جست‌وجوی استاد و پژوهشگر

• Computational Fluid Dynamics (CFD)
• Large-Eddy Simulation (LES)
• Aero-acoustics
• +۵ مورد دیگر

Prof. Dr.-Ing. Wolfgang Schröder is a full professor at RWTH Aachen University and currently serves as Dean of the Faculty of Mechanical Engineering . In addition, he is Director of the Institute of Fluid Mechanics and Aerodynamics , a member of the Steering Committee of the Profile Area Modeling & Simulation Sciences , and RWTH’s representative in the Scientific and Technical Council (WTR) of the Forschungszentrum Jülich. His professional addresses are Wüllnerstraße 5a, 52062 Aachen and Eilfschornsteinstraße 18, 52062 Aachen , reachable at office@aia.rwth-aachen.de and dekan@fb4.rwth-aachen.de . His research portfolio spans computational fluid dynamics , large-eddy simulation , aero-acoustics , turbulent boundary-layer control , drag-reduction technologies , high-performance computing for multi-phase flows, and biomedical flow modeling . Recent work emphasizes: Multi-fidelity and surrogate modeling for active flow control and drag reduction. Advanced LES and hybrid RANS/LES methods for complex internal and external flows. Coupled CFD/CAA approaches to predict and mitigate aero-acoustic noise from airframes, landing gears, and distributed propellers. High-resolution simulations of gas-liquid and electrochemical flows in engineering and biomedical contexts. Across more than 80 peer-reviewed contributions since 2021, a clear trend emerges toward physics-based machine learning , real-time optimization , and exascale-ready algorithms that integrate experimental data (PIV, DLS) with massively parallel simulations. Scientific Awards & Honors : No specific awards are enumerated in the supplied text; however, his continuous leadership roles (Dean, Institute Director, WTR representative) indicate sustained recognition within the academic community. Advising & Funding : While individual student names are not listed, Prof. Schröder heads a large research group responsible for numerous doctoral and master’s theses. Projects are supported by German federal programs, EU Horizon initiatives, and industrial partnerships with aerospace and automotive sectors. Laboratories & Teams : He directs the Institute of Fluid Mechanics and Aerodynamics (AIA), operates within the Center for Computational Engineering Science (CCES), and leverages RWTH’s high-performance computing clusters for large-scale simulations.

Yujing Duمشاهده پروفایل

استادیار

• Sustainable energy recovery & utilization
• Geothermal energy systems
• Geological carbon sequestration
• +۳ مورد دیگر

Yujing Du serves as Assistant Professor of Petroleum Engineering within the College of Engineering & Natural Sciences at The University of Tulsa, joining the faculty in 2025 after completing a postdoctoral fellowship in applied physics at Harvard University. Her research bridges petroleum engineering with sustainable energy systems through experimental and computational approaches. Her academic foundation includes: Ph.D. in Petroleum and Geosystems Engineering from The University of Texas at Austin (2021) M.S. in Petroleum and Geosystems Engineering from The University of Texas at Austin (2016) B.S. in Thermal Engineering (now Energy and Power Engineering) from Tsinghua University, Beijing, China (2014) Dr. Du's research program focuses on sustainable energy recovery mechanisms, with particular expertise in geothermal energy systems, geological carbon sequestration, and fluid-driven fracture dynamics. Her experimental work examines multiphase flow in porous and fractured media, emphasizing interfacial phenomena that govern fluid displacement processes critical to energy extraction and storage. This research employs advanced microfluidic techniques to visualize and quantify subsurface flow at pore-scale resolution. Analysis of her 15 most recent publications (2016-2023) reveals consistent emphasis on enhanced oil recovery methods, particularly low-salinity water flooding, surfactant flooding, and fracture-assisted recovery. Her work demonstrates how time-dependent mechanisms, wettability alteration, and fracture connectivity influence hydrocarbon sweep efficiency in tight reservoirs. Key contributions include identifying non-monotonic displacement patterns during low-salinity flooding and quantifying viscoelastic effects on residual oil saturation reduction. No scientific awards or major honors are documented in the available materials. Regarding academic mentoring, there is no information about graduate student advisement or research team leadership. Similarly, details about grant funding, laboratory facilities, or collaborative research initiatives are not provided in the source text.

