Huidong Tong | Structural Engineering | Best Researcher Award

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Dr. Huidong Tong | Structural Engineering | Best Researcher Award

Doctor student, Tongji university, China

Dr. Huidong Tong is currently a doctoral student at Tongji University, China, specializing in geotechnical and rock mechanics engineering. His research is centered around the mechanical behavior of rocks under multifactorial conditions, particularly the effects of thermal coupling, chemical corrosion, and long-term creep. With a keen interest in constitutive modeling, Dr. Tong has contributed to the development of innovative elastic-plastic and creep models that have advanced the understanding of rock deformation and failure mechanisms. He has published several peer-reviewed articles in prestigious journals such as Energy, Powder Technology, and Materials. In addition to his academic research, he is a named inventor on a patent involving intelligent digital building systems based on 6G digital twins. Dr. Tong’s work not only deepens theoretical knowledge but also supports practical engineering applications, particularly in underground construction, energy extraction, and hazard prevention. His dedication positions him as an emerging expert in his field.

Professional Profile

🔹 Education

Dr. Huidong Tong is currently pursuing his Doctor of Philosophy (PhD) in Civil Engineering at Tongji University, one of China’s leading institutions for science and engineering. His doctoral research focuses on rock mechanics, with a particular emphasis on the environmental factors—such as temperature and chemical corrosion—that influence the strength and deformation properties of rock materials. Prior to his PhD studies, Dr. Tong completed his Bachelor’s and Master’s degrees in Civil or Geological Engineering (institutional details not provided), where he laid the foundation in mechanics, materials science, and geotechnical analysis. During his academic journey, he has consistently demonstrated academic excellence and a strong aptitude for both theoretical modeling and experimental work. He has also received support from nationally funded projects like those under the National Natural Science Foundation of China, underscoring his academic promise and potential. His education is complemented by interdisciplinary exposure to materials science and computational mechanics.

🔹 Experience

Dr. Huidong Tong’s experience is rooted in both academic research and applied engineering science. As a doctoral researcher at Tongji University, he has been deeply involved in high-level scientific investigations into rock behavior under thermal-mechanical-chemical conditions. He has served as a principal or co-investigator in projects funded by the National Natural Science Foundation of China (Grant Nos. 51978401, 42107168), which has allowed him to explore damage modeling, true triaxial testing, and digital simulation of geo-materials. In parallel, Dr. Tong has collaborated with international scholars and contributed to several joint publications, showing his ability to work across disciplinary and institutional boundaries. His experience also extends to innovation, where he co-authored a patent on digital twin systems for intelligent buildings. His skills include constitutive modeling, finite element analysis, high-temperature testing, and multiphysical coupling analysis. With several SCI-indexed publications, he has built a strong profile as a researcher bridging theoretical advances with real-world geotechnical challenges.

🔹 Research Focus 

Dr. Huidong Tong’s research primarily investigates the transient and time-dependent mechanical properties of rocks under the influence of multi-physical environmental conditions, including thermal effects, chemical corrosion, and mechanical loading. His work emphasizes understanding both macroscopic mechanical behavior and microscopic damage evolution, enabling the development of sophisticated constitutive models. His current projects focus on modeling true triaxial creep behavior and coupled thermo-mechanical damage mechanisms, which are essential for underground energy storage, deep excavation stability, and geothermal systems. He integrates experimental testing with advanced numerical simulation, using models such as elasto-plastic and viscoelastic frameworks to characterize rock deformation. Another facet of his work includes hydrate-bearing and cemented sand behavior, essential for applications in offshore geotechnics and gas hydrate exploitation. Dr. Tong’s research aims to enhance predictive accuracy for rock mass behavior, contributing to engineering safety, design resilience, and infrastructure longevity under challenging environmental conditions.

🔍 Publication Top Notes

1. Chen, S., Tong, H.*, Du, X., & Chen, Q. (2025).

Title: A new elastic-plastic constitutive model for the coupled thermo-mechanical damaged rock considering dilatancy equation
Journal: Powder Technology
DOI: 10.1016/j.powtec.2025.121415
ISSN: 0032-5910

Summary:
This study introduces an elastic-plastic constitutive model that captures the effects of thermal-mechanical coupling in rocks, incorporating a novel dilatancy equation. The model accounts for damage evolution under elevated temperatures and triaxial loading, providing more accurate predictions of post-peak behavior. The theoretical framework was validated against experimental data and shown to enhance the simulation of deep underground rock deformation scenarios, improving the understanding of stress redistribution in rock masses.

