جست‌وجوی استاد و پژوهشگر

• Radiative heat transfer
• Computational thermal sciences
• Turbulence-radiation interaction
• +۴ مورد دیگر

Pedro Jorge Martins Coelho is a Professor in the Mechanical Engineering Department at Instituto Superior Técnico, University of Lisbon, Portugal. His academic career spans several decades with a focus on advanced thermal sciences and computational methods. His research has significantly contributed to the understanding of radiative heat transfer phenomena in complex systems. Dr. Coelho's educational background includes a Ph.D. in Mechanical Engineering, which has provided the foundation for his extensive research in thermal sciences. His work demonstrates a strong theoretical foundation combined with practical applications across various engineering domains. His primary research interests encompass radiative heat transfer, turbulence-radiation interaction, combustion modeling, and numerical methods for thermal systems. Recent work has expanded into biomedical applications of thermal radiation, particularly in laser-tissue interactions for cancer detection and treatment. His publications reveal a consistent focus on developing and refining computational methods for solving complex heat transfer problems, with particular emphasis on the radiative transfer equation in various media and geometries. Analysis of his recent publications shows a clear evolution toward more complex and interdisciplinary applications, including biomedical thermal applications, advanced turbulence modeling, and thermal management of electrical systems. His work consistently bridges fundamental theoretical developments with practical engineering applications, particularly in combustion systems, energy recovery, and thermal management. Dr. Coelho has served on editorial boards for prestigious journals including Heat Transfer Research, Computational Thermal Sciences, and International Journal of Energy for a Clean Environment, demonstrating his standing in the thermal sciences community. His research collaborations span numerous institutions and researchers worldwide, as evidenced by his extensive publication record with various co-authors across different countries. He has also been involved in conference organization, serving as Associate Editor for major international heat transfer conferences.

• Computational Fluid Dynamics
• Turbulence Modelling
• Multiphase Flows
• +۶ مورد دیگر

Dr. Zhihua Xie is a Reader in the School of Engineering at Cardiff University. He holds a PhD in Computational Fluid Dynamics from the University of Leeds, funded by the Marie Curie EST Fellowship. His career includes research roles at Cardiff University and Imperial College London. His research focuses on computational fluid dynamics, multiphase flows, and environmental fluid mechanics, supported by grants from EPSRC, Royal Society, and others. He has been awarded the Alexander von Humboldt Research Fellowship and multiple Baker Medals. Education: BEng in Environmental Engineering (Dalian Maritime University, 2003), Postgraduate study in Hydrodynamics (Dalian Maritime University, 2006), PhD in CFD (University of Leeds, 2010). Research interests span development and application of CFD codes for multiphase flows, turbulence modelling, and numerical methods. He is actively involved in editorial boards and professional societies like IAHR and ISOPE. Key contributions include adaptive moment-of-fluid methods, Cartesian cut-cell techniques, and large-eddy simulations. Awards include the Alexander von Humboldt Fellowship (2023), Baker Medal (2021, 2022), and EPSRC funding for wave energy converter modeling (EP/V040235/1). Grants and projects include ARCHER2 eCSE, Newton Advanced Fellowship, and collaborations on coastal engineering and offshore energy systems. His work addresses challenges in wave-structure interaction, fluid-structure dynamics, and environmental hydraulics.

Susheel Singhمشاهده پروفایل

استادیار

• Computational Fluid Dynamics
• Turbulence Modelling (RANS/LES)
• Thermal Engineering
• +۱ مورد دیگر

Susheel Singh, Ph.D. is an Assistant Professor in the Department of Aerospace and Mechanical Engineering at Saint Louis University's School of Science and Engineering. His research spans computational fluid dynamics, turbulence modeling, thermal engineering, and data science applications in engineering. Education: Ph.D. in Mechanical Engineering from Louisiana State University Education: B.S. in Mechanical Engineering from National Institute of Technology, Rourkela, India His work focuses on advanced numerical modeling of cooling systems, combining traditional engineering analysis with machine learning techniques. Recent publications highlight his expertise in: Jet impingement heat transfer Pin-fin configuration optimization Large Eddy Simulation (LES) methods Machine learning integration in thermal systems Before joining Saint Louis University, Singh worked as a data scientist in Detroit applying ML/DL to healthcare and energy sectors, and contributed to the Mid-Barataria Sediment Diversion project as an advanced numerical modeler.

