Systems and methods for predicting properties of coating types and estimating service life thereof

Patent metadata

Field	Value
Publication number	US-2024177811-A1
Application number	US-202318479480-A
Country	US
Kind code	A1
Filing date	Oct 2, 2023
Priority date	Nov 10, 2022
Publication date	May 30, 2024
Grant date	—

Abstract

Most techniques to estimate the service life of coatings are experimental in nature. Experimental testing of coatings is expensive (destructive in nature) and time consuming. Present disclosure provides system and method that predict change in chemical composition of the coating using reaction mechanism of the coating components in presence of weathering causing environmental agents. The system partial differential equations wherein chemical model is combined with the physical model. The changes in chemical composition enable determining the change in surface roughness and thickness as the weathering of the coating happens which can be correlated with other parameters such as gloss loss, fracture toughness, and the like. Rate of initiation reaction which leads to micro-randomness in concentration profile is randomized to mimic inherently stochastic (random) nature of coating degradation. Service life of coating is further estimated based on values of physical properties of coating beyond which the coating is characterized as unserviceable.

First claim

What is claimed is:

1 . A processor implemented method comprising:
obtaining, via one or more hardware processors, a coating type, and one or more weathering conditions that the coating type is to be subjected in an environment; identifying, via the one or more hardware processors, a polymer for the one or more weathering conditions for the coating type; identifying, via the one or more hardware processors, one or more relevant reactions based on the identified polymer and the one or more weathering conditions; estimating, via the one or more hardware processors, a mass balance equation for each chemical component comprised in the one or more relevant reactions; and solving, via the one or more hardware processors, the mass balance equation for each chemical component to (i) predict one or more properties of the coating type, and (ii) obtain an estimated service life.

2 . The processor implemented method of claim 1 , wherein the step of solving the mass balance equation for each chemical component comprises:
processing the mass balance equation for each chemical component by a first Partial Difference Equations (PDE) solver to obtain (i) a first concentration profile, and (ii) a second concentration profile comprising an associated depth for each chemical component; estimating, by using a first chemical-physical correlator, a first set of chemical-physical correlations of constituents comprised in the coating type based on (i) the second concentration profile comprising the associated depth and (ii) time at which the coating type is applied and (iii) the one or more weathering conditions that the coating type is to be subjected in the environment; estimating, via an optimizer, by using (i) the second concentration profile comprising the associated depth and (ii) the time at which the coating type is applied and (iii) the one or more weathering conditions that the coating type is to be subjected in the environment, one or more optimized reactions-based parameters; processing the one or more optimized reactions-based parameters via a second PDE solver and a third PDE solver to obtain a third concentration profile, and a fourth concentration profile, respectively; and estimating, by using a second chemical-physical correlator, a second set of chemical-physical correlations of constituents comprised in the coating type using at least one of the third concentration profile, and the fourth concentration profile.

3 . The processor implemented method of claim 2 , further comprising determining a change in surface roughness of the coating type with reference to time based on the second set of chemical-physical correlations of constituents comprised in the coating type.

4 . The processor implemented method of claim 3 , further comprising determining a change in thickness of the coating type with reference to time based on the first set of chemical-physical correlations and the second set of chemical-physical correlations of constituents comprised in the coating type.

5 . The processor implemented method of claim 4 , further comprising determining a change in (i) gloss, (ii) a Griffith's stress, and (iii) a wetting angle of the coating type based on the change in surface roughness of the coating type with reference to time.

6 . The processor implemented method of claim 5 , wherein the estimated service life is obtained based on at least one of (i) the change in surface roughness of the coating type, (ii) the change in thickness of the coating type, (iii) the gloss, (iv) the Griffith's stress, and (v) the wetting angle of the coating type.

7 . A system, comprising:
a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces, wherein the one or more hardware processors are configured by the instructions to: obtain a coating type, and one or more weathering conditions that the coating type is to be subjected in an environment; identify a polymer for the one or more weathering conditions for the coating type; identify one or more relevant reactions based on the identified polymer and the one or more weathering conditions; estimate a mass balance equation for each chemical component comprised in the one or more relevant reactions; and solve the mass balance equation for each chemical component to (i) predict one or more properties of the coating type, and (ii) obtain an estimated service life.

8 . The system of claim 7 , wherein the mass balance equation for each chemical component is solved by:
processing the mass balance equation for each chemical component by a first Partial Difference Equations (PDE) solver to obtain (i) a first concentration profile, and (ii) a second concentration profile comprising an associated depth for each chemical component; estimating, by using a first chemical-physical correlator, a first set of chemical-physical correlations of constituents comprised in the coating type based on (i) the second concentration profile comprising the associated depth and (ii) time at which the coating type is applied and (iii) the one or more weathering conditions that the coating type is to be subjected in the environment; estimating, via an optimizer, by using (i) the second concentration profile comprising the associated depth and (ii) the time at which the coating type is applied and (iii) the one or more weathering conditions that the coating type is to be subjected in the environment, one or more optimized reactions-based parameters; processing the one or more optimized reactions-based parameters via a second PDE solver and a third PDE solver to obtain a third concentration profile, and a fourth concentration profile, respectively; and estimating, by using a second chemical-physical correlator, a second set of chemical-physical correlations of constituents comprised in the coating type using at least one of the third concentration profile, and the fourth concentration profile.

9 . The system of claim 8 , wherein the one or more hardware processors are further configured by the instruction to determine a change in surface roughness of the coating type with reference to time based on the second set of chemical-physical correlations of constituents comprised in the coating type.

10 . The system of claim 9 , wherein the one or more hardware processors are further configured by the instruction to determine a change in thickness of the coating type with reference to time based on the first set of chemical-physical correlations and the second set of chemical-physical correlations of constituents comprised in the coating type.

11 . The system of claim 10 , wherein the one or more hardware processors are further configured by the instruction to determine a change in (i) gloss, (ii) a Griffith's stress, and (iii) a wetting angle of the coating type based on the change in surface roughness of the coating type with reference to time.

12 . The system of claim 11 , wherein the estimated service life is obtained based on at least one of (i) the change in surface roughness of the coating type, (ii) the change in thickness of the coating type, (iii) the gloss, (iv) the Griffith's stress, and (v) the wetting angle of the coating type.

13 . One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:
obtaining, a coating type, and one or more weathering conditions that the coating type is to be subjected in an environment; identifying a polymer for the one or more weathering conditions for the coating type; ide

Assignees

• Tata Consultancy Services Ltd

Inventors

• Shrivastava Surabhi
• Kausley Shankar Balajirao
• Bhattacharjee Suryadip
• Maiti Soumyadipta
• Rai Beena

Classifications

• 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

• G16C20/30

  Prediction of properties of chemical compounds, compositions or mixtures · CPC title

• C09D175/04

  Polyurethanes · CPC title