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A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications

Engineering applications of artificial intelligence, 2021-05, Vol.101, p.104232, Article 104232

2021

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Investigating the Effect of Temperature History on Crystal Morphology of Thermoplastic Composites Using In Situ Polarized Light Microscopy and Probabilistic Machine Learning

Polymers, 2022-12, Vol.15 (1), p.18

2022

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Effect of temperature history during additive manufacturing on crystalline morphology of PEEK

Advances in industrial and manufacturing engineering, 2022-05, Vol.4, p.100085, Article 100085

2022

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Multiscale characterization and representation of composite materials during processing

Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences, 2016-07, Vol.374 (2071), p.20150278-20150278

2016

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An Accelerated Process Optimization Method to Minimize Deformations in Composites Using Theory-guided Probabilistic Machine Learning

Composites. Part A, Applied science and manufacturing, 2024-01, Vol.176, p.107842, Article 107842

2024

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Investigating the impacts of processing variability on tool-part interaction for interply-toughened aerospace composites using a novel shear technique

Composites. Part A, Applied science and manufacturing, 2024-03, Vol.178, p.107973, Article 107973

2024

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Accelerated In Situ Inspection of Release Coating and Tool Surface Condition in Composites Manufacturing Using Global Mapping, Sparse Sensing, and Machine Learning

Journal of Manufacturing and Materials Processing, 2023-06, Vol.7 (3), p.81

2023

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Theory-guided machine learning for damage characterization of composites

Composite structures, 2020-08, Vol.246, p.112407, Article 112407

2020

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Machine learning assisted characterisation and simulation of compressive damage in composite laminates

Composite structures, 2021-10, Vol.273, p.114290, Article 114290

2021

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Measuring the negative pressure during processing of advanced composites

Composite structures, 2018-11, Vol.203, p.11-17

2018

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Development of aviation industry-oriented methodology for failure predictions of brittle bonded joints using probabilistic machine learning

Composite structures, 2022-10, Vol.297, p.115979, Article 115979

2022

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Implementation of a probabilistic machine learning strategy for failure predictions of adhesively bonded joints using cohesive zone modeling

International journal of adhesion and adhesives, 2022-10, Vol.118, p.103226, Article 103226

2022

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Fabrication of transparent advanced composites

Composites science and technology, 2020-09, Vol.197, p.108281, Article 108281

2020

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A stacked sublaminate-based damage-plasticity model for simulating progressive damage in composite laminates under impact loading

Thin-walled structures, 2020-11, Vol.156, p.107009, Article 107009

2020

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Bayesian parameter estimation for the inclusion of uncertainty in progressive damage simulation of composites

Composite structures, 2023-10, Vol.321, p.117257, Article 117257

2023

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Calibration and validation of a continuum damage mechanics model in aid of axial crush simulation of braided composite tubes

Composites. Part A, Applied science and manufacturing, 2017-04, Vol.95 (C), p.208-219

2017

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Efficient analysis of composites manufacturing using multi-fidelity simulation and probabilistic machine learning

Composites. Part B, Engineering, 2024-07, Vol.280, p.111499, Article 111499

2024

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An efficient multi-scale approach for viscoelastic analysis of woven composites under bending

Composite structures, 2022-07, Vol.292, p.115698, Article 115698

2022

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A machine learning framework for real-time inverse modeling and multi-objective process optimization of composites for active manufacturing control

Composites. Part B, Engineering, 2021-10, Vol.223, p.109150, Article 109150

2021

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Process-induced matrix defects: Post-gelation

Composites. Part A, Applied science and manufacturing, 2020-10, Vol.137, p.106007, Article 106007

2020

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A review of aging, degradation, and reusability of PA12 powders in selective laser sintering additive manufacturing

Materials today communications, 2023-03, Vol.34, p.105279, Article 105279

2023

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Efficient finite element simulation of compression after impact behaviour in quasi-isotropic composite laminates

Composites communications, 2021-12, Vol.28, p.100967, Article 100967

2021

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An infrared thermography-based method for the evaluation of the thermal response of tooling for composites manufacturing

Journal of composite materials, 2019-05, Vol.53 (10), p.1277-1290

2019

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Virtual characterization of nonlocal continuum damage model parameters using a high fidelity finite element model

Composite structures, 2021-01, Vol.256, p.113073, Article 113073

2021

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Temporal enhanced Ultrasound: A new method for detection of porosity defects in composites

Composites. Part A, Applied science and manufacturing, 2023-01, Vol.164, p.107259, Article 107259

2023

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A physics-informed machine learning approach for solving heat transfer equation in advanced manufacturing and engineering applications

Investigating the Effect of Temperature History on Crystal Morphology of Thermoplastic Composites Using In Situ Polarized Light Microscopy and Probabilistic Machine Learning

Effect of temperature history during additive manufacturing on crystalline morphology of PEEK

Multiscale characterization and representation of composite materials during processing

An Accelerated Process Optimization Method to Minimize Deformations in Composites Using Theory-guided Probabilistic Machine Learning

Investigating the impacts of processing variability on tool-part interaction for interply-toughened aerospace composites using a novel shear technique

Accelerated In Situ Inspection of Release Coating and Tool Surface Condition in Composites Manufacturing Using Global Mapping, Sparse Sensing, and Machine Learning

Theory-guided machine learning for damage characterization of composites

Machine learning assisted characterisation and simulation of compressive damage in composite laminates

Measuring the negative pressure during processing of advanced composites

Development of aviation industry-oriented methodology for failure predictions of brittle bonded joints using probabilistic machine learning

Implementation of a probabilistic machine learning strategy for failure predictions of adhesively bonded joints using cohesive zone modeling

Fabrication of transparent advanced composites

A stacked sublaminate-based damage-plasticity model for simulating progressive damage in composite laminates under impact loading

Bayesian parameter estimation for the inclusion of uncertainty in progressive damage simulation of composites

Calibration and validation of a continuum damage mechanics model in aid of axial crush simulation of braided composite tubes

Efficient analysis of composites manufacturing using multi-fidelity simulation and probabilistic machine learning

An efficient multi-scale approach for viscoelastic analysis of woven composites under bending

A machine learning framework for real-time inverse modeling and multi-objective process optimization of composites for active manufacturing control

Process-induced matrix defects: Post-gelation

A review of aging, degradation, and reusability of PA12 powders in selective laser sintering additive manufacturing

Efficient finite element simulation of compression after impact behaviour in quasi-isotropic composite laminates

An infrared thermography-based method for the evaluation of the thermal response of tooling for composites manufacturing

Virtual characterization of nonlocal continuum damage model parameters using a high fidelity finite element model

Temporal enhanced Ultrasound: A new method for detection of porosity defects in composites

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