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• A plant-wide model is presented for continuous biomanufacturing benchmarking. • The model includes a tailored control strategy for dynamic simulation performance. • Realistic sensors and actuators consider measurement's noise and lag time. • Case study framework and examples are provided for user guidance. The pharmaceutical industry's shift towards biological therapeutics has led to a transition from conventional batch production to continuous manufacturing. This change highlights the crucial need for effective process monitoring and control strategies to ensure consistent product quality and stability. Open-source benchmark simulation models have become essential tools for refining these processes, offering a platform for testing research hypotheses. This study uses the production of Lovastatin as a case study for continuous biopharmaceutical production. A comprehensive dynamic model covering upstream and downstream components provides an integrated perspective of the production process. The study introduces a basic control system emphasizing realistic sensor and actuator integration to enhance simulation accuracy. It assesses the benchmark through open-loop and closed-loop simulations, offering an in-depth analysis of the KTB1 model's dynamic response and functionality. KTB1 represents a model-driven decision support tool that enables the evaluation of monitoring strategies, process design, process optimization, and control for biomanufacturing. [ABSTRACT FROM AUTHOR]

• Dynamic adsorption bed performance during feed transitions is analysed using gPROMS®. • VOC mixtures of dichloromethane with acetone, trichloromethane and toluene are studied. • Industrially relevant scenaria portraying transient VOC mixture feed conditions are defined. • The onset and duration of breakthrough in the bed is visualised, for all mixtures and cases. • Dichloromethane (DCM) breakthrough onset is fastest (transition also longest) in all cases. Minimisation of environmental footprint in line with sustainability goals rests at the top of the agenda of the pharmaceutical industry. Volatile Organic Compounds (VOCs), while essential to primary pharmaceutical manufacturing, are solvents whose emissions pose a risk to human health and ecosystems. Adsorption on activated carbon beds is an established technology for end of pipe emissions control, which, however, faces efficiency limitations by quick and irregular bed saturation due to complex, transient feeds. This study employs a validated nonisothermal, multicomponent adsorption model to quantitatively assess the exact effect and potential value of waste stream feed sequencing towards activated carbon bed utilisation optimisation. Our results indicate that gradual increase of dichloromethane feed concentration in combination with a low, constant inlet concentration of the strongly adsorbing component leads to the latest breakthrough onset for the dichloromethane-acetone, dichloromethane-chloroform and dichloromethane-toluene mixtures. Transient vs. constant feeds usage and their interplay clearly affects bed behaviour, paving the way to industrial VOC emission abatement scheduling and process optimisation. [ABSTRACT FROM AUTHOR]

• A Bayesian optimization approach is proposed to reduce the computational cost of dynamic concentration operating condition design. • Fixed temperature difference control strategy outperforms other conventional control strategies, and is convenient for industrial operation. • A surrogate model is developed based on the first principles model for further optimization. • The method can be applied to similar dynamic operation with different solutes and solvents. In the synthesis of pharmaceutical intermediates, concentration is commonly employed to separate the product and recycle the solvents. To achieve a cost-effective manufacturing, operating parameters shall be adjusted over time, which could traditionally be achieved based on dynamic simulation, but with significant computation cost. In this work, we introduced a Bayesian optimization approach to design the optimal operating condition of a pharmaceutical intermediate in the production of Lamivudine. Using a Gaussian process regression as the surrogate model, the approach tremendously reduced the computational cost in searching for the optimal design. In comparison to other commonly used intelligent optimization algorithms, the results demonstrate that the presented approach confers evident advantages, especially in reducing the tendency of getting trapped in local optima and in improving the speed of convergence to an optimal solution. [ABSTRACT FROM AUTHOR]

• A compression refrigeration system with evaporators at two temperature levels using the same refrigerant is studied. • Realistic dynamic models are developed that account for the thermal capacitance of the units being cooled. • A simple and effective control structure is tested for disturbances in the refrigeration load. The need for refrigeration cooling at two different sub-ambient temperature levels is an important problem in some processes. A modern grocery store is an extremely important global example in which there is a need for a moderate temperature heat sink (5 °C) to keep food cool but also a need for a significantly colder heat sink (− 20 °C) for frozen food products. If the two temperatures are not too different, a single refrigerant can be used. The compression refrigeration configuration then consists of two compressors operating in parallel, a single condenser, a single refrigerant liquid surge drum and multiple evaporators. Liquid refrigerant at high pressure is split into a large number of parallel streams to feed individual evaporators in the cooling and freezing compartments. This paper studies how this multi-variable interacting dynamic system can be modeled and controlled using simple conventional controllers. [ABSTRACT FROM AUTHOR]

• To reduce the occurrence of alarm floods, improved rationalization strategies are introduced to evaluate the quality and effectiveness of multivariate alarm systems developed in recent research. • Strategies demonstrated on an exothermic CSTR result in a significant reduction in nuisance alarms. • Real-time risk of the rationalized alarm systems were evaluated using dynamic risk assessment by estimating their failure probabilities using multiple dynamic simulations. • The posterior distribution, constructed for the exothermic CSTR using Bayesian statistics, had much lower variance as compared to one developed using a flat prior. In this paper, improved alarm rationalization strategies are introduced to evaluate the quality of the multivariate alarm systems developed in previous work – with the alarm thresholds and response actions modified appropriately, based on key statistical metrics. For an exothermic CSTR, our strategies resulted in a significant reduction in the number of nuisance alarms, focusing on only quality alarms, which, if ignored, are more likely to result in an abnormal shift in operation to the undesirable regions. Next, their real-time performance is evaluated using dynamic risk analysis (DRAn), in which, the associated risk is analyzed by estimating the failure probabilities of the multivariate alarm systems using Bayesian statistics, based on multiple dynamic simulations for the process, inclusive of control, alarms and response actions. As expected, the failure probability distribution developed for the exothermic CSTR has a much lower variance as compared to one developed using a flat prior distribution. [ABSTRACT FROM AUTHOR]