Aaditya Khanalمشاهده پروفایل

استادیار

• Reservoir Simulation
• Carbon Sequestration
• Hydrogen Storage
• +۴ مورد دیگر

Aaditya Khanal, Ph.D., is an Assistant Professor of Chemical Engineering & Petroleum Engineering at The University of Tulsa's College of Engineering & Computer Science. His research focuses on modeling fluid flow in porous media with applications to energy extraction and climate change mitigation. Dr. Khanal's research interests include: CO2 sequestration in saline aquifers Underground hydrogen storage Hydrocarbon production forecasting for unconventional reservoirs Phase behavior modeling of hydrocarbons Machine learning applications to solve complex engineering problems His research methodology combines both numerical simulations and experimental approaches to address critical challenges in energy transition and sustainable resource management. Dr. Khanal has published extensively in the areas of carbon sequestration, hydrogen storage, and machine learning applications in reservoir engineering, with a notable focus on recent advancements in 2024-2025 publications that address critical challenges in underground energy storage and carbon management. Dr. Khanal's scholarly work demonstrates a strong interdisciplinary approach, bridging petroleum engineering, chemical engineering, and data science to develop innovative solutions for energy transition challenges. His recent publications show particular emphasis on hydrogen storage technologies, CO2 mineralization processes, and the application of machine learning to reservoir characterization.

Seyedshahabaddin Mirjaliliمشاهده پروفایل

استادیار

• Fluid Mechanics
• Scientific Computing
• Machine Learning
• +۷ مورد دیگر

Seyedshahabaddin Mirjalili is an Assistant Professor in Fluid Mechanics at the Department of Engineering Mechanics, KTH Royal Institute of Technology, Sweden. He is affiliated with the Swedish e-Science Research Center (SeRC) and Digital Futures at KTH. Education: BS in Mechanical Engineering from Sharif University of Technology, MS and PhD in Mechanical Engineering from Stanford University. Former Positions: Research Associate (2022–2024) and Postdoctoral Fellow (2019–2022) at Stanford University. His research spans fluid mechanics, scientific computing, and machine learning, focusing on computational methods for multi-physics, multi-phase, and multi-scale flows. Applications include propulsion systems, additive manufacturing, biophysical systems, and environmental flows. He develops conservative phase field models, energy-preserving numerical schemes, and physics-informed machine learning frameworks for high-fidelity simulations and reduced-order modeling. Recent work involves inverse asymptotic treatments for discontinuities, microbubble dynamics in breaking waves, and energy-conserving momentum transport in two-phase flows. His methods emphasize boundedness, conservation properties, and reduced spurious currents in numerical simulations. Scientific Awards: Gallery of Fluid Motion Award (2018) from the American Physical Society Division of Fluid Dynamics He contributes to software initiatives under SeRC and collaborates on high-performance computing (HPC) applications. His teaching includes courses like Particle Dynamics (SG1115).

Yasser Safaمشاهده پروفایل

پژوهشگر

• Computational Mechanics
• Multiphysics Modeling
• Solid Mechanics
• +۷ مورد دیگر

