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吴东方, Dongfang Wu, Wei Jiang and Jiancheng Zhou
J Chem Techno Biotechnol 2010; 85: 569-576,-0001,():
-1年11月30日
This paper presents a mathematical modeling and factorial analysis of the toluene combustion activity of acordierite monolith supported copper-manganese-silver mixed-oxide catalyst in the drying and calcination processes, usingresponse surface methodology. A central composite rotatable design is performed to collectively study the effect of drying temperature, calcination temperature and calcination time. Experimental results are provided to confirm the validity of the models developed.
catalytic combustion, monolithic catalysts, volatile organic compounds, factorial analysis, mathema tical modeling, Optimisation
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吴东方, Dongfang
Chemical Engineering Science 58 (2003) 3995-4004,-0001,():
-1年11月30日
The
Solid
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吴东方, Dongfang
Chemical Engineering Science 56 (2001) 7035-7044,-0001,():
-1年11月30日
A Monte Carlo simulation is used to obtain the statistical properties of the Weibull parameters estimated by the linear regression, weighted linear regression and maximum likelihood schemes, respectively. Results reveal that the natural logarithm of the Weibull size parameter can be determined with about the same precision as the Weibull modulus. For Weibull modulus estimation, a maximum likelihood method results in the highest estimation precision; however, with a low safety factor. The weighted linear regression method with a weight factor Wi =F2i and a probability estimator Pf(Fi)=(i−0.3)=(n+0.4) or Pf(Fi)=(i−3/8)=(n+1/4), which leads to a similar estimation precision and a much higher safety factor, is considered to be the best method for engineering design. Simulations show that the weight factors and the probability estimators have e ects on the estimation precision. It is also concluded that the precision of any estimation method increases with the increase of the sample size. It is rea;rmed that 30-60 specimens are required to obtain a reasonable estimation precision of the Weibull parameters.
Estimation
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吴东方, D.
Trans IChemE, Part A, December 2006, Chemical Engineering Research and Design, 84 (A12): 1152-1157,-0001,():
-1年11月30日
The mechanical strength of solid catalysts is distributed over a wide range of values. The suitability of the normal, lognormal and Weibull distributions to model the catalyst strength variation was judged by three goodness-of-fit criteria: the coefficient of determination, Akaike information criterion and Kolmogorov–Smirnov test. It is concluded that the Weibull distribution is most universal to represent the catalyst strength data, though sometimes it may not be the optimal candidate. It is elucidated that the catalyst strength variation results from the brittle fracture nature of the mechanical failure of solid catalyst materials. The low-strength/probability part of the catalyst strength distribution is the key domain for the mechanical reliability, while the mean strength that has traditionally been taken as a measure of the catalyst strength is of less importance. It is also pointed out that a mechanical strength distributed in a narrow window, i.e., with a high Weibull modulus, is beneficial to industrial applications of solid catalysts.
mechanical
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吴东方
,-0001,():
-1年11月30日
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