Steady-state Process Model Research Articles

Assessment of the operability of a 20 MWth calcium looping demonstration plant by advanced process modelling

The Calcium Looping (CaL) process is a promising technology for post-combustion CO2 capture from fossil-fired power plants and carbon intense industry. Within a CaL system, a limestone based sorbent stream is forced to circulation between two interconnected circulating fluidized bed (CFB) reactors. The main part of the CO2, contained in the flue gas stream is absorbed by CaO within the carbonator, whereas it is released during regeneration in the oxy-fired calciner. The feasibility of this technology was proven by numerous experimental investigations in semi-industrial scale. The next step in the development of this technology is expected to be a demonstration plant in the scale of approximately 20 MWth. The focus of this paper is the determination of the heat and mass balances and the assessment of the operability of a newly designed 20 MWth CaL demonstration plant. The investigations are based on a steady-state process model, which has been validated by experimental data from 1 MWth pilot tests. The aspect of solid entrainment during part load operation are addressed. In the present design case, a stable operation of the demonstration plant at 40 % equivalent carbonator load is feasible without additional flue gas recirculation.

Technical performance analysis and economic evaluation of a compressed air energy storage system integrated with an organic Rankine cycle

Energy storage becomes increasingly important in balancing electricity supply and demand due to the rise of intermittent power generation from renewable sources. The compressed air energy storage (CAES) system as one of the large scale (>100MW) energy storage technologies has been commercially deployed in Germany and the USA. However, the efficiency of current commercial CAES plants still needs to be improved. In this study, an integrated system consisting of a CAES system and an organic Rankine cycle (ORC) was proposed to recover the waste heat from intercoolers and aftercooler in the charging process and exhaust stream of the recuperator in discharging process of the CAES system. Steady state process models of the CAES system and ORC were developed in Aspen Plus®. These models were validated using data from the literature and the results appear in a good agreement. Process analysis was carried out using the validated models regarding the impact of different organic working fluids (R123, R134a, R152a, R245fa, R600a) of ORC and expander inlet pressures of the ORC on system performance. It was found that integrating ORC with the CAES system as well as selecting appropriate working fluid was a reasonable approach for improving performance of the CAES system. The round-trip efficiency was improved by 3.32–3.95% using five working fluids, compared to that of the CAES system without ORC. Economic evaluation on levelized cost of electricity (LCOE) was performed using Aspen Process Economic Analyser® (APEA). Different working fluids in ORC and different power sources (e.g. wind and solar) associated with the integrated system were considered to estimate the LCOEs. It was found that the LCOEs for the integrated system were competitive with fossil-fuel fired power and even lower than offshore wind power and solar power. The proposed research presented in this paper hopes to shed light on how to improve efficiency and reduce cost when implementing CAES.

Technoeconomic Evaluation of Multiple Mixed Suspension-Mixed Product Removal (MSMPR) Crystallizer Configurations for Continuous Cyclosporine Crystallization

Continuous crystallization using Mixed Suspension-Mixed Product Removal (MSMPR) crystallizers has been demonstrated as a feasible method for implementing continuous separations in pharmaceutical manufacturing processes. This work conducts a steady-state process modeling and simulation study of the continuous cooling crystallization of cyclosporine, comparing processes with and without solids recycle for their technoeconomic viability. The model describes population balance equations, crystallization kinetics, and process mass balances to compare attainable crystallization and plantwide yields of different process configurations. Total cost components using an established economic analysis methodology are compared for varying numbers of crystallizers, operating temperatures, total crystallizer cascade residence times and API feed concentrations. Economic analyses and the calculation of normalized cost components with respect to total crystallizer volumes identify the process without recycle as the most economically viable option, achieving the lowest total costs and low E-factors for pharmaceutical processes. The sensitivity of total costs to the selected total residence times for economic analyses highlights the need for rigorous comparison methodologies. This work identifies the need for technoeconomic optimization studies of continuous crystallization processes to establish the optimal design of manufacturing campaigns prior to further development.

