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• A fine-scale decomposition of process variations is proposed for closed-loop system supervised by process performance. • The influences of control actions on process performance and dynamics are concurrently analyzed for process monitoring. • Process static and dynamic information are separately analyzed for detection of different operating conditions. • The validity of the proposed method is illustrated with two industrial processes. Closed-loop control is widely used in modern industrial processes to ensure that process performance such as product quality and waste discharge are maintained at the predefined set-points. However, control actions which may compensate the disturbances on process performance and result in obvious process dynamics cause great challenges to process monitoring. The influences of control actions on process performance and dynamics for process monitoring have not been fully investigated before. Thus, a performance-relevant full decomposition of slow feature analysis termed PFDSFA here, is proposed for process monitoring under closed-loop control by simultaneously considering the influences of process variations on process performance and dynamics. First, the new algorithm extracts variations which are closely relevant to performance variables using canonical correlation analysis. Based on it, process variable space can be decomposed into performance-relevant subspace and process-relevant subspace. Then, both static and dynamic variations of each subspace are extracted to design monitoring statistics which can distinguish normal operating condition deviations from dynamic anomalies incurred by real faults. The proposed PFDSFA algorithm offers a fine-scale decomposition of process variations and achieves comprehensive process monitoring of process static and dynamic characteristics. Besides, it is efficient in indicating whether disturbances make influence on process performance and dynamics. Finally, two case studies are employed to illustrate the applicability and efficacy of the proposed algorithm in comparison with some other monitoring approaches. [ABSTRACT FROM AUTHOR]

The aspect of collaboration is gaining a considerable amount of importance in current logistics operations. The large number of dynamics that arise in collaborative logistics processes with numerous complexities and variations can make the modelling of such collaborative logistics processes a challenging task. Hence, a systematic modelling approach is required to make sense of the enormous amount of unorganised process information. In this paper, we present an ontological method for modelling the dynamics within collaborative logistics processes. An activity theory-guided approach is employed to elicit the process information, which is then formalised using an ontological model. Dynamic adaptations for the collaborative logistics process operations are supported through an instance level inference of the model. The applicability of the method is demonstrated by means of a case study. [ABSTRACT FROM AUTHOR]

In order to study the mechanical loads of a workpiece in manufacturing processes such as single-tooth milling, in-process measurements of workpiece deformations are required. To enable the resolution of shock waves due to the mechanical impact of the tool, a novel measurement system based on speckle photography is introduced to measure the dynamic deformations and strains with a high temporal and spatial resolution. The measurement results indicate deformations and strains propagating through the workpiece with the speed of sound triggered by the tool impact (i.e., the tool impact is shown to induce shock waves during milling). Finite element simulations of the workpiece behavior are performed in addition, which support the experimental findings. In the considered case, the dynamic excitation subsides after 300 ms. Hence, in processes with even shorter cyclic multiple loads, the tool encounters an already excited initial state during machining, which needs to be taken into account when precisely modeling the milling process and the resulting workpiece quality. Finally, the measurement results demonstrate that speckle photography in combination with modern high-speed cameras and compact short-pulse lasers provides a deeper understanding of individual manufacturing processes. [ABSTRACT FROM AUTHOR]

In order to provide more sensitive monitoring results, the time dynamics and steady-state operating conditions should be separately monitored by distinguishing time information from the steady-state counterpart. However, it is a more challenging task for batch processes because they vary from phase to phase presenting multiple steady states and complex dynamic characteristics. To address the above issue, a concurrent monitoring strategy of multiphase steady states and process dynamics is developed for batch processes in this paper. On one hand, multiple local models are constructed to identify a steady derivation from the normal operating condition for different phases. On the other hand, based on the recognition that the process dynamics can be considered to be irrelevant with the steady states, a global model is built to detect the dynamics anomalies by monitoring the time variations. Corresponding to alarms issued by different statistics, different operating statuses are indicated with meaningful physical interpretation and deep process understanding. To illustrate the feasibility and efficacy, the proposed algorithm is applied to the injection molding process, which is a typical multiphase batch process. [ABSTRACT FROM AUTHOR]

