|
|
|
|
|
| RODRIGUES,DIULIA C.Q.; SOARES JUNIOR,ATÍLIO P.; COSTA JUNIOR,ESLY F.; COSTA,ANDRÉA O.S.. |
| ABSTRACT Cement is one of the most used building materials in the world. The process of cement production involves numerous and complex reactions that occur under different temperatures. Thus, there is great interest in the optimization of cement manufacturing. Clinker production is one of the main steps of cement production and it occurs inside the kiln. In this paper, the dry process of clinker production is analysed in a rotary kiln that operates in counter flow. The main phenomena involved in clinker production is as follows: free residual water evaporation of raw material, decomposition of magnesium carbonate, decarbonation, formation of C3A and C4AF, formation of dicalcium silicate, and formation of tricalcium silicate. The main objective of this... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Clinker; Dynamic analysis; Mathematical modelling; Rotary kiln. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000603123 |
| |
|
|
| NIQUINI,GABRIELA R.; SILVA,SUZIMARA R.; COSTA JUNIOR,ESLY F.; COSTA,ANDRÉA O.S.. |
| Abstract: In this study, several linear regression models were tested to predict the cumulative 30-day methane yield produced in mesophilic solid-state anaerobic digestion, employing diverse lignocellulosic biomass sources. Data collected from 13 studies were utilized, totalizing 86 experimental points, divided into regression and validation. Models containing higher order terms, the inverse of variables and interactions among all eleven input variables were tested. Simple linear models utilizing a single variable were unable to describe the methane production, giving an R² lower than 0.37. However, combinations of multiple variables and its inverses as only independent variable permitted an increase in simple linear models predictive capacity up to 63% of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Lignocellulosic biomass; Linear regression; Methane; Polynomial models; Solid-state anaerobic digestion. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652019000700865 |
| |
|
|
|