• Optimal operation of a large-scale gas sweetening plant was conducted by application of self-optimizing control and model predictive control. • Optimization of the process was performed using surrogate models based on neural networks. • Performance analysis of the proposed control structure using traditional PIDs and modern multivariable MPCs was carried out using dynamic simulation. The most common method of removing acid gases from natural gas is through the use of solvent-based gas sweetening plants, which are energy-intensive. The present study aims to establish a plant-wide structure to operate natural gas sweetening plants optimally. Thus, a steady-state simulation of the Khangiran plant was carried out, and a 17% reduction in energy usage was achieved as a result of the optimization by the application of surrogate models. The self-optimizing method was applied to find the best set of controlled variables (CVs). There was found one unconstrained degree of freedom (DOF). The best CV for the remaining DOF was found to be the top stage temperature of the regenerator. Aspen Plus Dynamics was used to examine the performance of the proposed control structure utilizing simple traditional PIDs and compare it to modern feedback and feedforward MPCs. [Display omitted] [ABSTRACT FROM AUTHOR]

• Integrated bioreactor-filtration (primary recovery) design is key in biopharmaceutical manufacturing. • Detailed mathematical modelling and parameterisation of rotational filter behaviour is completed. • Dynamic optimisation of fed-batch and perfusion bioreactors for mAb production is achieved. • Technoeconomic evaluation of optimal integrated designs vs. a variety of parameters is performed. • Fed-batch bioreactors combined with stacked membrane microfilters emerge as industrially optimal. Primary post-cultivation biomass recovery (cell culture removal from API-rich solutions) is essential in biopharmaceutical manufacturing. Centrifugation and depth filtration are dominant industrial primary recovery technologies, but mechanistic dynamic models suitable for performance evaluation are scarce. This paper uses established literature models to present and analyse optimal operation strategies for integrated process designs of fed-batch or perfusion CHO bioreactors (for mAb cultivation via CHO cultures), with an explicit rotational disk (dynamic crossflow) filtration model (for primary recovery). A rigorous DAE filter model (Marke et al., 2020) is employed here, to evaluate system performance. Dynamic optimisation of bioreactor-filter systems has been completed for different bioreactor types, filter arrangements and feed manipulations, considering the same annual mAb plant production target. A technoeconomic analysis of optimal designs addresses industrial viability, confirming a clear cost advantage of fed-batch reactors combined with stacked membrane microfilters. [ABSTRACT FROM AUTHOR]

• A four-column extractive distillation system using natural gas liquid as heavy solvent is used to separate CO 2 –C 2 H 6 azeotrope. • Fixed reflux ratio and reflux/feed ratio control structure are used to investigate the controllability of four-column extractive distillation. • The reflux/feed ratio controller of four columns can adjust the reflux ratio in real time according to the disturbance of feed flow and composition, which greatly improves the stability of the top distillation products purity. The existence of heterogeneous azeotrope of CO 2 –C 2 H 6 makes it difficult to separate CO 2 from the hydrocarbons in the associated gas by cryogenic extractive distillation process. A four-column extractive distillation system using natural gas liquid as heavy solvent is used to separate CO 2 –C 2 H 6 azeotrope. Carbon dioxide, ethane, propane and butane are recovered from the top of the extractive distillation column, deethanizer, depropanizer and debutanizer respectively. The C3+ hydrocarbon mixture called natural gas liquid is recovered at the bottom of the debutanizer, one part of which is transported as NGL product and the other part is pumped back near the top of the extractive distillation column as solvent. The purpose of this paper is to develop an effective plant wide control structure for this four-column extractive distillation system. Fixed reflux ratio and reflux/feed ratio control structure are used to investigate the controllability of four-column extractive distillation. Results show that both control structures have successfully realize the dynamic simulation of the extractive distillation process. However, under the disturbance of feed flow rate and composition, the controllability of reflux/feed ratio control structure on purity of top distillation products is better than that of fixed reflux ratio control structure. The reflux/feed ratio controller of four columns can adjust the reflux ratio in real time according to the disturbance of feed flow and composition, which greatly improves the stability of the top distillation products purity. [ABSTRACT FROM AUTHOR]

• Systematic procedure to develop physics-based empirical models for predicting gas flow and power for reciprocating compressors with suction valve unloaders. • Embedding proposed models within commercial process simulators like Aspen HYSYS or Unisim. • Demonstrating utility of our empirical models for simulating steady state and dynamic operations of reciprocating compressors. • Illustrating the full range application of our contribution using real data from a BOG compression train in an LNG regasification terminal. • Usefulness of our empirical models for real life applications is elucidated by comparing them with popular machine learning approaches. Major countries are installing Liquefied Natural Gas (LNG) terminals worldwide, as they transition towards carbon-free economies. Compressors are energy-intensive equipment in LNG import/export terminals. While reciprocating compressors are in wide use, models to estimate volumetric and energetic efficiencies do not exist, especially for those with suction valve unloaders. Furthermore, commercial process simulators such as Aspen HYSYS or Unisim are not equipped to simulate them rigorously. This paper presents a procedure to develop empirical models for predicting flow and power based on process insights and real operational data. It also demonstrates how these models can be embedded inside simulators to simulate compressor operations in both steady and dynamic modes. Real data from a BOG compressor train in an LNG regasification terminal are used to illustrate the full range of their applications. Finally, the suitability and efficacy of data-driven machine learning approaches are evaluated to show the superiority of proposed empirical models. [ABSTRACT FROM AUTHOR]

Highlights • LabVIEW based Graphical User Interface to simulate the process behaviour. • Simplified functional decomposition approach based dynamic modelling. • Analysis of concentration polarization effect on process performance. • Reasonably high feed water temperature reduces specific energy consumption. Abstract The reverse osmosis (RO) process has become one of the prominent membrane-based technologies for water desalination to meet the demand for fresh water. This paper presents the results of simulations of the RO desalination process based on simplified functional-decomposition approach-based modelling to understand the process dynamics. The simulation model was validated by comparing the transient behaviour predicted by the model with experimental data from an industrial seawater desalination process. The proposed work was carried out using the Control Design and Simulation (CDSim) toolkit in the LabVIEW 2011 environment. The simulation analysis showed that the specific energy consumption of the RO system could be reduced at different fractional recovery rate by maintaining a reasonably high feed temperature. [ABSTRACT FROM AUTHOR]