Highlights • Mapping the variations in process gas and available excess heat of an integrated steel mill. • Investigation of the effects of steel mill operation variations on the performance of a chemical absorption CO 2 plant. • The capture plant responds to changes very differently depending on the season and the type of variation. • Implementing CO 2 capture with chemical absorption in an integrated steel mill requires flexible operation of the capture plant. Abstract The present work aims to map the variations in process gas and available excess heat of an integrated steel mill and to investigate the effects of these variations on the performance of a chemical absorption CO 2 plant. Two time-scales are considered for the variations: seasonal and hourly changes. Dynamic process simulations are used to investigate the dynamic interactions between the steel mill and the capture unit. This includes the effect that periodic variations in the reboiler heat duty have on the performance of the capture plant and the effect of implementing a control strategy. The mapping of the operation of the steel mill reveals numerous variations on an hourly basis that are important for the design and operation of the capture plant, including decreases in the blast furnace gas (BFG) flow to 0% on approximately 10 occasions per year and variations of ±30 MW in the available heat more than 40 times per year. The simulations show that the capture unit responds very differently depending on the season, with a generally slower response during winter operation due to a lower level of circulation of the solvent. The capture unit shows also non-linearity in its response to changes in heat load - the deviation from the steady-state value is more pronounced when the heat is increased than when it is decreased. Thus, the simulation results indicate that implementing CO 2 capture with chemical absorption in an integrated steel mill requires flexible operation of the capture plant. Dynamic simulations over a two-week period with historical (hourly) boundaries demonstrate that the capture process can operate in the presence of the steel mill variations. Implementation of a decentralized control strategy increases the amount of captured CO 2 by 1.2%. [ABSTRACT FROM AUTHOR]

How do people make decisions between an immediate but small reward and a delayed but large one? The outcome of such decisions indicates that people discount rewards by their delay and hence these outcomes are well described by discounting functions. However, to understand irregular decisions and dysfunctional behavior one needs models which describe how the process of making the decision unfolds dynamically over time: how do we reach a decision and how do sequential decisions influence one another? Here, we present an attractor model that integrates into and extends discounting functions through a description of the dynamics leading to a final choice outcome within a trial and across trials. To validate this model, we derive qualitative predictions for the intra-trial dynamics of single decisions and for the inter-trial dynamics of sequences of decisions that are unique to this type of model. We test these predictions in four experiments based on a dynamic delay discounting computer game where we study the intra-trial dynamics of single decisions via mouse tracking and the inter-trial dynamics of sequences of decisions via sequentially manipulated options. We discuss how integrating decision process dynamics within and across trials can increase our understanding of the processes underlying delay discounting decisions and, hence, complement our knowledge about decision outcomes.

Friction stir welding (FSW) is a resource-efficient and environmental-friendly solid state joining process that allows to combine especially aluminum alloys with superior joint quality. Therefore, FSW is perfectly suitable for light-weight applications. The interaction of material, welding tool and machine during welding results in process forces which show characteristic periodic variations. The reasons for this periodicity, however, are not completely understood yet. Since the welding force feedback data can presumably be used for online process monitoring, a deeper understanding of the processes leading to the friction stir welding dynamics is necessary. To reach this goal, an approach for a systematic investigation of the friction stir welding dynamics using postulated hypotheses is presented in this work. The hypotheses combine insights from literature as well as results from own welding experiments. In the experiments two aluminum alloys, EN AW 6016 and EN AW 6111, in tempers T4 and T6 each, were friction stir welded. The welding machine, the tool as well as the welding parameters were held constant for each material. The process forces, accelerations and spindle deflection were measured for each weld and additionally the joints were inspected visually for flaws. It was shown that the height of the process forces correlates loosely with the yield strength of the materials. The frequencies occurring during welding are identified to mainly consist of the spindle rotating speed and multiples thereof. The acceleration measurements are found to be a suitable way to identify welds with irregular surfaces, i.e. they provide a method for online process monitoring regarding the weld surface quality. Combining the findings from literature and insights from the experiments, five hypotheses are developed that allow a systematic investigation of the dynamics of the friction stir welding process. Each hypothesis covers a phenomenon that can lead to dynamic effects. The hypotheses consider not only the process but the whole system of process and machine. In addition to the hypotheses, a method to prove or disprove them, where the specific effects are triggered intentionally, is presented. [ABSTRACT FROM AUTHOR]

