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Enzymatic reactions can successfully replace complex chemical syntheses using milder reaction conditions and generating less waste. The developed model-based numerical analysis turned out to be a beneficial tool to determine the optimal operating policies of complex multienzymatic reactors. As proved, for such cases, the determination of a Fed-Batch Reactor (FBR) optimal operating policy results in a difficult multiobjective optimization problem. Exemplification is made for the bienzymatic reduction of D-fructose to mannitol by using MDH (mannitol dehydrogenase) and nicotinamide adenine dinucleotide (NADH) cofactor with the in situ continuous regeneration of NADH at the expense of formate degradation in the presence of FDH (formate dehydrogenase). For such a coupled system, the model-based engineering evaluations must account for multiple competing (opposable) optimization objectives. Among the multiple novelty elements: i) an optimally operated FBR with a tightly controlled variable feeding (of the time stepwise type) during the batch can lead to higher performance; ii) the optimally operated FBR reported better performance compared to an optimally single or cyclic BR, or to optimally serial batch-to-batch reactors (SeqBR), when considering a multiobjective optimization; iii) the concomitant variable feeding with substrate, enzymes, and cofactor during the FBR “time-arcs” is an option seldom approached in the literature but which is proved here, leading to consistent economic benefits.

Multi-enzymatic reactions can successfully replace complex chemical syntheses, using milder reaction conditions, and generating less waste. The present model-based analysis compares the performances of several optimally operated Batch Reactors (BR) with those of an optimally operated serial Sequence of BRs (SeqBR). In multi-enzymatic systems, SeqBR could be more advantageous and flexible, allowing the optimization of costly enzymes amounts used in each BR in the series. Exemplification was made for the bi-enzymatic reduction of D-fructose to mannitol by using MDH (mannitol dehydrogenase) and the NADH cofactor, with the in situ continuous regeneration of NADH at the expense of formate degradation in the presence of FDH (formate dehydrogenase). For such coupled enzymatic systems, the model-based engineering evaluations are difficult tasks, because they must account for the common species’ initial levels, their interaction, and their dynamics. The determination of optimal operating modes of sole BR or of a SeqBR turns into a multi-objective optimization problem with multiple constraints to be solved for every particular system. The study presents multiple elements of novelty: (i) the proof of higher performances of an optimal SeqBR (including N-BRs) compared to a sole optimal BR operated for N-number of runs and (ii) the effect of using a multi-objective optimization criteria on SeqBR adjustable dynamics.

Model-based evaluation of major accident consequences and effects occurring during the transport of dangerous substances presents a great interest, because it allows derivation of relevant conclusions on the cause-effect close relationship. Such a numerical (in-silico) analysis helps to improve safety regulations for the transport of hazardous substances aimed at preventing dramatic accidents causing many deaths, injuries, and structural damage. By using the standard TNT equivalency math model, coupled with the Probit functions technique, the consequences and effects of an accidental blast have been estimated.1,2 The approached case study here refers to the accidental explosion of a truck while transporting 20 t of ammonium nitrate (AN) in the proximity of Mihăileşti village (Romania) on 24 May 2004. The model-based simulated accident consequences and effects match the data taken on the spot after the accident. Multiple simulations lead to deriving relevant conclusions of practiced value for improving the transport safety of hazardous substances. This work is licensed under a Creative Commons Attribution 4.0 International License.

Bioreactor optimization is a common engineering problem difficult to be solved due to the large number of influential variables of high variability. Production of monoclonal antibody is a well-known method to synthesize a large number of identical antibodies (that is of uniform characteristics, also called monoclonal antibodies, mAb). Due to such reasons intense efforts have been invested to maximize the production of mAb by using hybridoma cell culture. Based on an adequate kinetic model from literature (experimentally checked) this paper focus on pointing-out the major role of the net evolution of the viable biomass (growth, and decay) in the location of the optimal operating setpoint (SP) of a three-phase mechanically agitated batch bioreactor (TPMAB) with immobilized hybridoma culture. This in-silico analysis opens the possibility I) to optimize the bioreactor performances by placing the SP in the most favourable location, by adjusting the substrate and biomass initial load in the bioreactor according to the preliminary determined characteristics of a modified / improved biomass; ii) to optimize the batch-to-batch operation mode (not approached here) according to the time-varying characteristics of the biomass culture, or iii) to determine the optimal operation of the bioreactor in a fed-batch operating mode (not approached here).

Optimal operation of chemical reactors of high thermal sensitivity is a central engineering problem of very high current interest. One elegant alternative to choose the optimal setpoint when at least two contrary (opposite) objectives are considered is based on the so-called Pareto-optimal front technique. This paper exemplifies how to generate Pareto optimal operating policies when reactor productivity and safety objectives (expressed in probabilistic terms) are simultaneously considered in the presence of technological constraints, uncertainty in safety boundaries, and random fluctuations in control variables. Beside the operating control variables, one important design variable is the reactor pipe diameter because it is directly related to the reaction heat removal. This paper exemplifies the influence of this design variable on the setpoint choice when applying the Pareto-optimal front method with computing the runaway-boundaries by using the generalized sensitivity criterion of Morbidelli and Varma (MV-criterion). An example is provided for an industrial fixed-bed tubular reactor used for the catalytic oxidation of benzene to maleic anhydride (MA) in vapour phase.

