Pilot Plant Data Research Articles

The influence of catalyst flow rate and superficial gas velocity on the modified two‐phase model for propylene polymerization in a gas‐phase fluidized bed reactor

AbstractOlefin polymerization, especially of propylene in gas‐phase fluidized bed reactors, is increasingly prevalent because of its ability to handle the continuous process, among other advantages. The challenge for modelling this process is solving the high nonlinearity phenomena in such a system. This research studies the influence of catalyst flow rate and superficial gas velocity on the modified two‐phase model. The catalyst flow rates were set at 1 × 10−4, 2 × 10−4, and 3 × 10−4 kg/s, while the superficial flow rates were set at 0.35, 0.5, and 0.65 m/s. Production rate, reactor temperature, and heat‐loss flow rate were found to be proportional to catalyst flow rate and inversely proportional to superficial gas velocity. Heat loss through the fluidized bed wall had an influence only on the reactor temperature. Finally, predicted reactor temperatures corresponded closely to the pilot plant data, with deviations smaller than 0.5%.

Prediction of ultra low sulphur diesel catalyst performance using limited pilot plant data

Due to the presence of refractory sulphur (S) compounds in the gasoil, the achievement of Ultra-low-Sulphur Diesel (ULSD) using the conventional bimetallic catalyst in the Hydrodesulphurization (HDS) process in order to bring sulphur down to less than 10 ppmwt is considered as a tough task/challenge and gain major attention due to the EPA regulations on the transportation fuel industry.In this work, a catalytic testing of four commercial alumina-supported cobalt–molybdenum (CoMo) catalysts were conducted using fixed bed pilot plant reactor using a complex real mixture of straight run gasoil fraction (C12-C20) in order to determine the operating conditions at industrial unit particularly by focusing on the refractory (S) compounds and determining their reaction kinetics parameters. A limited pilot plant real data and a simplified kinetic model were employed to estimate the kinetic parameters for the four tested CA, CB, CC and CD catalysts. A parameter estimation technique with explicit models was also used to determine their highest posterior density intervals. The technique is based on minimization of the sum of the square errors (SSE) between the experimental and predicted data of the residual sulphur concentrations in the product distributions. The results revealed that each catalyst showed, expectedly, different results translated into how longer a commercial run length can be extended.

Validation of Differential Temperature Control for a Dividing Wall Distillation Column

A novel dividing wall distillation column (DWC) control strategy was investigated using pilot plant experimentation and commercial scale column dynamic simulation. Results from both indicated that the differential temperature, PID based, control structure successfully rejected flow and composition disturbances. A four-component test system was utilized with three primary components and one trace component. Desired purities were achieved and steady state operation was maintained. The simulation results qualitatively matched the pilot plant data with discrepancies being attributed to equipment-scale dependent heat transfer effects.

Dynamic modeling: The influence of the improved solid elutriation correlation on the two‐phase mathematical model of polyolefin polymerization in a gas‐phase fluidized bed reactor

AbstractDynamic modeling of the polyolefin polymerization process in the gas phase is relatively complex due to its high nonlinearity. This nonlinearity is induced by several factors including the reaction mechanism, the heat and mass transfer mechanism, the flow properties in both solid and gas phases, the type of reactor, and the correlations between the operating conditions and the chemical and physical properties of the polyolefin. In this study, polymerization of the polypropylene was observed in a fluidized bed reactor to potentially improve the solid elutriation correlations proposed previously, to increase the reliability and the accuracy of this two‐phase model. By embedding the improved solid elutriation correlations, the production rate was reduced relative to earlier proposed solid elutriation correlations due to the loss of the product at the top of the fluidized bed reactor. The composition of the reactants and the catalyst flow rate also influenced the production rate, yet the inlet temperature did not. The current two‐phase model is validated with the pilot plant data with the deviations lower than the previously validated model with reference to the production rate, the concentration of propylene and hydrogen, and the temperature of the reactor.

