Dr. Öğr. Üyesi AIMAN TARIQ

Yayın Ağı

Makaleler 18

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

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

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

2. 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 , cilt.20, sa.2, 2026 (SCI-Expanded, Scopus)

3. 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 , cilt.45, sa.3-4, ss.781-799, 2026 (SCI-Expanded, Scopus)

4. 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 , cilt.159, 2025 (SCI-Expanded, Scopus)

5. 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 , 2025 (SCI-Expanded, Scopus)

6. 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 , 2025 (SCI-Expanded, Scopus)

7. 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)

8. 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 , sa.4, 2025 (SCI-Expanded, Scopus)

9. 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 , cilt.437, 2025 (SCI-Expanded, Scopus)

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

Tariq A., DELİKTAŞ B.

EXPERIMENTAL MECHANICS , cilt.65, sa.3, ss.325-349, 2025 (SCI-Expanded, Scopus)

11. 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 , 2025 (SCI-Expanded, Scopus)

12. 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 , cilt.60, sa.2, ss.131-151, 2025 (SCI-Expanded, Scopus)

13. 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 , cilt.31, sa.1, ss.177-198, 2025 (SCI-Expanded, Scopus)

14. 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 , sa.1, ss.33-52, 2025 (SCI-Expanded, Scopus)

15. 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 , cilt.15, sa.1, 2024 (ESCI, Scopus)

16. 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 , cilt.46, sa.9, 2024 (SCI-Expanded, Scopus)

17. 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 , cilt.104, sa.3, 2024 (SCI-Expanded, Scopus) Sürdürülebilir Kalkınma

18. 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 , cilt.31, sa.29, ss.12320-12343, 2024 (SCI-Expanded, Scopus)

Hakemli Bilimsel Toplantılarda Yayımlanmış Bildiriler 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, Azerbaycan, 2 - 05 Eylül 2025, ss.829-842, (Tam Metin Bildiri)

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

Tarıq A., Deliktaş B., Yaylı M. Ö.

24. ULUSAL MEKANİK KONGRESİ, Baku, Azerbaycan, 2 - 05 Eylül 2025, ss.200-212, (Tam Metin Bildiri)

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 Eylül 2021, ss.814-825, (Tam Metin Bildiri)

Metrikler

Yayın

Yayın (WoS)

Yayın (Scopus)

Atıf (Scholar)

300

H-İndeks (Scholar)

Proje

Açık Erişim

BM Sürdürülebilir Kalkınma Amaçları

Dr. Öğr. Üyesi AIMAN TARIQ

Yayınlar & Eserler

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

18. 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 öğrenimi

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

Yayın

Yayın (WoS)

Yayın (Scopus)

Atıf (Scholar)

H-İndeks (Scholar)

Proje

Açık Erişim