Today the modeling of the process dynamics and the complex two-phase flows in mills still remain a challenging task. In this study the dynamic comminution process in a fluidized bed opposed jet mill is investigated. For this purpose, well-defined model glass beads were ground in a lab-scale mill. The particle size distributions (PSDs) inside the mill and at the outlet, solid concentrations and the holdup of the mill were recorded. By comparing the morphology of the ground material with that of particles examined in single particle stressing experiments, we conclude that the predominant stressing mechanism in the mill is determined by a high number of low intensity stressing events. Furthermore, the grinding kinetics is strongly influenced by the solid holdup within the mill and the initial PSD of the feed material. A higher holdup leads to a higher product mass flow rate with slightly finer particles. The determined high solid concentration in the transport section of the mill indicates a high loading of the classifier which increases with the holdup. Our study shows that the internal recirculation is crucial for the overall performance of the mill: Due to imperfect classification, particles accumulate inside the mill which is further enhanced by a high holdup of fine particles. Our results clearly show that the classification and transport processes must be studied in detail for any in-depth understanding of dry fine grinding in fluidized bed opposed jet mills. [ABSTRACT FROM AUTHOR]

Solid waste management is an inevitable challenge for Chinese government during the island construction practice in the South China Sea. Composting, if it is properly put into application, can constitute an environment friendly and sustainable method for solid waste management on these newly-built artificial coral reefs, due to its great potential to improve coral sand soil with low cost. As the key components of island solid wastes, kitchen waste, faeces and sewage sludge were combined in ratio of 1:1:1, which conformed to the actual production and constituted a mixed waste system. Thus, using a self-made intelligent reactor, this paper presented the performance and potential of mixed treatment of kitchen waste, faeces and sewage sludge through co-composting with the coamendment of sawdust and cornstalk. A series of process parameters were monitored, the laws about degradation and resynthesis of organic matter, transformation and loss of nitrogen were revealed in this paper. The results indicated that applying the aerobic composting technology to the solid waste treatment in the mixed system of kitchen waste, faeces and sewage sludge with coamendment of sawdust and cornstalk was feasible, and the optimal mixed ratio of total waste to coamendment was 4:1 on analysis of technique and economics. [ABSTRACT FROM AUTHOR]

The energetics of the original Closed-Circuit RO (CCRO) may be improved by adding a reciprocating-piston cylinder whose size may not be adjusted in real time during operation, thus limiting the maximum stroke length of the piston. In this work, the effect of the actual-to-ideal ratio of cylinder sizing on the performance of the improved CCRO is analyzed. If the cylinder is under-sized, the CC filtration step may start with the original CCRO and transition to the improved CCRO. If over-sized, only the improved CCRO is implemented, while the CC filtration and flushing periods are extended. For ultra-high recovery applications studied in this work, under-sizing the cylinder by 70 % or over-sizing by 50 % revealed a 2 % or less extra energy consumption using a spatiotemporal model, confirming its operational flexibility. [ABSTRACT FROM AUTHOR]

The wetting behavior in laser brazing can be designated as inconstant, caused largely by external process discontinuities such as the wire feeding. To reveal periodic melt pool propagation effects that occur during laser brazing of aluminum and for a better understanding of those effects in laser brazing in general, this paper analyzes high-speed recordings of the brazing process with aluminum alloy. It is demonstrated that two main effects of periodic melt pool behavior in different frequency scales occur during the process, related directly to the wire feeding.

In order to study the mechanical loads of a workpiece in manufacturing processes such as single-tooth milling, in-process measurements of workpiece deformations are required. To enable the resolution of shock waves due to the mechanical impact of the tool, a novel measurement system based on speckle photography is introduced to measure the dynamic deformations and strains with a high temporal and spatial resolution. The measurement results indicate deformations and strains propagating through the workpiece with the speed of sound triggered by the tool impact (i.e., the tool impact is shown to induce shock waves during milling). Finite element simulations of the workpiece behavior are performed in addition, which support the experimental findings. In the considered case, the dynamic excitation subsides after 300 ms. Hence, in processes with even shorter cyclic multiple loads, the tool encounters an already excited initial state during machining, which needs to be taken into account when precisely modeling the milling process and the resulting workpiece quality. Finally, the measurement results demonstrate that speckle photography in combination with modern high-speed cameras and compact short-pulse lasers provides a deeper understanding of individual manufacturing processes.