Experimental, simulation and thermodynamic modeling of an acid gas removal pilot plant for CO2 capturing by mono-ethanol amine solution

In this study, by setting up a dynamic pilot plant, we carried out capturing of CO2 using the aqueous Mono-Ethanol Amine at various concentrations and temperatures. Moreover, the various thermodynamic models were used to calculate CO2 absorption and desorption using gas feeds containing high and low CO2 concentration. Four models of eNRTL-Bishnoi, Gabrielsen's approach, ASPEN eNRTL default and ASPEN-eNRTL Regressed-DRS were used for thermodynamic modeling and simulation of the pilot plant data. Using Gabrielsen's approach, the average absolute deviations for absorber and desorber columns were 10.2 and 10.3, respectively, using MEA (27 wt %); 10.2 and 9.4 using MEA (29 wt%) with high CO2 feed gas. Moreover, using the different MEA concentrations with low CO2 feed gas, the AAD% were 9.9 and 10.6 for the absorber and desorber columns, respectively. In addition, we compared the results of overall energy consumptions in regeneration section obtained by experimental data using the present models.

Absorber Modeling of Pilot Plant Data with Aqueous Piperazine

Absorber Modeling of Pilot Plant Data with Aqueous Piperazine

A quantitative risk analysis approach to a process sequence under uncertainty – A case study

Process plants for the manufacture of pharmaceutical products often need to be designed and built quickly to make the most of available patent life which necessitates using uncertain or unavailable data. It is common that pilot plant equipment and data are available and new data can be generated if they are important. We present a model based approach to risk analysis to aid design for pharmaceutical processes which combines systematic modelling procedures with Hammersley sampling based uncertainty analysis and sensitivity analysis used to quantify predicted performance uncertainty and to identify key uncertainty contributions. The main contribution of the paper is the demonstration of the methodology on an industrial case study where the process flowsheet was fixed and some pilot data was available. Expected performance was improved by considering the propagation of uncertainty over the whole process. The case study results indicate the importance of considering uncertainty systematically and quantitatively. The methodology showed the opportunity to improve process performance potential through considering uncertainty systematically.

Pilot Plant Data Assessment in Anaerobic Digestion of Organic Fraction of Municipal Waste Solids

In this paper, a preliminary study of anaerobic digestion of organic fraction of municipal solid wastes (OFMSW) in presented with the aim to compare the performances of both wet- and dry-type reactors. The treatment of OFMSW via anaerobic digestion (AD) producing biogas is a process that is receiving a growing interest because two different needs can be coupled: the request of sustainable municipal waste treatments and increasing demand renewable energy. This paper aims to offer experimental results comparing batch test and continuous experimental reactors under different conditions of humidity and solid content. Results show that both the investigated configurations may be used for converting OFMSW into a high quality biogas and that the increase of dry matter in the continuous process still allows to achieve significant biogas production rates. A slight reduction of the methane content was observed (less than 5% relative) that can be also related to the change in the level of volatile fatty acids. These results are very promising in supporting the possibility of operating an industrial scale plant with a dry-process without affecting the system performance.

A carbon-number lump based model for simulation of industrial hydrotreaters: Vacuum gas oil (VGO)

A detailed, molecule-based trickle bed reactor model has been developed to simulate industrial vacuum gas oil (VGO) hydrotreaters. A feed characterization module is used to calculate the composition of the feed without any detailed experimental component analysis. Feed VGO is represented by a pre-defined set of 120 pure molecules, from carbon numbers C14 to C33, and the proportion of these components is calculated using an optimization algorithm so as to match the physico-chemical properties of the mixture with those of VGO, as measured in the laboratory. This molecular composition is used as an input to model the reactions occurring in a hydrotreating reactor. The main reactions occurring in the hydrotreater such as hydro desulfurization, hydro denitrogenation and aromatic saturation reactions, are modeled. The kinetic parameters for these reactions have been estimated from a comprehensive set of experimental pilot plant data spanning a wide range of process conditions. Simulation results showed that the model reproduces the product distribution by boiling range, composition and the temperature rise in the catalyst bed for a range of operating conditions for industrial refinery units.

Development of a Rigorous Modeling Framework for Solvent-Based CO2 Capture. Part 2: Steady-State Validation and Uncertainty Quantification with Pilot Plant Data

The U.S. DOE’s Carbon Capture Simulation Initiative (CCSI) has a strong focus on the development of state of the art process models for accelerating the development and commercialization of postcombustion carbon capture system technologies. One of CCSI’s goals is the development of a process model that will serve not only as a definitive reference for benchmarking of the performance of solvent-based CO2 capture systems but also as a framework for the development of highly predictive models of advanced solvent systems. In Part 1 of this paper and previous work, submodels for the system were developed, including those for physical properties, kinetics, mass transfer, and column hydraulics, by calibrating model parameters to fit relevant experimental data. For individual submodels, a Bayesian inference methodology was used to refine the estimates of the parameter values and to quantify the parametric uncertainty of the models. This work is focused on incorporating these submodels into a complete process mode...

