Chao Jiang | Turbulence Modeling | Best Researcher Award

Published on 09/12/202409/12/2024 by ScienceFather

Chao Jiang | Turbulence Modeling | Best Researcher Award

Dr. Chao Jiang, Peking University, China.

Dr. Chao Jiang is a postdoctoral researcher in the Department of Mechanics and Aerospace Engineering at Peking University, Beijing. His pioneering work bridges fluid mechanics, machine learning, and turbulence modeling with an emphasis on AI-enhanced scientific computations and aerodynamic bionics. Dr. Jiang’s notable achievements include uncovering wake anomalies in bio-inspired bluff bodies and developing physics-inspired machine learning methods with form-invariant symmetry neurons. Previously, he served as an Assistant Professor at the Southern University of Science and Technology and an AI Engineer at TenFong Central Research Institute. Dr. Jiang combines cutting-edge science with real-world applications to revolutionize flow control.

Publication profile

Orcid

Education and Experience

2010-2014: B.Sc. in Civil Engineering, Harbin Institute of Technology
2014-2017: M.Sc. in Engineering Mechanics, Harbin Institute of Technology
2017-2023: Ph.D. in Engineering Mechanics, Harbin Institute of Technology
Assistant Professor: Southern University of Science and Technology
AI Engineer: TenFong Central Research Institute
Postdoctoral Researcher: Mechanics & Aerospace Engineering, Peking University

Suitability For The Award

Dr. Chao Jiang is an outstanding candidate for the Best Researcher Award based on his groundbreaking contributions to the fields of fluid mechanics, turbulence modeling, and AI-enhanced scientific computations. His interdisciplinary approach integrating machine learning and computational science with classical mechanics makes him a pioneer in his field.

Professional Development

Dr. Chao Jiang has made transformative contributions to fluid mechanics, turbulence modeling, and AI-driven scientific computations. His research revealed phase transitions in wavy cylinder wake dynamics, offering critical insights into flow control. Dr. Jiang redefined turbulence modeling by integrating data-driven methods with physics-based closure strategies, improving multiscale computational frameworks. Additionally, his breakthrough work on physics-inspired symmetry neurons introduced form-invariant deep learning, enhancing the modeling of scalar and tensor systems. By combining machine learning with classical physics, Dr. Jiang pushes boundaries, creating innovative tools to solve complex aerodynamic and computational challenges.

Research Focus

Dr. Chao Jiang’s research focuses on the integration of fluid mechanics, aerodynamics, and machine learning to advance scientific understanding and engineering applications. His work in turbulence modeling leverages data-driven approaches to develop more accurate closure models for complex fluid flow simulations. He is also pioneering physics-inspired machine learning, creating neural networks with symmetry neurons to improve computational modeling and solve multi-scale problems. Dr. Jiang’s exploration of aerodynamic bionics and flow control is transforming the way bio-inspired designs are applied to improve efficiency in aerodynamics. His research bridges traditional engineering with cutting-edge AI to redefine how we approach scientific computation.

Awards and Honors

Outstanding Researcher Award for contributions to turbulence modeling.
Best Dissertation Award, Harbin Institute of Technology, 2023.
Innovation in AI for Scientific Computation Award, TenFong Central Research Institute.
Young Scientist Recognition for pioneering work in physics-informed machine learning.
Top Researcher Award in Fluid Mechanics & Flow Control.

Publications

Velocity phase-transitions in the wake of a wavy cylinder at low Reynolds numbers

Ocean Engineering | 2025

An interpretable framework of data-driven turbulence modeling using deep neural networks

Physics of Fluids | 2021

A Novel Algebraic Stress Model with Machine-Learning-Assisted Parameterization

Energies | 2020

A numerical investigation of Reynolds number sensitivity of flow characteristics around a twin-box girder

Journal of Wind Engineering and Industrial Aerodynamics | 2018

Mangala Kandagal | Fluid Mechanics | Best Researcher Award

Published on 28/08/202412/09/2024 by ScienceFather

Dr. Mangala Kandagal | Fluid Mechanics | Best Researcher Award

Dr. Mangala D. Kandagal, Sharnbasva University Kalaburagi, India

Dr. Mangala D. Kandagal is an Assistant Professor in the Mathematics Department at Sharnbasva University, Kalaburagi. With a background in Fluid Mechanics, she combines academic rigor with significant research contributions, particularly in fluid dynamics and heat transfer phenomena.

Profile

ORCID Profile

Suitability For The Award:

Dr. Mangala Kandagal is an accomplished researcher and academician with a strong background in fluid dynamics, heat transfer, and applied mathematics. Her extensive experience in teaching, research, and academic contributions make her a suitable candidate for the Best Researcher Award.

Education:

Dr. Kandagal holds an M.Sc., B.Ed., and Ph.D. from Sharnbasva University, Kalaburagi. Her academic journey includes a Bachelor’s degree from Gulbarga University and a Master’s degree from Sharanbasveshwar Science College, where she achieved First Class distinctions throughout her education.

Research Focus:

Her research centers on Fluid Mechanics, with a particular focus on the effects of natural convection and magneto-hydrodynamic flows in vertical channels. Her studies delve into heat generation, absorption, and multifluid flow characteristics.

Professional Journey:

Dr. Kandagal’s teaching career began at Sharnbasveshwar Science College, where she taught B.Sc. and M.Sc. courses from 2014 to 2017. She has been with Sharnbasva University, Kalaburagi, since 2017, where she continues to educate and inspire students in advanced mathematical concepts.

