Systems and methods for determining properties of composite materials for predicting behaviour of structures

Patent metadata

Field	Value
Publication number	US-2019065645-A1
Application number	US-201815936896-A
Country	US
Kind code	A1
Filing date	Mar 27, 2018
Priority date	Aug 24, 2017
Publication date	Feb 28, 2019
Grant date	—

Abstract

Engineered structures include materials in certain arrangement and proportions to make a composite that provides desired properties to a structure. The mechanical and physical properties of the materials are measured through expensive and time consuming mechanical testing, and structural design is carried out using these properties thus warranting more time and cost spent on physical testing. Embodiments of the present disclosure provide multi-scale modeling and simulation techniques (MSMST) for design of composite materials with desired macro-scale properties wherein the (lower) MSMST are interconnected and each can pass on corresponding desired outputs to higher length-scales, which in turn evaluate macro-scale physical and mechanical properties/either to scale up the structure simulation, or to fine tune computational materials parameters thereby predicting behaviour of the structure based on determined properties of composite materials of the structure.

First claim

What is claimed is:

1 . A computer implemented method, comprising:
obtaining information pertaining to composite materials, wherein the information comprises at least one of one or more molecular and one or more nano-scale components of a structure ( 202 ); simulating the information pertaining to the one or more molecular and the one or more nano-scale components to obtain simulated data ( 204 ); performing, using a first Molecular Dynamics (MD) simulation technique, (i) a structural densification on the simulated data to obtain a densified structure output, and (ii) an equilibration technique on the densified structure output to determine an equilibration of the structure ( 206 ); simulating the densified structure output to determine at least one of (i) one or more relevant mechanical properties from a set of mechanical properties and (ii) one or more relevant thermal properties from a set of thermal properties and (iii) one or more thermodynamic properties ( 208 ); performing, a Constitutive Analytical Modeling (CAM) simulation technique, on the one or more relevant mechanical properties to obtain one or more CAM outputs ( 210 ); performing, a second MD simulation technique, on (i) the one or more relevant mechanical properties and the one or more relevant thermal properties, (ii) the one or more CAM outputs and (iii) the one or more thermodynamic properties to generate one or more second MD outputs ( 212 ); and performing, a Finite Element Analysis (FEA) modeling, on at least some of (i) the one or more relevant mechanical properties and the one or more relevant thermal properties, (ii) the one or more CAM outputs, and the one or more second MD outputs to predict a behaviour of the structure ( 214 ).

2 . The method of claim 1 , wherein the one or more relevant mechanical properties from a set of mechanical properties comprise Non-equilibrium molecular dynamics (NEMD) and Nano fracture, cyclic stress-strain, pressure response, Nano-filler dispersion, and phase-interface strength.

3 . The method of claim 1 , wherein the one or more relevant thermal properties from the set of thermal properties comprise thermal expansion, heat conduction and phonon, and wherein the one or more thermodynamic properties comprise thermodynamics derived cohesive energy.

4 . The method of claim 1 , wherein the one or more CAM outputs comprise equilibrium stress-strain and elastic moduli, cyclic loading analysis of polymer matrix composites, Payne and Mullins effects, stress-strain hysteresis with one or more strain rates.

5 . The method of claim 1 , wherein the first MD simulation technique comprises an all-atomistic MD simulation technique.

6 . The method of claim 1 , wherein the second MD simulation technique comprises a Coarse-graining molecular dynamics (CGMD) simulation technique, and wherein the one or more second MD outputs comprise equilibrium and non-equilibrium stress-strain relationships, Dynamic mechanical analysis (DMA), local micro structural evolution, localized fracture, Radial distribution function (RDF) and Glass transition temperature (GTT), and one or more inputs for Dissipative particle dynamics-second MD (DPD-SMD) simulation technique.

7 . The method of claim 1 , wherein the behaviour of the structure is predicted based on the densified structure output, and the determined equilibration of the structure.

