U
Ujjwal Shrestha
Researcher at Mokpo National University
Publications - 13
Citations - 34
Ujjwal Shrestha is an academic researcher from Mokpo National University. The author has contributed to research in topics: Turbine & Impeller. The author has an hindex of 3, co-authored 10 publications receiving 19 citations.
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Journal ArticleDOI
A CFD-Based Shape Design Optimization Process of Fixed Flow Passages in a Francis Hydro Turbine
Ujjwal Shrestha,Young-Do Choi +1 more
TL;DR: In this article, a CFD-based shape design optimization process is proposed with response surface methodology (RSM) to improve the flow uniformity in the fixed flow passages of a Francis hydro turbine model.
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Establishment of Numerical Analysis Method of Pump-Turbine for Pumped Storage
Jun-Won Suh,Seung-Jun Kim,Jin-Hyuk Kim,Hyeon-Mo Yang,Won-Gu Joo,Tae-Gyu Hwang,Kanghee Lee,Ujjwal Shrestha,Zhenmu Chen,Hyunkyoo Cho,Young-Do Choi,Jungwan Park,Young-Seok Choi +12 more
TL;DR: In this paper, a three-dimensional steady-state Reynolds-averaged Navier-Stokes (RANS) equation was solved to evaluate the internal flow characteristics in the turbine mode.
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Improvement of flow behavior in the spiral casing of Francis hydro turbine model by shape optimization
Ujjwal Shrestha,Young-Do Choi +1 more
TL;DR: In this paper, the shape of a spiral casing is optimized based on a steady-state flow analysis and numerical optimization is performed using response surface methodology (RSM) and multiobjective genetic algorithm (MOGA).
Journal ArticleDOI
Numerical studies on sediment erosion due to sediment characteristics in Francis hydro turbine
TL;DR: In this article, the effect of sediment erosion on the turbine blades of the runner of a hydropower turbine has been investigated and a modification such as a change in thickness, blade angle and coating is proposed.
Journal ArticleDOI
Suppression of flow instabilities in the stay vane passage of the Francis hydro turbine model by design optimization
Ujjwal Shrestha,Young-Do Choi +1 more
TL;DR: In this article, the authors used a multi-objective genetic algorithm to find the optimal shape of the stay vane to improve the flow behavior around the stay-vane.