Representing the uncertainties with a set of scenarios, the optimization problem resulting from a robust nonlinear model predictive control (NMPC) strategy at each sampling instance can be viewed as a large-scale stochastic program. This paper solves these optimization problems using the parallel Schur complement method developed to solve stochastic programs on distributed and shared memory machines. The control strategy is illustrated with a case study of a multidimensional unseeded batch crystallization process. For this application, a robust NMPC based on min⁻max optimization guarantees satisfaction of all state and input constraints for a set of uncertainty realizations, and also provides better robust performance compared with open-loop optimal control, nominal NMPC, and robust NMPC minimizing the expected performance at each sampling instance. The performance of robust NMPC can be improved by generating optimization scenarios using Bayesian inference. With the efficient parallel... [more]

Hot-melt extrusion is commonly applied for forming products, ranging from metals to plastics, rubber and clay composites. It is also increasingly used for the production of pharmaceuticals, such as granules, pellets and tablets. In this context, mathematical modeling plays an important role to determine the best process operating conditions, but also to possibly develop software sensors or controllers. The early models were essentially black-box and relied on the measurement of the residence time distribution. Current models involve mass, energy and momentum balances and consists of (partial) differential equations. This paper presents a literature review of a range of existing models. A common case study is considered to illustrate the predictive capability of the main candidate models, programmed in a simulation environment (e.g., MATLAB). Finally, a comprehensive distributed parameter model capturing the main phenomena is proposed.

Steam reforming of ethanol in the membrane reactor using the Pd77Ag23 membrane was evaluated in Ni/CeO₂ and Co/CeO₂ at atmospheric pressure. At 673 K, the H₂ yield in the Pd77Ag23 membrane reactor over Co/CeO₂ was found to be higher than that over Ni/CeO₂, although the H₂ yield over Ni/CeO₂ exceeded that over Co/CeO₂ at 773 K. This difference was owing to their reaction mechanism. At 773 K, the effect of H₂ removal could be understood as the equilibrium shift. In contrast, the H₂ removal kinetically inhibited the reverse methane steam reforming at low temperature. Thus, the low methane-forming reaction rate of Co/CeO₂ was favorable at 673 K. The addition of a trace amount of Ru increased the H₂ yield effectively in the membrane reactor, indicating that a reverse H₂ spill over mechanism of Ru would enhance the kinetical effect of H₂ separation. Finally, the effect of membrane performance on the reactor performance by using amorphous alloy membranes with different compositions was evalua... [more]

Homogenizers are commonly used to produce oil-in-water emulsions that consist of emulsifier-coated oil droplets suspended within an aqueous phase. The functional attributes of emulsions are usually controlled by selecting appropriate ingredients (e.g., surfactants, co-surfactants, oils, solvents, and co-solvents) and processing conditions (e.g., homogenizer type and operating conditions). However, the functional attributes of emulsions can also be tailored after homogenization by manipulating their composition, structure, or physical state. The interfacial properties of lipid droplets can be altered using competitive adsorption or coating methods (such as electrostatic deposition). The physical state of oil droplets can be altered by selecting an oil phase that crystallizes after the emulsion has been formed. The composition of the disperse phase can be altered by mixing different kinds of oil droplets together to induce inter-droplet exchange of oil molecules. The local environment of... [more]

This paper reports the findings of a FP7 project (DEMCAMER) that developed materials (catalysts and membranes) and new processes for four industrially relevant reaction processes. In this project, active, stable, and selective catalysts were developed for the reaction systems of interest and their production scaled up to kg scale (TRL5 (TRL: Technology Readiness Level)). Simultaneously, new membranes for gas separation were developed; in particular, dense supported thin palladium-based membranes for hydrogen separation from reactive mixtures. These membranes were successfully scaled up to TRL4 and used in various lab-scale reactors for water gas shift (WGS), using both packed bed and fluidized bed reactors, and Fischer-Tropsch (FTS) using packed bed reactors and in prototype reactors for WGS and FTS. Mixed ionic-electronic conducting membranes in capillary form were also developed for high temperature oxygen separation from air. These membranes can be used for both Autothermal Reformin... [more]

This paper presents an experimental study of the self-initiation reaction of n-butyl acrylate (n-BA) in free-radical polymerization. For the first time, the frequency factor and activation energy of the monomer self-initiation reaction are estimated from measurements of n-BA conversion in free-radical homo-polymerization initiated only by the monomer. The estimation was carried out using a macroscopic mechanistic mathematical model of the reactor. In addition to already-known reactions that contribute to the polymerization, the model considers a n-BA self-initiation reaction mechanism that is based on our previous electronic-level first-principles theoretical study of the self-initiation reaction. Reaction rate equations are derived using the method of moments. The reaction-rate parameter estimates obtained from conversion measurements agree well with estimates obtained via our purely-theoretical quantum chemical calculations.

