Method to produce evolving concrete mixture heuristic

Patent metadata

Field	Value
Publication number	US-2023094676-A1
Application number	US-202217671109-A
Country	US
Kind code	A1
Filing date	Feb 14, 2022
Priority date	Sep 24, 2021
Publication date	Mar 30, 2023
Grant date	—

Abstract

Methods, systems, and apparatus for generating a recipe for a concrete mixture, comprising: obtaining an optical characterization of a set of particles; determining, based on the optical characterization, physical characteristics of the set of particles; generating a multispherical approximation of the set of particles; selecting, based on the physical characteristics of the set of particles and from a database of performance rules, performance rules applicable to the set of particles; predicting performance of a proposed recipe for a concrete mixture formed from the set of particles by: determining a wet flowability rating of the proposed recipe based on the selected performance rules; and determining a dry packing rating of the proposed recipe based on the multispherical approximation; iteratively altering the proposed recipe and predicting performance of the altered proposed recipe until the predicted performance satisfies performance criteria to obtain a final recipe; and outputting the final recipe.

First claim

What is claimed is:

1 . A method of generating a recipe for a concrete mixture, comprising:
obtaining an optical characterization of a set of particles; determining, based on the optical characterization, physical characteristics of the set of particles; generating, by applying the physical characteristics of the set of particles to an autoencoder, a multispherical approximation of the set of particles; selecting, based on the physical characteristics of the set of particles and from a database of performance rules, performance rules applicable to the set of particles to obtain selected performance rules; predicting performance of a proposed recipe for a concrete mixture formed from the set of particles to obtain a predicted performance by:
determining a wet flowability rating of the proposed recipe based on the selected performance rules; and
determining a dry packing rating of the proposed recipe based on the multispherical approximation;
iteratively altering the proposed recipe and predicting performance of the altered proposed recipe until the predicted performance satisfies performance criteria to obtain a final recipe; and outputting the final recipe.

2 . The method of claim 1 , comprising:
mixing a concrete mixture using the final recipe; evaluating performance of the concrete mixture using one or more performance tests; and updating the performance rules based on the evaluated performance of the concrete mixture.

3 . The method of claim 2 , wherein updating the performance rules comprises generating, based on the evaluated performance, a limit curve for sets of particles matching the physical characteristics of the set of particles.

4 . The method of claim 2 , wherein updating the performance rules comprises adjusting, based on the evaluated performance, a limit curve of the database of performance rules for sets of particles matching the physical characteristics of the set of particles.

5 . The method of claim 1 , wherein the performance rules include curves representing wet flowability limits.

6 . The method of claim 1 , wherein iteratively altering the proposed recipe and predicting performance of the altered proposed recipe comprises:
obtaining data representing ingredients of the multispherical approximation; and altering a first proposed recipe to generate a second proposed recipe based on the wet flowability rating of the first proposed recipe, the dry packing rating of the first proposed recipe, and the data representing the ingredients of the multispherical approximation.

7 . The method of claim 1 , comprising determining the dry packing rating by applying the multispherical approximation of the set of particles to a physics simulator.

8 . The method of claim 7 , wherein the physics simulator comprises a discrete element method simulator.

9 . The method of claim 1 , wherein the performance criteria comprises a highest dry packing rating subject to an acceptable wet flowability rating.

10 . The method of claim 1 , wherein obtaining the optical characterization of the set of particles comprises scanning the set of particles with an imaging device.

11 . The method of claim 1 , wherein the physical characteristics of the particles comprise one or more of particle size, particle shape, or particle sphericity.

12 . The method of claim 1 , wherein the multispherical approximation has reduced dimensionality compared to the optical characterization.

13 . The method of claim 1 , wherein the physical characteristics have reduced dimensionality compared to the optical characterization.

14 . The method of claim 1 , wherein the optical characterization of the set of particles comprises heightmap representations of the set of particles.

15 . The method of claim 14 , wherein determining the physical characteristics of the set of particles comprises applying the heightmap representations of the particles to a dimension reducer to obtain the physical characteristics of the particles.

16 . A system comprising one or more computers and one or more storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
obtaining an optical characterization of a set of particles; determining, based on the optical characterization, physical characteristics of the set of particles; generating, from the optical characterization and using an autoencoder, a multispherical approximation of the set of particles; selecting, based on the physical characteristics of the set of particles and from a database of performance rules, performance rules applicable to the set of particles to obtain selected performance rules; predicting performance of a proposed recipe for a concrete mixture formed from the set of particles by:
determining a wet flowability rating of the proposed recipe based on the selected performance rules; and
determining a dry packing rating of the proposed recipe based on the multispherical approximation;
iteratively altering the proposed recipe and predicting performance of the altered proposed recipe until the predicted performance satisfies performance criteria to obtain a final recipe; and outputting the final recipe.

17 . A method of generating a recipe for a concrete mixture, comprising:
obtaining an optical characterization of a set of particles; determining, based on the optical characterization, physical characteristics of the set of particles; selecting, from a database of multispherical approximations and based on the physical characteristics, a multispherical approximation of the set of particles; selecting, based on the physical characteristics of the set of particles and from a database of performance rules, performance rules applicable to the set of particles to obtain selected performance rules; predicting performance of a proposed recipe for a concrete mixture formed from the set of particles to obtain a predicted performance by:
determining a wet flowability rating of the proposed recipe based on the selected performance rules; and
determining a dry packing rating of the proposed recipe based on the multispherical approximation;
iteratively altering the proposed recipe and predicting performance of the altered proposed recipe until the predicted performance satisfies performance criteria to obtain a final recipe; and outputting the final recipe.

18 . The method of claim 17 , comprising:
mixing a concrete mixture using the final recipe; evaluating performance of the concrete mixture using one or more performance tests; and updating the performance rules based on the evaluated performance of the concrete mixture.

19 . The method of claim 17 , wherein the optical characterization of the set of particles comprises three-dimensional representations of the set of particles.

20 . The method of claim 19 , wherein determining the physical characteristics of the set of particles comprises applying the three-dimensional representations of the particles to a dimension reducer to obtain the physical characteristics of the particles.

Assignees

• X Dev Llc

Inventors

• Papania-Davis Antonio Raymond
• Yan Weishi

Classifications

• C04B7/36

  Manufacture of hydraulic cements in general · CPC title

• C04B28/02

  containing hydraulic cements other than calcium sulfates · 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

• G06F30/25

  using particle-based methods · CPC title

• G01N33/383 Primary

  Concrete or cement · CPC title