Process Modelling of the Calcium Looping Process and Validation Against 1 MWth Pilot Testing

The calcium carbonate looping (CaL) process is a promising post-combustion technology for CO2 capture from fossil-fired power plants and carbon intense industries like steel and cement manufacturing. A CaL system consists basically of two interconnected circulating fluidized bed (CFB) reactors using natural limestone as a sorbent. Inside the carbonator, CO2 contained in the flue gas is absorbed by the exothermic carbonation reaction, during endothermic sorbent regeneration in the calciner, CO2 is released consequently. The CaL technology has proven its feasibility in semi-industrial scale by pilot testing in various test rigs all over the world. For the further development of the process, models are required for the prediction of process characteristics in terms of heat and mass flows. Most critical to the calculation of an overall process performance is the CO2 absorption efficiency in the carbonator and, moreover, the decreasing CO2 carrying capacity of the sorbent during operation. The enrichment of impurities like ash or calcium sulfate in the circulating sorbent as well as the reduction in particle size due to attrition needs also to be taken into account when assessing the performance of a CaL system. The main focus of this paper is the development of an advanced steady state process model and its validation against 1 MWth long term pilot testing. The validation of the process model showed good agreement in predicting the CO2 absorption efficiency of the carbonator as well as the sorbent regeneration in calciner. Furthermore, the composition, and the effect of attrition to particle size distribution of the circulating sorbent are reproduced with good accordance. The process model is further applied for a sensitivity study to show the influence of crucial parameters on the particle size reduction as well as on the calciner efficiency.

Modelling and process analysis of post-combustion carbon capture with the blend of 2-amino-2-methyl-1-propanol and piperazine

Recent pilot plant experiments have proved that a novel solvent blend of 2-amino-2-methyl-1-propanol (AMP) and piperazine (PZ) has better performance in energy saving than the traditional solvent monoethanolamine (MEA) for chemical absorption CO2 capture process. This paper presented the systemic study on modeling and process analysis of the CO2 capture process with an AMP+PZ aqueous solvent using Aspen Plus® software. A rate-based steady state process model was developed by updating the thermodynamic model and chemistry reactions with kinetic parameters of the AMP-PZ-H2O-CO2 system. The process model was validated with the experimental data and the results showed an excellent agreement. The process model was then scaled up to match the capacity of an industrial scale coal-fired power plant. A parametric study of the industrial scale model shows that the reboiler duty would be reduced upon lowering the CO2 removal rate, increasing the ratio of AMP in the solvent, and increasing the stripper pressure. Process configuration modifications, including intercooled absorber (ICA), lean vapor compressor (LVC) and rich solvent split (RSS), have been implemented and the energy demand were reduced by 6.7%, 2.7%, and 8.5% accordingly. The combination of ICA+LVC, ICA+RSS, and RSS+LVC modifications obtained an energy saving of 8.5%, 14%, and 9.3%, respectively. The combination of ICA+RSS+LVC reduced the energy demand by 15.2%.

Modelling and improving natural gas condensate process with stripping and heat integration

Fractionation has been proven to be an efficient method among different methods that can be used in stabilizing natural gas condensate. In this paper, an issue of improving a process that stabilizes natural gas condensate is raised and different process alternatives are proposed based on heat integration scenarios. The resulting process systems have reboilers that use the bottoms product and compressed overhead product to preheat the feed. Steady state process models for different case scenarios were developed using HYSYS software, and dynamic control of the optimal complex interacting systems are studied. A control structure is developed and tested using conventional PI controller.

Improving Prediction Accuracy of a Rate-Based Model of an MEA-Based Carbon Capture Process for Large-Scale Commercial Deployment

Carbon capture and storage (CCS) technology will play a critical role in reducing anthropogenic carbon dioxide (CO2) emission from fossil-fired power plants and other energy-intensive processes. However, the increment of energy cost caused by equipping a carbon capture process is the main barrier to its commercial deployment. To reduce the capital and operating costs of carbon capture, great efforts have been made to achieve optimal design and operation through process modeling, simulation, and optimization. Accurate models form an essential foundation for this purpose. This paper presents a study on developing a more accurate rate-based model in Aspen Plus® for the monoethanolamine (MEA)-based carbon capture process by multistage model validations. The modeling framework for this process was established first. The steady-state process model was then developed and validated at three stages, which included a thermodynamic model, physical properties calculations, and a process model at the pilot plant scale, covering a wide range of pressures, temperatures, and CO2 loadings. The calculation correlations of liquid density and interfacial area were updated by coding Fortran subroutines in Aspen Plus®. The validation results show that the correlation combination for the thermodynamic model used in this study has higher accuracy than those of three other key publications and the model prediction of the process model has a good agreement with the pilot plant experimental data. A case study was carried out for carbon capture from a 250 MWe combined cycle gas turbine (CCGT) power plant. Shorter packing height and lower specific duty were achieved using this accurate model.