An electromagnetic continuous casting mould designed is proposed with a non-uniform slit distribution structure. This design has aimed to reduce the number of slits so that the mould’s strength is enhanced, whilst maintaining a similar metallurgy effect. In this paper, the metallurgy effect for the designed mould is investigated through the magnetic field distribution along the casting direction, the uniformity feature in the vicinity of the meniscus region, the temperature variation of the molten alloy pool and the mould wall. The results show that the designed mould achieved a similar effect as compared to the original mould; however, the configuration is simplified. This research highlights the topic of mould structure optimization, which would enable the Electromagnetic continuous casting (EMCC) technique to be utilized with greater ease by industry.

Application of titanium dioxide (TiO₂) as a photocatalyst has presented a promising avenue for the safe photocatalytic degradation of pollutants. Increasing levels of the release of pharmaceuticals in the environment and formation of the intermediates during their degradation may impose health and environmental risks and therefore require more attention. Photocatalytic degradation of acetylsalicylic acid (aspirin) was carried out in the presence of the TiO₂-filled polymeric film as a photocatalyst under solar light irradiation. The polymeric film incorporates TiO₂ in the matrix, which acts as a photocatalyst under solar illumination and degrades the acetyl salicylic acid (ASA) into a range of organic compounds before complete demineralization (formation of carbon dioxide and water as final products). Among the intermediates, acetic acid was found to be present in a larger amount compared to other organic acids. The qualitative/quantitative analyses of the intermediates resulted in the... [more]

The authors wish to correct Table A1 of the published paper in Processes [1].[...]

In this paper, measurable disturbance compensation techniques are analyzed, focusing the problem on the input-output and disturbance-output time delays. The feedforward compensation method is evaluated for the common structures that appear between the disturbance and process dynamics. Due to the presence of time delays, the study includes causality and instability phenomena that can arise when a classical approach for disturbance compensation is used. Different feedforward configurations are analyzed for two feedback control techniques, PID (Proportional-Integral-Derivative) and MPC (Model Predictive Control) that are widely used for industrial process-control applications. The specific tuning methodology for the analyzed process structure is used to obtain improved disturbance rejection performance regarding classical approaches. The evaluation of the introduced disturbance rejection schemes is performed through simulation, considering process constraints in order to highlight the adv... [more]

In production of electricity from coal, integrated gasification combined cycle plants typically operate with conventional packed bed reactors for the water-gas shift reaction, and a Selexol process for carbon dioxide removal. Implementation of membrane reactors in place of these two process units provides advantages such as increased carbon monoxide conversion, facilitated CO₂ removal/sequestration and process intensification. Proposed H₂-selective membranes for these reactors are typically of palladium alloy or ceramic due to their outstanding gas separation properties; however, on an industrial scale, the cost of such materials may become exorbitant. High-performance polymeric membranes, such as polybenzimidazoles (PBIs), present themselves as low-cost alternatives with gas separation properties suitable for use in such membrane reactors, given their significant thermal and chemical stability. In this work, the performance of a class of high-performance polymeric membranes is assesse... [more]

This work focuses on designing the optimum raceway pond by considering the effects of sunlight availability, temperature fluctuations, and harvest time on algae growth, and introduces a dynamic programing model to do so. Culture properties such as biomass productivity, growth rate, and concentration, and physical properties, such as average velocity, pond temperature, and rate of evaporation, were estimated daily depending on the dynamic behavior of solar zenith angle, diurnal pattern of solar irradiance, and temperature fluctuations at the location. Case studies consider two algae species (Phaeodactylum. tricornutum and Isochrysis. galbana) and four locations (Tulsa, USA; Hyderabad, India; Cape Town, South Africa; and Rio de Janeiro, Brazil). They investigate the influences of the type of algae strain and geographical location on algae biomass production costs. From our case studies, the combination of I. galbana species grown in Hyderabad, India, with a raceway pond geometry of 30 cm... [more]