Highlights • Several control structure are proposed and evaluated based on selected control performance criteria. • An effective control structure using a feed-forward ratio with composition controller for this process is determined. • Model-based HAZOP is conducted for safety analysis and hazard identification by integration of dynamic simulation and HAZOP. • A quantitative variables trend and change rate due to quantitative deviations is obtained through dynamic simulation. • A general procedure based on simulation for design and safety analysis of chemical process is proposed. Abstract In this article, the plantwide control of a novel process for diethyl oxalate production via two steps is investigated. The unique feature of this process is that there is a closed regeneration-coupling circulation. It results in that two steps should be matched properly and mass balance for overall reaction should be satisfied precisely. An effective control structure using a feedforward ratio with composition controller is determined. Later, safety analysis for this process is investigated by the integration of dynamic simulation and HAZOP (hazard and operability analysis). In comparison with heuristic HAZOP, quantitative deviations can be introduced. Quantitative variation trends and change rates of important variables can be determined. Determining increase rate in temperature and pressure is significantly important, since response time as indirect indictor can be used to assess the possibility of risk. Finally, a general procedure based on simulation for design and safety analysis of chemical process is proposed. [ABSTRACT FROM AUTHOR]

Highlights • Semi-batch production of nitrile from fatty acid and ammonia was computer simulated using Aspen Plus and Aspen Plus Dynamics. • Comparison and validation with industrial data was done. • Opportunities for improving the process were evaluated and the main result is a reduction in batch cycle time. Abstract A semi-batch reactor is used to produce nitriles by reacting fatty acids and ammonia. Despite it is an old chemical process and many patents are available in the literature, its mathematical model was not developed until now. This process comprises a semi-batch reactor with recycle, which makes the numerical solution a challenge to face. In this paper, the entire process has been computer simulated for the very first time. Aspen Plus software was used to find the initial condition for the set of differential algebraic equations, which will be solved by Aspen Plus Dynamics, the key tool to ensure that the entire batch cycle could be properly programmed. Besides that, PI controllers were implemented to guarantee normal and safety operation of the process evaluated, in other words, controllers performed well in tracking pressure and composition profiles, target conversion for the desired product and level behavior. The simulated results were validated with industrial data and opportunities for improving the process were evaluated. The main result was a reduction in batch cycle time for around 40 min. [ABSTRACT FROM AUTHOR]

Highlights • A Gaussian process based model is constructed to simulate a complex biological system. • Model accuracy and predictive capability is compared against the neural network model. • Dynamic optimisation under uncertainty is conducted to maximise algal lutein production. • A framework to build bioprocess models with Gaussian Processes is presented. Abstract Dynamic modeling is an important tool to gain better understanding of complex bioprocesses and to determine optimal operating conditions for process control. Currently, two modeling methodologies have been applied to biosystems: kinetic modeling, which necessitates deep mechanistic knowledge, and artificial neural networks (ANN), which in most cases cannot incorporate process uncertainty. The goal of this study is to introduce an alternative modeling strategy, namely Gaussian processes (GP), which incorporates uncertainty but does not require complicated kinetic information. To test the performance of this strategy, GPs were applied to model microalgae growth and lutein production based on existing experimental datasets and compared against the results of previous ANNs. Furthermore, a dynamic optimization under uncertainty is performed, avoiding over-optimistic optimization outside of the model's validity. The results show that GPs possess comparable prediction capabilities to ANNs for long-term dynamic bioprocess modeling, while accounting for model uncertainty. This strongly suggests their potential applications in bioprocess systems engineering. [ABSTRACT FROM AUTHOR]

Pressure swing adsorption (PSA) has attracted significant recent interest for chemical process intensification due to its potential for high energy efficiency and amenability to small, modular designs. However, the lack of simulation tools that are readily available, transparent, and trusted, has been identified as a serious impediment to widespread adoption of PSA, as well as to further research on PSA modeling, numerical solution, optimization, and control. This paper presents a complete framework for dynamic modeling and simulation of PSA processes and its implementation in an open-source simulator called toPSAil. The presentation is tutorial and includes many modeling and implementation details often overlooked in existing literature. Novel methods are presented for handling flow reversals and implementing various pressure–flow relationships, along with controlled boundary conditions. Finally, the code contains several innovations designed to improve efficiency and reduce the extensive trial-and-error tuning often required to produce a working PSA cycle. [Display omitted] • Presents a complete framework for dynamic modeling and simulation of pressure swing adsorption (PSA) processes. • Introduces a new MATLAB ®-based open-source dynamic simulator for PSA processes called toPSAil. • Novel methods for modeling and implementing various pressure–flow relationships and controlled boundary conditions. • Novel methods for improving efficiency and reducing extensive trial-and-error tuning often required to produce working PSA cycles. [ABSTRACT FROM AUTHOR]

The dynamic response of benzene alkylation process to a set of deviations is analyzed with Aspen Plus Dynamics. A quantitative risk assessment is developed through simulations of deviation scenarios. The process comprises a reactor and three distillation columns with a recycle stream. The simulation scenarios are determined according to lessons learnt from accidents. This study underlines the conditions that induce an overpressure or a flooding in a distillation column. Three scenarios are proposed: feed flowrate variations, coolant flowrate reduction and cooling of the reboiler steam. Thereafter, the results allow calculating a set of risk indexes related to flooding and overpressure phenomena. This study underlines the deviation propagation effects that can be expected in all the process equipment. Moreover, it represents a significant contribution to the definition of the process control strategy and the necessary safety barriers. [ABSTRACT FROM AUTHOR]