• Computational Fluid Dynamics
• Spectral Element Method
• Large Eddy Simulation
• +۳ مورد دیگر

Paul Fischer is a Professor at the University of Illinois, holding dual appointments in the Siebel School of Computing and Data Science and the Mechanical Science and Engineering department. His research focuses on advanced numerical methods for fluid dynamics, particularly leveraging spectral element techniques and high-performance computing. He is a core contributor to the Nek5000/NekRS computational frameworks. Recent work emphasizes turbulence modeling, exascale CFD simulations, and multiphase flow dynamics in complex systems like pebble bed reactors. His research interests span spectral methods, large eddy simulation (LES), direct numerical simulation (DNS), and parallel computing architectures. Key projects include developing scalable algorithms for Reynolds-averaged Navier-Stokes (RANS) models and exploring non-conforming domain decomposition approaches for reacting flows. His contributions bridge computational methodology and engineering applications, with a focus on exascale-ready solutions. Publications from 2024-2025 highlight advancements in energy-efficient CFD simulations, turbulence transition mechanisms in granular media, and reduced order modeling for turbulent flows. Collaborations involve cross-disciplinary teams focusing on combustion, fluid-structure interaction, and high-fidelity flow analysis. He maintains active involvement in computational fluid dynamics communities and contributes to open-source software tools critical for industrial and academic research. Current efforts prioritize scalability, accuracy, and adaptability in numerical methods for next-generation supercomputing platforms.

Travis B. Thompsonمشاهده پروفایل

استادیار

• Mathematical Modeling
• Scientific Computing
• Machine Learning in Medicine
• +۵ مورد دیگر

Travis B. Thompson, Ph.D. is an Assistant Professor in the Department of Mathematics and Statistics at Texas Tech University, leading the TM4 (Texas Tech Translational and Theoretical Mathematical Modeling and Machine Learning in Medicine) research group. His academic journey includes postdoctoral work at Rice University, Simula Research Laboratory, and the University of Oxford, focusing on mathematics applied to neurodegenerative diseases. Education: Ph.D. in Mathematics from Texas A&M University (2013) Dr. Thompson develops theoretical mathematical models and applies scientific computing and machine learning to study neurological pathologies, particularly Alzheimer’s disease. His work explores complex biological processes on networks, translational healthcare applications, and nutritional security implications. Current research trends integrate neuroimaging data with finite element simulations to model tau progression , amyloid beta dynamics , and glymphatic clearance in age-related diseases. Scientific awards and honors were not explicitly mentioned in the provided materials. Dr. Thompson’s interdisciplinary approach connects computational neuroscience with biomedical engineering , utilizing techniques like diffusion tensor imaging and level set methods to analyze pathological protein spread and brain tissue mechanics . The TM4 research group focuses on network neurodegeneration , personalized medicine , and machine learning diagnostics . Their work spans from microfluidic cancer detection to computational modeling of brain clearance mechanisms , addressing challenges in both neurodegenerative diseases and biomedical engineering through rigorous mathematical frameworks.

Tilak Chandratillekeمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Heat and Mass Transfer
• Thermal Design
• +۳ مورد دیگر

Professor Tilak Chandratilleke is a faculty member in the School of Civil and Mechanical Engineering at Curtin University, part of the Faculty of Science and Engineering. He holds a PhD from the University of Cambridge and has extensive post-nominals including MIEAust, CPEng, and MASME. His research focuses on advanced thermal engineering, computational fluid dynamics (CFD), and heat transfer optimization. Key areas of interest include thermal energy storage systems, fluid flow in curved ducts, and thermal design for industrial applications. He also serves in the Office of the Provost, contributing to academic governance. Research Interests: - Computational Fluid Dynamics (CFD) modeling of complex thermal systems. - Heat and mass transfer in energy storage and manufacturing processes. - Design and analysis of heat exchangers and thermal recuperators. - Fluid dynamics in curved geometries and secondary vortex structures. - Applications in renewable energy systems and advanced manufacturing. Selected Publications (2022–2010): - Investigated high-temperature thermal energy storage using CaCO₃/Al₂O₃ reactors (2022). - Developed numerical models for metal hydride thermal storage systems (2021). - Analyzed boiling heat transfer in curved ducts and laser-assisted machining thermal effects (2020–2019). - Advanced CFD methodologies for convective boiling and turbulent flow modeling (2018–2016). - Pioneered studies on Dean vortices and microfluidic heat enhancement (2011–2010). Teaching: - Thermodynamics and Heat Transfer. - Fluid Mechanics and Engineering Applications. Labs/Teams: - Involved in Curtin’s thermal energy and advanced manufacturing research groups. - Collaborates with industry partners on renewable energy and thermal system optimization projects.

Ashley Willisمشاهده پروفایل

مدرس ارشد

• Fluid Dynamics
• Turbulence
• Astrophysical Fluid Dynamics
• +۳ مورد دیگر

Dr. Ashley Willis is a Senior Lecturer in Fluid Dynamics at the University of Sheffield's School of Mathematical and Physical Sciences. He holds roles including Admissions Head and Programme Leader for Study Abroad. His research focuses on fluid dynamics, turbulence, astrophysical flows, and magnetohydrodynamics, with applications in clean energy and planetary systems. Willis completed his Ph.D. in Applied Mathematics at Newcastle University (2002) and has held postdoctoral positions at the University of Bristol, Leeds, and a Marie Curie Fellowship at Ecole Polytechnique, Paris. He leads the Fluid Dynamics Group and is part of the cross-faculty Sheffield Fluid Mechanics Group. His research interests include transition to turbulence, nonlinear dynamics, and magnetic field generation in planetary interiors. He supervises PhD students like Shijun Chu and collaborates with industry on projects like turbulence suppression in pipe flows. Key contributions include the open-source Openpipeflow simulation code and studies on dynamo action in geophysical flows. Publications highlight work on turbulent transition mechanisms, optimal flow configurations, and dynamo theory. His teaching includes courses on mechanics, fluid dynamics, and mathematical modeling of natural systems.

