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Materials (Basel, Switzerland)
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March 29, 2023
Influences of Flood Conditions on Dynamic Characteristics of Novel 3D-Printed Porous Bridge Bearings
Pasakorn Sengsri, Sakdirat Kaewunruen
Sensors (Basel, Switzerland)
|
October 29, 2025
Advancing Circular Economy Implementation for High-Speed Train Rolling Stocks by the Integration of Digital Twins and Artificial Intelligence
Lalitphat Khongsomchit, Sakdirat Kaewunruen
Scientific Reports
|
April 12, 2022
Prognostics of unsupported railway sleepers and their severity diagnostics using machine learning
Jessada Sresakoolchai, Sakdirat Kaewunruen
Scientific Reports
|
February 10, 2023
Railway infrastructure maintenance efficiency improvement using deep reinforcement learning integrated with digital twin based on track geometry and component defects
Jessada Sresakoolchai, Sakdirat Kaewunruen
Sensors (Basel, Switzerland)
|
January 8, 2023
Track Geometry Prediction Using Three-Dimensional Recurrent Neural Network-Based Models Cross-Functionally Co-Simulated with BIM
Jessada Sresakoolchai, Sakdirat Kaewunruen
The Science of the Total Environment
|
February 11, 2018
The effect of ground borne vibrations from high speed train on overhead line equipment (OHLE) structure considering soil-structure interaction
Chayut Ngamkhanong, Sakdirat Kaewunruen
Scientific Reports
|
February 7, 2023
Dealing with disruptions in railway track inspection using risk-based machine learning
Sakdirat Kaewunruen, Mohd Haniff Osman
Journal of Environmental Management
|
January 15, 2017
Life cycle analysis of mitigation methodologies for railway rolling noise and groundbourne vibration
Mariana Valente Tuler, Sakdirat Kaewunruen
Scientific Reports
|
August 23, 2022
Fatigue damage assessment of complex railway turnout crossings via Peridynamics-based digital twin
Mehmet Hamarat, Mayorkinos Papaelias, Sakdirat Kaewunruen
Waste Management (New York, N.Y.)
|
January 1, 2025
An explainable machine learning system for efficient use of waste glasses in durable concrete to maximise carbon credits towards net zero emissions
Xu Huang, Junhui Huang, Sakdirat Kaewunruen
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of 4
Search research articles
Search
Showing results (1-10 of 33) with videos related to
Sort By:
Page
of 4
Materials (Basel, Switzerland)
|
March 29, 2023
Influences of Flood Conditions on Dynamic Characteristics of Novel 3D-Printed Porous Bridge Bearings
Pasakorn Sengsri, Sakdirat Kaewunruen
Sensors (Basel, Switzerland)
|
October 29, 2025
Advancing Circular Economy Implementation for High-Speed Train Rolling Stocks by the Integration of Digital Twins and Artificial Intelligence
Lalitphat Khongsomchit, Sakdirat Kaewunruen
Scientific Reports
|
April 12, 2022
Prognostics of unsupported railway sleepers and their severity diagnostics using machine learning
Jessada Sresakoolchai, Sakdirat Kaewunruen
Scientific Reports
|
February 10, 2023
Railway infrastructure maintenance efficiency improvement using deep reinforcement learning integrated with digital twin based on track geometry and component defects
Jessada Sresakoolchai, Sakdirat Kaewunruen
Sensors (Basel, Switzerland)
|
January 8, 2023
Track Geometry Prediction Using Three-Dimensional Recurrent Neural Network-Based Models Cross-Functionally Co-Simulated with BIM
Jessada Sresakoolchai, Sakdirat Kaewunruen
The Science of the Total Environment
|
February 11, 2018
The effect of ground borne vibrations from high speed train on overhead line equipment (OHLE) structure considering soil-structure interaction
Chayut Ngamkhanong, Sakdirat Kaewunruen
Scientific Reports
|
February 7, 2023
Dealing with disruptions in railway track inspection using risk-based machine learning
Sakdirat Kaewunruen, Mohd Haniff Osman
Journal of Environmental Management
|
January 15, 2017
Life cycle analysis of mitigation methodologies for railway rolling noise and groundbourne vibration
Mariana Valente Tuler, Sakdirat Kaewunruen
Scientific Reports
|
August 23, 2022
Fatigue damage assessment of complex railway turnout crossings via Peridynamics-based digital twin
Mehmet Hamarat, Mayorkinos Papaelias, Sakdirat Kaewunruen
Waste Management (New York, N.Y.)
|
January 1, 2025
An explainable machine learning system for efficient use of waste glasses in durable concrete to maximise carbon credits towards net zero emissions
Xu Huang, Junhui Huang, Sakdirat Kaewunruen
Page
of 4