Simulation and optimization of concrete recipe

Patent metadata

Field	Value
Publication number	US-11796530-B2
Application number	US-202217934361-A
Country	US
Kind code	B2
Filing date	Sep 22, 2022
Priority date	Sep 24, 2021
Publication date	Oct 24, 2023
Grant date	Oct 24, 2023

Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for simulating a concrete mixture. One of the methods includes obtaining an optical characterization of physical particles, generating a multispherical approximation of the physical particles, the multispherical approximation having reduced dimensionality compared to the optical characterization, simulating an aggregate mixture by applying the multispherical approximation of the particles to a physics simulator to obtain a predicted performance of the proposed aggregate mixture, selectively altering the aggregate mixture based on a comparison with performance metrics and simulating the altered aggregate mixture until the predicted performance satisfies the performance metrics to obtain a final aggregate mixture, and outputting the final aggregate mixture.

First claim

The invention claimed is:

1. A method of simulating a concrete mixture, the method comprising:
obtaining an optical characterization of physical particles;
generating a multispherical approximation of the physical particles, the multispherical approximation having reduced dimensionality compared to the optical characterization;
simulating an aggregate mixture by applying the multispherical approximation of the particles to a physics simulator to obtain a predicted performance of a proposed aggregate mixture;
selectively altering the aggregate mixture based on a comparison with performance metrics and simulating the altered aggregate mixture until the predicted performance satisfies the performance metrics to obtain a final aggregate mixture, wherein the performance metrics comprise concrete post-curing characteristics; and
outputting the final aggregate mixture.

2. The method of claim 1 , wherein the optical characterization comprises 3D photogrammetry models of the particles, and wherein generating the multispherical approximation comprises:
applying the 3D photogrammetry models of the particles to a parcel dimension reducer to obtain low dimensional physical characteristics of the particles; and
selecting the multispherical approximation of the particles from a database by comparing the low dimensional physical characteristics to entries in the database.

3. The method of claim 1 , wherein the optical characterization comprises heightmap representations of the particles, and wherein generating the multispherical approximation comprises:
applying the heightmap representations of the particles to a parcel dimension reducer to obtain low dimensional physical characteristics of the particles; and
determining the multispherical approximation of the particles by applying the low dimensional physical characteristics of the particles to an autoencoder.

4. The method of claim 1 , wherein the physics simulator comprises a Bayesian inference network and a discrete element method (DEM) simulator.

5. The method of claim 1 further comprising:
controlling an ingredient metering system to measure and add a plurality of ingredients to a concrete mixture based on the final aggregate mixture;
measuring, using a particle analyzer, characteristics of at least one ingredient of the ingredients;
determining, based on the measured characteristics, an estimated rheometry measurement of for the concrete mixture by:
generating multispherical approximations of the ingredients based on the measured characteristics, and
simulating the concrete mixture containing the plurality of ingredients by applying the multispherical approximations of the ingredients to the physics simulator to obtain the estimated rheometry measurement;

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.

6. The method of claim 5 , wherein the characteristics of the at least one ingredient comprises one or more of a particle size distribution, a particle shape distribution, or particle sphericity.

7. The method of claim 6 , wherein determining an estimated rheometry measurement of the concrete mixture comprises determining, based on the characteristics, a particle packing efficiency for the at least one ingredient, and determining the estimated rheometry measurement based at least in part on the particle packing efficiency.

8. The method of claim 7 , wherein determining the estimated rheometry measurement based at least in part on the particle packing efficiency comprises comparing the particle packing efficiency to a multi-dimensional lookup table that associates particle packing efficiencies to experimentally determined expected rheometry measurements.

9. The method of claim 7 , wherein determining the particle packing efficiency comprises applying characteristics as input to a Bayesian optimization algorithm.

10. The method of claim 5 , further comprising:
iteratively adjusting the concrete mixture until a stop condition is achieved, wherein each iteration comprises:
obtaining rheometry measurements of the concrete mixture;
determining, based on the rheometry measurements, whether the concrete mixture satisfies the stop condition;
in response to the rheometry measurements not satisfying the stop condition:
determining additional portions for one or more of the ingredients to be added to the concrete mixture in order to meet a set of target concrete characteristics, and
controlling the ingredient metering system to measure and add the additional portions to the concrete mixture; and

in response to determining that the concrete mixture satisfies the stop condition, ceasing the iteratively adjusting the concrete mixture.

11. The method of claim 10 , wherein the stop condition is the set of target concrete characteristics.

12. The method of claim 10 , wherein determining whether the concrete mixture satisfies the stop condition comprises determining whether the rheometry measurements indicate that the concrete mixture is likely to achieve at least one of the set of target concrete characteristics within a threshold value.

13. The method of claim 12 , wherein determining whether the rheometry measurements indicate that the concrete mixture is likely to achieve at least one of the set of target concrete characteristics comprises:
determining target rheometry parameters based on a multi-dimensional lookup table associating experimentally obtained post-curing characteristics to concrete mixtures with known rheological properties; and
comparing the rheometry measurements to the target rheometry parameters.

14. A system comprising:
at least one processor; and a data store coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to perform operations comprising:
obtaining an optical characterization of physical particles;
generating a multispherical approximation of the physical particles, the multispherical approximation having reduced dimensionality compared to the optical characterization;
simulating an aggregate mixture by applying the multispherical approximation of the particles to a physics simulator to obtain a predicted performance of a proposed aggregate mixture;
selectively altering the aggregate mixture based on a comparison with performance metrics and simulating the altered aggregate mixture until the predicted performance satisfies the performance metrics to obtain a final aggregate mixture, wherein the performance metrics comprise concrete post-curing characteristics; and
outputting the final aggregate mixture.

15. The system of claim 14 , wherein the optical characterization comprises 3D photogrammetry models of the particles, and wherein generating the multispherical approximation comprises:
applying the 3D photogrammetry models of the particles to a parcel dimension reducer to obtain low dimensional physical characteristics of the particles; and
selecting the multispherical approximation of the particles from a database by comparing the low dimensional physical characteristics to entries in the database.

16. The system of claim 14 , wherein the optical characterization comprises heightmap representations of the particles, and wherein generating the multispherical approximation comprises:
applying the heightmap representations of the particles to a parcel dimens

Assignees

• X Dev Llc

Inventors

• Bush Jeffrey
• Papania-Davis Antonio Raymond
• Yan Weishi
• Mittal Kartikye

Classifications

• G01N33/383 Primary

  Concrete or cement · CPC title

• G01N11/00

  Investigating flow properties of materials, e.g. viscosity, plasticity; Analysing materials by determining flow properties · CPC title

• G01N15/14

  Optical investigation techniques, e.g. flow cytometry · CPC title

• G06F30/25

  using particle-based methods · CPC title

• G16C60/00 Primary

  Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation · CPC title