Concrete Mixture Rheometry Control via Particle Analysis
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Solution Overview
Problem
The inconsistency in concrete material properties due to variations in ingredient materials and processing leads to overuse and inefficiency, necessitating large safety margins for achieving desired performance levels.
Innovation Solution
A system and process that uses rheometry measurements to characterize and adjust concrete mixtures by incrementally adding ingredients based on measured characteristics, employing particle analyzers and machine learning models to predict and achieve desired post-curing properties such as strength, flowability, and thermal insulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional concrete preparation methods are used with fixed recipes, then production simplicity is maintained, but material property inconsistency occurs leading to overuse and waste
Solution Approach 1:
The system performs preliminary characterization of raw ingredients (aggregate, cement, sand) before mixing, measuring particle size distribution, shape, and other properties. This preliminary action allows the system to predict mixture rheometry and adjust recipes in advance, ensuring consistent concrete properties without requiring complex real-time adjustments during production
Solution Approach 2:
The system implements feedback loops where rheometry measurements of the concrete mixture are continuously monitored and compared against target values. The system automatically adjusts ingredient proportions based on this feedback, creating a closed-loop control system that maintains material property consistency while adapting to variations in raw materials
2Reliability
If large safety margins are used to ensure desired performance levels, then reliability is improved, but material overuse and cost increase
Solution Approach 1:
The system changes the approach from using fixed safety margins to dynamically adjusting ingredient parameters (particle size distribution, water-cement ratio, admixture proportions) based on actual raw material characteristics. This allows achieving reliable concrete performance with optimized material quantities rather than excessive safety margins
Solution Approach 2:
Instead of consistently adding excessive materials to ensure minimum performance levels, the system applies partial adjustments only when and where needed based on actual material properties and performance requirements, optimizing material usage while maintaining reliability
3Manufacturing precision
If iterative adjustment process is implemented to optimize concrete properties, then manufacturing precision is improved, but production time increases
Solution Approach 1:
The system performs preliminary characterization of all raw ingredients and predictive rheometry calculations before the actual mixing process. This preliminary action provides a strong starting point for the iterative adjustment process, reducing the number of iterations needed and minimizing impact on production time
Solution Approach 2:
The system uses predictive models and lookup tables to skip lengthy computational iterations by estimating rheometry outcomes from ingredient characteristics. This allows the system to rush through the optimization process using pre-computed relationships between ingredient properties and concrete performance
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for preparing a concrete mixture. One of the methods includes controlling an ingredient metering system to measure and add a plurality of ingredients to a concrete mixture, measuring characteristics of at least one ingredient of the ingredients using a particle analyzer, determining an estimated rheometry measurement of for the concrete mixture, obtaining an actual rheometry measurement of the concrete mixture, and selectively controlling the ingredient metering system to add one or more additional ingredients to the concrete mixture based on a comparison of the estimated rheometry measurement with the actual rheometry measurement.