Bhagyashri Patgiri – Fluid Mechanics­­­­­­­­ – Best Researcher Award

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Ms. Bhagyashri Patgiri - Fluid Mechanics­­­­­­­­ - Best Researcher Award 

Cotton University - India 

Author Profile

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Orcid

🎓 Early Academic Pursuits

Ms. Bhagyashri Patgiri began her academic journey with a strong foundation in mathematics, eventually earning her M.Sc. from the National Institute of Technology, Meghalaya, in 2019. Her academic rigor and commitment to excellence established the groundwork for her advanced studies, leading her to the Department of Mathematics at Cotton University, where she now pursues her research as a dedicated scholar.

💼 Professional Endeavors

Currently a Research Scholar at Cotton University, Ms. Patgiri has focused her professional endeavors on Computational Fluid Dynamics, an area where she has made significant advancements. Her work, particularly in computational heat and mass transfer involving nanofluids, reflects her dedication to solving complex problems in fluid mechanics. Through these efforts, she has become a recognized contributor to international research, collaborating with scholars and engaging in projects that push the boundaries of this field.

🔬 Contributions and Research Focus

Ms. Patgiri’s primary research focus is on computational heat and mass transfer, particularly within the scope of advanced nanofluids. Her contributions include several publications in highly respected international journals, such as Materials Today Communication, Numerical Heat Transfer Part A: Application, and Journal of Taibah University for Science. Her work advances the understanding of fluid mechanics and computational modeling, especially in the context of nanofluid applications. Additionally, her experience as a reviewer for prominent journals, including Numerical Heat Transfer Part B: Fundamentals and Journal of Thermal Engineering, highlights her expertise and influence in the academic community.

🌍 Impact and Influence

Ms. Patgiri’s influence within the field of fluid mechanics is reflected in her published research, which is widely recognized and frequently cited by peers. Her findings on computational heat and mass transfer have implications for both academic and practical applications, particularly in engineering, energy management, and environmental sciences. Her role as a reviewer for numerous international journals further solidifies her status as a respected figure within the research community, where she contributes to maintaining the quality and advancement of research in computational fluid dynamics.

🏆Academic Cites

The impact of Ms. Patgiri’s research is evidenced by her extensive list of citations across international journals. Her publications are frequently referenced in studies on computational fluid dynamics and fluid mechanics, underlining her contributions to this evolving field. Her work serves as a resource for researchers seeking advanced insights into computational techniques and nanofluid applications.

🌟 Legacy and Future Contributions

As she continues her research, Ms. Bhagyashri Patgiri is expected to make further advancements in computational heat and mass transfer, particularly with evolving nanofluid technologies. Her future contributions are likely to drive new applications in fluid mechanics, shaping the way complex fluid systems are modeled and understood. Her legacy will include her groundbreaking work in fluid mechanics, her commitment to academic excellence, and her mentorship of upcoming researchers.

📝Fluid Mechanics

Ms. Patgiri’s research in fluid mechanics has established her as a key contributor to computational modeling techniques, particularly with her work on fluid mechanics applications in heat and mass transfer involving nanofluids. Her future in fluid mechanics holds promise for pioneering insights and technological advancements, continuing to impact both academia and industry.

Notable Publication

📝Computational study of Jeffrey Hybrid nanofluid flow over a non-uniformly heated permeable exponentially stretching surface with Arrhenius activation energy and inclined magnetic field

Authors: N. Sarma, A. Paul, B. Patgiri

Journal: Hybrid Advances

Year: 2024

Citations: 5

📝Numerical assessment of viscoelastic tetra hybrid nanofluid flow across a stretchable rotatory disk under the Soret and Dufour aspects

Authors: B. Patgiri, A. Paul, N. Sarma

Journal: Multidiscipline Modeling in Materials and Structures

Year: 2024

Citations: 1

📝Transformer oil-based Casson ternary hybrid nanofluid flow configured by a porous rotating disk with hall current

Authors: A. Paul, B. Patgiri, N. Sarma

Journal: ZAMM Zeitschrift für Angewandte Mathematik und Mechanik

Year: 2024

Citations: 8

📝A numerical investigation of the polyethylene glycol-based tetra hybrid nanofluid flow over a stretched porous rotatory disk

Authors: B. Patgiri, A. Paul

Journal: ZAMM Zeitschrift für Angewandte Mathematik und Mechanik

Year: 2024

Citations: 0

📝Flow and thermal characteristics of diathermic oil-based tri-hybrid nanofluid

Authors: B. Patgiri, A. Paul

Book: Nanofluids Technology for Thermal Sciences and Engineering Research, Development, and Applications

