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Abstract

The aim of the present study was to investigate the sensitivity of a multiphase Eulerian CFD model with respect to relations defining drag forces between phases. The mean relative error as well as standard deviation of experimental and computed values of pressure gradient and average liquid holdup were used as validation criteria of the model. Comparative basis for simulations was our own data-base obtained in experiments carried out in a TBR operating at a co-current downward gas and liquid flow. Estimated errors showed that the classical equations of Attou et al. (1999) defining the friction factors Fjk approximate experimental values of hydrodynamic parameters with the best agreement. Taking this into account one can recommend to apply chosen equations in the momentum balances of TBR.

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Authors and Affiliations

Grażyna Bartelmus
Daniel Janecki
Andrzej Burghardt
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Abstract

The cometabolic biodegradation of 4-Chlorophenol (4-CP) by the Stenotrophomonas maltophilia KB2 strain in the presence of phenol (P) was studied. In order to determine the kinetics of biodegradation of both substrates, present alone and in cometabolic systems, a series of tests was carried out in a batch reactor changing, in a wide range, the initial concentration of both substrates. The growth of the tested strain on phenol alone was described by Haldane kinetic model (mm = 0:9 1/h, Ksg = 48:97 gg/m3, KIg = 256:12 gg/m3, Yxg = 0:5715). The rate of 4-CP transformation by resting cells of KB2 strain was also described by Haldane equation and the estimated parameters of the model were: kc = 0:229 gc=gxh, Ksc = 0:696 gc=m3, KIc = 43:82 gc=m3. Cometabolic degradation of 4-CP in the presence of phenol was investigated for a wide range of initial 4-CP and phenol concentrations (22–66 gc/m3 and 67–280 gg/m3 respectively). The experimental database was exploited to verify the two kinetic models: CIModel taking only the competitive inhibition into consideration and a more universal CNIModel considering both competitive and non-competitive inhibition. CNIModel approximated experimental data better than CIModel.

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Authors and Affiliations

Agnieszka Gąszczak
Grażyna Bartelmus
Izabela Greń
Adam Rotkegel
Daniel Janecki

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