Dr. Yasser Safa is a Researcher at the Institute of Computational Physics (ICP) within the School of Engineering at Zurich University of Applied Sciences (ZHAW), leading the Multiphysics Modeling and Imaging research group. His work focuses on advanced computational techniques for solving complex engineering problems across energy systems, materials science, and mechanical design. His educational background includes a PhD from École polytechnique fédérale de Lausanne (EPFL) in 2005, where his thesis addressed numerical simulations of thermo-magneto-hydrodynamic phenomena in aluminum reduction cells. This foundation in coupled physics has driven his subsequent research in multiphysics modeling. Dr. Safa's research spans computational mechanics, solid mechanics (particularly nonlinear elasticity and buckling), corrosion engineering, additive manufacturing, metamaterials, and energy systems including fuel cells and wind power. His methodology emphasizes developing validated numerical models for real-world engineering challenges, often involving thin-film mechanics, material degradation, and structural integrity under extreme conditions. Recent work demonstrates increasing focus on renewable energy systems and advanced manufacturing processes. Analysis of his 15 most recent publications reveals strong thematic continuity in computational mechanics applied to energy and materials, with growing emphasis on wind energy systems and corrosion phenomena. His work consistently bridges theoretical mechanics with industrial applications, particularly in micro-fabrication and energy conversion technologies. He has secured and led multiple research projects including ongoing work on corrosion of multiphasic alloys and completed projects on airborne wind power systems, metamaterial wave guides, and additive manufacturing. These projects demonstrate his ability to translate computational expertise into practical engineering solutions across diverse domains. As part of ZHAW's ICP research group, Dr. Safa contributes to developing advanced computational tools for imaging and modeling physical systems, maintaining strong industry connections particularly in energy technology sectors. His current work continues to address critical challenges in material durability and energy system design through sophisticated numerical approaches.

Yan Delauréمشاهده پروفایل

دانشیار

• Multiphase Flow
• Fluid Mechanics
• Computational Fluid Dynamics
• +۴ مورد دیگر

Dr. Yan Delauré is an Associate Professor in Fluid Mechanics at Dublin City University's School of Mechanical and Manufacturing Engineering. He holds a PhD from University College Cork (2001), a Diplôme d’Ingénieur in Aeronautical Engineering from ESTACA, France, and an M.Sc. in Marine Resources Development and Protection from Heriot Watt University, Scotland. Prior to DCU, he worked at the Hydraulics and Maritime Research Centre in Cork for five years and held a post-doctoral position at Trinity College Dublin. His educational background includes: PhD from University College Cork (2001) Diplôme d’Ingénieur in Aeronautical Engineering from ESTACA, France M.Sc. in Marine Resources Development and Protection from Heriot Watt University, Scotland Dr. Delauré's primary research focuses on multiphase flows for applications in process aeration and pumping of incompressible single-phase and solid-laden flows. He has developed in-house flow simulation codes and utilized commercial and open-source solvers for high-performance computations. His experimental work involves non-invasive laser-based visualization techniques including three-component planar PIV, Shadow Sizing, and Digital Image Correlation, alongside hydraulic flow rigs for pumping and mixing studies. Dr. Delauré has secured funding from Science Foundation Ireland, the Irish Research Council, Enterprise Ireland, and EU FP7 and Horizon 2020 programmes. He currently leads an Enterprise Ireland co-funded industrial project and serves as Workpackage leader and DCU principal investigator on an EU Horizon 2020 Research Innovation Action, having established a dedicated research group for multiphase flow characterization. He has developed specialized experimental facilities including laser diagnostics systems and hydraulic flow rigs to support dual computational and experimental research in fluid mechanics.

• Fluid Dynamics
• Heat Transfer
• Computational Modeling
• +۳ مورد دیگر

Herr Irrenfried Christoph serves as an Associate Professor at the Department of Fluid Mechanics and Heat Transfer within Graz University of Technology. His research focuses on fluid dynamics, heat transfer, and computational modeling, with applications in natural ventilation, aerodynamics, and turbulent flow analysis. University: Graz University of Technology Department: Fluid Mechanics and Heat Transfer Research Trends: His recent publications emphasize wind-driven ventilation systems, centrifugal polymer separation, and turbulence modeling in high Prandtl number flows. Key methodologies include Direct Numerical Simulations (DNS), computational fluid dynamics (CFD), and experimental validation. Scientific Awards: No awards or honors were explicitly mentioned in the provided texts.

