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

Patent metadata

Field	Value
Publication number	US-10977398-B2
Application number	US-201815936896-A
Country	US
Kind code	B2
Filing date	Mar 27, 2018
Priority date	Aug 24, 2017
Publication date	Apr 13, 2021
Grant date	Apr 13, 2021

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 or more molecular and one or more nano-scale components of a polymer structure;
simulating, using an All-Atomistic Molecular Dynamics (MD) simulation technique, the information pertaining to the one or more molecular and the one or more nano-scale components to obtain simulated data, wherein the simulated data represents an initial input structure for multiscale modelling of the polymer;
performing, using the All-Atomistic MD simulation technique, (i) a structural densification on the simulated data to obtain a densified polymer structure output, and (ii) an equilibration technique on the densified polymer structure output to determine an equilibration of the polymer structure, wherein the structural densification is performed by constant temperature-pressure (NPT) equilibration technique;
simulating the densified polymer structure output to determine at least (i) one of one or more relevant mechanical properties from a set of mechanical properties, (ii) one of one or more relevant thermal properties from a set of thermal properties, and (iii) one of one or more thermodynamic properties, wherein the relevant thermal properties are determined by subjecting the densified polymer structure output to different temperatures ranging from 50 K to 450 K, and wherein the determined one or more relevant mechanical properties are analyzed to determine storage modulus (G′), loss modulus (G″), and tan (δ) loss factor of the densified polymer structure using dynamic mechanical analysis (DMA);
performing, a Constitutive Analytical Modeling (CAM) simulation technique, on the determined one or more relevant mechanical properties to obtain one or more CAM outputs based on input parameters comprising volume of crosslinked polymer structure, number of polymer segments and number of crosslinkers per polymer chain in the polymer structure;
performing, a Coarse Grain Molecular Dynamics (CGMD) simulation technique, on (i) the one or more relevant mechanical properties and the one or more relevant thermal properties determined from the All-Atomistic MD simulation, (ii) the one or more CAM outputs, and (iii) the one or more thermodynamic properties determined from the All-Atomistic MD simulation, to generate one or more CGMD outputs; and
performing, a Finite Element Analysis (FEA) modeling, on at least (i) some of the one or more relevant mechanical properties and the one or more relevant thermal properties, (ii) some of the one or more CAM outputs, and (iii) some of the one or more CGMD outputs to predict a behaviour of the polymer structure, wherein the densified polymer structure output and equilibration are provided as inputs for performing the FEA modeling, and wherein the behaviour of the polymer structure is predicted from FEA outputs including structural response at macro level, design optimization based on local microstructure, design validation through experimentation, interfacial failure through cohesive analysis, and damage and failure analysis.

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 one or more CGMD 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-CGMD (DPD-CGMD) simulation technique.

6. 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, information pertaining to composite materials, wherein the information comprises at least one or more molecular and one or more nano-scale components of a polymer structure;
simulate, using an All-Atomistic Molecular Dynamics (MD) simulation technique, the information pertaining to the one or more molecular and the one or more nano-scale components to obtain simulated data, wherein the simulated data represents an initial input structure for multiscale modelling of the polymer;
perform, using the All-Atomistic MD simulation technique, (i) a structural densification on the simulated data to obtain a densified polymer structure output, and (ii) an equilibration technique on the densified polymer structure output to determine an equilibration of the polymer structure, wherein the structural densification is performed by constant temperature-pressure (NPT) equilibration technique;
simulate the densified polymer structure output to determine at least (i) one of one or more relevant mechanical properties from a set of mechanical properties, (ii) one of one or more relevant thermal properties from a set of thermal properties, and (iii) one of one or more thermodynamic properties, wherein the relevant thermal properties are determined by subjecting the densified polymer structure output to different temperatures ranging from 50 K to 450 K, and wherein the determined one or more relevant mechanical properties are analyzed to determine storage modulus (G′), loss modulus (G″), and tan (δ) loss factor of the densified polymer structure using dynamic mechanical analysis (DMA);
perform, a Constitutive Analytical Modeling (CAM) simulation technique, on the determined one or more relevant mechanical properties to obtain one or more CAM outputs based on input parameters comprising volume of crosslinked polymer structure, number of polymer segments and number of crosslinkers per polymer chain in the polymer structure;
perform, a Coarse Grain Molecular Dynamics (CGMD) simulation technique, on (i) the one or more relevant mechanical properties and the one or more relevant thermal properties determined from the All-Atomistic MD simulation, (ii) the one or more CAM outputs, and (iii) the one or more thermodynamic properties determined from the All-Atomistic MD simulation to generate one or more CGMD outputs; and
perform, a Finite Element Analysis (FEA) modeling, on at least (i) some of the one or more relevant mechanical properties and the one or more relevant thermal properties, (ii) some of the one or more CAM outputs, and (iii) some of the one or more CGMD outputs to predict a behaviour of the polymer structure, wherein the densified polymer structure output and equilibration are provided as inputs for performing the FEA modeling, and wherein the behaviour of the polymer structure is predicted from FEA outputs including structural response at macro level, design optimization based on local microstructure, design validation through experimentation, interfacial failure through cohesive analysis, and damage and failure analysis.

7. The system of claim 6 , wherein the one or more relevant mechanical properties from a set of mechanical propert

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

• G06Q50/04 Primary

  Manufacturing · CPC title

• G06F30/17

  Mechanical parametric or variational design · CPC title

• Y02P90/30

  Computing systems specially adapted for manufacturing · CPC title

• G06F30/20

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