Maryam Mousavifard | Civil Engineering | Research Excellence Award

Dr. Maryam Mousavifard | Civil Engineering | Research Excellence Award

Fasa University | Iran

Seyedeh Maryam Mousavi Fard is an accomplished civil and water engineering scholar specializing in transient flow analysis, leak detection in water systems, and the integration of machine learning into hydraulic and environmental applications. She serves as an Assistant Professor of Civil Engineering at Fasa University, where she has also held key academic leadership and advisory roles. Her research spans pressurized pipe transients, turbulence behavior, cavitation, sensor placement, optimization, water and wastewater treatment, and water quality monitoring, with strong expertise in both numerical modeling and data-driven approaches. She is proficient in MATLAB, Python, and major hydraulic and CFD software, and actively applies machine learning techniques to engineering and interdisciplinary problems. Her scholarly output includes influential journal articles across hydraulic engineering, environmental engineering, and food and bioprocess systems, reflecting broad interdisciplinary collaboration. Recognized for excellence in teaching, she is known for innovative, student-centered learning methods and strong academic mentorship at undergraduate and postgraduate levels.

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Featured Publications

Numerical simulation of turbulent pipe flow for water hammer

Journal of Fluids Engineering, 137(11), 111203

A review of one-dimensional unsteady friction models for transient pipe flow

Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi

Alexey Beskopylny | Structural Engineering | Best Researcher Award

Prof. Dr. Alexey Beskopylny | Structural Engineering | Best Researcher Award

Prof. Dr. Alexey Beskopylny | Don State Technical University | Russia

Dr. Alexey N. Beskopylny, Doctor of Technical Sciences and Professor, currently serves as Vice-Rector at Don State Technical University and works in the Department of Transport Systems. A distinguished researcher in civil and materials engineering, his work focuses on advanced construction materials, sustainable concrete technologies, and the integration of artificial intelligence in structural analysis. Over his prolific career, he has authored more than 190 scientific publications, with 151 indexed in the Web of Science, accumulating over 1,500 citations and an H-index of 20. Prof. Beskopylny’s recent research (2020–2025) emphasizes eco-friendly and high-performance concretes, geopolymer binders, nanomaterial reinforcement, and machine learning-based predictive modeling for structural behavior. He has pioneered studies on the use of waste materials—including glass, coffee grounds, banana leaf ash, and natural fibers such as hemp and flax—to enhance the mechanical, thermal, and ecological properties of concrete. His works on digital image correlation, ultrasonic diagnostics, and computer vision demonstrate innovative methods for assessing microstructure, defects, and performance in concrete and composite materials. A major theme in his publications is the optimization of concrete properties through numerical simulations, AI algorithms, and experimental validation, bridging sustainable construction with digital engineering. He has published extensively in leading journals such as Scientific Reports, Applied Sciences, Materials, Polymers, Buildings, and Case Studies in Construction Materials. Through his interdisciplinary approach, Prof. Beskopylny has significantly advanced the fields of civil engineering, materials science, and sustainable infrastructure. His contributions have provided new pathways for developing energy-efficient, durable, and environmentally responsible construction materials—positioning him as a leading voice in modern engineering innovation and green construction technologies.

Profiles: Scopus | Orcid | Research Gate

Featured Publications 

Zubarev, K. P., Razveeva, I., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., Mailyan, L. R., Shakhalieva, D. M., Chernil’nik, A., & Nikora, N. I. (2025). Predicting the strength of heavy concrete exposed to aggressive environmental influences by machine learning methods. Buildings, 15(21), 3998. https://doi.org/10.3390/buildings15213998

Özkılıç, Y. O., Kalkan, İ., Aksoylu, C., Madenci, E., Umiye, O. A., Althaqafi, E., Stel’makh, S. A., Shcherban’, E. M., & Beskopylny, A. N. (2025). Effect of stirrup spacing and recycled steel wires on the shear and energy dissipation of pultruded GFRP hybrid beams. Journal of Engineered Fibers and Fabrics. https://doi.org/10.1177/15589250251380680

Ecemiş, A. S., Yildizel, S. A., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., Aksoylu, C., Madenci, E., & Özkılıç, Y. O. (2025). Sustainable concrete with waste tire rubber and recycled steel fibers: Experimental insights and hybrid PINN–CatBoost prediction. Polymers, 17(21), 2910. https://doi.org/10.3390/polym17212910

Özkılıç, Y. O., Başaran, B., Aksoylu, C., Karalar, M., Zeybek, Ö., Althaqafi, E., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., & Umiye, O. A. (2025, October 21). Bending performance of reinforced concrete beams with partial waste glass aggregate replacement assessed by experimental, theoretical and digital image correlation analyses. Scientific Reports. https://doi.org/10.1038/s41598-025-20716-0

Stel’makh, S. A., Shcherban’, E. M., Beskopylny, A. N., Mailyan, L. R., Shilov, A. A., Razveeva, I., Oganesyan, S., Pogrebnyak, A., Chernil’nik, A., & Elshaeva, D. (2025). Enhancing the mechanical properties of sulfur-modified fly ash/metakaolin geopolymers with polypropylene fibers. Polymers, 17(15), 2119. https://doi.org/10.3390/polym17152119