A comparative study of MEA and DEA for post-combustion CO2 capture with different process configurations

This paper presented a comparative study of monoethanolamine (MEA) and diethanolamine (DEA) for post-combustion CO2 capture (PCC) process with different process configurations to study the interaction effect between solvent and process. The steady state process model of the conventional MEA-based PCC process was developed in Pro/II® and was validated with the experimental data. Then ten different process configurations were simulated for both MEA and DEA. Their performances in energy consumption were compared in terms of reboiler duty and total equivalent work. The results show that DEA generally has better thermal performances than MEA for all these ten process configurations. Seven process configurations provide 0.38%–4.61% total energy saving compared with the conventional PCC process for MEA, and other two configurations are not favourable. For DEA, except one configuration, other process configurations have 0.27%–4.50% total energy saving. This work also analyzed the sensitivities of three key parameters (amine concentration, stripper pressure and lean solvent loading) in conventional process and five process modifications to show optimization strategy.

Process control of the advanced flash stripper for CO2 solvent regeneration

The advanced flash stripper (AFS) is an intensified process design for CO2 solvent regeneration in amine scrubbing. This work identified self-optimizing controlled variables for the energy recovery bypass flowrates of the AFS, as well as a controller configuration for the steam extraction flowrate. Two self-optimizing variables were selected using a high-fidelity steady state process model: the temperature difference at the top of the stripper packing and the temperature difference on the hot end of the stripper overhead heat exchanger. Ranges of possible off-design conditions for the rich loading, absorber temperature, rich flowrate, and flash tank operating temperature were evaluated, and the worst case heat duty for CO2 stripping of the self-optimizing control scheme was within 1% of the true system optimum. A low-order dynamic model was used to test the proposed self-optimizing control strategy and showed no significant control loop interactions in the closed-loop response. Cascade control, where the inner loop controlled the steam heater effluent temperature and the outer loop controlled the flash tank temperature, was found to have favorable dynamic performance compared to a non-cascaded structure with uncontrolled flash tank temperature.

Optimal operation of MEA-based post-combustion carbon capture for natural gas combined cycle power plants under different market conditions

Carbon capture for fossil fuel power generation attracts an increasing attention in order to address the significant challenge of global climate change. This study aims to explore the optimal operation under different market conditions for an assumed existing natural gas combined cycle (NGCC) power plant integrated with MEA-based post-combustion carbon capture (PCC) process. The steady state process models for NGCC power plant, PCC process and CO2 compression train were developed in Aspen Plus® to give accurate prediction of process performance. Levelised cost of electricity (LCOE) is formulated as the objective function in optimization studies. Economic evaluation was carried out for the base case of the integrated system including CO2 transport and storage (T&S). The optimal operations were investigated for the carbon capture level under different carbon price, fuel price and CO2 T&S price. The study shows that carbon price needs to be over €100/ton CO2 to justify the total cost of carbon capture from the NGCC power plant and needs to be €120/ton CO2 to drive carbon capture level at 90%. Higher fuel price and CO2 T&S price would cause a higher operating cost of running carbon capture process thus a higher carbon price is needed if targeted carbon capture level is to be maintained.

Process Disturbance Cause & Effect Analysis Using Bayesian Networks

Process disturbances can propagate over entire plants and it can be difficult to locate their root causes from observed effects. Bayesian Networks offer a way to represent unit operations, processes and whole plants as probabilistic models which can be used to infer and rank likely causes from observed effects. This paper presents a methodology to use deterministic steady-state process models to derive Bayesian Networks based on alarm event detection. An example heat recovery network is used to illustrate the model building and inferential procedures.

Carbon Capture Simulation Initiative: a case study in multiscale modeling and new challenges.