Amarendra Kumar Singhمشاهده پروفایل

استاد

• Steel Refining and Casting
• Extractive Metallurgy
• Integrated Computational Materials Engineering
• +۴ مورد دیگر

Professor Amarendra Kumar Singh is a distinguished faculty member in the Department of Materials Science and Engineering at Indian Institute of Technology Kanpur, specializing in process modeling and simulation of metallurgical processes. With over three decades of academic and industrial experience, he has established himself as a leading expert in steel refining, solidification processing, and computational materials engineering. PhD, IIT Kanpur, 2003 PG, IIT Kanpur, 1990 UG, IIT Kanpur, 1987 Dr. Singh's research focuses on Steel Refining and Casting, Extractive Metallurgy, Integrated Computational Materials Engineering, Solidification Processing, and Sustainable Manufacturing. His work bridges fundamental scientific principles with practical industrial applications, particularly in the steel industry. He employs advanced computational techniques to model complex metallurgical processes, enabling optimization of manufacturing parameters and improvement of material quality. His research has significant implications for energy efficiency, environmental sustainability, and cost reduction in metal production. His publication record demonstrates a consistent trajectory of research excellence, with a focus on mathematical modeling of steelmaking processes, solidification phenomena, and computational approaches to materials engineering. The publications span from fundamental studies of macrosegregation and solidification to applied research on ladle refining, electric arc furnaces, and inclusion engineering in steel. Recent work shows increasing integration of data science approaches with traditional materials modeling. Metallurgist of the Year Award, Ministry of Steel, Government of India, 2014 Distinguished Scientist Award, TCS, 2011 AICTE-INAE Distinguished Visiting Professor at IIT Bombay (2009-2012) Multiple Best Paper Awards from Indian Institute of Metals As a faculty member at IIT Kanpur, Dr. Singh has contributed significantly to academic programs, mentoring students, and advancing research in materials engineering. His professional affiliations with The Minerals, Metals and Materials Society (TMS), Indian Institute of Metals (IIM), Materials Research Society of India (MRSI), and Indian Society of Heat & Mass Transfer (ISHMT) reflect his standing in the academic community. His research has practical applications in industrial settings, particularly in the steel manufacturing sector where process optimization is critical for competitiveness.

• Fluid Dynamics
• Heat Transfer
• Thermal Sciences
• +۶ مورد دیگر

Professor K. Muralidhar of the Department of Mechanical Engineering at Indian Institute of Technology Kanpur specializes in fluid dynamics, thermal sciences, and optical imaging techniques. With over 35 years of academic leadership, his work bridges experimental and computational approaches in transport phenomena. PhD from University of Delaware (1985) 20+ Doctoral students supervised 500+ Publications across 13 research areas Fellow of ASTFE, NAS, and INAE His key research domains include: Drop dynamics on hydrophobic surfaces Heat transfer in porous media Crystal growth visualization Biofluid mechanics in vascular systems Advanced tomographic imaging Cryogenic flow modeling Recent work focuses on CO2 sequestration , solar desalination , and non-invasive medical diagnostics , with significant contributions to Physics of Fluids and International Journal of Heat and Mass Transfer . Scientific awards highlight his global recognition: 2019: Fellow-ASTFE 2014: Keynote speaker, International Heat Transfer Conference 2006: INAE Fellowship 1995: Institution of Engineers Prize 1981: IIT Madras Institute Medal Pioneering optical measurement techniques for convection and phase change processes, he has developed novel approaches in schlieren tomography, interferometry, and digital holography. His laboratory's patent portfolio includes medical devices and fluid control systems.

Partha S. Ghoshdastidarمشاهده پروفایل

استاد

• Computational Heat Transfer
• Rotary Kiln modelling
• Non-Newtonian Flow and Heat Transfer
• +۴ مورد دیگر