Year: 2024

Citations: 0

Wei Huang – Fluid Mechanics­­­­­­­­ – Best Researcher Award

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Dr. Wei Huang - Fluid Mechanics­­­­­­­­ - Best Researcher Award 

Gatech - United States 

Author Profile

ORCID

🎓 Early Academic Pursuits

Dr. Wei Huang began his academic career with a strong focus on materials physics, earning his BA from the University of Science and Technology in Beijing (USTB), where he was recognized with the Special Awarded Prize for being in the top 0.5% of his class. His passion for materials science led him to pursue a Master’s degree at the University of California, Berkeley, where he gained significant recognition, including the Fung Excellence Scholarship and being featured as a Graduate of Distinction. His academic path was shaped by a deep interest in understanding the physics behind material properties and advanced manufacturing processes, culminating in his current role as a PhD candidate in Mechanical Engineering at the Georgia Institute of Technology.

💼 Professional Endeavors

In his professional endeavors, Dr. Wei Huang has focused primarily on additive manufacturing, materials properties, and microstructure evolution. His work at Georgia Tech, under the supervision of Dr. Steven Y. Liang, has centered on the analytical modeling of multi-phase materials and the microstructural evolution that affects grain size, texture, defects, and residual stress. This research has been critical in advancing the understanding of material behavior in additive manufacturing processes. He has also led projects investigating the intersection of big data, artificial intelligence, and materials research at UC Berkeley, reflecting his forward-thinking approach to material science.

🔬 Contributions and Research Focus

Dr. Huang’s contributions to the field of additive manufacturing are centered on the fluid mechanics of materials and the intricate relationship between microstructure evolution and material properties. His analytical models provide new insights into grain size prediction, texture formation, and defect management during manufacturing processes such as laser powder bed fusion. His research has been instrumental in optimizing manufacturing techniques to enhance the performance and reliability of materials in various industries. His work on the use of big data and AI for materials discovery further reflects his innovative approach to solving complex material science problems.

🌍 Impact and Influence

Dr. Wei Huang’s research has had a significant impact on both academia and industry. His work on fluid mechanics and its role in material behavior during additive manufacturing has been widely recognized and presented at prominent conferences such as the Annual International Solid Freeform Fabrication Symposium and the International Mechanical Engineering Congress & Exposition (IMECE). His contributions have influenced the development of more efficient and precise manufacturing processes, leading to advancements in industries that rely heavily on materials science. Additionally, his use of machine learning and AI in material research has opened new avenues for innovation.

🏆Academic Cites

Dr. Huang’s research has garnered attention and citations in top academic journals and conferences. His analytical models of microstructure evolution in additive manufacturing, particularly his work on fluid mechanics in the context of materials behavior, have been widely cited by other researchers. His projects have provided key insights that are foundational to ongoing research in both materials science and manufacturing processes.

🌟 Legacy and Future Contributions

Looking to the future, Dr. Wei Huang is poised to continue making groundbreaking contributions to the fields of additive manufacturing and materials science. His legacy will likely be defined by his pioneering work on the microstructural aspects of materials and their relationship with fluid mechanics, as well as his innovative integration of AI and big data into materials research. As he continues to collaborate with experts and lead research projects, his influence on the development of next-generation manufacturing techniques and materials properties will undoubtedly grow.

📝Fluid Mechanics

Dr. Wei Huang’s research has notably explored the interplay between fluid mechanics and materials properties in additive manufacturing. His contributions in this area have been instrumental in developing new models that improve the prediction and control of grain size and texture during the manufacturing process. The application of fluid mechanics in his research has helped optimize material performance, reducing defects and enhancing the efficiency of manufacturing techniques.

Notable Publication

📝Analytical Prediction of Multi-Phase Texture in Laser Powder Bed Fusion

Journal: Journal of Manufacturing and Materials Processing

Publication Date: October 17, 2024

Contributors: Wei Huang, Mike Standish, Wenjia Wang, Jinqiang Ning, Linger Cai, Ruoqi Gao, Hamid Garmestani, Steven Y. Liang

📝Analytical Model of Quantitative Texture Prediction Considering Heat Transfer Based on Single-Phase Material in Laser Powder Bed Fusion

Journal: Journal of Manufacturing and Materials Processing

Publication Date: March 30, 2024

Contributors: Wei Huang, Wenjia Wang, Jinqiang Ning, Hamid Garmestani, Steven Y. Liang