Molecular-Level Kinetic Model for C12 Continuous Catalytic Reforming

A detailed kinetic model for a continuous catalytic reforming (CCR) process was developed. The model included 447 naphtha molecules (C1–C12) that underwent 1469 reactions. Paraffin and naphthenic isomers up to C9 components were fully depicted, whereas aromatic isomers were fully described up to C10. Coking kinetics and the corresponding deactivation of the catalyst were integrated into the model. The steady state kinetic parameters were tuned using pilot plant data for a widely used industrial catalyst. To enable the use of commercial plant data, the energy balance and catalyst moving mechanism of typical CCR reactors were also formulated. The model was then used to simulate an industrial unit loaded with the same catalyst after deactivation calibration by adjusting a few deactivation parameters. The results showed that calculated PONA fractions, individual aromatic species, and the temperature drops of each reactor were in good accord with industrial data.

Maximizing utilization of reactivated and left-over catalysts in heavy gas oil hydrotreater: A case study of ADNOC Refining

Recently, ADNOC Refining Research Center (ARRC) has studied the possibility to maximize the reutilization of left-overs and reactivated hydrodesulfurization catalysts for one of its hydrotreater producing Ultra Low Sulfur Diesel (ULSD) from Heavy Gas Oil (HGO). Based on the refinery inventory, several catalyst configurations composed of different amounts of reactivated and fresh CoMo catalyst, including a full reactivated configuration having a stacked CoMo/NiMo/CoMo combination (50/25/25), have been tested in a pilot-plant reactor under commercially-relevant conditions. Experimental results in terms of reactor bed temperature, H2 consumption, aromatics and diesel yields have been analyzed and compared to the current commercial hydrotreater load and catalyst supplier forecasts for the studied configurations. Results show excellent performances of reactivated catalysts and a strong effect of the NiMo layer in the case of the stacked configuration. In a pure CoMo configuration, up to 75% reactor volume of reactivated catalyst could be utilized without impacting the product quality and cycle length, compared to a full fresh CoMo catalyst load. The full reactivated stacked configuration performed even better than the full fresh CoMo catalyst, without impacting product quality and diesel yield. Potential effect of the reactivated catalysts on the reaction selectivity and the role of the NiMo layer in the stacked configuration are discussed. Pilot-plant experimental data were in strong accordance with catalyst supplier commercial forecasts, emphasizing the quality of the pilot-plant study. Implementation of one of the studied configuration by the refinery could lead to between 30% and 55% savings on the cost of catalyst for the next load.

Rigorous design of multiphase reactors: Identification of optimal conditions for mass transfer limited reactions

Multiphase reaction systems are often complex due to the interaction of reaction and transport processes. To design optimal reactors for such systems, a rigorous optimization is necessary. In this regard, this work proposes extensions of a reactor design methodology based on rigorous optimization. Each phase is represented by one fluid element, subject to different mass and energy fluxes. While the unlimited external fluxes are optimally provided along the reaction route, sensitivity analysis of the parameters related to the limited external fluxes is performed. The extended methodology is applied in the reactor design for chemical absorption of CO2 as an example for complex multiphase reaction systems with severe mass transfer limitation. An accurate model which is also numerically suitable for optimization has been set up and validated with pilot plant data from literature. Optimal temperature profiles which result from balancing the different temperature-dependent phenomena are identified for cases with different inlet conditions, and tailor-made heat control strategies are shown for these cases. The potential of the developments in improving mass transfer rates by, e.g., structural design or solvent design has been quantified. This model-based design methodology is generally applicable to different multiphase reaction systems with severe mass transfer limitation.