Polymer processes often contain state variables whose distributions are multimodal; in addition, the models for these processes are often complex and nonlinear with uncertain parameters. This presents a challenge for Kalman-based state estimators such as the ensemble Kalman filter. We develop an estimator based on a Gaussian mixture model (GMM) coupled with the ensemble Kalman filter (EnKF) specifically for estimation with multimodal state distributions. The expectation maximization algorithm is used for clustering in the Gaussian mixture model. The performance of the GMM-based EnKF is compared to that of the EnKF and the particle filter (PF) through simulations of a polymethyl methacrylate process, and it is seen that it clearly outperforms the other estimators both in state and parameter estimation. While the PF is also able to handle nonlinearity and multimodality, its lack of robustness to model-plant mismatch affects its performance significantly.

This work presents a methodology to represent logical decisions in differential algebraic equation simulation and constrained optimization problems using a set of continuous algebraic equations. The formulations may be used when state variables trigger a change in process dynamics, and introduces a pseudo-binary decision variable, which is continuous, but should only have valid solutions at values of either zero or one within a finite time horizon. This formulation enables dynamic optimization problems with logical disjunctions to be solved by simultaneous solution methods without using methods such as mixed integer programming. Several case studies are given to illustrate the value of this methodology including nonlinear model predictive control of a chemical reactor using a surge tank with overflow to buffer disturbances in feed flow rate. Although this work contains novel methodologies for solving dynamic algebraic equation (DAE) constrained problems where the system may experience... [more]

Chemical processes with complex reaction mechanisms generally lead to dynamic models which, while beneficial for predicting and capturing the detailed process behavior, are not readily amenable for direct use in online applications related to process operation, optimisation, control, and troubleshooting. Surrogate models can help overcome this problem. In this research article, the first part focuses on obtaining surrogate models for emulsion copolymerization of nitrile butadiene rubber (NBR), which is usually produced in a train of continuous stirred tank reactors. The predictions and/or profiles for several performance characteristics such as conversion, number of polymer particles, copolymer composition, and weight-average molecular weight, obtained using surrogate models are compared with those obtained using the detailed mechanistic model. In the second part of this article, optimal flow profiles based on dynamic optimisation using the surrogate models are obtained for the product... [more]

This paper discusses the initial steps towards the formulation and implementation of a generic and flexible model centric framework for integrated simulation, estimation, optimization and feedback control of polymerization processes. For the first time it combines the powerful capabilities of the automatic continuous on-line monitoring of polymerization system (ACOMP), with a modern simulation, estimation and optimization software environment towards an integrated scheme for the optimal operation of polymeric processes. An initial validation of the framework was performed for modelling and optimization using literature data, illustrating the flexibility of the method to apply under different systems and conditions. Subsequently, off-line capabilities of the system were fully tested experimentally for model validations, parameter estimation and process optimization using ACOMP data. Experimental results are provided for free radical solution polymerization of methyl methacrylate.

The editors of Processes would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2015. [...]

A nonlinear reduced-order state observer is applied to estimate the degree of polymerization in a series of polycondensation reactors. The finishing stage of polyethylene terephthalate synthesis is considered in this work. This process has a special structure of lower block triangular form, which is properly utilized to facilitate the calculation of the state-dependent gain in the observer design. There are two possible on-line measurements in each reactor. One is continuous, and the other is slow-sampled with dead time. For the slow-sampled titration measurement, inter-sample behavior is estimated from an inter-sample output predictor, which is essential in providing continuous corrections on the observer. Dead time compensation is carried out in the same spirit as the Smith predictor to reduce the effect of delay in the measurement outputs. By integrating the continuous-time reduced-order observer, the inter-sample predictor and the dead time compensator together, the degree of polym... [more]