Highlights • Very accurate RSM surrogate models for three high-dimensional plant simulations. • Used for quick calculation of operability characteristics. • Limitations of Plant-wide control structures revealed. Abstract This work generalizes a preliminary investigation (Georgakis and Li, 2010) in which we examined the use of Response Surface Methodology (RSM) for the estimation of surrogate models as accurate approximations of high-dimensional knowledge-driven models. Three processes are examined with higher complexity than before, accounting for a much larger number of input and output variables. The surrogate models obtained are used to analyze several steady-state plant-wide characteristics. In all processes, the knowledge-driven model is a dynamic simulation with a plant-wide control structure of multiple SISO controllers. This type of controller proves to not be robust enough in its stability characteristics to enable substantial changes in the set-points. The net-elastic regularization is successfully used for the estimation of the metamodel parameters, avoiding overfitting and eliminating insignificant terms. Cross validation is used to compare and evaluate the relative accuracy of the quadratic and cubic models. [ABSTRACT FROM AUTHOR]

This article advocates a nonsmooth differential-algebraic equations (DAEs) modeling paradigm for dynamic simulation and optimization of process operations. A variety of systems encountered in chemical engineering are traditionally viewed as exhibiting hybrid continuous and discrete behavior. In many cases such discrete behavior is nonsmooth (i.e. continuous but nondifferentiable) rather than discontinuous, and is appropriately modeled by nonsmooth DAEs. A computationally relevant theory of nonsmooth DAEs (i.e. well-posedness and sensitivity analysis) has recently been established ( Stechlinski and Barton, 2016a, 2017 ) which is suitable for numerical implementations that scale efficiently for large-scale dynamic optimization problems. Challenges posed by competing hybrid modeling approaches for process operations (e.g. hybrid automata) are highlighted as motivation for the nonsmooth DAEs approach. Several examples of process operations modeled as nonsmooth DAEs are given to illustrate their wide applicability before presenting the appropriate mathematical theory. [ABSTRACT FROM AUTHOR]

Here, the implementation of the gradient-based Economic MPC (Model Predictive Control) in an industrial distillation system is studied. The approach is an alternative to overcome the conflict between the MPC and RTO (Real Time Optimization) layers in the conventional control structure. The study is based on the rigorous dynamic simulation software (SimSciDynsim ® ) that reproduces the real system very closely and is able to communicate with Matlab. The gradient of the economic function, is obtained through the sensitivity tool of the real-time optimization package (SimSciROMeo ® ). In order to study the pros and cons of the new strategy, a propylene distillation system is simulated with both, the proposed approach (one-layer MPC + RTO) and the conventional two-layer hierarchical structure of control and optimization. The results show that, for this particular system, from the performance, stability and disturbance rejection viewpoint, the proposed gradient-based extended control method is equivalent or better than the conventional approach. [ABSTRACT FROM AUTHOR]

Accurate physical dynamic models applied as digital twins are vital for developing advanced control strategies and optimizing dynamic plant operation. First principle models are often large-scale, complex, computationally expensive, and not real-time capable. As a result, they need to be reduced for application in optimization and control. This article introduces the Dynamic Edmister Method, which is a generic numerically robust model reduction approach used for dynamic distillation columns. In illustrative case studies, the Dynamic Edmister Method is applied to a digital twin of the pressure column of an air separation unit. The method is validated by simulations of a start-up procedure and a step test. Both case studies show that the reduced models accurately reproduce the dynamic and steady-state behavior of the underlying rigorous model while reducing the calculation effort by 70%. The model reduction approach presented is a significant first step towards using digital twins for dynamic optimization. • Development of a novel model reduction approach for distillation columns. • Dynamic adaptation of the Edmister short-cut method. • Integration of the model reduction approach into the ASU digital twin concept. • Up to 70% reduction of the required CPU time in a column start-up and step test scenario. • Accurate approximation of the column's process dynamics and steady state profiles. [ABSTRACT FROM AUTHOR]

Volatile Organic Compound (VOC) use is extremely widespread in the pharmaceutical industry, posing great risks, as potential organic gas releases are harmful to both environment and human health. Fixed-bed columns containing Activated Carbon (AC) or other adsorbents selectively remove VOCs from gas effluent streams. Nevertheless, adsorbing beds can be quickly and/or irregularly saturated, due to simultaneous and significant variations of flowrates and mixture compositions. This paper presents the development and implementation of a dynamic, non-isothermal adsorption model used for studying binary VOC mixture adsorption on industrial AC beds for a wide variety of structural and operating conditions. A scenario-based investigation of binary mixture behaviour examines (via multiple dynamic simulations, experimental corroboration and predictive formulas) the effect of key parameter changes on bed performance. Theoretical bed performance analysis (employing Glueckauf hodographs) has been employed to provide valuable insight into nonisothermal VOC capture bed operation, for both clean and used beds. [ABSTRACT FROM AUTHOR]

A comprehensive dynamic model for an LNG storage tank in a typical regasification terminal, operating in holding mode, is presented. The model incorporates LNG recirculation for cooling the transfer lines for loading/unloading. It assumes a hypothetical thin vapour interface in equilibrium with the liquid to compute LNG evaporation, which allows the boil-off gas to be hotter than the tank LNG, as observed in practice. A numerical procedure based on the secant method is implemented in MATLAB for solving the governing ordinary differential equations. For the special case of N 2 -free LNG, a semi-analytical solution is proposed to solve the dynamic model for this relatively complex system and compute the amount of boil-off gas (BOG). The semi-analytical solution is subsequently used to optimize the LNG storage tank and recirculation loop designs. [ABSTRACT FROM AUTHOR]