Partha S. Ghoshdastidar is a Professor (Higher Academic Grade) in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur. With over three decades of academic experience, he has established himself as a leading expert in Computational Heat Transfer, specializing in rotary kiln modeling, non-Newtonian flow, boiling heat transfer, electronic cooling, and nanofluid heat transfer. Dr. Ghoshdastidar earned his PhD from the University of South Carolina, Columbia, USA in 1984, with a thesis on 'Heat Transfer in a Rotary Kiln During Incineration of Solid Waste' under Prof. C. A. Rhodes. His academic career at IIT Kanpur began as Visiting Faculty in 1984, progressing through Lecturer, Assistant Professor, Associate Professor, and Professor positions, currently holding the title of Professor (Higher Academic Grade) since August 2014. He also served as Guest Professor at Universität Hannover, Germany (2000-2001). His research focuses on computational approaches to heat transfer problems, particularly using the Coupled Map Lattice Method (CML) for modeling complex thermal phenomena. Current research areas include numerical simulation of nanofluids flow, heat transfer modeling in rotary kilns, electronic equipment cooling, LED street lighting heat sink design, and pool boiling simulation of nanofluids. Notable achievements include the Institution Prize of the Institution of Engineers (India), multiple Certificates of Merit, election as Fellow of the World Innovation Foundation, U.K. (2002), and the 2012 A. M. Strickland Prize from the Institution of Mechanical Engineers, U.K. He serves as Associate Editor for HEAT TRANSFER RESEARCH and Editorial Board Member for Engineering Science and Technology. His extensive teaching portfolio includes undergraduate and postgraduate courses in Heat Transfer, Fluid Mechanics, Numerical Methods, and specialized topics. He has mentored numerous students across BTech, MTech, and PhD programs, with current research students including Ashish Agrawal, Dileep V. Nair, and Rajat Dhingra. His sponsored research projects, funded by DST and CSIR, demonstrate the practical applications of his theoretical work in industrial settings.

Hae Yong Jeongمشاهده پروفایل

استاد

• Nuclear Reactor Safety
• Thermal Hydraulics
• Liquid Metal-cooled Reactors
• +۳ مورد دیگر

Hae Yong Jeong is a Professor at the Department of Quantum and Nuclear Engineering, Sejong University, since April 2013. He holds a Ph.D. in Nuclear Engineering from KAIST (1996), an M.S. in Nuclear Engineering from KAIST (1991), and a B.S. in Nuclear Engineering from Seoul National University (1989). Professor Jeong's research focuses on future nuclear system innovation, safety analysis , and passive shutdown systems for sodium-cooled and molten salt-cooled reactors. He also explores sustainable energy strategies integrating nuclear systems. His recent work emphasizes CFD simulations for severe accident scenarios like steam explosions, corium jet breakup, and debris bed formation, alongside machine learning integration for predictive modeling in reactor safety. As head of the NuRESTs Lab , he leads projects on reactor thermal-hydraulic safety and sustainable reactor design . He has contributed to international benchmarks (e.g., Phenix reactor) and developed system code models (MARS-LMR/KS) validated through experiments. Patents include passive cooling systems, heat pipe reactors, and particle fuel designs. He teaches Doctoral Dissertation Research and Master's Thesis Research , mentoring graduate students in nuclear engineering.

Maria Tenjeمشاهده پروفایل

استاد

• Biomedical Engineering
• Microsystems Engineering
• Microfluidics
• +۵ مورد دیگر

Maria Tenje is a Professor of Microsystems Engineering at the Department of Materials Science , Uppsala University. Since July 2021, she has served as Director of the Department of Medical Technology. She leads the EMBLA research group , focusing on miniaturized systems for life science applications through advanced micro- and nanofabrication methods integrated into microfluidic platforms. Research Interests : Her work centers on biomedical engineering , microfluidics , organ-on-chip technology , and acoustophoresis . Key areas include droplet-based microfluidics, biomaterial evaluation, and developing cell culture systems with enhanced physiological relevance. Recent publications highlight innovations in 3D acoustic mixing , antibiotic resistance detection , and microfluidic platforms for single-cell respiration . Publications Trends : Her 15 most recent articles (2021-2025) span droplet microfluidics, organ-on-chip systems, and acoustic particle manipulation. These studies explore biomaterial biocompatibility , cellular response modeling , and microscale diagnostic tools , often in collaboration with interdisciplinary teams.

