Kinetic Parameter Estimation for the Causticizing Reaction Using a Differential Algebraic Optimization Technique

Sethuraman, Jagadeesan; Ramdoss, Prakash K.; Vaidyanathan, Ragavan; Krishnagopalan, Gopal A.

doi:10.1080/00986449608936660

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…Since the ordinary differential equations encountered were stiff, Gear's algorithm was used to solve them. More details of the techniques are provided in our earlier studies. , In the outer level, the procedure successively seeks parameters that reduce the objective function value.…”

Section: Resultsmentioning

confidence: 99%

Modeling of Two-Stage Coal Coprocessing Process

Ramdoss

Tarrer

1997

Energy Fuels

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Coal coprocessing can be done either in a single-stage or in a multistage process. It has been found that multistage processing offers some advantages over single-stage processing. In this study, a two-stage process was selected for coal liquefaction. In the first stage (solvent production stage), the waste materials were liquefied at milder conditions to obtain a suitable solvent for the coal liquefaction. In the second stage, the liquid product obtained from the first stage was used as solvent for coal. The two-stage liquefaction process was carried out in the absence of externally added catalysts. The reactions were carried out in a tubing bomb microreactor at temperatures of 350-450°C and 1250 psig of cold hydrogen pressure for reaction times of 15-120 min at 10% coal loading. Total conversion, and conversion to asphaltenes, oils, etc., were monitored. A model for coal liquefaction has been developed as part of this study. A rigorous parameter estimation method was used to estimate the model parameters. The predictions for the coal conversions were found to be within (3% of the observed values. Total conversion as high as 99% and oil conversion up to 90% were obtained in two-stage processing. Two-stage processing leads to higher coal conversion and oil yield compared to single-stage processing. The model parameters for the single-stage and two-stage processes were compared.

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Section: Resultsmentioning

confidence: 99%

Modeling of Two-Stage Coal Coprocessing Process

Ramdoss

Tarrer

1997

Energy Fuels

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“…Modeling of the causticizing reaction [12,13] [16], and the solubility of PbSO 4 -NiSO 4 mixtures in the metallurgical and mining industries [17]. In our study, the input parameters to the program were the amounts of different species, as well as temperature and pressure.…”

Section: The Program and Simulation Proceduresmentioning

confidence: 99%

Effects of Chloride, Potassium, and Sulfate on the Causticizing Reaction in the Kraft Recovery Process

Saeidi¹,

Tran²,

Papangelakis³

2009

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We studied the effects of chloride (Cl), potassium (K), and sulfate (SO4) on the equilibrium of the causticizing reaction over a wide range of causticizing conditions, using OLI, an advanced thermodynamic program for equilibrium calculations in aqueous solutions of ionic salts. Cl, K, and SO4 were shown to have little or no effect on the causticizing equilibrium. Under a given causticizing condition, coastal mills, due to their much higher NaCl concentration, are predicted to have a causticizing efficiency 1%–2% lower than that of inland mills.

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Kinetic Parameter Estimation for the Causticizing Reaction Using a Differential Algebraic Optimization Technique

Cited by 2 publications

References 2 publications

Modeling of Two-Stage Coal Coprocessing Process

Modeling of Two-Stage Coal Coprocessing Process

Effects of Chloride, Potassium, and Sulfate on the Causticizing Reaction in the Kraft Recovery Process

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