Seawater desalination is an important method for producing fresh water, a critical resource in many areas of the globe. Multi-stage flash distillation (MSF) is a leading technology within the thermal desalination field. Mathematical modelling and simulation provides a means to enhance engineering and operation of complicated production plants. This paper presents a new method for one-dimensional modelling and dynamic simulation of thermal desalination processes. The approach combines the simultaneous mass, momentum, and energy solution, local phase equilibrium by Rachford-Rice equation, and rigorous calculation of the seawater properties as function of temperature, pressure and salinity. A brine recycling MSF plant was modelled as a case study, presenting advanced and unpublished simulated features and transients. The successful results suggest that the method presented is a competent approach for dynamic simulation of thermal desalination processes. [ABSTRACT FROM AUTHOR]

Liquefied natural gas (LNG) is a prominent clean energy source available in abundance. LNG has high calorific value, while lower price and emissions. Vapors generated from LNG due to heat leak and operating-condition-changes are called boil-off gas (BOG). Because of the very dynamic in nature, the rate of BOG generation during LNG loading (jetty BOG, or JBOG) changes significantly with the loading time, which has not been well studied yet. In this work, the LNG vessel loading process is dynamically simulated to obtain JBOG generation profiles. The effect of various parameters including holding-mode heat leak, initial-temperature of LNG ship-tank, JBOG compressor capacity, and maximum cooling-rate for ship-tank, on JBOG profile is studied. Understanding JBOG generation would help in designing and retrofitting BOG recovery facilities in an efficient way. Also, several JBOG utilization strategies are discussed in this work. The study would help proper handling of BOG problems in terms of minimizing flaring at LNG exporting terminals, and thus reducing waste, saving energy, and protecting surrounding environments. [ABSTRACT FROM AUTHOR]

“Abnormal situation management” (ASM) in general refers to the various tasks required for online fault diagnosis and also hazard mitigation. Although quite a few ASM-related studies have already been carried out in the past, none of them addressed the wide range of issues consistently and rigorously with the same modeling tool. An automata-based strategy is therefore proposed in this work to synthesize all operating procedures needed for diagnostic tests and also other emergency response operations in the batch processes. The proposed model building techniques are suitable not only for characterizing all components in any given process, but also for representing the operation targets of all ASM tasks. Finally, notice that every resulting procedure can be readily expressed with an implementable sequential function chart (SFC). [ABSTRACT FROM AUTHOR]

• Dynamic simulation model of 660MW ultra-supercritical circulating fluidized bed boiler. • "Core-annulus" flow structure for gas-solid phase. • Dynamic characteristics of hot and cold start-up processes. This study involved the development of a full-scale dynamic simulation model for a 660MW ultra-supercritical circulating fluidized bed (CFB) boiler–with the largest scale and maximum capacity. The boiler is presently under construction in China and includes a water-steam system, an air-flue gas system, a material supply system, and an ash circulation system. The gas–solid flow in the furnace was modeled based on the "core-annulus" flow structure, and the six-equation solution for the water–steam flow was used to simulate the dynamic behaviors of the water-steam system. Based on a design condition of 50% turbine heat acceptance (THA), a steady-state simulation model was established and calibrated. Consequently, cold and hot start-up processes at 0-50% THA were simulated to investigate the dynamic behaviors of the CFB boiler. Compared with the design conditions, the steady-state and transient simulation models demonstrated high accuracy. [ABSTRACT FROM AUTHOR]

Dynamic reduced models (D-RMs) derived from rigorous models are highly desired for speeding up dynamic simulations. A useful software tool named D-RM Builder was developed to automatically generate data-driven D-RMs from high-fidelity dynamic models. It allows a user to configure input/output variables, sample input space and generate sequences of step changes, launch high-fidelity model simulations, fit simulation results to a D-RM, and finally visualize and validate the D-RM. The Decoupled A-B Net (DABNet) nonlinear system identification model was used as the main D-RM type and was enhanced to model nonlinear multiple input and multiple output dynamic systems with options for double-pole formulation to handle fast/slow time scales and pole value optimization. The D-RM Builder tool has been successfully used to generate D-RMs for a highly nonlinear pH neutralization reactor system and a two-time-scale bubbling fluidized bed adsorber-reactor for CO 2 capture. [ABSTRACT FROM AUTHOR]

Dividing wall column configurations have a large savings potential in terms of capital and energy. This paper uses dynamic simulation to investigate three alternative control structures for one of these configurations, namely the Kaibel column. Four components, here selected as methanol, ethanol, n -propanol and n -butanol, are separated into pure products within a single column shell. Control structure 1 (CS1) uses only temperature controllers and is therefore particularly interesting from an industrial point of view. Since the control objective is to control the four product compositions, the two other control structures use also composition controllers. Surprisingly, for composition control, the simple temperature control scheme (CS1) is almost as good at steady-state and much better from a dynamic point of view than the two other more complex control structures. [ABSTRACT FROM AUTHOR]

The current work presents a modeling-on-demand-based multivariable control performance monitoring (CPM) strategy. The suggested approach addresses several challenging topics in multi input-multi output CPM area such as data-driven characteristics, recursive/adaptive philosophy, modeling, plant-wide control (PWC) performance/feasibility indicator, simple structure, minimum interference with the process operation and recovering actions suggestions. The new model-on-demand (MoD) algorithm combines partial least squares (block-wise and moving-window), model quality index, and the reference matrix concepts to improve the robustness characteristics of the recursive process, i.e. the model adaptation is only performed when it is needed. Recovery actions may involve changes on tuning parameters as well as control structure modifications. The proposed strategy allows to identify static and dynamic abnormal events in the process which could produce strong degradation of the PWC performance. The robustness of the proposed methodology is tested by dynamic simulations on the well-known Shell fractionator process and compared with some classical recursive algorithms. • Modeling-on-demand-based multivariable control performance monitoring. • Plant-wide control performance/feasibility indicator. • Integrated block-wise and moving-window PLS approach. • Recovery actions: retuning and control structure modifications. • Minimally invasive strategy from the process point of view. [ABSTRACT FROM AUTHOR]

