Control heat of hydration by characterizing cementitious components
US-11225595-B2 · Jan 18, 2022 · US
US12241333B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12241333-B2 |
| Application number | US-201916632462-A |
| Country | US |
| Kind code | B2 |
| Filing date | Apr 5, 2019 |
| Priority date | Apr 5, 2019 |
| Publication date | Mar 4, 2025 |
| Grant date | Mar 4, 2025 |
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A method for designing a cement composition may include: providing a target compressive strength and a target composition density; selecting at least one cementitious material from a plurality of cementitious materials; calculating a required amount of water to produce a cement composition with the target composition density, the cement composition comprising the water and the at least one cementitious material; calculating a compressive strength of the cement composition based at least in part on a model of compressive strength; comparing the calculated compressive strength to the target compressive strength; and preparing the cement composition with the calculated compressive strength.
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What is claimed is: 1. A method for designing a cement composition comprising: providing a target compressive strength and a target composition density; selecting at least one cementitious material from a plurality of cementitious materials; calculating a required amount of water to produce a cement composition with the target composition density, the cement composition comprising the water and the at least one cementitious material; calculating a compressive strength of the cement composition based at least in part on a model of compressive strength wherein the model of compressive strength includes a component of reactivity index for each cementitious material in the cement composition; comparing the calculated compressive strength to the target compressive strength; and preparing the cement composition with the calculated compressive strength. 2. The method of claim 1 further comprising: adjusting a concentration of the at least one cementitious material in the cement composition after the step of comparing; and recalculating the compressive strength of the cement composition. 3. The method of claim 2 wherein the step of adjusting comprises at least one of: i. increasing a concentration of at least one cementitious material with a relatively higher reactivity index as compared to other cementitious materials if the calculated compressive strength is lower than the target compressive strength, ii. increasing a concentration of at least one cementitious material with a relatively lower specific gravity as compared to other cementitious materials if the calculated compressive strength is lower than the target compressive strength, iii. increasing a concentration of at least one cementitious material with a relatively lower reactivity index as compared to other cementitious materials if the calculated compressive strength is greater than the target compressive strength, or iv. increasing a concentration of at least one cementitious material with a relatively higher specific gravity as compared to other cementitious materials if the calculated compressive strength is greater than the target compressive strength. 4. The method of claim 1 wherein the model of compressive strength comprises at least one correlation between compressive strength and concentration of cementitious material. 5. The method of claim 1 wherein the model of compressive strength comprises a model with the form of: ln ( CS ) = ln ( A ) - 1.5 * ln ( B ) * 1 - ρ S ρ D ρ S ρ W - 1 where CS is compressive strength, A and B are constants dependent on concentrations of cementitious materials in the cement composition calculated by a regression model, ρ s is density of the cement composition, d is density of a dry blend comprising the cementitious materials, and ρ w is a density of water. 6. The method of claim 1 wherein the model of compressive strength comprises a model with the form of: where: CS = CS 0 ( w c eff ) n where : c eff = c cement + Σ α i c i and where c cement is the mass fraction of Portland cement in a dry blend comprising the cementitious materials, α i is a reactivity index of component i in a dry blend comprising the cementitious materials, c i is the mass fraction of cementitious component i in the dry blend, w/c eff is water-to-cement ratio, CS is compressive strength, CS 0 is a compressive strength of a Portland cement composition where a water to cement ratio is 1, and n is a constant. 7. The method of claim 6 wherein the reactivity index is calculated based at least in part on a correlation comprising constants, wherein the correlation has the general form of: reactivity index=Π f (p i ) where p i is a measurable physicochemical property of the cementitious component. 8. The method of claim 1 wherein the model of compressive strength comprises a model with the form of: CS=ΣCS i ; where CS i is a compressive strength contribution of component I in a dry blend comprising the cementitious materials. 9. A system comprising: a predictive model database comprising at least one model of compressive strength for a plurality of cementitious materials wherein the model of compressive strength includes a component of reactivity index for each cementitious material; and a computer system configured to: accept an input of compressive strength and composition density; query the predictive model database and select a model; generate a cement composition, based at least in part on the selected model, compressive strength, and composition density; and display the cement composition to a user. 10. The system of claim 9 wherein the at least one model of compressive strength correlates concentration of cementitious material to compressiv
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