Software sensor based control of exothermic batch reactors

Regnier, N.; Defaye, G.; Caralp, L.; Vidal, Creto Augusto

doi:10.1016/s0009-2509(96)00329-6

Cited by 27 publications

(14 citation statements)

References 24 publications

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“…Software sensors have been described for diverse applications, such as chemical reactors (Régnier et al, 1996), analytical devices (Matsumura et al, 1998), environmental processes (Carstensen et al, 1996), and bioprocesses (Kiviharju et al, 2008). In addition, software sensors support the ambition of process analytical technology (PAT) to establish on-line monitoring methods for high quality manufacture of pharmaceutical products (FDA, 2004;Gnoth et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of software sensors for on-line estimation of culture conditions in an Escherichia coli cultivation expressing a recombinant protein

Warth

Rajkai²,

Mandenius

2010

Journal of Biotechnology

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Section: Introductionmentioning

confidence: 99%

Evaluation of software sensors for on-line estimation of culture conditions in an Escherichia coli cultivation expressing a recombinant protein

Warth

Rajkai²,

Mandenius

2010

Journal of Biotechnology

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“…However, this approach can be developed to become more less model-dependent, using a hybrid modelling approach to estimate the kinetic reaction or one (or more) unknown nonlinear parameters, which are then incorporated into the balance equations. This hybrid modelling approach can be based on semi-empirical models such as neural network models (Benkouider, 2007;Ng & Hussain, 2004) and linear input/output relationship (Regnier, Defaye, Caralp, & Vidal, 1996).…”

Section: Resultsmentioning

confidence: 99%

Fault detection in semi-batch reactor using the EKF and statistical method

Benkouider¹,

Buvat²,

Cosmao³

et al. 2009

Journal of Loss Prevention in the Process Industries

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“…Optimization techniques were used for parameter estimation to minimize the sum of squared differences between experimental and calculated values. 45 Among them, nonlinear (NLN) optimization was the most popular method, which was widely used to estimate the best value of chemical process kinetic parameters. For hydroprocessing, the Levenberg−Marquardt and SQP methods are particularly suitable.…”

Section: Modeling Methodologymentioning

confidence: 99%

Kinetic Parameter Calculation and Trickle Bed Reactor Simulation Based on Pilot-Scale Hydrodesulfurization Test of High-Temperature Coal Tar

et al. 2020

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At present, a few chemicals can be separated after further processing of high-temperature coal tar (HTCT) distillates, which have a lower utilization. However, hydrogenation to produce clean fuel oil has not been widely reported in literature. Thus, due to the use of new feedstocks and the implementation of more severe environmental legislations, deep hydrodesulfurization (HDS) of HTCT will face formidable challenges. A series of HDS experiments were performed in a continuous isothermal trickle bed reactor in which the reactor temperature was varied from 648 to 678 K, the pressure from 12 to 16 MPa, and the liquid hourly space velocity (LHSV) from 0.25 to 0.35 h–1, and hydrogen-to-oil ratio kept constant at 2000 L/L. Based on the experimental data, possible reaction pathways of HDS reaction were investigated, and a modified Langmuir–Hinshelwood (LH) HTCT desulfurization kinetic model was established. gPROMS software was used to obtain optimal kinetic parameters that are as follows: EA = 26,842, K 0 = 93,958, α = −1.14, n = 1.65, and m = 0.86. The model can well reproduce various working conditions and has better prediction accuracy. Some characteristics of HTCT HDS reactions were discovered; the reaction order (n) of HTCT HDS is slightly higher than that of crude oil and medium/low-temperature coal tar (M/LTCT), but the activation energy (EA) is relatively smaller. The established reactor model was used to predict the changes of the concentration of hydrogen, hydrogen sulfide, and sulfur compounds in the gas, liquid, and solid phases along the length of the reactor, respectively. The model was also used to predict the effects of pressure, temperature, and LHSV on the conversion rate of sulfur and catalyst effectiveness factors. The results showed that the LHSV has a greater impact on the conversion rate, and the pressure and temperature are less pronounced at high-severity operating conditions; the effectiveness factor is significantly smaller than that of other HDS processes, temperature has a greater effect on the effectiveness factor, followed by pressure and LHSV. The conclusion can provide a basis for further understanding the HTCT hydrotreating process.

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Software sensor based control of exothermic batch reactors

Cited by 27 publications

References 24 publications

Evaluation of software sensors for on-line estimation of culture conditions in an Escherichia coli cultivation expressing a recombinant protein

Evaluation of software sensors for on-line estimation of culture conditions in an Escherichia coli cultivation expressing a recombinant protein

Fault detection in semi-batch reactor using the EKF and statistical method

Kinetic Parameter Calculation and Trickle Bed Reactor Simulation Based on Pilot-Scale Hydrodesulfurization Test of High-Temperature Coal Tar

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