• Rate-based dynamic absorption/desorption model including the plant periphery. • Transient experiments carried out in a absorption/desorption pilot plant. • First successful validation of a dynamic absorption/desorption model. • The model is general and extendable to other absorption-loop systems. Reactive absorption is one of the most important separation processes used within the chemical industry to address the environmental protection challenges. In this process, undesirable gaseous components are captured by chemical reaction in a solvent and the loaded solvent is then regenerated in the desorption unit. Both process steps take place simultaneously and strongly interact resulting in a very complex process behavior. To ensure stable and safe process operation, even in presence of instabilities/malfunctions, understanding of the dynamic process behavior is essential. In this work, the development of a novel dynamic model for simulation of a reactive absorption/desorption process in a closed-loop configuration including the periphery of the plant is presented. The validation of the model is accomplished based on two dynamic experiments carried out in our own pilot plant. The deviations between experimental and simulated outlet gas concentrations are below 10% for both experiments. [Display omitted] [ABSTRACT FROM AUTHOR]

This paper presents computer-based design and analysis of control systems for centrifugal compressors when the operating fluid is supercritical CO 2 . It reports a non-linear dynamic model including a main forward compression line and two different configurations for the recycle antisurge line. Disturbance scenarios are proposed for testing the configurations and performance indicators are suggested to evaluate control performance and power consumption of the compression system. The paper demonstrates that compared to the hot recycle, the process configuration including a cold gas recycle has better overall stability, but higher power consumption and lower values for the control performance indicators. Based on the previous considerations, the paper gives suggestions regarding the choice of the recycle configuration. Moreover it compares subcritical and supercritical compression during surge prevention and highlights the importance of the selection of the gas recycle configuration when full recycle is needed. [ABSTRACT FROM AUTHOR]

A number of decentralized and distributed control schemes based on model predictive control (MPC) have been introduced in the last years. They have been proposed as viable solutions to the computational, transmission and robustness issues arising in the centralized context in case of large-scale and/or distributed plants. Such MPC-based control schemes are very heterogeneous, based on different model structures and realizations, with different features and infrastructural/memory/computational requirements. In this paper, we test and compare, with a realistic case study, a robust non-cooperative scheme and a cooperative iterative one. The main scope is to analyze and unravel, in a fair comparison scenario, these methods from different viewpoints, spanning from the model realization issues to the communication and computational requirements, to the control performances. The benchmark case study consists of an existing natural gas refrigeration plant. Realistic simulations and validation tests are obtained through in the DynSim industrial process simulation environment. [ABSTRACT FROM AUTHOR]

A generalized approach for the calculation of complex chemical and phase equilibria is presented that is based on the simulation of the dynamic evolution of a mixture from non-equilibrium initial composition towards the final equilibrium composition. The proposed method is able to solve pure chemical or phase equilibria as well as simultaneous chemical/phase equilibria. The advantage of our approach compared to conventional equilibrium calculations is the fact that the approach is physically motivated and can handle chemical and phase equilibria as well as simultaneous chemical and phase equilibria. [ABSTRACT FROM AUTHOR]

In this communication, the concept of bottom flashing under the mechanical heat pump system is introduced in the batch distillation columns. Proposing an operating strategy at transient state, a numerical control mechanism is formulated to simultaneously adjust the following variables aiming to ensure the optimal use of internal heat source: flow rate of reboiler liquid subjected to bottom flashing, operating pressure of throttling valve, compression ratio for pressure adjustment in the isentropic compressor and external heat input to the reboiler. The potential of this novel energy efficient batch distillation is numerically quantified in terms of the two performance indexes, namely energy savings and cost. Finally, a binary system is dynamically simulated to demonstrate the proposed configuration. [ABSTRACT FROM AUTHOR]

Natural gas liquefaction process using mixed and/or cascade refrigerant is popular in onshore LNG (liquefied natural gas) plant. Similar attempt has been adopted for FLNG (floating LNG) but still needed for the improvement of the process to enhance its efficiency as well as reliability. The dynamic modeling of cold box which is a core equipment in LNG/FLNG plant enabling to liquefy natural gas is crucial in order to develop or improve a liquefaction process concerning operability and controllability. A decomposition methodology for dynamic modeling of cold box in the case of lack of internal design data at early design stage is presented. The proposed methodology is validated through the industrial application of offshore natural gas liquefaction process and expected to be extensively applied to the various process designs which require dynamic simulation of cold box unit. [ABSTRACT FROM AUTHOR]

Molecular weight distribution (MWD) is an important quality index of polymer products. Many methods have been proposed to dynamically simulate the MWD of polymerization, but these methods are normally designed for serial computations. In this paper, a multi-thread parallel computation method was proposed for multisite free-radical polymerization. Analysis of the relationship among different subtasks revealed a combined parallel strategy by fully exploiting the parallel feature of the process. A good performance was obtained to accelerate the dynamic simulation of MWD based on Flory method. We theoretically analyzed the speedup ratio (SR) and parallel efficiency (PE). Results showed that software algorithm and hardware configuration exhibited a good match. The efficiency of the proposed parallel method was presented through industrial slurry processes that used high-density polyethylene (HDPE). [ABSTRACT FROM AUTHOR]

Vacuum/pressure swing adsorption is an attractive and often energy efficient separation process for some applications. However, there is often a trade-off between the different objectives: purity, recovery and power consumption. Identifying those trade-offs is possible through use of multi-objective optimisation methods but this is computationally challenging due to the size of the search space and the need for high fidelity simulations due to the inherently dynamic nature of the process. This paper presents the use of surrogate modelling to address the computational requirements of high fidelity simulations needed to evaluate alternative designs. We present SbNSGA-II ALM, surrogate based NSGA-II, a robust and fast multi-objective optimisation method based on kriging surrogate models and NSGA-II with the Active Learning MacKay (ALM) design criterion. The method is evaluated by application to an industrially relevant case study: a two column six step system for CO 2 /N 2 separation. A 5 times reduction in computational effort is observed. [ABSTRACT FROM AUTHOR]

