Ting-Yu Fan – Structural Engineering – Best Researcher Award

Published on by Civil

Ting-Yu Fan | Structural Engineering | Best Researcher Award

National Atomic Research Institute - Taiwan

AUTHOR PROFILE

ORCID

SCOPUS

SUMMARY

Ting-Yu Fan is a dedicated engineer and researcher at the National Atomic Research Institute, Taiwan. His expertise spans seismic analysis, soil-structure interaction, and thermal-hydraulic coupling, with a strong focus on nuclear and renewable energy infrastructures. Having contributed to international collaborative projects like DECOVALEX, he brings global perspective and depth to structural safety assessments. Through multidisciplinary research, industry consultancy, and cutting-edge modeling work, Fan continues to make notable advances in the safety and performance of critical energy systems under extreme environmental conditions.

EDUCATION

Ting-Yu Fan completed his Master of Engineering at National Cheng Kung University, Taiwan. His academic foundation centers on structural integrity assessment, seismic performance, and coupled thermal-hydraulic analysis. These areas laid the groundwork for his contributions to national and international research, especially in structural modeling and nuclear energy safety. His education provided the theoretical and technical base to tackle complex challenges in energy systems, particularly those involving fault mechanics, soil-structure interaction, and the behavior of engineered systems under extreme stress conditions.

PROFESSIONAL EXPERIENCE

Currently serving at the National Atomic Research Institute, Fan leads and participates in several government and industry-funded projects on nuclear safety and structural resilience. His prior engagements include critical work on offshore wind turbine support structures and safety cases for spent nuclear fuel disposal. He has contributed to structural evaluations against natural disasters such as typhoons and earthquakes. His professional journey reflects a continuous effort to bridge theoretical modeling with real-world engineering solutions in high-risk and sensitive infrastructures.

RESEARCH INTEREST

Ting-Yu Fan’s research interests span seismic performance evaluation of nuclear infrastructure, structural integrity under multi-hazard conditions, safety case development for spent nuclear fuel disposal, and advanced numerical modeling. He is particularly engaged in soil-structure interaction studies and fault reactivation modeling. His work also includes pioneering research in seismic isolation technologies for small modular reactors and extreme load responses of offshore wind support systems. These themes converge in his quest to enhance the safety, reliability, and sustainability of modern energy infrastructures.

AWARD AND HONOR

Ting-Yu Fan’s selection and participation in the DECOVALEX international research initiative reflect peer recognition of his expertise. His leadership roles in high-stakes government-funded projects further demonstrate his standing in Taiwan’s nuclear and structural engineering communities. His publications and project outcomes have contributed significantly to both academic knowledge and practical advancements in infrastructure safety, earning him a reputation as a trusted expert in the seismic and structural behavior of critical energy systems.

RESEARCH SKILL

Ting-Yu Fan brings advanced skills in seismic analysis, THM modeling, structural integrity evaluation, and numerical simulations. His toolkit includes fault activation modeling, soil-structure interaction analysis, and safety case development for complex nuclear systems. He is proficient in handling multidisciplinary data for integrated assessments of structural and geotechnical systems under environmental stressors. His ability to interpret seismic and thermal data and simulate real-world behaviors under extreme conditions stands as a cornerstone of his research success.

PUBLICATIONS

Title: Modeling the Influence of Soil-Structure-Interaction on Seismic Response of Jacket Substructure for the DTU 10MW Offshore Wind Turbine
Authors: Fan, T.-Y.; Lin, C.-Y.; Huang, C.-C.
Journal: International Journal of Offshore and Polar Engineering (2022)

Title: Strength Analysis for a Jacket-Type Substructure of an Offshore Wind Turbine under Extreme Environment Conditions
Authors: Fan, T.-Y.; Chen, S.-H.; Huang, C.-C.
Journal: International Journal of Offshore and Polar Engineering (2020)

Title: Time-Domain Fatigue Analysis of Multi-Planar Tubular Joints for a Jacket-Type Substructure of Offshore Wind Turbines
Authors: Fan, T.-Y.; Lin, C.-Y.; Huang, C.-C.; Chu, T.-L.
Journal: International Journal of Offshore and Polar Engineering (2020)

Title: Fatigue Analysis for Jacket-Type Substructure of 5MW Offshore Wind Turbine in Time Domain and Evaluation of Fatigue Damage
Authors: Fan, T.-Y.; Lin, C.-Y.; Huang, C.-C.; Chu, T.-L.
Journal: Journal of the Chinese Institute of Civil and Hydraulic Engineering (2018)

Title: Numerical Fatigue Analysis for Jacket-Type Substructure of Offshore Wind Turbines under Local Environmental Conditions in Taiwan
Authors: Fan, T.-Y.; Lin, C.-Y.; Huang, C.-C.; Chu, T.-L.
Journal: Proceedings of the International Offshore and Polar Engineering Conference (2018)

Title: Fatigue Analysis for Jacket-Type Support Structure of Offshore Wind Turbine under Local Environmental Conditions in Taiwan
Authors: Fan, T.-Y.; Huang, C.-C.; Chu, T.-L.
Journal: Proceedings of the International Offshore and Polar Engineering Conference (2017)

Title: Reissner's Mixed Variational Theorem-Based Finite Cylindrical Layer Methods for the Three-Dimensional Free Vibration Analysis of Sandwich Circular Hollow Cylinders with an Embedded Functionally Graded Material Layer
Authors: Wu, C.-P.; Fan, T.-Y.; Li, H.-Y.
Journal: Journal of Vibration and Control (2014)

CONCLUSION

Ting-Yu Fan exemplifies a modern researcher committed to public safety and energy resilience. His interdisciplinary approach blends engineering rigor with policy-oriented research outcomes. Through his contributions to nuclear safety, renewable energy systems, and geotechnical modeling, he enhances the scientific foundations for infrastructure design in seismically active and environmentally challenging regions. His work continues to impact engineering practices, regulatory standards, and academic collaboration, positioning him as a key contributor to the evolving field of energy systems engineering.

