
This report presents part of results of STAGE 6 Sensitivity analysis and scenario evaluation of the PROJECT “Microalloyed steels and their microalloying elements: materials for processing and combustion of ternary mixtures with green diesel biofuel”. The objective of the analysis was to evaluate the main effects and interaction effects of the investigated factors on the response variable TC (Corrosion rate), as well as to assess the adequacy and statistical significance of the proposed regression model. The analysis includes effect estimates, regression coefficients, analysis of variance (ANOVA), Pareto charts of standardized effects, fitted response surfaces, and residual diagnostics. These tools were used to identify statistically significant factors, quantify their influence on the response, and verify the assumptions underlying the statistical model. All analyses were conducted using STATISTICA® software, adopting a significance level of α = 0.05. The results presented herein provide a quantitative basis for interpreting the influence of experimental variables on the response and for supporting subsequent technical or scientific conclusions. The experimental and analytical activities were carried out at the Laboratory of Industrial Processes and Nanotechnology (LPIN), State University of Rio de Janeiro (UERJ).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