8 . A system ( 100 ), comprising:
a memory ( 102 ) storing instructions; one or more communication interfaces ( 106 ); and one or more hardware processors ( 104 ) coupled to the memory ( 102 ) via the one or more communication interfaces ( 106 ), wherein the one or more hardware processors ( 104 ) are configured by the instructions to:
obtain, information pertaining to composite materials, wherein the information comprises at least one of one or more molecular and one or more nano-scale components of a structure;
simulate the information pertaining to the one or more molecular and the one or more nano-scale components to obtain simulated data;
perform, using a first Molecular Dynamics (MD) simulation technique, (i) a structural densification on the simulated data to obtain a densified structure output, and (ii) an equilibration technique on the densified structure output to determine an equilibration of the structure;
simulate the densified structure output to determine at least one of (i) one or more relevant mechanical properties from a set of mechanical properties and (ii) one or more relevant thermal properties from a set of thermal properties, and (iii) one or more thermodynamic properties;
perform, a Constitutive Analytical Modeling (CAM) simulation technique, on the one or more relevant mechanical properties to obtain one or more CAM outputs;
perform, a second MD simulation technique, on (i) the one or more relevant mechanical properties and the one or more relevant thermal properties, (ii) the one or more CAM outputs and (iii) the one or more thermodynamic properties to generate one or more second MD outputs; and
perform, a Finite Element Analysis (FEA) modeling, on at least some of (i) the one or more relevant mechanical properties and the one or more relevant thermal properties, (ii) the one or more CAM outputs, and the one or more second MD outputs to predict a behaviour of the structure.

9 . The system of claim 8 , wherein the one or more relevant mechanical properties from a set of mechanical properties comprise Non-equilibrium molecular dynamics (NEMD) and Nano fracture, cyclic stress-strain, pressure response, Nano-filler dispersion, and phase-interface strength.

10 . The system of claim 8 , wherein the one or more relevant thermal properties from the set of thermal properties comprise thermal expansion, heat conduction and phonon, and wherein the one or more thermodynamic properties comprise thermodynamics derived cohesive energy.

11 . The system of claim 8 , wherein the one or more CAM outputs comprise equilibrium stress-strain relationships and elastic moduli, cyclic loading analysis of polymer matrix composites, Payne and Mullins effects, stress-strain hysteresis with one or more strain rates.

12 . The system of claim 8 , wherein the first MD simulation technique comprises an all-atomistic MD simulation technique.

13 . The system of claim 8 , wherein the second MD simulation technique comprises a Coarse-graining molecular dynamics (CGMD) simulation technique, and wherein the one or more second MD outputs comprise equilibrium and non-equilibrium stress-strain relationships, Dynamic mechanical analysis (DMA), local micro structural evolution, localized fracture, Radial distribution function (RDF) and Glass transition temperature (GTT), and one or more inputs for Dissipative particle dynamics-second MD (DPD-SMD) simulation technique.

14 . The system of claim 8 , wherein the behaviour of the structure is predicted based on the densified structure output, and the determined equilibration of the structure.

15 . 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 information pertaining to composite materials, wherein the information comprises at least one of one or more molecular and one or more nano-scale components of a structure; simulating the information pertaining to the one or more molecular and the one or more nano-scale components to obtain simulated data; performing, using a first Molecular Dynamics (MD) simulation technique, (i) a structural densification on the simulated data to obtain a densified structure output, and (ii) an

Assignees

• Tata Consultancy Services Ltd

Inventors

• Maiti Soumyadipta
• Salvi Amit Gangadhar
• Rai Beena
• Mishra Shashank
• Chaube Suryanaman
• Basavarsu Purushottham Gautham

Classifications

• G16C60/00

  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

• G06F30/20

  Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title

• G06Q50/04 Primary

  Manufacturing · CPC title

• G06F2113/26

  Composites · CPC title

• G06F30/23 Primary

  using finite element methods [FEM] or finite difference methods [FDM] · CPC title