Tryptophan (TRP) is an aromatic non-polar α-amino-acid essential, whose biosynthesis maximization is of high practical importance in industry, and medicine. On one hand, it is to underline that TRP synthesis is an oscillatory process strongly connected to the glycolysis through the PEP (phosphoenolpyruvate) node. On the other hand, it is well-known that glycolysis, under certain environmental conditions, displays autonomous oscillations of the glycolytic intermediates’ concentrations thus reflecting the dynamics of the control and regulation of this major catabolic pathway with a major role in the cell central carbon metabolism (CCM) in living cells. Consequently, glycolysis model is the ‘core’ module of any systematic and structured model-based analysis of most of metabolic sub-process. By coupling two adequate reduced kinetic models for the glycolysis and TRP synthesis in the E. coli cells, adopted from literature, with the model of a semi-continuous bioreactor, this paper derives, for the first time, an in silico analysis of the optimal operating conditions of the bioreactor used for tryptophan synthesis, with accounting for the two interfering oscillatory processes.

While in the first part of the study, general concepts of the novel whole-cell simulation of metabolic processes in living cells are presented, by considering a variable-volume modelling framework, in the present paper exemplification is made for approaching several case studies when building-up modular model structures, for instance by developing modular kinetic representations of the homeostatic gene expression regulatory modules (GERM) that control the protein synthesis and homeostasis of metabolic processes. Past and current experience with GERM linking rules is presented in order to point-out how optimized globally efficient kinetic models for the genetic regulatory circuits (GRC) can be obtained to reproduce experimental observations. Based on quantitative regulatory indices evaluated vs. simulated dynamic and stationary environmental perturbations, the paper exemplifies with GERM-s from E. coli, at a generic level, how this methodology can be extended to characterize the GERM module efficiency, species connectivity, and system stability.

Novel coupled enzymatic systems reported important applications in the industrial bio-catalysis. Multi-enzymatic reactions can successfully replace complex chemical syntheses, using milder reaction conditions, and generating less waste. For such systems acting simultaneously, the model-based engineering calculations (design, reactor operation optimization) are difficult tasks, because they must account for interacting reactions, differences in enzymes optimal activity domains and deactivation kinetics. The determination of the optimal operating mode (enzyme ratios, enzyme feeding policy, temperature, pH) often turns into a difficult multi-objective optimization problem with multiple constraints to be solved for every particular system. The paper focuses on applying a modular screening procedure that can identify the optimal operating policy of an enzymatic reactor, which minimizes the enzyme consumption, given the process kinetic model, and an imposed production capacity. Following an optimization procedure, the process effectiveness is evaluated in a systematic approach, by including simple batch reactor (BR), batch with intermittent addition of the key-enzyme following certain optimal policies (BRP). Exemplification is made for the case of the enzymatic reduction of D-fructose to mannitol by using suspended MDH (mannitol dehydrogenase) and NADH (Nicotinamide adenine dinucleotide) cofactor, with the in-situ continuous regeneration of the cofactor by the expense of formate degradation in the presence of suspended FDH (Formate dehydrogenase).

One essential engineering problem when developing an industrial enzymatic process concerns the choice of the reactor operating alternative based on a-priori knowledge of the process kinetics and enzyme inactivation characteristics. For a multi-enzymatic system, involving complex interactions among enzymes that exhibit optimal activity on different parametric domains, and a high-order deactivation, this problem requires an extended analysis. The optimization and control engineering problems become very challenging due to the process high nonlinearity and the presence of a large number of complex constraints. All these will translate into a multi-objective optimization problem to be solved for each case. An elegant option developed in this paper is to obtain sets of Pareto optimal solutions, also called Pareto-optimal fronts, successively generated for pairs of adverse objectives. Then, the final choice of the enzymatic reactor operating policy results from the comparative analysis of these Pareto-fronts. Exemplification is made for the complex case of the oxidation of D-glucose (DG) to 2-keto- d -glucose (kDG) in the presence of P2Ox (Pyranose oxidase, EC 1.1.3.10) and catalase, continuously operated in a three-phase mechanically agitated semibatch reactor (MASCR) with co-immobilized enzymes on alginate beads. Optimal operating policy choice is based on the minimum amount of required P2Ox that ensures an imposed reaction conversion and maximum reactor productivity under various technological constraints, and for catalase/P2Ox ratios of 200–300 U/U.

A model-based analysis of a three-phase continuously operated fluidized bed bioreactor is developed in order to determine the multi-objective optimal feeding policy of the immobilized biomass used for removing mercury ions from wastewater. The analysis is focus on finding the optimal feeding policy of alginate porous beads of known particle size containing immobilized biomass (Pseudomonas putida bacteria) to minimize the biomass consumption, while keeping a quasi-constant high conversion. The extended bioreactor model is accounting for the biomass growth, biodegradation, and its partial leakage and washout. Bioreactor dynamics prediction has been generated by using a simple Michaelis–Menten kinetic model adopted from literature. The resulted optimal feeding policy of the bioreactor points out the importance of the adoption of an extended and adequate process/reactor model able to solve engineering operation problems by quickly adjusting the feeding conditions according to the time-varying characteristics of the biomass culture and to the limited possibilities to control the process during the wastewater residence time in the bioreactor. © 2016 Curtin University of Technology and John Wiley & Sons, Ltd.