A dynamic system is analyzed by the simulation of two subsystems (for the part and the tool) that interact through the dynamic link formed by the machining process. This link corresponds to the smoothing forces, which may be expressed in terms of the state of the dynamic system. The dynamic stability and behavior of the system are expressed in terms of displacements from equilibrium. [ABSTRACT FROM AUTHOR]

Repeated counteraction of current knowledge and reality observation generates new knowledge and can be viewed as a dynamic process. When observed objects are not results of human activity, the dynamics results in acquisition of new knowledge, usually as a refinement of the existing one. Otherwise, adjustment between incomplete knowledge and reality can be a result of intentional modification of objects in question, as it happens in design of any artifact. In this case convergence of the process is questionable, for example, it may imply the end of the technical progress. In worst case scenario, the same computable criteria used simultaneously to modify objects and evaluate the result quality causing drift from an established goal and devaluation of acquired knowledge. [ABSTRACT FROM AUTHOR]

The industrially important selective oxidation of n -butane over vanadium phosphorus oxide catalysts in fixed bed reactors is affected by phosphorus induced dynamic changes of the catalyst activity. An economic process management therefore requires an adequate control of the operating conditions including the precise addition of a phosphorus containing compound in the ppm range. In a previous work (Lesser et al., 2016) we experimentally investigated these phenomena and related our findings to the diverse literature discussions abound reaction mechanism and active sites. Based on our conclusions, the present work provides a detailed model for the phosphorus dynamics which is connected to a two-dimensional heterogeneous reactor model. The model is able to describe the reactor behavior properly over 500 h time on stream including many variations of the operating conditions. The dynamically changing activity profiles reflect the evolution of temperature profiles and product compositions with only minor deviations. [ABSTRACT FROM AUTHOR]

This paper presents a set of steady-state and transient data for dynamic process model validation of the chemical absorption process with monoethanolamine (MEA) for post-combustion CO2 capture of exhaust gas from a natural gas-fired power plant. The data selection includes a wide range of steady-state operating conditions and transient tests. A dynamic process model developed in the open physical modeling language Modelica is validated. The model is utilized to evaluate the open-loop transient performance at different loads of the plant, showing that pilot plant main process variables respond more slowly at lower operating loads of the plant, to step changes in main process inputs and disturbances. The performance of four decentralized control structures is evaluated, for fast load change transient events. Manipulation of reboiler duty to control CO2 capture ratio at the absorber's inlet and rich solvent flow rate to control the stripper bottom solvent temperature showed the best performance. [ABSTRACT FROM AUTHOR]

This work aims at proposing a batch rectifier with bottom flashing (BRBF) scheme, in which, a fraction of reboiler content is dynamically flashed to lower its temperature so that the exiting liquid can be used as a heat sink against the overhead vapor (heat source) in the condenser. Receiving latent heat from that vapor, the flashed liquid gets vaporized and merges with the flashed vapor. Recovering pressure of this combined stream, it is used as a boil-up vapor in the reboiler, thus lowers the external heat duty. By this way, the proposed BRBF arrangement reduces the utility consumption in both the reboiler and condenser. To improve the energetic potential further, the boil-up vapor produced in the flashing loop is proposed to split into a couple of fractions and distributed in intermediate stage(s) along with the reboiler. The BRBF coupled with this interreboiling action is subjected to economic feasibility test, for which, the concerned column configurations need to be dynamically close, if not same. Since the batch processing is inherently a transient operation, it is not trivial to have their dynamics close. To make the comparison meaningful, we formulate an open-loop control scheme that makes sure that the BRBF follows the conventional batch rectifier (CBR) dynamics, which is used as a basis. Finally, a binary system is simulated to demonstrate the proposed BRBF with and without interreboiling. It is investigated that the BRBF configuration provides an about 68% energy savings with a payback time of 3 yr. Further, proposing interreboiling in the BRBF column increases the energy savings to 81%, reducing the payback time to 2.32 yr. [ABSTRACT FROM AUTHOR]

In this work a novel integrated biokinetic wastewater treatment (WWT) model based on the smoothed particle hydrodynamics (SPH) method as hydraulic model is proposed. Significant outcomes of this work are the computation of a detailed spatial distribution of compounds in WWT basins and the quantification of the effects of the stirrer induced mixing on the evolution of compounds. SPH is a meshfree particle method which herein is applied to compute a treatment plant's reactor hydraulics. The characteristic feature of SPH is to describe a fluid's dynamics by particles that move along with the flow. The present WWT model takes advantage of this principle by assigning the compounds’ concentrations, which are defined by the activated sludge model no. 1, to SPH particles. A full-scale treatment plant simulation with a variable stirrer induced mixing intensity in the denitrification basin is performed. A spatial distribution of the compounds’ concentrations, which up to now was unknown for unsteady flows, is computed and analysed. The developed framework is generic and therefore expected to be applicable for modelling chemical engineering processes which are influenced by hydrodynamic effects. [ABSTRACT FROM AUTHOR]

