Publications
Papers in ISI peer-reviewed journals
2023
30. [5] Dang Xuan Hung, Le Tien Thinh, Nguyen Van Long, Tran Minh Tu, Dang Xuan Trung. Bending analysis of FGSP nanoplate resting on elastic foundation by using nonlocal quasi-3D theory. Thin-Walled Structures, 2023. Link
29. [4] Van-Hai Nguyen, Tien-Thinh Le, Minh Vuong Le, Hoang Dao Minh & Anh-Tu Nguyen, Multi-objective optimization based on machine learning and non-dominated sorting genetic algorithm for surface roughness and tool wear in Ti6Al4V turning, Machining Science and Technology, 2023. Link
28. [3] Tien-Thinh Le, Huan Thanh Duong*, Hieu Chi Phan. Optimization of Neural Network architecture and derivation of closed-form equation to predict ultimate load of functionally graded material plate. Advances in Mechanical Engineering, 2023. Link
27. [2] Tien-Thinh Le*, Hieu Chi Phan, Huan Thanh Duong, Minh Vuong Le. Optimal Design of Circular Concrete-Filled Steel Tubular Columns based on a Combination of Artificial Neural Network, Balancing Composite Motion Algorithm and a Large Experimental Database. Expert Systems with Applications, 2023. Link
26. [1] Nguyen, V.-H.; Le, T.-T.*; Truong, H.-S.; H. T. Duong; Le, M. V., Predicting Volumetric Error Compensation for Five-axis Machine Tool Using Machine Learning. International Journal of Computer Integrated Manufacturing, 2023. Link
2022
25. [5] Duong, T.H., Le, T.-T. & Le, M.V., Practical Machine Learning Application for Predicting Axial Capacity of Composite Concrete-Filled Steel Tube Columns Considering Effect of Cross-Sectional Shapes. International Journal of Steel Structures, 2022. Link
24. [4] Tien-Thinh Le, Athanasia D. Skentou, Anna Mamou & Panagiotis G. Asteris, Correlating the Unconfined Compressive Strength of Rock with the Compressional Wave Velocity Effective Porosity and Schmidt Hammer Rebound Number Using Artificial Neural Networks. Rock Mechanics and Rock Engineering, 2022. Link
23. [3] Anh-Tu Nguyen, Van-Hai Nguyen*, Tien-Thinh Le, and Nhu-Tung Nguyen, Multiobjective Optimization of Surface Roughness and Tool Wear in High-Speed Milling of AA6061 by Machine Learning and NSGA-II. Advances in Materials Science and Engineering, 2022. Link
22. [2] Duong, T.H, Le, T.-T.*, Nguyen, S.X., Le, M.V., Adaptive-neuro-fuzzy-inference-system model for prediction of ultimate load of rectangular concrete-filled steel tubular columns. Journal of Intelligent & Fuzzy Systems, in-press, pp. 1-19, 2022. Link
21. [1] Dong Van Dao*, Hung Viet Tran, Hai-Bang Ly, Tien-Thinh Le, Calibration of a stress-strain response for geopolymer concrete under axial compressive load. Proceedings of the Institution of Mechanical Engineers, Part L: Journal of Materials: Design and Applications 2022. Link
2021
20. [10] Le, T.-T.*, Investigation of force transmission, critical breakage force and relationship between micro-macroscopic behaviors of agricultural granular material in a uniaxial compaction test using discrete element method. Particulate Science and Technology 2021. Link
19. [9] Asteris, P. G.*, Lemonis, M. E., Le, T.-T.*, Tsavdaridis, K. D., Evaluation of the ultimate eccentric load of rectangular CFSTs using advanced neural network modeling. Engineering Structures 2021. Link
18. [8] Ho, N.X., Le, T.-T.*, Le, M.V., Development of artificial intelligence based model for the prediction of Young’s modulus of polymer/carbon-nanotubes composites. Mechanics of Advanced Materials and Structures 2021. Link
17. [7] Le, T.-T.; Asteris, P. G.*; Lemonis, M.E. Prediction of axial load capacity of rectangular concrete-filled steel tube columns using machine learning techniques. Engineering with Computers 2021. Link
16. [6] Nguyen, V.-H.*; Le, T.-T.*; Truong, H.-S.; Le, M. V.; Ngo, V.-L.; Nguyen, A. T.; Nguyen, H. Q. Applying Bayesian Optimization for Machine Learning Models in Predicting the Surface Roughness in Single-Point Diamond Turning Polycarbonate. Mathematical Problems in Engineering 2021, e6815802. Link