Modeling and validation of a pilot-scale aqueous mineral carbonation reactor for carbon capture using computational fluid dynamics

In anticipation of the successful establishment of carbon capture, utilization, and storage (CCUS) technology, a pilot-scale aqueous mineral carbonation plant, that removes CO2 through a reaction with a Ca(OH)2 solution, was built in Incheon, South Korea. Using computational fluid dynamics (CFD), two reactors with a diameter of 2.2 m and a height of 6.0 m were modeled and validated for reactor scale-up and optimization. Because a direct simulation of bubble breakage, coalescence, and interphase mass transfer results in enormous computational costs for modeling the pilot-scale multiphase reactor, a CFD-lumped correlation model was introduced to simulate a large reactor; this resulted in acceptable computational costs and maintained the simulation accuracy. In order to ensure the acceptability of the CFD model, two-step verification was conducted. The CFD model results were compared with the experimental data and published empirical correlations with regard to the gas holdup, interfacial area, and mass transfer coefficient. Subsequently, the CO2 removal efficiencies of the CFD model were compared with the pilot-plant data. The errors of the CFD model for three hydrodynamic parameters and the CO2 removal efficiencies were in the range of 1–8%. The validated CFD model will be used for designing a four times larger mineral carbonation reactor, that will be built in 2017.

Modeling of absorber pilot plant performance for CO2 capture with aqueous piperazine

A CO2 capture pilot plant with the advanced flash stripper was operated with aqueous piperazine (PZ) at The University of Texas Separations Research Program (UT-SRP) in March 2015. A wide range of absorber operating conditions (solvent concentration, lean loading, flue gas CO2, gas rate, liquid-to-gas ratio) and intercooling configurations was tested in the pilot plant campaign.The pilot plant measurements closed the material balance (±2%) around the absorber. 5m PZ was tested for the first time and outperformed 8m PZ at comparable absorber conditions due to enhanced mass transfer rates in the absorber. Operating with 5m PZ increased the number of transfer units (NTU) by ∼20% for each of 3 tests even though 8m PZ was operated with greater solvent capacity and greater driving force. Operation with full spray intercooling doubled the NTU compared to operation without spray or intercooling at identical absorber conditions.The pilot plant data were used for further validation of the rigorous rate-based absorber model in Aspen Plus®. The pilot plant absorber model has been developed over several pilot plant campaigns, and a consistent method for absorber model validation and correction utilizing a rigorous data reconciliation method with the Independence PZ model was used to predict pilot plant performance for the March 2015 campaign. Pilot plant data suggested that interfacial area correction and CO2 correction provided similar predictions of pilot plant absorber performance and could be used interchangeably to correct the model. The inhibitor correction to density-predicted loadings was consistent with model-predicted correction to titration data and might provide an explanation for pilot-model offsets. Pilot plant data also suggested a possible time dependence, and absorber NTU values were slightly over-predicted (mean ratio of model-predicted NTU to pilot plant-measured NTU=1.08). A possible explanation is that several high CO2 removal cases in the March 2015 campaign were outside the range where the previous model corrections were developed, where the controlling mass transfer resistance in the absorber differed. This observation provides an opportunity to investigate future model corrections at different column mass transfer limiting mechanisms. The column temperature profiles of different intercooling configurations were matched within 2% mean absolute percentage error.

Catalyst performance and experimental validation of a rigorous desorber model for low temperature catalyst-aided desorption of CO2 in single and blended amine solutions

In this study, experimental results of an integrated CO2 capture pilot plant utilizing blended MEA-MDEA solution and two solid acid catalysts (γ-Al2O3 and HZSM-5) in the desorber are presented, and a model developed in-house was validated against the experimental data. The model showed good agreement with the pilot plant data with an absolute average deviation (AAD) of 7.7% for CO2 production rates and could predict well the temperature profiles in the column. The model which has been previously validated against experimental data utilizing MEA and the two solid acid catalysts, was used to predict the performance (in terms of their contribution to the overall reaction rates) of the solid acid catalysts in both solvents (single and blended amine solutions). The performance results showed that the catalysts contributed more to the process as the temperature and amount of catalyst increased with HZSM-5 yielding as high as 95% increase to the overall rate of reaction in the single amine system. The results of the performance of the catalysts in the blended solvent were quite low compared to those of the single amine solution. It was observed that the predicted gas phase CO2 concentration profiles in the desorber, which was not readily available experimentally, was quite high and undesired. Thus, further steps should be taken to address this problem.

