Asst. Prof. AIMAN TARIQ

Publication Network

Articles 20

1. On the development of neural network and phenomenological constitutive models for polycarbonate under thermomechanical and impact loading: Experimental and numerical approaches

Kapcı C. I., TARIQ A., YAZICI M., DELİKTAŞ B., Voyiadjis G. Z.

European Journal of Mechanics, A/Solids , vol.119, 2026 (SCI-Expanded, Scopus)

2. A validated computational framework for investigating the manufacturing heterogeneities induced from injection molding

Polat A., Kurt G., TARIQ A., DELİKTAŞ B., YAZICI M., Voyiadjis G. Z.

International Journal of Mechanical Sciences , vol.322, 2026 (SCI-Expanded, Scopus)

3. Thermodynamically consistent physics-informed neural network approach for thin films with nonstandard boundary conditions

TARIQ A., DELİKTAŞ B., Voyiadjis G. Z.

Thin-Walled Structures , vol.225, 2026 (SCI-Expanded, Scopus)

4. On the machine learning approach for computational homogenization of short fiber-reinforced composites with elastoplastic behavior

Polat A., TARIQ A., DELİKTAŞ B., YAZICI M., Voyiadjis G. Z.

JOURNAL OF REINFORCED PLASTICS AND COMPOSITES , vol.45, no.11-12, pp.2726-2746, 2026 (SCI-Expanded, Scopus)

5. Developing a Vertical Federated Machine Learning Framework for Predicting Energy Consumption in Wastewater Treatment Plants: A Case Study of Melbourne

DELİKTAŞ B., TARIQ A., Kurt G., UYGUR A.

International Journal of Environmental Research , vol.20, no.2, 2026 (SCI-Expanded, Scopus)

6. Boosting machine learning algorithms for predicting the macroscopic material behavior of continuous fiber reinforced composite

Tarıq A., Polat A., Deliktaş B.

JOURNAL OF REINFORCED PLASTICS AND COMPOSITES , vol.45, no.3-4, pp.781-799, 2026 (SCI-Expanded, Scopus)

7. Semi-analytical and machine learning approaches for investigating the torsional vibration behavior of nano-sized viscoelastic tubes

Tariq A., Kadioglu H. G., UZUN B., DELİKTAŞ B., YAYLI M. Ö.

MECHANICS OF ADVANCED MATERIALS AND STRUCTURES , vol.33, 2026 (SCI-Expanded, Scopus)

8. Investigation of the torsional dynamics of viscoelastic nanorod through Gaussian process-based surrogate modeling and semi-analytical approaches

Kadioglu H. G., TARIQ A., DELİKTAŞ B., YAYLI M. Ö.

MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES , vol.54, no.1, 2026 (SCI-Expanded, Scopus) Sustainable Development

9. Bending analysis of cantilever microbeams with three porosity distributions using physics-informed neural network and modified couple stress theory

Tarıq A., Uzun B., Deliktaş B., Yaylı M. Ö.

Engineering Applications of Artificial Intelligence , vol.159, 2025 (SCI-Expanded, Scopus)

10. Investigation of the critical buckling load of a column with linearly varying moment of inertia using analytical, numerical, and hybrid machine learning approaches

Polat A., TARIQ A., Okay F., DELİKTAŞ B.

JOURNAL OF STRAIN ANALYSIS FOR ENGINEERING DESIGN , 2025 (SCI-Expanded, Scopus)

11. Modeling the viscoelastic behavior of a FG nonlocal beam with deformable boundaries based on hybrid machine learning and semi-analytical approaches

Tariq A., Kadioglu H. G., UZUN B., DELİKTAŞ B., YAYLI M. Ö.

ARCHIVE OF APPLIED MECHANICS , no.4, 2025 (SCI-Expanded, Scopus)

12. On the use of physics-based constraints and validation KPI for data-driven elastoplastic constitutive modelling

Lourenço R., Tariq A., Georgieva P., Andrade-Campos A., DELİKTAŞ B.

Computer Methods in Applied Mechanics and Engineering , vol.437, 2025 (SCI-Expanded, Scopus)

13. An Inverse Parameter Identification in Finite Element Problems Using Machine Learning-Aided Optimization Framework

Tariq A., DELİKTAŞ B.

EXPERIMENTAL MECHANICS , vol.65, no.3, pp.325-349, 2025 (SCI-Expanded, Scopus)

14. Application of machine learning methodology for investigating the vibration behavior of functionally graded porous nanobeams

Tariq A., UZUN B., DELİKTAŞ B., YAYLI M. Ö.

Journal of Strain Analysis for Engineering Design , vol.60, no.2, pp.131-151, 2025 (SCI-Expanded, Scopus)

15. Size dependent dynamics of a bi-directional functionally graded nanobeam via machine learning methods

Tariq A., Uzun B., AKPINAR M., YAYLI M. Ö., DELİKTAŞ B.

ADVANCES IN NANO RESEARCH , no.1, pp.33-52, 2025 (SCI-Expanded, Scopus)

16. A machine learning approach for buckling analysis of a bi-directional FG microbeam

Tariq A., Uzun B., DELİKTAŞ B., YAYLI M. Ö.

MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS , vol.31, no.1, pp.177-198, 2025 (SCI-Expanded, Scopus)

17. ANN-based evaluation system for erosion resistant highway shoulder rocks

Tariq A., Abualshar B., Deliktaş B., Song C. R., Al-Nimri B., Barret B., et al.

INTERNATIONAL JOURNAL OF GEO-ENGINEERING , vol.15, no.1, 2024 (ESCI, Scopus)

18. An investigation on ensemble machine learning algorithms for nonlinear stability response of a two-dimensional FG nanobeam

Tariq A., Uzun B., Deliktaş B., Yaylı M. Ö.

JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING , vol.46, no.9, 2024 (SCI-Expanded, Scopus)

19. Assessment of machine learning methods predicting the axial vibration frequencies of microbars

Tariq A., Uzun B., Deliktaş B., Yaylı M. Ö.

ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK , vol.104, no.3, 2024 (SCI-Expanded, Scopus) Sustainable Development

20. Vibration analysis of embedded porous nanobeams under thermal effects using boosting machine learning algorithms and semi-analytical approach

Tariq A., Uzun B., Deliktaş B., Yaylı M. Ö.

Mechanics of Advanced Materials and Structures , vol.31, no.29, pp.12320-12343, 2024 (SCI-Expanded, Scopus)

Papers Presented at Peer-Reviewed Scientific Conferences 7

1. Machine learning-assisted homogenization approach for predicting the elastoplastic behavior of short fiber reinforced composite

Polat A., Tarıq A., Deliktaş B., Yazıcı M., Yaylı M. Ö.

INTERNATIONAL CONGRESS ON NEW TRENDS IN MECHANICS, Baku, Azerbaijan, 2 - 05 September 2025, pp.829-842, (Full Text)

2. Sonlu elemanlar analizinde malzeme modellerinin verimli kalibrasyonu için yeni bir makine öğrenimi destekli ters metodolojisi

Tarıq A., Deliktaş B., Yaylı M. Ö.

24. ULUSAL MEKANİK KONGRESİ, Baku, Azerbaijan, 2 - 05 September 2025, pp.200-212, (Full Text)

7. Computational modeling the non-linear behavior of critical members causing progressive collapse in steel lattice towers

Tariq A., Deliktaş B.

22. ULUSAL MEKANİK KONGRESİ, 6 - 08 September 2021, pp.814-825, (Full Text)

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UN Sustainable Development Goals

Asst. Prof. AIMAN TARIQ

Publications & Works

1. On the development of neural network and phenomenological constitutive models for polycarbonate under thermomechanical and impact loading: Experimental and numerical approaches

2. A validated computational framework for investigating the manufacturing heterogeneities induced from injection molding

3. Thermodynamically consistent physics-informed neural network approach for thin films with nonstandard boundary conditions

4. On the machine learning approach for computational homogenization of short fiber-reinforced composites with elastoplastic behavior

5. Developing a Vertical Federated Machine Learning Framework for Predicting Energy Consumption in Wastewater Treatment Plants: A Case Study of Melbourne

6. Boosting machine learning algorithms for predicting the macroscopic material behavior of continuous fiber reinforced composite

7. Semi-analytical and machine learning approaches for investigating the torsional vibration behavior of nano-sized viscoelastic tubes

8. Investigation of the torsional dynamics of viscoelastic nanorod through Gaussian process-based surrogate modeling and semi-analytical approaches

9. Bending analysis of cantilever microbeams with three porosity distributions using physics-informed neural network and modified couple stress theory

10. Investigation of the critical buckling load of a column with linearly varying moment of inertia using analytical, numerical, and hybrid machine learning approaches

11. Modeling the viscoelastic behavior of a FG nonlocal beam with deformable boundaries based on hybrid machine learning and semi-analytical approaches

12. On the use of physics-based constraints and validation KPI for data-driven elastoplastic constitutive modelling

13. An Inverse Parameter Identification in Finite Element Problems Using Machine Learning-Aided Optimization Framework

14. Application of machine learning methodology for investigating the vibration behavior of functionally graded porous nanobeams

15. Size dependent dynamics of a bi-directional functionally graded nanobeam via machine learning methods

16. A machine learning approach for buckling analysis of a bi-directional FG microbeam

17. ANN-based evaluation system for erosion resistant highway shoulder rocks

18. An investigation on ensemble machine learning algorithms for nonlinear stability response of a two-dimensional FG nanobeam

19. Assessment of machine learning methods predicting the axial vibration frequencies of microbars

20. Vibration analysis of embedded porous nanobeams under thermal effects using boosting machine learning algorithms and semi-analytical approach

1. Machine learning-assisted homogenization approach for predicting the elastoplastic behavior of short fiber reinforced composite

2. Sonlu elemanlar analizinde malzeme modellerinin verimli kalibrasyonu için yeni bir makine öğrenimi destekli ters metodolojisi

3. Dynamic characterization of polycarbonate: A constitutive model capturing temperature and strain rate effects

4. Neural network modeling for predicting the elastoplastic behavior of short fiber reinforced polymers

5. Implementing a dual-phase machine learning strategy to develop ANN based constitutive models

6. SmartFIT: A tool for optimizing the constitutive model parameters

7. Computational modeling the non-linear behavior of critical members causing progressive collapse in steel lattice towers

Publication

Publication (WoS)

Publication (Scopus)

Citation (Scholar)

H-Index (Scholar)

Project

Open Access