Theo Glashier – Structural Health Monitoring – Best Researcher Award

Published on by Civil

Theo Glashier - Structural Health Monitoring - Best Researcher Award

Imperial College London - United Kingdom

AUTHOR PROFILE

GOOGLE SCHOLAR
SCOPUS
ORCID

SUMMARY

Theo Glashier is a motivated PhD student at Imperial College London specializing in infrastructure monitoring and structural health assessment. His research focuses on data-driven strategies for interpreting measurement data from civil infrastructure under varying environmental conditions. With a keen interest in applying statistical methods and machine learning, Theo aims to advance real-time performance evaluations of critical structures. His hands-on experience includes working with the MX3D 3D-printed steel bridge and mentoring Master’s students. He is actively involved in academic dissemination and conference participation, laying the foundation for a promising research career in civil infrastructure health monitoring.

EDUCATION

Theo is currently completing his PhD in Civil and Environmental Engineering at Imperial College London (2021–2024), with a thesis focused on temperature-based measurement interpretation in critical civil infrastructure. He holds a First-Class Honours MEng in Mechanical Engineering from the University of Sheffield (2015–2019). His academic path includes a strong foundation in solid mechanics, structural dynamics, and nonlinear system analysis. His undergraduate and postgraduate studies have consistently emphasized research-led innovation, reflected in high-impact projects and publications. He has developed specialized expertise in regression models, machine learning applications, and sensor-based structural monitoring techniques.

PROFESSIONAL EXPERIENCE

Theo’s experience spans academia and industry. He worked at Total Energies in France (2019–2020) managing large-scale sensor data from offshore assets, leading a CO₂ monitoring initiative, and building a data infrastructure in PI System. He also contributed to NASA’s High-Altitude Student Platform via Project Sunbyte, launching a balloon-mounted solar flare imaging system. His research career includes fieldwork on the MX3D Bridge in Amsterdam and multiple in-person large-scale structural tests. He has developed strong communication skills through presenting at global conferences and managing collaborative research efforts with both academic and industrial stakeholders.

RESEARCH INTEREST

Theo is passionate about structural health monitoring and real-time infrastructure assessment. His core research explores data preparation techniques to filter environmental and operational variability from structural measurements. He integrates statistical regression, machine learning, and high-performance computing to derive accurate and interpretable predictions from complex datasets. Current projects focus on temperature-based interpretations and long-term monitoring strategies for steel bridges. His work advances the application of smart sensors and computational modeling in civil engineering, aiming to enhance the resilience, safety, and longevity of critical infrastructure systems through automated diagnostics and predictive analytics.

AWARD AND HONOR

Theo has earned several academic honors, including the Skempton PhD Scholarship and 2nd Prize at the Imperial College PhD Summer Showcase 2023. He received research travel grants such as the Milija Pavlovic Fund and institutional support to attend leading conferences like EWSHM and IABMAS 2024. His presentation skills led to an invitation to speak at the 25th Young Researchers Conference. These accolades reflect his exceptional contributions to structural monitoring research, recognized by both academic peers and industry professionals. They also underscore his ability to communicate complex findings to diverse audiences.

RESEARCH SKILL

Theo has advanced technical proficiency in Python, Matlab, and C, alongside hands-on expertise in SolidWorks, Ansys, and PI System for data acquisition. He is well-versed in machine learning for regression analysis, statistical data filtering, and signal visualization. His practical experience includes designing and deploying sensor networks, conducting in-situ structural testing, and high-performance computing for large datasets. He is multilingual, fluent in English and French, and conversational in Italian and Spanish. His interdisciplinary skill set equips him to manage complex infrastructure datasets and lead data-centric engineering projects with both academic and commercial stakeholders.

PUBLICATIONS

Title: Temperature-based measurement interpretation of the MX3D Bridge
Authors: T. Glashier, R. Kromanis, C. Buchanan
Journal: Engineering Structures, Vol. 305, Article 116736, 2024

Title: An iterative regression-based thermal response prediction methodology for instrumented civil infrastructure
Authors: T. Glashier, R. Kromanis, C. Buchanan
Journal: Advanced Engineering Informatics, Vol. 60, Article 102347, 2024

Title: Temperature-based Damage Detection for the Commissioning Dataset of the MX3D Bridge
Authors: T. Glashier, R. Kromanis, C. Buchanan
Journal: 11th European Workshop on Structural Health Monitoring (EWSHM), 2024

Title: Thermal response prediction of the MX3D bridge's operational dataset
Authors: T. Glashier, C. Buchanan, R. Kromanis
Journal: Bridge Maintenance, Safety, Management, Digitalization and Sustainability, 2024

Title: Predicting the environmental response of critical infrastructure, using the first metal 3D printed structure as a case study
Author: T. Glashier
Journal: Proceedings of the 25th Young Researchers Conference, 2023

CONCLUSION

Theo Glashier exemplifies the new generation of civil engineers driving innovation in structural health monitoring. His blend of technical skill, academic dedication, and practical experience positions him as a rising contributor to resilient infrastructure systems. With a clear vision for a research-led career, he seeks to bridge the gap between data science and civil engineering. His work not only provides scientific insight but also addresses real-world challenges in maintaining and assessing the health of built environments. Theo’s research trajectory reflects excellence, innovation, and a strong commitment to societal infrastructure advancement.