Impact of solid waste treatment from spray dryer absorber on the levelized cost of energy of a coal-fired power plant

Coal-fired power plants with semi-dry flue gas desulfurization (semi-dry FGD) system produce daily tones of ashes contaminated with calcium sulphite. To turn this solid waste useful (e.g. to the cement industry) and avoid landfill disposal, the present study suggests a semi-dry FGD solid waste treatment unit, that promotes the dry oxidation of calcium sulfite to calcium sulfate. Sizing of main equipment using pilot-plant and patents data allows economic evaluation of capital expenditure, operational and maintenance costs, and sale of the treated residue, which permits estimation of levelized cost of energy to assess the impact of the technology on the electricity price of a power plant using the proposed solid waste treatment unit. As base case, a Brazilian coal-fired power plant facing decision making process on semi-dry FGD waste destination is selected. Results demonstrate that the semi-dry FGD, without the solid treatment unit, has total levelized cost of energy increased in 0.56% (from 94.44 to 94.97 $/MWh) resulting from solids waste disposal. If the treated semi-dry FGD waste was transferred (at zero revenue) as additive to a cement industry, the levelized cost of energy of the power plant would remain approximately unchanged. This is because the increase of 0.51$/MWh resulting from the investment and operation and maintenance cost of the treatment unit is compensated by the decrease of 0.53$/MWh, in virtue of the avoided waste disposal costs. However, if the commercialization as raw material of the treated semi-dry FGD waste is considered, a reduction of 2.83 $/MWh (∼3%) on the levelized cost of energy (to 92.14 $/MWh) would occur. In both cases, the proposed treatment unit shows small impact on the total power plant levelized cost of energy, besides solving the solid management problems of landfill saturation, land use and costs related to landfill maintenance. Thus, it is adequate to implement the semi-dry FGD waste treatment unit on the power plant in question. The conclusion can be extended to plants with similar design and economic parameters.

Applicability and Validation of Use of Equilibrium-based Absorber Models with Reduced Stage Efficiency for Dynamic Simulation of Post-combustion CO2 Capture Processes

Use of complex rate-based models for absorbers in a post-combustion CO2 capture process may lead to high computational complexity and simulation time. Method using reduced stage efficiency in equilibrium-based model for such columns may provide acceptable range of accuracy with comparatively much less simulation time and thereby enabling them to be used simultaneously with dynamic models of power plants. This paper discusses the applicability of such method and presents the validation of use of such methods using two pilot plant data at both steady state and transient operation. Steady state plant data were used to determine the reduced stage efficiencies for the pilot plants. The dynamic models with those stage efficiencies were simulated to predict both the steady state operation and transient operation under step change in solvent flow rate scenario with nominal deviations in a range of 3-6% in the simulation results with simulation time 35 times higher than the real-time.

Stochastic Modeling and Simulation Approach for Industrial Fixed-Bed Hydrocrackers

In this study, we developed a comprehensive model to simulate vacuum gas oil (VGO) hydrocracking. The model incorporates knowledge of feedstock composition and reaction chemistry at the molecular level and is tuned with pilot plant data. The molecular makeup of the feedstock is derived from its analytical characterization via statistical modeling. Hydrocracking reactivity is described based on the molecular structure of the reactants. Progression of chemical reactions is simulated using a kinetic Monte Carlo algorithm. A stochastic heat balance equation is integrated into the model to represent adiabatic operation. Vapor–liquid equilibrium (VLE) calculations are executed in parallel with an in-house flash program. Hydrocracker simulations were conducted covering the typical range of conversion levels observed in commercial operation. The model generates detailed information on product distribution as well as product quality. In addition, the model is able to track the evolution of hydrogen consumption, hy...

A molecular lump based model for simulation of industrial naphtha hydro treators

A detailed, molecule-based kinetic model has been developed to simulate industrial naphtha hydro treators. A feed characterization module has been developed to calculate the composition of pre-defined pure molecules representing the feed quality without any detailed experimental component analysis. Feed naphtha is represented by a pre-defined set of 95 pure molecules, from carbon numbers C5 to C11, and the proportion of these components is calculated using an optimization algorithm so as to match the physico-chemical properties of the mixture with those of naphtha, as measured in the laboratory. The output from this optimization model is used as a direct input to a model of a hydro treating reactor. The main reactions occurring in the hydro treator, such as hydro desulfurization reactions and olefin saturation reactions, are modeled. The kinetic parameters for these reactions have been estimated from a comprehensive set of experimental pilot plant data spanning a wide range of process conditions. The kinetic model quantitatively predicts the exit composition, temperature rise and pressure drop in the catalyst bed for a range of conditions for two industrial refinery units.