Advanced multiscale modeling and simulation have the potential to dramatically reduce the time and cost to develop new carbon capture technologies. The Carbon Capture Simulation Initiative is a partnership among national laboratories, industry, and universities that is developing, demonstrating, and deploying a suite of such tools, including basic data submodels, steady-state and dynamic process models, process optimization and uncertainty quantification tools, an advanced dynamic process control framework, high-resolution filtered computational-fluid-dynamics (CFD) submodels, validated high-fidelity device-scale CFD models with quantified uncertainty, and a risk-analysis framework. These tools and models enable basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to synthesize and optimize a process. The resulting process informs the development of process control systems and more detailed simulations of potential equipment to improve the design and reduce scale-up risk. Quantification and propagation of uncertainty across scales is an essential part of these tools and models.

Direct-Chill Co-Casting of AA3003/AA4045 Aluminum Ingots via Fusion™ Technology

Laboratory-scale experiments were conducted to cast AA3003/AA4045 clad ingots via Fusion™ Technology, a novel process developed by Novelis Inc. for the production of aluminum clad materials such as brazing sheet. Experimental results were used to validate a steady-state thermofluids model of the Fusion™ Technology co-casting process. The numerical model was able to accurately predict the temperature field within the AA3003/AA4045 clad ingot as well as the shape of the AA3003 liquid sump. The model was also used to quantify the temperature, fraction solid, and velocity fields in a clad ingot cast with an asymmetrical molten metal-feeding system. Feeding of core and clad molten metals at opposite corners of the mold was found to reduce the risks of hot spots and liquid metal breakthrough from the core sump to the clad side of the Fusion™ Technology mold. The use of a diffuser for the AA3003 core molten metal and of a vertical feeding tube for the AA4045 clad produced different flow patterns and liquid sump shapes on either side of the mold. The quality of the metallurgical bond at the core/clad interface appeared good near the clad inlet and at the ingot centerline, but poor near the edges of the ingot. SEM–EDS analysis of the chemical composition across the interface showed that a 1 to 20-μm-deep penetration of silicon from the AA4045 clad into the AA3003 core had occurred at visually acceptable interfaces, whereas silicon diffusion across poor interfaces was very limited. A study of the model-predicted fraction solid history at different points along the interface indicated that reheating of the AA3003 core is not required to form a visually acceptable metallurgical bond. However, a sufficient amount of interaction time between the solid AA3003 core shell and the silicon-rich AA4045 clad liquid is required to chemically dissolve the surface of the core and form a good metallurgical bond. An approximate dissolution depth of 750 to 1000 μm was observed along the visually good interface. Partial dissolution of the Mn-rich AA3003 core led to the formation of Al(Mn,Fe)Si intermetallic particles in the AA4045 clad and an increased manganese concentration near the core/clad interface.

A Combined Neural Network and Genetic Algorithm Optimization of Operational Parameter in Nitric Acid Process

It will be face some problems about the complicated reaction mechanism, environment uncertainty, serious nonlinear in nitric acid process .a method of creating steady-state model of nitric acid process using neural network. and used genetic algorithm to optimize parameter on neural network model. The result can provide reference for analyzing and optimizing the parameters of nitric acid process.

Solving equations describing the steady-state model of MSF desalination process using Solver Optimization Tool of MATLAB software

This work presents an algorithm for solving the large system of non-linear equations describing the steady state model of the two main layouts for the MSF process (the multistage flashing with brine recirculation and the once-through multistage flash desalination (MSF-OT)). The model accounts for the geometry of the stage, the mechanism of heat transfer, and the variation of the thermophysical properties of various fluids with temperature and salinity. In addition, the overall heat transfer coefficient was evaluated at each stage using convective heat transfer coefficient for internal and external flows, tube thermal conductivity and fouling resistance. Furthermore, the model takes into consideration the dependence of thermodynamic losses on stream flow rate, temperature, and the brine salinity. The system of equations was solved through an iterative procedure by using Solver Optimization Tool of MATLAB software. For each stage, the developed model was then used for evaluating the temperatures of the brine, distillate and cooling brine, the flow rates of brine outlet, distillate production, and steam heating. Finally, the resolution method was validated against the simulation results reported in the literature and the actual plant data at MSF-OT installation in Doha, Kuwait. The agreement was found to be good.

