Asphalt Emulsion Prediction Tool for Crude Slate Adaptability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The unpredictability of asphalt emulsion properties due to variations in emulsifier quality and crude oil sources limits the ability to use new crude slates in asphalt production, leading to reduced flexibility in refining operations and increased testing requirements.
Innovation Solution
A predictive model that represents asphalt emulsion properties as a linear combination of properties from individual asphalt components, allowing for the characterization and modeling of new asphalt fractions based on characterized components, and a tool for modifying emulsion formation conditions to achieve desired viscosity and breaking index ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If asphalt emulsions are produced from blends of oils from multiple crude sources, then the variety of available asphalt sources increases, but the reliability of resulting asphalt quality prediction decreases
Solution Approach 1:
The patent segments the complex asphalt fraction into individual asphalt components (SARA components: saturates, aromatics, resins, asphaltenes). By characterizing each component separately and using their individual properties to predict emulsion behavior, the system can reliably handle blends from multiple crude sources. This segmentation transforms an unpredictable blended system into a sum of predictable individual contributions.
Solution Approach 2:
The patent changes the approach from predicting properties of the whole asphalt fraction to predicting properties based on individual component parameters. By measuring and utilizing specific parameters of each SARA component (such as their individual emulsion formation characteristics), the system can accurately predict blend behavior through linear combination, enabling reliable quality prediction for new crude slates.
2Reliability
If asphalt purchases are limited to asphalts from known crudes and known combinations of crudes, then the reliability of asphalt quality prediction improves, but the flexibility of refining operations decreases
Solution Approach 1:
The patent changes the predictive approach from whole-fraction modeling to component-level modeling. By characterizing asphalt in terms of its SARA components and their individual emulsion properties, the system enables reliable prediction for any crude slate combination. This parameter transformation allows refiners to flexibly change crude slates while maintaining quality prediction reliability through component-based calculations.
Solution Approach 2:
The patent performs preliminary characterization of individual asphalt components and stores their emulsion formation properties. This advance preparation of component data enables rapid prediction of blend behavior without requiring extensive new testing when new crude slates are introduced, thus maintaining both reliability and flexibility.
3Reliability
If extensive testing is performed to ensure emulsion properties fall within desired ranges, then the reliability of emulsion quality is improved, but the time and resources required increase
Solution Approach 1:
The patent performs preliminary characterization of individual asphalt components (SARA fractions) and stores their emulsion formation properties in advance. When a new asphalt blend is proposed, the system uses the pre-characterized component data to predict emulsion properties through linear combination, eliminating the need for extensive new testing while ensuring quality reliability.
Solution Approach 2:
The patent creates a virtual model of emulsion properties based on component data rather than requiring physical testing of every possible blend. By copying and combining the known properties of individual components mathematically, the system predicts blend behavior accurately without time-consuming physical experiments.
Data Source
AI summary
Methods are provided for predicting the properties of an asphalt emulsion, such as an asphalt emulsion that contains an asphalt fraction derived from a plurality of crude oils. Corresponding tools are provided to allow for visualization of the predicted asphalt emulsion properties. The properties of the asphalt components in an asphalt fraction for forming an emulsion can be represented based on using a simplified functional form to represent each emulsion property of each asphalt component. The emulsion properties of an asphalt fraction, composed of a plurality of asphalt components, can be modeled based on a linear combination of the emulsion properties of the asphalt components.