2. Tong, H., Chen, Y., Du, X., Chen, S., Pan, Y., Wang, S., … & Fernandez-Steeger, T. M. (2024).

Title: A state-dependent elasto-plastic model for hydrate-bearing cemented sand considering damage and cementation effects
Journal: Materials, 17(5), 972
DOI: 10.3390/ma17050972

Summary:
This paper presents a state-dependent constitutive model for hydrate-bearing cemented sands, factoring in cementation degradation and particle interaction effects. The research is critical for offshore and arctic engineering, where hydrate dissociation and mechanical disturbance can destabilize foundations. The model was verified using lab tests and implemented numerically, highlighting its utility for risk assessment and ground response prediction during gas hydrate extraction or thermal stimulation.

3. Tong, H., Chen, Y., Du, X., Xiao, P., Wang, S., Dong, Y., … & Long, Z. (2023).

Title: A true triaxial creep constitutive model of rock considering the coupled thermo-mechanical damage
Journal: Energy, 285, 129397
DOI: 10.1016/j.energy.2023.129397

Summary:
In this publication, Dr. Tong develops a true triaxial creep model for rock under thermo-mechanical loading, considering anisotropic damage and long-term deformation behavior. This model improves the understanding of rock mechanics in high-temperature environments such as geothermal reservoirs, deep tunnels, and nuclear waste storage sites. The results showed high agreement with experimental data, making it suitable for engineering applications involving sustained thermal and stress exposure.

🏁 Conclusion

The Best Researcher Award in Structural Engineering serves as a prestigious platform to recognize individuals whose scholarly work has made significant advancements in understanding, modeling, and improving structural systems. In an era where infrastructure faces multifaceted challenges from environmental degradation, climate change, and evolving societal needs, the role of innovative research in structural engineering becomes more vital than ever. By honoring researchers like Dr. Huidong Tong—who exemplify excellence in experimental and theoretical modeling under complex environmental conditions—this award not only celebrates individual brilliance but also inspires a culture of academic and professional innovation. Through contributions such as damage constitutive modeling, thermo-mechanical coupling, and true triaxial testing, awardees influence the future of construction safety, sustainability, and resilience. This recognition is more than an accolade; it is an affirmation of dedication, impact, and forward-thinking vision in the engineering world. We welcome applications from global researchers committed to shaping the structural future.

Amir Abdollahi | Electrical Engineering | Best Researcher Award

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Prof. Dr. Amir Abdollahi | Electrical Engineering | Best Researcher Award

Professor, Shahid Bahonar University of Kerman, Iran

Professor Amir Abdollahi, born on September 3, 1985, is a distinguished researcher and educator in power systems engineering. He serves as a full professor and Head of the Energy and Environment Research Institute at Shahid Bahonar University of Kerman, Iran. Prof. Abdollahi earned his Ph.D. from Tarbiat Modares University, Tehran, focusing on dynamic demand response from the ISO perspective. His professional journey spans high-impact teaching, cutting-edge research in electricity markets, smart grids, and renewable energy systems. Recognized for his leadership and innovation, he is an active member of IEEE and a published expert across several energy domains. His contributions address national and global challenges in energy reliability, economics, and optimization.

Profiles

🎓 Education

Professor Abdollahi’s academic journey reflects excellence across Iran’s premier institutions. He completed his Ph.D. in Electrical Engineering (Power Systems) from Tarbiat Modares University, Tehran, in 2012 under the mentorship of Prof. Mohsen Parsa Moghaddam. His doctoral research explored Dynamic Demand Response Scheduling from the ISO perspective, laying the foundation for future work in energy systems optimization. He holds a Master’s degree (M.Sc., 2009) from Sharif University of Technology, where he worked with Prof. Mehdi Ehsan on Security-Constrained Unit Commitment and Generation Scheduling. He began his academic pursuit with a B.Sc. in Electrical Engineering from Shahid Bahonar University, where his undergraduate thesis focused on the Impact of Restructuring on Power System Operation. These milestones have shaped his versatile expertise in energy management, smart grids, and system reliability.