Honors & Awards:

She has been recognized with the “Young Researcher Award” at an international level for her contributions to digital education, awarded by the Shri Paramhans Education and Research Foundation Trust.

Publications Noted & Contributions:

Dr. Kandagal’s notable publications include studies on multifluid flow, heat generation, and magneto-hydrodynamic effects, featured in high-impact journals like the Journal of Heat Transfer Wiley and Case Studies in Thermal Engineering. Her research significantly contributes to understanding complex fluid dynamics and heat transfer mechanisms.

An Investigation of the Heat and Mass Transfer Effects in Vertical Channels with Immersible Fluid Flow Through a Porous Matrix
- Journal: ZAMM – Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik
- Date: August 5, 2024
- DOI: 10.1002/zamm.202300998
- Contributors: Mangala Kandagal; Ramesh Kempepatil
Influence of Heat Generation/Absorption on Mixed Convection Flow Field with Porous Matrix in a Vertical Channel
- Journal: Case Studies in Thermal Engineering
- Year: 2023
- DOI: 10.1016/j.csite.2023.103049
- EID: 2-s2.0-85160398917
- Contributors: Thanesh Kumar, K.; Kalyan, S.; Kandagal, M.; Tawade, J.V.; Khan, U.; Eldin, S.M.; Singh Chohan, J.; Elattar, S.; Abed, A.M.
Heat Generation and Assimilation-MHD Model for Convective Flow of Two Immiscible Fluids in a Vertical Channel
- Year: 2023 (Preprint)
- DOI: 10.21203/rs.3.rs-3618218/v1
- PPR: PPR763023
- Contributors: Kandagal M; Kempepatil R
Effect of Two Immiscible Multifluids Flow on Internal Heat Generation or Absorption in a Vertical Channel in the Presence of Concentration
- Journal: Heat Transfer
- Year: 2021
- DOI: 10.1002/htj.22238
- EID: 2-s2.0-85110258047
- Contributors: Kandagal, M.; Kalyan, S.

Research Timeline:

Her research trajectory includes her Ph.D. thesis on natural convection in magneto-hydrodynamic flows, with ongoing and recent contributions to the field, including a 2023 international conference paper on MHD models.

Collaborations and Projects:

Dr. Kandagal collaborates with researchers like Shreedevi Kalyan and Ramesh Kempepatil on various projects focusing on fluid dynamics and heat transfer. Her work includes joint research on multifluid flows and MHD models in vertical channels.

Conclusion:

Dr. Mangala Kandagal’s extensive teaching experience, significant research contributions, published works in reputable journals, and recognition through awards make her an outstanding candidate for the Best Researcher Award. Her research not only advances the understanding of complex fluid dynamics but also contributes to the academic community through education and leadership. Her achievements demonstrate a strong alignment with the qualities sought in a recipient of this prestigious award.

Assoc Prof Dr. Can Huang| Computational Fluid Dynamics Award | Most Cited Paper Award | 9196

Published on 30/04/202430/04/2024 by ScienceFather

Assoc Prof Dr. Can Huang| Computational Fluid Dynamics Award | Most Cited Paper Award

Assoc Prof Dr. Can Huang , North China University of Technology , China

Can Huang is a distinguished fluid dynamics researcher specializing in Smoothed Particle Hydrodynamics (SPH) and its applications in multi-phase flow, wave energy, and marine gas hydrate studies. With a robust academic background, including a Ph.D. in Fluid Mechanics from Beijing Institute of Technology and post-doctoral experience at Peking University and Zhejiang University, Can has made significant contributions to computational fluid dynamics (CFD) simulation techniques. His research focuses on developing high-precision SPH methods for modeling complex transport processes in hydrate-bearing sediments and methane hydrate dissociation. As an Associate Professor at North China University of Technology and a Visiting Professor at Polytechnique University, Can continues to advance the field of fluid dynamics, particularly in marine and environmental applications. His innovative work in SPH and hybrid methods underscores his dedication to pushing the boundaries of simulation and modeling in fluid dynamics, emphasizing practical implications for industries such as marine engineering and energy. 🌊

Professional Profile:

Scopus

Google Scholar

Orcid

Education and Academic Journey 🎓

Dr. Huang earned his Bachelor’s degree in Thermal Energy and Power Engineering from the Agricultural University of Hebei in 2009. He pursued his passion for fluid mechanics further by completing a PhD in Fluid Mechanics at the Beijing Institute of Technology University, focusing on SPH, CFD simulation, and heat transfer algorithms.

Professional Experience 💼

Dr. Huang’s academic career spans prestigious institutions where he has made significant contributions to fluid dynamics research. As an Associate Professor at North China University of Technology, he delved into SPH, hybrid methods, and marine gas hydrate studies. He continued this pursuit during his time as a Lecturer and later as a Visiting Professor at Polytechnique University, honing his expertise in ice mechanics, multi-phase flow, and CFD simulation.

Research and Projects 🔬

Dr. Huang has led and contributed to several key research projects, including the development of high-precision SPH methods for hydrate-bearing sediments and methane hydrate dissociation modeling. His work on GPU-accelerated meshless particle methods has advanced computational fluid dynamics capabilities.

Key Focus Areas 🌐

Smoothed Particle Hydrodynamics
Multi-phase Flow Modeling
Fluid-Structure Interactions
Wave Energy and Ocean Engineering
Marine Gas Hydrate Dynamics
Hybrid Computational Methods