15. [5] Asteris, P. G.; Mamou, A.; Hajihassani, M.; Hasanipanah, M.; Koopialipoor, M.; Le, T.-T.; Kardani, N.; Armaghani, D. J. Soft Computing Based Closed Form Equations Correlating L and N-Type Schmidt Hammer Rebound Numbers of Rocks. Transportation Geotechnics 2021, 100588. Link
14. [4] Le, T.-T.*, Le, M.V., Nanoscale Effect Investigation for Effective Bulk Modulus of Particulate Polymer Nanocomposites Using Micromechanical Framework. Advances in Materials Science and Engineering 2021. Link
13. [3] Phan, C.H., Le, T.-T., Bui, D.N., Duong, T.H., Pham, D.T., An empirical model for bending capacity of defected pipe combined with axial load. International Journal of Pressure Vessels and Piping 2021. Link
12. [2] Le, T.-T.*, Le, M.V., Development of user-friendly kernel-based Gaussian process regression model for prediction of load-bearing capacity of square concrete-filled steel tubular members. Materials and Structures 2021. Link
11. [1] Ho, N.X., Le, T.-T.*, Effects of variability in experimental database on machine-learning-based prediction of ultimate load of circular concrete-filled steel tubes. Measurement 2021. Link
2020
10. [7] Le, T.-T.*, Phan, C. H., Prediction of Ultimate Load of Rectangular CFST Columns Using Interpretable Machine Learning Method. Advances in Civil Engineering 2020. Link
9. [6] Le, T.-T.* Practical Machine Learning-Based Prediction Model for Axial Capacity of Square CFST Columns. Mechanics of Advanced Materials and Structures 2020, 0 (0), 1–16. Link
8. [5] Le, T.-T.* Practical Hybrid Machine Learning Approach for Estimation of Ultimate Load of Elliptical Concrete-Filled Steel Tubular Columns under Axial Loading. Advances in Civil Engineering 2020. Link
7. [4] Le, T.-T.* Probabilistic Investigation of the Effect of Stochastic Imperfect Interfaces in Nanocomposites. Mechanics of Materials 2020, 103608. Link
6. [3] Le, T.-T.* Prediction of Tensile Strength of Polymer Carbon Nanotube Composites Using Practical Machine Learning Method. Journal of Composite Materials 2020. Link
5. [2] Thanh Duong, H.; Chi Phan, H.; Le, T.-T.; Duc Bui, N. Optimization Design of Rectangular Concrete-Filled Steel Tube Short Columns with Balancing Composite Motion Optimization and Data-Driven Model. Structures 2020, 28, 757–765. Link
4. [1] Le, T.-T.* Probabilistic Modeling of Surface Effects in Nano-Reinforced Materials. Computational Materials Science 2021, 186, 109987. Link
2018
3. [1] Le, T. T.*; Miclet, D.; Heritier, P.; Piron, E.; Chateauneuf, A.; Berducat, M. Morphology Characterization of Irregular Particles Using Image Analysis. Application to Solid Inorganic Fertilizers. Computers and Electronics in Agriculture 2018, 147, 146–157. Link
2016
2. [1] Le, T. T.; Guilleminot, J.; Soize, C. Stochastic Continuum Modeling of Random Interphases from Atomistic Simulations. Application to a Polymer Nanocomposite. Computer Methods in Applied Mechanics and Engineering 2016, 303, 430–449. Link
2013
1. [1] Guilleminot, J.; Le, T. T.; Soize, C. Stochastic Framework for Modeling the Linear Apparent Behavior of Complex Materials: Application to Random Porous Materials with Interphases. Acta Mechanica Sinica 2013, 29 (6), 773–782. Link
Papers in SCOPUS peer-reviewed journals
2023
10. [3] Anh-Tu Nguyen, Van-Hai Nguyen, Tien-Thinh Le, Nhu-Tung Nguyen, A hybridization of machine learning and NSGA-II for multi-objective optimization of surface roughness and cutting force in AISI 4340 alloy steel turning, Journal of Machine Engineering, 2023 . Link
9. [2] Tien-Thinh Le, Thong Chung Nguyen, Xuan Son Nguyen, Huan Thanh Duong, Lu Minh Le, Anh Tu Nguyen & Van Hai Nguyen (2023) Discrete Element Modeling Based Determination of Shear Behavior in a Granular Medium Through Displacement Field. Lecture Notes in Networks and Systems, Springer, Cham. Link
8. [1] Huan Thanh Duong, Tien-Thinh Le, Xuan Son Nguyen, Minh Vuong Le, Hieu Chi Phan, Lu Minh Le & Van Hai Nguyen (2022) Balancing Composite Motion Optimization and Artificial Neural Network for the Prediction of Critical Load of Concrete-Filled Steel Tubes Under Axial Compression. Lecture Notes in Networks and Systems, Springer, Cham. Link
2022