• Industrial scale fed-batch and perfusion bioreactors are optimised to maximise mAb outputs. • Seeding densities and campaign length are varied to probe their effect on bioreactor performance. • Technoeconomic analysis of optimised designs completed by means of plant-life costing metrics. • Fed-batch operation (high initial seed density, short campaign time) is the most cost-effective design. • Monoclonal antibody (mAb) cellular yield is greater for perfusion, indicating strong future promise. The variation of antigen binding sites on monoclonal antibodies (mAbs) enables manufacturing of the latter for targeted treatment of a variety of ailments, including cancer types and autoimmune diseases. Fed-batch operation of biochemical reactors used to manufacture mAbs grants the ability to manipulate cell dynamics via intermittent feeding of nutrients/substrates. Regulatory authority agendas (e.g. the U.S. Food & Drug Administration) consider the development of continuous technologies (e.g. perfusion reactors) as essential towards improved technoeconomic potential and biopharmaceuticals quality control. This paper presents dynamic simulations for multiple operational scenaria of a fed-batch and a perfusion reactor, in which a hybridoma cell culture is used to secrete mAb glycoforms. A novel dynamic optimisation of the fed-batch as well as perfusion reactors has also been conducted towards maximising the total mAb mass produced. Nonlinear Programming (NLP) formulations with the use of APOPT and IPOPT solvers have been employed to derive the manipulation, state and controlled variable trajectories, to achieve the mAb production maximisation objective. The detailed technoeconomic analysis clearly highlights strong benefits for the fed-batch bioreactor (especially over a plant-life time horizon), but also showcases a definite cost-related promise of perfusion bioreactor technologies, given the higher mAb yield. [ABSTRACT FROM AUTHOR]

• A dynamic model of a fludized bed catalytic cracker is developed. • The model includes the reactor and fractionator for the cracked products. • A regulatory control system is included. • An open-source MATLAB implementation is provided. The present study describes the capabilities of an open source integrated framework for the dynamic simulation and control of a refining operation, comprising a fluidized bed catalytic cracker (FCC) and a fractionator. A detailed cracking reaction scheme that yields realistic predictions of product distributions is used. In addition, the fractionator is rigorously modeled and solved using the dynamic stagewise adiabatic flash algorithm. A regulatory control layer is also included. Two simulation examples are shown for set point tracking and FCC feed quality disturbance rejection, respectively. We expect that the model can serve as a platform for multiple research efforts, including algorithm development and benchmarking in fault detection, control and process operations. The model can be downloaded using the following link: https://github.com/Baldea-Group/FCC-Fractionator. [ABSTRACT FROM AUTHOR]

• A computer-aided toolbox for design and control of reactive distillation systems is presented. • The toolbox allows study of different reacting systems with in-house and user-added designs. • Two integration of design and control methods are compared for a benchmark. • Reactive distillation system involving ethyl tert-butyl ether production. • Integration of design and control of a reactive distillation system involving ethyl acetate production. • With multiple feed streams and multiple products is presented. Control and operation of intensified processes are inherently difficult due to a reduced region of controllability, which originates from a high degree of interaction between the design-control parameters. As a result, a design with feasible steady-state operation may be dynamically inoperable due to the inability to ensure stability in the open-loop or closed-loop. To address these issues, an integrated design-control toolbox, which is tailor-made for reactive distillation (RD) processes, is proposed in this work. Given a set of design-control parameters, this RD-Toolbox links in-house tools to required external tools and guides the user to set-up steady-state and dynamic simulations and perform controllability analysis. To demonstrate the range of functionalities of the RD-Toolbox, two case studies are presented, i.e., ethyl tert-butyl ether (ETBE), and ethyl acetate production. For the ETBE case study, the design-control parameters are obtained through two integrated design-control methods, namely the superstructure optimization method and the driving force-based method. In terms of controllability, both designs for the ETBE system could efficiently reject feed disturbances. For the ethyl acetate case, the suggested set of design-control parameters corresponding to the maximum driving force-based design could exhibit satisfactory control performance. The results illustrate the advantages of using the RD-Toolbox for fast, reliable, and efficient solution and analysis of RD processes. [ABSTRACT FROM AUTHOR]

A procedure is suggested to separating a minimum-boiling azeotrope of toluene and ethanol via heat integration pressure swing distillation (PSD), and an optimized separation configuration is obtained via taking the minimization of the total annual cost (TAC) as an objective function. The result demonstrates that PSD with heat integration is more economical than conventional PSD without heat integration. Based on steady-state simulation results, several control structures were explored using Aspen Dynamics. The results indicate that the composition/temperature cascade control structure and the pressure-compensated temperature control of a PSD process with partial heat integration with stage 21 selected as the control stage in the low pressure column can handle disturbances well. As for the PSD with full heat integration, stage 20 of the low pressure column can act as the control stage because of its more efficient controllability under feed flow rate and feed composition disturbances. [ABSTRACT FROM AUTHOR]

Convection dominated processes in chemical engineering are frequently accompanied by steep propagating fronts. Numerical simulation of corresponding models with uniform fixed grids requires an excessive amount of grid points along the expected range of the front movement. In this contribution the implementation of an efficient adaptive grid method is presented and applied to two relevant spatially one-dimensional cases, the chlorination stage of the Deacon process and oxygen storage processes in a three-way catalyst. The algorithm exhibits a high accuracy with a much lower number of grid points and a therefore reduced computational effort as opposed to a fixed grid simulation. The present work demonstrates that the algorithm allows for a robust, simple, and fast implementation of the adaptive grid method in common simulation tools and, together with adequate supplementary material, aims to make the method readily accessible to the interested reader. [ABSTRACT FROM AUTHOR]

Highlights: [•] Novel computational platform for dynamic process models within a computer algebra system (Mathematica™). [•] DAE model encapsulation and related data-structures with solver interface. [•] DAE model optimization tool (standalone reverse-communication SQP solver). [•] Standardized routines for model pre-processing and post-solution analysis. [•] Seamless computational workflow for complex calculations a part of which are dynamic simulation and optimization. [ABSTRACT FROM AUTHOR]

