Dynamic Tray Model To Predict Start-Up Transients in Concentrated Absorbers

Gunaseelan, Praveen; Wankat, Phillip C.

doi:10.1021/ie990587u

Cited by 4 publications

(16 citation statements)

References 6 publications

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“…Although the predicted transient behavior could not be tested quantitatively because of the lack of dynamic data, the behavior agrees qualitatively with prior studies on concentrated adsorption 1 and concentrated absorption in tray columns. 3,4 The model does not predict the experimentally observed overshoots in gas pressure and liquid holdup as reported by Stanek and coworkers. 11,12 According to Stanek et al, 12 the overshoot is possibly due to a change in hydrodynamic regimes that requires extra energy to redistribute phases.…”

Section: Model Testingmentioning

confidence: 62%

“…13 It also results in a sign convention for solvent transfer, which is the opposite of what we use in our equilibrium tray model. 3,4 The general form of the current model favors a uniform sign convention for all transferring species. The overall balance equations (1b) and (2b) are equivalent to stating that the mole fractions in each phase sum to unity and can be used interchangeably with the summations.…”

Section: Model Equationsmentioning

confidence: 99%

“…Column Design for the Base Case. The column for the packed absorber was designed along the same lines as the tray absorber 3,4 to facilitate comparison between the two systems. We used the same feed flow rates and conditions (gas, 0.05 kmol/s at 0 °C; liquid, 0.3 kmol/s at 100 °C) that were used in the tray column and the same purity constraint in the vent gas (<0.3 wt % HCl).…”

Section: Model Testingmentioning

confidence: 99%

“…Previous studies have shown that large changes in the concentration of feed gas to adsorption and tray absorption columns can result in significant fluctuations in the gas flow rate and pressure. [1][2][3][4] This paper reports an analogous study of packed absorbers.…”

Section: Introductionmentioning

confidence: 99%

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Transient Pressure and Flow Predictions for Concentrated Packed Absorbers Using a Dynamic Nonequilibrium Model

Gunaseelan

Wankat

2002

Ind. Eng. Chem. Res.

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A dynamic, nonisothermal, nonequilibrium model is developed to predict detailed transient behavior during startup and transition to standby for concentrated random-packed absorbers. The model accounts for solvent evaporation and transient hydraulic behavior and is used to simulate the aqueous absorption of gaseous HCl. During startup, the simulations show a large decrease in the gas flow rate followed by a recovery due to high rates of solvent evaporation. The model predicts a spike in the solute composition in the gas during the startup transient. At low mass-transfer rates, this spike can cause unacceptable solute levels in the vent. During the transition to standby operation (where feed gas is replaced with carrier gas), there is an appreciable increase in the gas flow rate and pressure in the column. The peak transient gas flow rates are about 3 times greater than the feed rate, and the peak pressure drops are about 20 times greater than those at flooding. These spikes may be too brief to flood the column, but mechanical damage is possible. The transient also shows solute being desorbed from the bottom part of the column and re-absorbed in the upper part of the column, which causes a burp of solute in the vent gas. In less concentrated columns, the burp can result in unacceptable solute levels in the vent. These problems can be addressed by initially reducing the carrier gas flow rate. The model also applies to the use of scrubbers for the control of toxic vent emissions.

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Section: Model Testingmentioning

confidence: 62%

Section: Model Equationsmentioning

confidence: 99%

Section: Model Testingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Transient Pressure and Flow Predictions for Concentrated Packed Absorbers Using a Dynamic Nonequilibrium Model

Gunaseelan

Wankat

2002

Ind. Eng. Chem. Res.

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“…for the vapor pressure of HCl-water system, 20 following Gunaseelan and Wankat. 21 The heat capacity and the heat of absorption are also obtained from empirical data. 22,23 This approach mitigates the highly complex and nonlinear modeling for the absorber.…”

Section: Reaction Schemementioning

confidence: 99%

Demand‐based optimization of a chlorobenzene process with high‐fidelity and surrogate reactor models under trust region strategies

Yoshio

Biegler

2020

AIChE Journal

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This work demonstrates the optimization of the industrial scale chlorobenzene process, which continuously produces multiple products and includes a multiphase reaction with bubble column reactors (BCRs). The trust region filter (TRF) method is applied to carry out the demand‐based optimization of large chlorobenzene process with high‐fidelity BCR models. The TRF method uses surrogate models that substitute the high‐fidelity BCR models in the process model, and avoids the direct implementation of high‐fidelity models, which leads to a large and intractable optimization problem. The surrogate models are constructed based on basis functions that apply first order corrections from the gradients of high‐fidelity models. Different basis functions, CSTR and linear models, are studied in this work. As a result, the usage of CSTR models for the basis function leads to fewer function evaluations of the high‐fidelity model because CSTR model is a reasonable approximation of the high‐fidelity models and an initial guess of the optimization problem. Also, the TRF with surrogate models successfully provides an optimal solution of the high‐fidelity process model with few iterations and function evaluations of the high‐fidelity model itself. From the comparison with a low‐fidelity CSTR model, the solution with the TRF presents more accurate results. The surrogate approaches also make a smooth transition from low‐ to high‐fidelity models in process development. We apply this approach to a demand‐based optimization that integrates nontrivial business options, including optimal shortage of customer demands for profitable operation.

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Investigation of new control strategies for acid gas absorber columns to improve the response rates using dynamic process simulation

Heinze

Higman²,

Marasigan

et al. 2017

Fuel

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Dynamic Tray Model To Predict Start-Up Transients in Concentrated Absorbers

Cited by 4 publications

References 6 publications

Transient Pressure and Flow Predictions for Concentrated Packed Absorbers Using a Dynamic Nonequilibrium Model

Transient Pressure and Flow Predictions for Concentrated Packed Absorbers Using a Dynamic Nonequilibrium Model

Demand‐based optimization of a chlorobenzene process with high‐fidelity and surrogate reactor models under trust region strategies

Investigation of new control strategies for acid gas absorber columns to improve the response rates using dynamic process simulation

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