A pollution reduction methodology in reactor design

Chen, Qishi; Feng, Xiao

doi:10.1016/j.cep.2004.03.006

Cited by 10 publications

(3 citation statements)

References 9 publications

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“…Substituting Equations ( 6)- (10) in Equation (3) using dimensionless variables, the obtained equations, with the boundary conditions, are shown in Table 2.…”

Section: Axial Dispersion Model (Adm)mentioning

confidence: 99%

“…Substitute the rate Equations ( 6)- (10) in Equation ( 17) for the species A, B, C, D, and E. Using dimensionless concentrations, the obtained material balance equations are given in Table 3, with the feed composition for the first reactor. The dimensionless concentration of each species can be found if the number of reactors and residence time in each reactor are known.…”

Section: Differential Equationmentioning

confidence: 99%

“…Compared to ADM, the TISM was found to be more realistic and advantageous for simulating Fischer-Tropsch slurry bubble column reactors [9]. In their design of batch reactors for the production of allyl chloride, Chen and Feng [10] included environmental impact parameters and potential environmental impact (PEI) to simulate the effect of reaction conditions, backmixing, mass, and heat transfer on the environmental performance of the process. The use of PFR would decrease the PEI generation rate, compared to CSTR (high backmixing), which increases the emission of the PEI of the process.…”

Section: Introductionmentioning

confidence: 99%

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Acrylonitrile Process Enhancement through Waste Minimization: Effect of Reaction Conditions and Degree of Backmixing

Reesh

2021

Sustainability

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Waste minimization in reactor design is an effective approach for pollution control, when compared to the traditional practice of the end-of-pipe treatment. Reactor degree of backmixing and operating conditions are important factors that determine the performance of chemical process, including environmental impact. For the purpose of waste minimization, two modeling methods were used for simulating the performance of the acrylonitrile production reactor, based on the ammoxidation of propylene. The effect of residence time, temperature, degree of backmixing on the steady-state propylene conversion, and production of waste were determined. The tanks-in-series model and the axial dispersion model were used to account for the degree of backmixing. The two main by-products in the acrylonitrile process are acetonitrile and hydrogen cyanide, which are both highly toxic waste. Extensive reactor backmixing reduces propylene conversion, especially at high temperature and residence time. Minimum acetonitrile production is favored by low residence time, high to moderate temperature, and no backmixing. Minimum hydrogen cyanide production is favored by low residence time, low temperature, and no backmixing. At 450 °C, the percentage of increase in the selectivity of acrylonitrile, with respect to hydrogen cyanide at plug-flow reactor conditions, as compared to a continuous stirred tank reactor, is 87.1, 74.3, 50.9, 30.4, and 12.4% at a residence time of 1, 2, 4, 6, and 8 s, respectively. The reactor degree of backmixing and operating conditions are important factors that affect the environmental friendliness of the acrylonitrile production process.

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“…Substituting Equations ( 6)- (10) in Equation (3) using dimensionless variables, the obtained equations, with the boundary conditions, are shown in Table 2.…”

Section: Axial Dispersion Model (Adm)mentioning

confidence: 99%

Section: Differential Equationmentioning

confidence: 99%