👨‍🏫 Experience

Prof. Abdollahi brings over a decade of academic and research experience. As a Professor at Shahid Bahonar University, he teaches undergraduate and graduate courses such as Power System Operation, Planning, Reliability, Restructuring, and Smart Grids. He has supervised numerous MSc and PhD theses in cutting-edge areas like energy market modeling, demand-side management, and renewable integration. He also leads the Energy and Environment Research Institute, where he spearheads interdisciplinary projects and national collaborations. His service as a mentor, administrator, and curriculum designer has significantly contributed to engineering education in Iran. He is also active in the IEEE community and often collaborates on international platforms involving smart electricity grids and optimization algorithms. His dynamic presence bridges research, teaching, and innovation.

🔬 Research Focus 

Prof. Abdollahi’s research encompasses power system flexibility, smart electricity grids, demand response, energy economics, and renewable integration. His doctoral and post-doctoral work on Dynamic Demand Response Scheduling laid a foundation for modern smart grid control mechanisms. He investigates ways to optimize electricity markets under uncertainty, often using game theory, multi-criteria decision making (MCDM), and hybrid optimization methods. His ongoing projects explore the interaction of distributed energy resources with power system operation, market simulation, and energy resilience strategies. He combines theoretical modeling with real-world scenarios, contributing solutions for grid reliability, peak load management, and market regulation in developing and developed contexts. With energy systems undergoing rapid digital transformation, his work stands at the intersection of engineering, economics, and sustainability.

📄 Publication Top Notes

1. Flexible demand response programs modeling in competitive electricity markets

Authors: M.P. Moghaddam, A. Abdollahi, M. Rashidinejad
Journal: Applied Energy, Volume 88, Issue 9, 2011, Pages 3257–3269
Cited by: 391
Summary:
This paper develops a detailed framework for modeling various flexible demand response (DR) programs in competitive electricity markets. It distinguishes between incentive-based and price-based mechanisms, incorporating customer behavior in response to market signals. By applying optimization techniques, the authors evaluate the impact of DR on market performance, load profiles, and system reliability. The study concludes that DR can significantly enhance both economic efficiency and grid stability.

2. Investigation of economic and environmental-driven demand response measures incorporating UC

Authors: A. Abdollahi, M.P. Moghaddam, M. Rashidinejad, M.K. Sheikh-El-Eslami
Journal: IEEE Transactions on Smart Grid, Volume 3, Issue 1, 2011, Pages 12–25
Cited by: 211
Summary:
This work integrates economic and environmental considerations into a unit commitment (UC) model enhanced with demand response. It proposes a flexible UC framework that incorporates DR as a scheduling tool for power system operators. Using scenario-based simulations, the authors demonstrate that DR reduces both operational costs and CO₂ emissions. The paper emphasizes the strategic role of DR in achieving sustainability goals in smart grid operations.

3. Coordinated wind-thermal-energy storage offering strategy in energy and spinning reserve markets using a multi-stage model

Authors: H. Khaloie, A. Abdollahi, M. Shafie-Khah, A. Anvari-Moghaddam, S. Nojavan, et al.
Journal: Applied Energy, Volume 259, 2020, Article 114168
Cited by: 159
Summary:
The study proposes a multi-stage stochastic model for coordinated operation of wind, thermal, and energy storage systems in energy and spinning reserve markets. The model effectively handles uncertainties in wind power and market prices, offering optimal bidding strategies to maximize profit while ensuring system reliability. This paper highlights how energy storage enhances the dispatchability of renewable energy and supports reserve provision in volatile market conditions.

4. A comprehensive sequential review study through the generation expansion planning

Authors: H. Sadeghi, M. Rashidinejad, A. Abdollahi
Journal: Renewable and Sustainable Energy Reviews, Volume 67, 2017, Pages 1369–1394
Cited by: 152
Summary:
This review comprehensively analyzes generation expansion planning (GEP) techniques, classifying them by modeling approaches, uncertainty treatment, and objective criteria (economic, environmental, technical). It covers classical methods, stochastic programming, robust optimization, and scenario analysis, providing a step-by-step understanding of GEP frameworks. The study also explores integration of renewable energy, environmental regulations, and modern computational tools, making it a valuable reference for researchers and planners.

