Faculty profile

Kaan Inal

ResearcherMechanical and Mechatronics EngineeringUniversity of Waterloo

This profile is built from public research funding records (CIHR, NSERC and SSHRC) and PubMed. We have not imported them from a University of Waterloo directory, so their courses and email address may be missing. Find their university profile.

Kaan Inal

Researcher

Mechanical and Mechatronics Engineering

Engineering

University of Waterloo

Waterloo, Ontario, Canada

Supervision signals

Has led research grants, which requires an independent research appointment. Ask their department whether they supervise graduate students.
2 publications in the last five years, latest in 2024.
Senior (last) author on 1 recent paper, a sign of leading a research group.
Principal investigator on 18 research grants (18 NSERC), most recently in 2024.

These signals come from public records, including CIHR, NSERC and SSHRC funding decisions. Ask the professor or the graduate program whether they are taking new students.

Academic metrics

Publications

Citations

Collaborators

Grants

Publications by year

Counts cover the publications linked to this profile. Citations and the h-index appear when the source records them.

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Signals and details

Research

Computational Mechanics CP based Finite Element Models Crystal Plasticity (CP)Large Strain Plasticity Process Modelling Wrought Aluminum Alloys crashworthiness crystal plasticity

Latest papers

Deep convolutional generative adversarial network for generation of computed tomography images of discontinuously carbon fiber reinforced polymer microstructures.
Scientific reports · 2024
Experimental investigation and development of a deep learning framework to predict process-induced surface roughness in additively manufactured aluminum alloys
Welding in the World, Le Soudage Dans Le Monde · 2023 · senior author

All 2 publications

Latest funding

Advanced MultiScale Constitutive Models Coupled with Machine Learning to Predict the Performance (Forming, Fracture and Crashworthiness) of Aluminum Alloys
NSERC · 2024 · Principal investigator
$62,000
A machine learning-based constitutive model to predict fracture and crashworthiness of quenched and partitioned steels
NSERC · 2024 · Principal investigator
$60,000
Multiscale Modelling of Formability and Fracture in Magnesium Alloys at Various Temperatures and Strain Rates
NSERC · 2024 · Principal investigator
$103,088

All 28 grants and awards

Advanced MultiScale Constitutive Models Coupled with Machine Learning to Predict the Performance (Forming, Fracture and Crashworthiness) of Aluminum Alloys

Principal investigatorNSERC2024Discovery Grants Program - Individual

Principal investigators: Inal, Kaan

Keywords: multiscale modelling; crystal plasticity finite element model; machine learning; formability; fracture; crashworthiness; aluminum alloys; microstructure; localized deformation

$62,000

A machine learning-based constitutive model to predict fracture and crashworthiness of quenched and partitioned steels

Principal investigatorNSERC2024Alliance Grants

Principal investigators: Inal, Kaan KA

Keywords: crashworthiness; crystal plasticity; ductile fracture; finite element method; long short term memory nn; machine learning; mechanical testing; quenched and partitioned steels; recurrent neural networks

$60,000

Multiscale Modelling of Formability and Fracture in Magnesium Alloys at Various Temperatures and Strain Rates

Principal investigatorNSERC2024Alliance Grants

Principal investigators: Inal, Kaan KA

Keywords: crystal plasticity; dynamic recrystallization; fast fourier transform model; finite element method; formability; fracture; magnesium alloys; m-k analysis; phase field model

$103,088

Development of DEM-FEM and machine learning models for optimizing vibratory peening of aircraft parts

Co-investigatorNSERC2024Alliance Grants

Principal investigators: Martin, Etienne E

Keywords: artificial intelligence; finite element simulations; mechanical properties; vibratory peening

$176,200

Robust AI-supported virtual tools to accelerate the constitutive characterization and modelling of lightweight fiber-reinforced composite materials

Co-investigatorNSERC2023Alliance Grants

Principal investigators: Montesano, Giovanni G

Keywords: ai-supported prediction tools; electric vehicle lightweighting; failure and damage mechanics; fiber-reinforced composite materials; micromechanics-based models; process-structure-property relations; rate-dependent material behaviour; safety and crashworthiness

$143,282

Multiscale Process Modeling for 6000 Series Aluminum Alloys

Principal investigatorNSERC2022Alliance Grants

Principal investigators: Inal, Kaan KA

Keywords: computational mechanics; cp based finite element models; crystal plasticity (cp); large strain plasticity; process modelling; wrought aluminum alloys

$225,000

Development of a new battery casing for electric vehicles using 3D printing

Co-investigatorNSERC2022Alliance Grants

Principal investigators: Martin, Etienne E

Keywords: additive manufacturing; artificial intelligence; battery electric vehicles; finite element analysis; materials characterization

$599,958

An artificial intelligence based approach to account for the effects of microstructure gradients and residual stresses on fatigue performance of additively manufactured aluminum

Principal investigatorNSERC2021Alliance Grants

Principal investigators: Inal, Kaan

$30,000

Micromechanics based Modelling of Formability and Fracture in Dual Phase and Quenched and Partitioned Steels

Principal investigatorNSERC2020Alliance Grants

Principal investigators: Inal, Kaan AK

$250,000

Artificial intelligence (AI) based deep learning of defects, surface roughness and their linkage to mechanical performance of additively manufactured (AM) aluminum alloys_x000d_ _x000d_

Principal investigatorNSERC2019Alliance Grants

Principal investigators: Inal, Kaan

$30,000

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

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Kaan Inal

Research

Latest papers

Latest funding

Deep convolutional generative adversarial network for generation of computed tomography images of discontinuously carbon fiber reinforced polymer microstructures.

Experimental investigation and development of a deep learning framework to predict process-induced surface roughness in additively manufactured aluminum alloys

Advanced MultiScale Constitutive Models Coupled with Machine Learning to Predict the Performance (Forming, Fracture and Crashworthiness) of Aluminum Alloys

A machine learning-based constitutive model to predict fracture and crashworthiness of quenched and partitioned steels

Multiscale Modelling of Formability and Fracture in Magnesium Alloys at Various Temperatures and Strain Rates

Development of DEM-FEM and machine learning models for optimizing vibratory peening of aircraft parts

Robust AI-supported virtual tools to accelerate the constitutive characterization and modelling of lightweight fiber-reinforced composite materials

Multiscale Process Modeling for 6000 Series Aluminum Alloys

Development of a new battery casing for electric vehicles using 3D printing

An artificial intelligence based approach to account for the effects of microstructure gradients and residual stresses on fatigue performance of additively manufactured aluminum

Micromechanics based Modelling of Formability and Fracture in Dual Phase and Quenched and Partitioned Steels

Artificial intelligence (AI) based deep learning of defects, surface roughness and their linkage to mechanical performance of additively manufactured (AM) aluminum alloys_x000d_ _x000d_

Frequent collaborators

Jidong Kang