The process dynamics of single-screw extrusion on mixtures of polypropylene (PP) and recycled PP were studied using a statistical, design of experiments (DoE) approach. For a conventional screw design, the barrel temperature, screw speed and two vastly different melt viscosity polypropylene mixtures were selected as the independent factors, whilst melt pressure, mass output, screw torque and temperature rise at the die due to shear heating were the dependent responses. A central composite design (CCD) in the framework of response surface methodology (RSM) was constructed, and an analysis of variance (ANOVA) was carried out to determine the significance of the response surface models. The resulting statistical and response surface predictions have demonstrated that the low viscosity component concentration in the blend is a dominating factor on melt pressure and screw torque, apart from the expected effect of screw speed on output. Viscous heating is affected only by screw speed and recycled polypropylene concentration. Furthermore, the predictions have identified a wider process operating window with increased low-viscosity component concentration. The data confirm that statistical tools make quantitative predictions for the effects of experimental process variables, in accordance with the expected qualitative trends towards process optimisation, providing scope towards its application in scaled-up industrial processes. [ABSTRACT FROM AUTHOR]

Recently, a novel heat-pump-assisted extractive distillation process taking place in a dividing-wall column was proposed for bioethanol dehydration. This integrated design combines three distillation columns into a single unit that allows over 40% energy savings and low specific energy requirements of 1.24 kWh/kg ethanol. However, these economic benefits are possible only if this highly integrated system is also controllable to ensure operational availability. This paper is the first to address the challenges related to process dynamics and control of this highly integrated system. After showing the control difficulties associated with the original design owing to thermal unbalance, an efficient control structure is proposed which introduces a by-pass and an additional external duty stream to the side reboiler. The range of the external duty is rather small, about 5% of the combined duty of the reboilers, but sufficient to stabilize the system by controlling the temperature on the pre-concentration side of the column. Two quality control loops ensure product purity when the system is affected by feed flowrate and composition disturbances. [ABSTRACT FROM AUTHOR]

Este trabajo presenta un método para la construcción de Modelos Semifisicos de Base Fenomenológica (MSBF). El método se basa en los fenómenos de transporte, tránsito, transmisión o transferencia, y en el principio de conservación. Se da una descripción detallada de los pasos del método propuesto. Luego se aplica el método en la construcción de un modelo que describe el comportamiento de cinco dinámicas (volumen, biomasa, sustrato, producto y temperatura) en un proceso de fermentación en continuo. La simulación muestra que el modelo obtenido puede predecir de forma adecuada el comportamiento dinámico de dicho bioproceso.This work presents a method for building Phenomenological Based Semiphysical Models (PBSM). The method is based on transport, transfer, transmission or transit phenomena and conservation principle. A detailed description of proposed method steps is given. Next, the method is applied to attaining a model for describing the behavior of five dynamics (volume, biomass, substrate, product and temperature) of a continuous fermentation process. Model simulation shows that obtained model can predict dynamic performance of real process adequately.

A volume-varying stirred tank with a free-piston are placed in front of DuPont's Closed-Circuit RO (CCRO) system to achieve improved energetics. Valves are used to direct fluid flow and piston motion to enable cyclic operations consisting of CC filtration and flushing steps. Similar to CCRO, overall system recovery in the proposed system is controlled by the CC/flushing time ratio, and uninterrupted permeate production is possible if the flushing is done at high pressures. Spatiotemporal system-level models are developed and formulated as a set of coupled partial differential equations (PDEs) and ordinary differential equations (ODEs). Detailed numerical simulations and parametric studies are carried out to explore the flow and mass transfer characteristics and to compare its performance at the cyclic steady-state (CSS) with the original CCRO and the conventional steady-state RO. • An improved CCRO design is proposed to achieve the energetics of BRO. • Continuous permeate production is possible in the proposed system. • Cyclic dynamics are investigated using spatiotemporal models. • Approximate analytical solutions are provided to analyze energy breakdowns. • Advantages and limitations of original and improved CCROs are discussed. [ABSTRACT FROM AUTHOR]