5. Co-optimized bidding strategy of an integrated wind-thermal-photovoltaic system in deregulated electricity market under uncertainties

Authors: H. Khaloie, A. Abdollahi, M. Shafie-Khah, P. Siano, S. Nojavan, et al.
Journal: Journal of Cleaner Production, Volume 242, 2020, Article 118434
Cited by: 130
Summary:
This paper introduces a co-optimization strategy for hybrid renewable-conventional power systems (wind, thermal, and solar) in deregulated electricity markets. A stochastic programming approach accounts for uncertainties in generation, demand, and market prices. The findings show improved profitability and resilience of integrated energy systems. It also emphasizes the advantages of diversification and coordination among different energy sources under competitive market conditions.

6. The energy hub: An extensive survey on the state-of-the-art

Authors: H. Sadeghi, M. Rashidinejad, M. Moeini-Aghtaie, A. Abdollahi
Journal: Applied Thermal Engineering, Volume 161, 2019, Article 114071
Cited by: 104
Summary:
This extensive review presents the concept of the “energy hub” as a pivotal solution for managing multiple energy carriers (electricity, gas, heat, etc.) in a smart and integrated manner. It classifies energy hub models based on their mathematical formulation, control strategies, and optimization approaches. The review also discusses the role of energy hubs in smart cities and highlights future challenges in terms of uncertainty modeling, renewable integration, and cyber-physical system design.

7. Evaluation of plug-in electric vehicles impact on cost-based unit commitment

Authors: E. Talebizadeh, M. Rashidinejad, A. Abdollahi
Journal: Journal of Power Sources, Volume 248, 2014, Pages 545–552
Cited by: 101
Summary:
The paper investigates the influence of plug-in electric vehicles (PEVs) on traditional unit commitment strategies. A cost-based unit commitment model is enhanced by incorporating vehicle-to-grid (V2G) capabilities. The analysis reveals that coordinated charging and discharging of PEVs can flatten load profiles, improve generation scheduling, and reduce overall operational costs. This study showcases the benefits of integrating transportation electrification with power system operation.

8. Probabilistic multiobjective transmission expansion planning incorporating demand response resources and large-scale distant wind farms

Authors: A. Hajebrahimi, A. Abdollahi, M. Rashidinejad
Journal: IEEE Systems Journal, Volume 11, Issue 2, 2017, Pages 1170–1181
Cited by: 95
Summary:
This work introduces a probabilistic multiobjective framework for transmission expansion planning (TEP), considering both demand response and large-scale remote wind integration. Using a scenario-based optimization model, it evaluates trade-offs among cost, reliability, and environmental factors. The study emphasizes the significant impact of demand-side resources and renewables on reducing transmission investments and increasing system flexibility.

9. The role of energy storage and demand response as energy democracy policies in the energy productivity of hybrid hub system considering social inconvenience cost

Authors: S. Dorahaki, A. Abdollahi, M. Rashidinejad, M. Moghbeli
Journal: Journal of Energy Storage, Volume 33, 2021, Article 102022
Cited by: 63
Summary:
The authors explore how energy storage and demand response can support energy democracy and enhance energy productivity in hybrid hub systems. A multi-objective optimization model is proposed, which includes social inconvenience costs—representing the discomfort experienced by users due to participation in DR programs. The findings advocate for people-centered energy policies that balance technical efficiency with consumer welfare.

10. Risk-based probabilistic-possibilistic self-scheduling considering high-impact low-probability events uncertainty

Authors: H. Khaloie, A. Abdollahi, M. Rashidinejad, P. Siano
Journal: International Journal of Electrical Power & Energy Systems, Volume 110, 2019, Pages 598–612
Cited by: 61
Summary:
This paper proposes a hybrid probabilistic-possibilistic model for the self-scheduling of power producers under uncertainty. It particularly addresses high-impact low-probability (HILP) events, such as extreme weather or cyberattacks. The model integrates risk-averse strategies with operational decision-making to maintain reliability and cost-effectiveness. The approach is validated using case studies that show how HILP scenarios influence bidding and reserve commitments in electricity markets.

Conclusion

Professor Amir Abdollahi is a highly qualified and influential academic in the field of Power Systems Engineering. His academic leadership, diverse teaching, and research focus on modern challenges in energy systems make him a strong candidate for the Best Researcher Award, particularly at the national or institutional level.