Abstract: One approach for representing uncertainty is the use of fuzzy sets or fuzzy numbers. A new approach is described for the solution of nonlinear dynamic systems with parameters and/or initial states that are uncertain and represented by fuzzy sets or fuzzy numbers. Unlike current methods, which address this problem through the use of sampling techniques and do not account rigorously for the effect of the uncertain quantities, the new approach is not based on sampling and provides mathematically and computationally rigorous results. This is achieved through the use of explicit analytic representations (Taylor models) of state variable bounds in terms of the uncertain quantities. Examples are given that demonstrate the use of this new approach and its computational performance. [Copyright &y& Elsevier]

Abstract: Liquefied petroleum products such as propane, butane, LPG and LNG are transported by ships and stored in tanks in storage terminals. These products are conveyed from the jetty by above-ground insulated pipelines to storage terminals that are typically situated 12–20km inland. Unloading of petroleum products is energy intensive and results in excessive BOG (boil off gas) generation and pressure build up in the storage tank. In this work, a dynamic model of the unloading operation is developed to predict temperature dynamics of pipeline, pressure and inventory changes in the storage tank. This model consists of a lumped dynamic model for the storage tank coupled with a distributed parameter model for the pipeline. The model is validated using limited data collected from an operating plant during unloading of propane. Dynamic simulation results of the model are presented to indicate the trade-off that exists between the pre-cooling and unloading operating strategies. [Copyright &y& Elsevier]

Abstract: Ethyl-acetate is generally produced by the esterification reaction of ethanol with acetic-acid. Since the reaction is equilibrium-limited, the use of reactive distillation is an attractive option. A new double-column system is suggested for ethyl-acetate production by applying reactive pressure swing batch distillation. The system was investigated by a feasibility study based on the analysis of reactive and non-reactive residue curve maps. Two different process options were found to be feasible. In the first option, the reactive column operates at the lower pressure (1.01bar), and the non-reactive column that removes ethyl-acetate from the system operates at the higher pressure (10bar). The second option allows the reactive column to operate at the higher pressure (10bar), and the non-reactive column removes water at the lower pressure (1.01bar). The first process option was studied by rigorous simulation based on less simplifying assumptions using a professional dynamic simulator. The influence of the most important operation parameters was also studied. [Copyright &y& Elsevier]

Abstract: Dynamic simulation models can be used along with flow and pressure measurements, for on-line leak detection and identification in gas pipeline networks. In this two part paper, a methodology is proposed for detecting and localizing leaks occurring in gas pipelines. The main features of the proposed methodology are: (i) it is applicable to both single pipelines and pipeline networks and (ii) it considers non-ideal gas mixtures. In order to achieve the desired computational efficiency for on-line deployment, an efficient state estimation technique based on a transfer function model, previously developed by the authors, is embedded in a hypothesis testing framework. In Part-I of this paper, a detailed description of the methodology is presented, and its performance is evaluated using simulations on two illustrative pipeline systems. The proposed method is shown to perform satisfactorily even with noisy measurements and during transient conditions, provided there is sufficient redundancy in the measurements. [Copyright &y& Elsevier]

Abstract: In Part-I of this two part paper, a method is proposed for on-line leak detection and identification in gas pipeline networks using flow and pressure measurements. Simulations on two illustrative networks were used to demonstrate the applicability of the proposed method. In this paper, the performance of the proposed leak detection and identification methodology was evaluated using experiments with compressed air on a laboratory scale network. The on-line applicability of the proposed methodology was demonstrated through field level leak detection tests carried out on a 204.7km long pipeline in India, supplying natural gas to a power plant. The laboratory and field tests demonstrated that the proposed methodology can be used for quick on-line detection of leaks, and locating the leaks reasonably accurately. [Copyright &y& Elsevier]

Abstract: Two new double column systems operated in closed mode are suggested for pressure swing batch distillation. These configurations are investigated by feasibility studies based on several simplifying assumptions (e.g., infinite plate number, no stage hold-up) and are compared with double column batch rectifier and double column batch stripper in open mode. We study the configurations also by rigorous simulation based on less simplifying assumptions using a professional dynamic simulator. For the different configurations the influence of the most important operational parameters is studied. The results obtained for open and close modes are compared. The calculations and the simulations are performed for a binary minimum (acetone–n-pentane) and for a maximum (ethylene-diamine–water) azeotrope mixture. [ABSTRACT FROM AUTHOR]

Abstract: A new double column system (DCS) operated in closed mode is suggested for heterogeneous batch distillation. This configuration is investigated by feasibility studies based on the assumption of maximal separation and is compared with the traditional batch rectifier (BR). We study the configurations also by dynamic simulation based on a detailed model using a professional simulator. For the new configuration the minimal duration of the process is determined. The influence of the most important operational parameters is studied. The calculations and the simulations are performed for a binary (n-butanol–water) and for a ternary heteroazeotropic mixture (isopropanol–water+benzene as entrainer). One of the advantages of the DCS is that distillation of binary and ternary systems is performed in only one step. Furthermore the recovery of components is usually higher and the amount of byproducts is lower. [Copyright &y& Elsevier]

Abstract: The objective of this paper was to compare the prediction of the equilibrium (EQ) and nonequilibrium (NEQ) models during safety analysis of a reactive distillation column focusing on the identification of hazardous situations or particular operability problems. The safety and operability analyses are based on application of the HAZOP procedure integrated with a mathematical model with the aim to determine the column response to deviations from normal operation conditions or during a nonstandard procedure, e.g. the start-up of the reactive distillation column. A significant part of the safety and operability problems analysis is the identification of multiple steady states and their stability. A reactive distillation column can in general exhibit multiple steady states which reduce the column operability and controllability during perturbations of the manipulated variables and particularly during the start-up and shut down procedures. The EQ and NEQ models were compared focusing on prediction of the multiple steady states phenomenon and of the consequences which can result from this phenomenon. [Copyright &y& Elsevier]