This study aimed to develop optimal microwave assisted extraction conditions for recovery of phenolic compounds and antioxidant properties from the macadamia skin, an abundant waste source from the macadamia industry. Water, a safe, accessible, and inexpensive solvent, was used as the extraction solvent and Response Surface Methodology (RSM) was applied to design and analyse the conditions for microwave-assisted extraction (MAE). The results showed that RSM models were reliable for the prediction of extraction of phenolic compounds and antioxidant properties. Within the tested ranges, MAE radiation time and power, as well as the sample-to-solvent ratio, affected the extraction efficiency of phenolic compounds, flavonoids, proanthocyanidins, and antioxidant properties of the macadamia skin; however, the impact of these variables was varied. The optimal MAE conditions for maximum recovery of TPC, flavonoids, proanthocyanidins and antioxidant properties from the macadamia skin were MAE ti... [more]

Kinetic modeling of the bulk copolymerization of d-limonene (Lim) and n-butyl acrylate (BA) at 80 °C was performed using PREDICI®. Model predictions of conversion, copolymer composition and average molecular weights are compared to experimental data at five different feed compositions (BA mol fraction = 0.5 to 0.9). The model illustrates the significant effects of degradative chain transfer due to the allylic structure of Lim as well as the intramolecular chain transfer mechanism due to BA.

Integrated process and control design approach for cyclic distillation columns is proposed. The design methodology is based on application of simple graphical design approaches, known from simpler conventional distillation columns. Here, a driving force approach and McCabe-Thiele type analysis is combined. It is demonstrated, through closed-loop and open-loop analysis, that operating the column at the largest available driving force results in an optimal design in terms of controllability and operability. The performance of a cyclic distillation column designed to operate at the maximum driving force is compared to alternative sub-optimal designs. The results suggest that operation at the largest driving force is less sensitive to disturbances in the feed and inherently has the ability to efficiently reject disturbances.

Six Aspen Plus simulation files for the conversion of petroleum coke and/or natural gas to liquid fuels (synthetic gasoline and diesel) are presented. The base simulation files were designed with carbon capture and sequestration (CCS) technology with the corresponding plant without CCS.

The processes may include various technologies such as petcoke gasification, integrated gasification and autothermal natural gas reforming, gas cleaning, water gas shift reaction, MDEA based carbon capture, Claus process, FT synthesis, and other processing steps.

The six processes are: PSG_CCS (petcoke standalone gasification with CCS), PSG_No_CCS (petcoke standalone gasification without CCS), PG-INGR_CCS (petcoke gasification integrated natural gas reformer with CCS), PG-INGR_No_CCS (petcoke gasification integrated natural gas reformer without CCS), PG-ENGR_CCS (petcoke gasification external natural gas reformer with CCS), PG-ENGR_No_CCS (petcoke gasification external natural gas reformer with... [more]

This is the LAPSE stakeholder report for 2018, including news, new features, and the plan for the next year.

Dette er det LAPSE interessenter rapport for 2018, inkludert nyheter, nye funksjoner, og planen for neste år.

This paper describes the progress of our efforts to lead the CACHE (Computer Aids for Chemical Engineering Education) Task Force in transforming from chemical process design toward chemical product design. Through CACHE, we are coordinating the development of a library of product-design case studies. Beginning with preliminary product designs created previously over several semesters, we are arranging for faculty experts, knowledgeable in the underlying technology platforms, to work with student groups to enrich the product designs. Over a 3-year period, a collection of approximately 25 case studies is being prepared. This article describes the research envisioned as innovative product designs are created, both egarding applications of new technologies, and product design evolution/evaluation; and in advancing strategies for teaching product design. The anticipated use of these case studies in departments worldwide for design courses taught by similar technology experts, just a few in... [more]

Artificial neural networks (ANNs) are used in various applications for data-driven black-box modeling and subsequent optimization. Herein, we present an efficient method for deterministic global optimization of ANN embedded optimization problems. The proposed method is based on relaxations of algorithms using McCormick relaxations in a reduced-space [\textit{SIOPT}, 20 (2009), pp. 573-601] including the convex and concave envelopes of the nonlinear activation function of ANNs. The optimization problem is solved using our in-house global deterministic solver MAiNGO. The performance of the proposed method is shown in four optimization examples: an illustrative function, a fermentation process, a compressor plant and a chemical process optimization. The results show that computational solution time is favorable compared to the global general-purpose optimization solver BARON.