7. [4] Le TT., Le M.V. (2022) Prediction Model for Tensile Modulus of Carbon Nanotube–Polymer Composites. In: Nguyen D.C., Vu N.P., Long B.T., Puta H., Sattler KU. (eds) Advances in Engineering Research and Application. ICERA 2021. Lecture Notes in Networks and Systems, vol 366. Springer, Cham. Link
6. [3] Duong H.T., Phan H.C., Le TT. (2022) Critical Buckling Load Evaluation of Functionally Graded Material Plate Using Gaussian Process Regression. In: Nguyen D.C., Vu N.P., Long B.T., Puta H., Sattler KU. (eds) Advances in Engineering Research and Application. ICERA 2021. Lecture Notes in Networks and Systems, vol 366. Springer, Cham. Link
5. [2] Van Vo Tran M., Le L.M., Phan H., Le M.V., Nguyen VH., Le TT. (2022) Development and Identification of Working Parameters for Threshing Unit of Peanut Tuber Picking Machine. In: Khang N.V., Hoang N.Q., Ceccarelli M. (eds) Advances in Asian Mechanism and Machine Science. ASIAN MMS 2021. Mechanisms and Machine Science, vol 113. Springer, Cham. Link
4. [1] Nguyen VH., Le TT. (2022) Developing Geometric Error Compensation Software for Five-Axis CNC Machine Tool on NC Program Based on Artificial Neural Network. In: Khang N.V., Hoang N.Q., Ceccarelli M. (eds) Advances in Asian Mechanism and Machine Science. ASIAN MMS 2021. Mechanisms and Machine Science, vol 113. Springer, Cham. Link
2021
3. [1] Le, T.-T.*, Nguyen V.H., Le, M.V. Development of Deep Learning Model for the Recognition of Cracks on Concrete Surfaces. Applied Computational Intelligence and Soft Computing 2021. Link
2020
2. [1] Le, T.-T.* Multiscale Analysis of Elastic Properties of Nano-Reinforced Materials Exhibiting Surface Effects. Application for Determination of Effective Shear Modulus. Journal of Composites Science 2020, 4(4), 172. Link
2015
1. [1] Soize, C.; Desceliers, C.; Guilleminot, J.; Le, T.-T.; Nguyen, M.-T.; Perrin, G.; Allain, J.-M.; Gharbi, H.; Duhamel, D.; Funfschilling, C. Stochastic Representations and Statistical Inverse Identification for Uncertainty Quantification in Computational Mechanics. In Proceeding of UNCECOMP 2015, 1st ECCOMAS Thematic International Conference on Uncertainty Quantification in Computational Sciences and Engineering; 2015; pp 1–26. Link
Papers in other peer-reviewed journals
2021
2. [1] Le, T.-T.*, Nguyen, T.N., Bui, A.T., Le, M.V. Numerical prediction model for ultimate load of rectangular concrete-filled steel tube structures (Mô hình số dự đoán tải trọng tới hạn của các cấu kiện ống thép nhồi bê tông tiết diện chữ nhật). Tạp chí Giao thông vận tải, 08/2021, 89–92. Link
2020
1. [1] Le, T.-T.* Analysis of elastic deformation of amorphous polyethylene in uniaxial tensile test by using molecular dynamics simulation. Computer Methods in Materials Science 2020, 20, 38–44. Link
Book chapters
2022
2. [2] Van Vo Tran M., Le L.M., Phan H., Le M.V., Nguyen VH., Le TT. (2022) Development and Identification of Working Parameters for Threshing Unit of Peanut Tuber Picking Machine. In: Khang N.V., Hoang N.Q., Ceccarelli M. (eds) Advances in Asian Mechanism and Machine Science. ASIAN MMS 2021. Mechanisms and Machine Science, vol 113. Springer, Cham. Link
1. [1] Nguyen VH., Le TT. (2022) Developing Geometric Error Compensation Software for Five-Axis CNC Machine Tool on NC Program Based on Artificial Neural Network. In: Khang N.V., Hoang N.Q., Ceccarelli M. (eds) Advances in Asian Mechanism and Machine Science. ASIAN MMS 2021. Mechanisms and Machine Science, vol 113. Springer, Cham. Link
Other papers
2017
2. [1] Le, T. T.*; Piron, E.; Miclet, D.; Chateauneuf, A.; Berducat, M.; Heritier, P. Centrifugal Fertilizer Spreader: Control of Working Width and Fertilization Quality. Proceeding of 1st AXEMA-EurAgEng Conference “Intensive and environmentally friendly agriculture: an opportunity for innovation in machinery and systems”, Paris, France, 25 February 2017 2017, 97–104. Link
2013
1. [1] Le, T. T.*; Guilleminot, J.; Soize, C. Modélisation Probabiliste Des Effets de Surface Pour Des Matériaux Nano-Renforcés. In Proceeding of 21ème Congrès Français de Mécanique 2013 (CFM 2013); 2013; pp 1–6. Link