general vision of its potential and the precautions that must be taken when using this effective reagent. First, the chemistry of the glutaraldehyde/amino reaction will be commented upon. This reaction is still not fully clarified, but it seems to be based on the formation of 6-membered heterocycles formed by 5 C and one O. Then, we will discuss the production of intra- and inter-molecular enzyme crosslinks (increasing enzyme rigidity or preventing subunit dissociation in multimeric enzymes). Special emphasis will be placed on the preparation of cross-linked enzyme aggregates (CLEAs), mainly in enzymes that have low density of surface reactive groups and, therefore, may be problematic to obtain a final solid catalyst. Next, we will comment on the uses of glutaraldehyde in enzymes previously immobilized on supports. First, the treatment of enzymes immobilized on supports that cannot react with glutaraldehyde (only inter and intramolecular cross-linkings will be possible) to prevent enzyme leakage and obtain some enzyme stabilization via cross-linking. Second, the cross-linking of enzymes adsorbed on aminated supports, where together with other reactions enzyme/support crosslinking is also possible; the enzyme is incorporated into the support. Finally, we will present the use of aminated supports preactivated with glutaraldehyde. Optimal glutaraldehyde modifications will be discussed in each specific case (one or two glutaraldehyde molecules for amino group in the support and/or the protein). Using preactivated supports, the heterofunctional nature of the supports will be highlighted, with the drawbacks and advantages that the heterofunctionality may have. Particular attention will be paid to the control of the first event that causes the immobilization depending on the experimental conditions to alter the enzyme orientation regarding the support surface. Thus, glutaraldehyde, an apparently old fashioned reactive, remains the most widely used and with broadest application possibilities among the compounds used for the design of biocatalyst.

Mathematical programming model for heat exchanger design through optimization of partial objectives

Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature.

Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014.

Logic-Based Outer Approximation for the Design of Discrete-Continuous Dynamic Systems with Implicit Discontinuities

We address the optimization of discrete-continuous dynamic optimization problems using a disjunctive multistage modeling framework, with implicit discontinuities, which increases the problem complexity since the number of continuous phases and discrete events is not known a-priori. After setting a fixed alternative sequence of modes, we convert the infinite-dimensional continuous mixed-logic dynamic (MLDO) problem into a finite dimensional discretized GDP problem by orthogonal collocation on finite elements. We use the Logic-based Outer Approximation algorithm to fully exploit the structure of the GDP representation of the problem. This modelling framework is illustrated with an optimization problem with implicit discontinuities (diver problem).

Optimal Design of a Hybrid Membrane System Combining Reverse and Forward Osmosis for Seawater Desalination

In this work we study Forward Osmosis (FO) as an emerging desalination technology, and its capability to replace totally or partially Reverse Osmosis (RO) in order to reduce the great amount of energy required in the current desalination plants. For this purpose, we propose a superstructure that includes both membrane based desalination technologies, allowing the selection of only one of the technologies or a combination of both of them seeking for the optimal configuration of the network. The optimization problem is solved for a seawater desalination plant with a given fresh water production. The results obtained show that the optimal solution combines both desalination technologies to reduce not only the energy consumption but also the total cost of the desalination process in comparison with the same plant but operating only with RO.

Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks

In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process.

Rigorous design of distillation columns using surrogate models based on Kriging interpolation

The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this article, we propose to address this challenging problem by substituting the distillation columns by Kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate Kriging-based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush–Kuhn–Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.

Design of hybrid asymmetric capacitors in aqueous electrolyte using ZTC and ultraporous activated carbons

The use of two different materials as electrodes allows the construction of asymmetric and hybrid capacitors cells with enhanced energy and power density. This approach is especially well-suited for overcoming the limitations of pseudocapacitive materials that provide a huge capacitance boost, but in a limited potential window. In this work, we introduce the concepts and protocols that are required for a successful design of such systems, which is illustrated by the construction of an asymmetric hybrid cell where a zeolite-templated carbon and an ultraporous activated carbon have been combined.

An authoring tool for decision support systems in context questions of ecological knowledge

Decision support systems (DSS) support business or organizational decision-making activities, which require the access to information that is internally stored in databases or data warehouses, and externally in the Web accessed by Information Retrieval (IR) or Question Answering (QA) systems. Graphical interfaces to query these sources of information ease to constrain dynamically query formulation based on user selections, but they present a lack of flexibility in query formulation, since the expressivity power is reduced to the user interface design. Natural language interfaces (NLI) are expected as the optimal solution. However, especially for non-expert users, a real natural communication is the most difficult to realize effectively. In this paper, we propose an NLI that improves the interaction between the user and the DSS by means of referencing previous questions or their answers (i.e. anaphora such as the pronoun reference in “What traits are affected by them?”), or by eliding parts of the question (i.e. ellipsis such as “And to glume colour?” after the question “Tell me the QTLs related to awn colour in wheat”). Moreover, in order to overcome one of the main problems of NLIs about the difficulty to adapt an NLI to a new domain, our proposal is based on ontologies that are obtained semi-automatically from a framework that allows the integration of internal and external, structured and unstructured information. Therefore, our proposal can interface with databases, data warehouses, QA and IR systems. Because of the high NL ambiguity of the resolution process, our proposal is presented as an authoring tool that helps the user to query efficiently in natural language. Finally, our proposal is tested on a DSS case scenario about Biotechnology and Agriculture, whose knowledge base is the CEREALAB database as internal structured data, and the Web (e.g. PubMed) as external unstructured information.

A Sequential Algorithm for the Rigorous Design of Thermally Coupled Distillation Sequences

A sequential design method is presented for the design of thermally coupled distillation sequences. The algorithm starts by selecting a set of sequences in the space of basic configurations in which the internal structure of condensers and reboilers is explicitly taken into account and extended with the possibility of including divided wall columns (DWC). This first stage is based on separation tasks (except by the DWCs) and therefore it does not provide an actual sequence of columns. In the second stage the best arrangement in N-1 actual columns is performed taking into account operability and mechanical constraints. Finally, for a set of candidate sequences the algorithm try to reduce the number of total columns by considering Kaibel columns, elimination of transfer blocks or columns with vertical partitions. An example illustrate the different steps of the sequential algorithm.

Design of Activated Carbon/Activated Carbon Asymmetric Capacitors

Supercapacitors are energy storage devices that offer a high power density and a low energy density in comparison with batteries. Their limited energy density can be overcome by using asymmetric configuration in mass electrodes, where each electrode works within their maximum available potential window, rendering the maximum voltage output of the system. Such asymmetric capacitors are optimized using the capacitance and the potential stability limits of the electrodes, with the reliability of the design largely depending on the accuracy and the approach taken for the electrochemical characterization. Therefore, the performance could be lower than expected and even the system could break down, if a well thought out procedure is not followed. In this work, a procedure for the development of asymmetric supercapacitors based on activated carbons is detailed. Three activated carbon materials with different textural properties and surface chemistry have been systematically characterized in neutral aqueous electrolyte. The asymmetric configuration of the masses of both electrodes in the supercapacitor has allowed to cover a higher potential window, resulting in an increase of the energy density of the three devices studied when compared with the symmetric systems, and an improved cycle life.