Moura, Carlos, Viegas, Bruno, Tavares, Maria, Macedo, Emanuel, Estumano, Diego. (1401). Estimation of Parameters and Selection of Models Applied to Population Balance Dynamics via Approximate Bayesian Computational. هنرهای کاربردی, 9(1), 53-64. doi: 10.22075/jhmtr.2022.25186.1361
Carlos Henrique Moura; Bruno Marques Viegas; Maria Tavares; Emanuel Macedo; Diego Cardoso Estumano. "Estimation of Parameters and Selection of Models Applied to Population Balance Dynamics via Approximate Bayesian Computational". هنرهای کاربردی, 9, 1, 1401, 53-64. doi: 10.22075/jhmtr.2022.25186.1361
Moura, Carlos, Viegas, Bruno, Tavares, Maria, Macedo, Emanuel, Estumano, Diego. (1401). 'Estimation of Parameters and Selection of Models Applied to Population Balance Dynamics via Approximate Bayesian Computational', هنرهای کاربردی, 9(1), pp. 53-64. doi: 10.22075/jhmtr.2022.25186.1361
Moura, Carlos, Viegas, Bruno, Tavares, Maria, Macedo, Emanuel, Estumano, Diego. Estimation of Parameters and Selection of Models Applied to Population Balance Dynamics via Approximate Bayesian Computational. هنرهای کاربردی, 1401; 9(1): 53-64. doi: 10.22075/jhmtr.2022.25186.1361

Estimation of Parameters and Selection of Models Applied to Population Balance Dynamics via Approximate Bayesian Computational

Journal of Heat and Mass Transfer Research
دوره 9، شماره 1 - شماره پیاپی 17، مرداد 2022، صفحه 53-64    اصل مقاله (2.34 M)
نوع مقاله: Full Length Research Article
شناسه دیجیتال (DOI): 10.22075/jhmtr.2022.25186.1361
نویسندگان
Carlos Henrique Moura1؛ Bruno Marques Viegas2؛ Maria Tavares3؛ Emanuel Macedo1، 4؛ Diego Cardoso Estumano* 2
1Graduate Program in Chemical Engineering, PPGEQ/ITEC/UFPA, Federal University of Pará, Belém, PA, Brazil
2School of Biotechnology and Bioprocess Engineering, Federal University of Para, Belém, PA, Brazil
3Graduate Program in Mathematics and Statistics, Federal University of Para, Belém, PA, Brazil
4Natural Resources Engineering, Federal University of Para, Belém, PA, Brazil.
چکیده
Population balance models mathematically describe the particle size distribution based on modeling physical phenomena that influence the distribution, such as aggregation, growth, and breakage. Due to the wide range of mechanisms present, several models are presented in the literature since several hypotheses are considered. In the current work, the Approximate Bayesian Computational statistical technique was used to select four different models of population balance and estimate their parameters. Three strategies were applied to the drawing of parameters, evaluating the correlation between the parameters of the models. An adaptive tolerance in each population and a stopping criterion, based on Morozov's uncertainty principle, were used for the algorithm. The technique obtained reasonable estimates for the phenomenological rates of the models. The algorithm correctly selected the model used for generating measurements, and the three draw strategies demonstrated good applicability. The results obtained showed that the algorithm presented accuracy and precision in estimating the parameters and properly selected the models analyzed.
کلیدواژه‌ها
Particulate systems؛ Population balance؛ Bayesian Statistics؛ Approximate Bayesian Computational
مراجع
آمار
تعداد مشاهده مقاله: 784
تعداد دریافت فایل اصل مقاله: 683
دانشگاه سمنان
پیوندهای مفید
آمار
تعداد نشریات22
تعداد شماره‌ها721
تعداد مقالات10,358
تعداد مشاهده مقاله72,747,454
تعداد دریافت فایل اصل مقاله64,400,701