A bias-corrected ensemble model for quantifying additive content variations in complex lubricant systems

Key Points

• Quantifying additive content variations improves the understanding of lubricant systems' performance.
• The ensemble model achieved a bias correction of 15%, enhancing predictive accuracy in complex systems.
• Assessment utilized a novel approach by integrating multiple modeling techniques to enhance reliability.
• Highlights the need for accurate quantification methods to support the development of lubricant formulations.