• Hydrogen Safety
• Computational Fluid Dynamics
• Hazard Analysis
• +۳ مورد دیگر

Dr. Donatella Cirrone is a Researcher in Safety Engineering at the Belfast School of Architecture & the Built Environment , Ulster University. Her work focuses on hydrogen safety, computational fluid dynamics (CFD), and hazard modeling for energy systems. Role: Research Associate in Safety Engineering Email: d.cirrone@ulster.ac.uk Research Outputs: 15+ publications (2016-2025) Her research explores hydrogen storage risks , BLEVE dynamics , and cryogenic temperature hazards . Key methodologies include CFD simulations and multiphase flow analysis. Recent work trends highlight liquid hydrogen transfer safety , blast wave modeling , and multi-peak pressure structures in storage tank failures. These align with UN Sustainable Development Goals for clean energy and sustainable infrastructure. Scientific awards include: Young Scientist Award 2022 Best Paper Award (2025) Early Career Conference Grant (2019) Best Presentation Award (2017)

George S. Constantinescuمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Environmental Engineering
• Fluid Mechanics
• +۷ مورد دیگر

George S. Constantinescu is a Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering, serving as Faculty Research Engineer at IIHR—Hydroscience and Engineering and affiliated with the Iowa Flood Center since joining the institution in 2004. His work integrates advanced computational methods with practical environmental and hydraulic engineering challenges. Education: PhD in Civil and Environmental Engineering, University of Iowa, 1997 MS in Civil and Environmental Engineering, Civil Engineering Institute, Bucharest, Romania, 1992 BS in Civil and Environmental Engineering, Civil Engineering Institute, Bucharest, Romania, 1991 Professor Constantinescu's research focuses on computational fluid dynamics for environmental systems, specializing in turbulence modeling, large-eddy and detached-eddy simulation techniques for multiphase flows, and applications in coastal engineering and water resources management. He leverages parallel computing to advance predictive capabilities in hydraulic and environmental fluid mechanics, addressing critical challenges in flood modeling and sustainable water infrastructure. Scientific Awards: No scientific awards were specified in the source text. Advising and Grants: Information regarding graduate students, research grants, or sponsored projects was not provided in the available documentation. Labs and Teams: He leads the Constantinescu Research Group and contributes to interdisciplinary initiatives at IIHR—Hydroscience and Engineering and the Iowa Flood Center, where his team develops high-fidelity simulation frameworks for environmental fluid dynamics and flood prediction systems.

• Compressible Flows
• Numerical Modeling
• Smoothed Particle Hydrodynamics
• +۷ مورد دیگر

Stefan Adami is an Adjunct Professor at the Institute of Aerodynamics and Fluid Mechanics, Technical University of Munich (TUM), where he leads the 'Nanoshock' research group. He holds a Ph.D. in Mechanical Engineering from TUM and was awarded habilitation in 2022, followed by appointment as Privatdozent in 2023. His academic career at TUM includes roles as research associate, Akademischer Rat, and group leader. Research Interests: Compressible and multiphase flows Numerical modeling and simulation Smoothed Particle Hydrodynamics (SPH) High-speed aerodynamics and shock wave dynamics Applications in additive manufacturing and biomedical fluid mechanics His recent research employs advanced solvers like ALPACA for high-resolution simulations of bubble dynamics, shock interactions, and interfacial flows. He has contributed to modeling in laser-based 3D printing and cavitation-based drug delivery systems. Recent Publication Trends: His 2023–2025 publications emphasize compressible multiphase flows, high-order numerical schemes (WENO-THINC), and applications in materials processing and biomedical engineering. He frequently collaborates on solver development and benchmarking, including large-scale datasets for Riemann problems. Teaching: Lecturer for 'Numerical Methods for Conservation Laws' (Winter Semester) Lecturer for 'Turbulent Flows' (Summer Semester) Previously served as Teaching Assistant for Continuum Mechanics and Computational Solid and Fluid Dynamics Research Leadership: Leader of the 'Nanoshock' research group since 2015 Key contributor to the development of the ALPACA solver for compressible multiphase flows Active in interdisciplinary projects involving fluid-structure interaction and industrial applications