A Numerical Study of the Direct-Chill Co-Casting of Aluminum Ingots via Fusion™ Technology

For the last 70 years, direct-chill (DC) casting has been the mainstay of the aluminum industry for the production of monolithic sheet and extruded products. Traditionally, clad aluminum sheet products have been made from separate core and clad DC cast ingots by an expensive roll-bonding process; however, in 2005, Novelis unveiled an innovative variant of the DC casting process called the Fusion™ Technology process that allows the production of multialloy ingots that can be rolled directly into laminated or clad sheet products. Of paramount importance for the successful commercialization of this new technology is a scientific and quantitative understanding of the Fusion™ casting process that will facilitate process optimization and aid in the future development of casting methodology for different alloy combinations and ingot and clad dimensions. In the current study, a numerical steady-state thermofluids model of the Fusion™ Technology casting process was developed and used to simulate the casting of rectangular bimetallic ingots made from the typical brazing sheet combination of AA3003 core clad with an AA4045 aluminum alloy. The analysis is followed by a parametric study of the process. The influence of casting speed and chill-bar height on the steady-state thermal field within the ingot is investigated. According to the criteria developed with the thermofluids model, the AA3003/AA4045 combination of aluminum alloys can be cast successfully with casting speeds up to 2.4 mm s−1. The quality of the metallurgical bond between the core and the clad is decreased for low casting speeds and chill-bar heights >35 mm. These results can be used as a guideline for improving the productivity of the Fusion™ Technology process.

Process modelling of dimethyl ether production from Victorian brown coal—Integrating coal drying, gasification and synthesis processes

Power plants using Victorian brown coal operate at low efficiency. Being reactive and spontaneously combustible, dried brown coals cannot be exported either. Synthesis of dimethyl ether (DME) is one option for the production of liquid fuel, an exportable product for power generation and transportation. This paper presents a steady-state process model for DME production using brown coal including drying, gasification and DME synthesis. The yield of the DME was a maximum for H2 to CO molar ratio of 1.41 and 0.81 at the gasifier outlet and the DME reactor inlet respectively. A process efficiency of 32% and CO2 emission of 2.91kg/kg of DME was obtained. Improved yield of DME is achieved when CO2 is removed from the fuel gas prior to feeding to the synthesis reactor. Integration of waste heat and design of appropriate catalyst for gasification and DME synthesis can result in further improvements in the process.

Early-stage design methodology for biorefinery capital appropriation

This paper presents a methodology for enhancing the strategic investment decision-making process for retrofit forest biorefinery (FBR) implementation. This is achieved by improving the link between retrofit process design and capital appropriation activities through cost accounting. This methodology is based on step-wise screening of retrofit alternatives where (1) traditional techno-economic analysis and multivariate stochastic risk analysis are used in the first pre-screening step, and (2) an advanced analysis framework based on steady-state process modeling, product costing using principles of activity-based costing (ABC), and panel-based multicriteria decision-making (MCDM) is used in the second screening step. In the MCDM, financial- and risk-based decision-making criteria are used. A case study considering the retrofit implementation of a biorefinery into a kraft pulp and paper mill demonstrates the methodology.

Optimal selection of control structure using a steady-state inversely controlled process model

The profitability of chemical processes strongly depends on their control systems. The design of a control system involves selection of controlled and manipulated variables, known as control structure selection. Systematic generation and screening alternative control structures requires optimization. However, the size of such an optimization problem is much larger when candidate controllers and their parameters are included and it rapidly becomes intractable. This paper presents a novel optimization framework using the notion of perfect control, which disentangles the complexities of the controllers. This framework reduces the complexity of the problem while ensuring controllability. In addition, the optimization framework has a goal-driven multi-objective function and requires only a steady-state inverse process model. Since dynamic degrees of freedom do not appear in a steady-state analysis, engineering insights are employed for developing the inventory control systems. The proposed optimization framework was demonstrated in a case study of an industrial distillation train.

CATALYTIC REFORMING OF HEAVY NAPHTHA, ANALYSIS AND SIMULATION

In this paper, one-dimensional steady-state mathematical model of a semi regenerative naphtha catalytic reforming process had been made. This model incorporated a detailed kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins (n and iso) and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The effect of pressure drop was considered through Ergun equation. The model explains the composition, temperature and pressure distributions along the four reforming reactors.
 The simulation results of the proposed model were compared with the experimental results obtained from literature to validate the model. The results showed good agreement between the reformate composition of proposed model with the experimental reformate composition. Finally, the mathematical model was used to study the effect of reactor feed temperature, total pressure and hydrogen to hydrocarbon feed ratio on the reformate compositions