• A high-order tensor slow feature model for the 3D batch data is proposed. • The 3D batch data are analyzed directly without unfolding operation. • The slowly varying dynamics within batch processes is efficiently extracted. • Two sub-optimal problems are iteratively used to solve the propsoed method. • Within-batch detection can be conducted based on the applied wavelet functions. How to establish efficient monitoring models for complex batch processes is a challenging problem because of the three-dimensional (3-D) data array and serious dynamics. The unfolding operation in most methods would destroy the batch data structure and increase the dimensions of modeling data obviously. Meanwhile, it is more practical to perform within-batch detection rather than end-of-batch detection. In this work, a novel high-order tensor slow feature analysis model is proposed to handle the 3-D and dynamical issues simultaneously. The proposed model can be solved by iteratively tackling two sub-optimal problems. Within-batch detection is performed based on the properly defined monitoring statistics to timely detect the abnormal situation. The multi-phase property is further considered in this work to improve detection accuracy. A simulated case and an industrial case are taken to show the merits of the proposed method. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effects of the characteristics of basic crop substrates, such as the carbon, nitrogen, ash and volatile fatty acids contents, on the dynamics of the anaerobic digestion process. For this purpose, the stepwise anaerobic digestion of silage from six different plant species was carried out. Scaled probability distributions (log-normal, log-logistic, logistic, Weibull and Gompertz) were used to approximate the cumulative methane production curves obtained. The results indicated that the Gompertz distribution best fit the process. The hazard function of the Gompertz distribution was used to describe the process change dynamics. Ridge regression models were made and tested to clarify the impact of the crop properties on the distribution parameters. The analysis results indicated that the initial rate of the process depended on the reactor acidity and that the nitrogen content of the substrate was a key factor that affected the process dynamics. [ABSTRACT FROM AUTHOR]

How do people make decisions between an immediate but small reward and a delayed but large one? The outcome of such decisions indicates that people discount rewards by their delay and hence these outcomes are well described by discounting functions. However, to understand irregular decisions and dysfunctional behavior one needs models which describe how the process of making the decision unfolds dynamically over time: how do we reach a decision and how do sequential decisions influence one another? Here, we present an attractor model that integrates into and extends discounting functions through a description of the dynamics leading to a final choice outcome within a trial and across trials. To validate this model, we derive qualitative predictions for the intra-trial dynamics of single decisions and for the inter-trial dynamics of sequences of decisions that are unique to this type of model. We test these predictions in four experiments based on a dynamic delay discounting computer game where we study the intra-trial dynamics of single decisions via mouse tracking and the intertrial dynamics of sequences of decisions via sequentially manipulated options. We discuss how integrating decision process dynamics within and across trials can increase our understanding of the processes underlying delay discounting decisions and, hence, complement our knowledge about decision outcomes. [ABSTRACT FROM AUTHOR]

This work initially focuses on developing a computational fluid dynamics (CFD) model of an industrial-scale steam methane reforming reactor (reforming tube) used to produce hydrogen. Subsequently, we design and evaluate three different feedback control schemes to drive the area-weighted average hydrogen mole fraction measured at the reforming tube outlet ( x ¯ H 2 outlet ) to a desired set-point value ( x ¯ H 2 set ) under the influence of a tube-side feed disturbance. Specifically, a CFD model of an industrial-scale reforming tube is developed in ANSYS Fluent with realistic geometry characteristics to simulate the transport and chemical reaction phenomena with approximate representation of the catalyst packing. Then, to realize the real-time regulation of the hydrogen production, the manipulated input and controlled output are chosen to be the outer reforming tube wall temperature profile and x ¯ H 2 outlet respectively. On the problem of feedback control, a proportional (P) control scheme, a proportional-integral (PI) control scheme and a control scheme combining dynamic optimization and integral feedback control to generate the outer reforming tube wall temperature profile based on x ¯ H 2 set are designed and integrated into real-time CFD simulation of the reforming tube to track x ¯ H 2 set . The CFD simulation results demonstrated that feedback control schemes can drive the value of x ¯ H 2 outlet toward x ¯ H 2 set in the presence of a tube-side feed disturbance and can significantly improve the process dynamics compared to the dynamics under open-loop control. [ABSTRACT FROM AUTHOR]