Monika Nedaمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Turbulence
• Numerical Methods for Partial Differential Equations
• +۴ مورد دیگر

Monika Neda is a Professor in the Department of Mathematical Sciences and Associate Dean for Research at the University of Nevada, Las Vegas (UNLV). She holds a Ph.D. in Mathematics from the University of Pittsburgh (2007) and a B.S. in Mechanical Engineering from the Technical Faculty Mihajlo Pupin in Serbia (2001). Her research focuses on theoretical and computational fluid dynamics, turbulence modeling, and numerical methods for partial differential equations, with particular emphasis on Navier-Stokes equations and sensitivity analysis. Her work explores model derivation, numerical stability, finite element error estimates, and computational simulations of fluid flow problems. She also investigates educational strategies to improve STEM students' foundational math skills through game-based and activity-based instruction. Neda is affiliated with UNLV's Center for Applied Math & Statistics and has contributed to interdisciplinary projects involving engineering education and photovoltaic panel efficiency. Recent research trends highlight advancements in stabilization techniques for fluid models (e.g., time relaxation, deconvolution operators) and innovative pedagogical approaches leveraging technology platforms like Canvas. Her publications span computational mathematics, turbulence closure models, and education-focused interventions. Neda's academic leadership includes roles in curriculum development and institutional research, reflecting her dual commitment to scholarship and academic administration.

• Aerospace Engineering
• Fluid Dynamics
• Computational Fluid Dynamics
• +۳ مورد دیگر

Di Zhou is a Researcher specializing in aerospace engineering and fluid dynamics, focusing on turbulence modeling, aeroacoustics, and computational fluid dynamics (CFD). His work integrates advanced numerical methods such as large-eddy simulation (LES) with machine learning techniques like reinforcement learning to address challenges in wall modeling and flow prediction. Current affiliations are not explicitly stated, but his research involves collaborations in turbulence, rotor noise, and high-Reynolds-number flows. Research interests span turbulent boundary layers, adverse pressure gradients, and rotor aeroacoustic response. He has pioneered the application of multi-agent reinforcement learning for wall modeling in LES, advancing accuracy in simulating complex flows over periodic hills and Gaussian bumps. His studies also explore optimal sensor placement for lift prediction under gust loads and noise generation mechanisms in rotor systems. Recent trends in his publications highlight machine learning-driven turbulence modeling, sensitivity analysis of LES closure models, and computational analysis of rotor ingestion noise. Despite no listed awards, his work contributes significantly to both fundamental fluid dynamics and applied aerospace problems. No specific advising roles or labs are mentioned, but his research likely involves collaboration with experimental and numerical groups in aerodynamics and acoustics.

• Computational Mathematics
• Numerical Analysis
• Finite Element Methods
• +۳ مورد دیگر

Prof. Joachim Schöberl is a faculty member at TU Wien's Faculty of Mathematics and Geoinformation, leading the Scientific Computing and Modelling research group. His academic career includes roles as a university professor (Univ.Prof.) with engineering and technical doctorates (Dipl.-Ing., Dr.techn.). Research focuses on advanced numerical methods, including finite element methods, computational fluid dynamics, and partial differential equations. He has pioneered high-order schemes for fluid-structure interaction, shell mechanics, and electromagnetic simulations. Notable contributions include the NGSolve finite element library and innovative approaches to curvature approximation in discrete geometry. Recent work emphasizes nonlinear elasticity modeling, fractional diffusion problems, and shape optimization for biomembranes. His team collaborates on projects like metascreen upscaling, micromorphic continuum models, and eddy current simulations in laminated materials. Prof. Schöberl advises PhD students researching mixed finite element methods, fractional operators, and computational mechanics. His lab develops open-source tools for high-performance scientific computing.

Robert J. Trappمشاهده پروفایل

استاد

• Severe Storms
• Tornadoes
• Radar Meteorology
• +۵ مورد دیگر

Robert J. Trapp serves as Director of the School of Earth, Society, and Environment and Head of Climate, Meteorology and Atmospheric Sciences at the University of Illinois, while also holding a Professorship at the National Center for Supercomputing Applications (NCSA). His leadership spans both academic and research domains within atmospheric sciences. Trapp's research focuses on severe convective storms, tornado dynamics, and radar meteorology with significant contributions to understanding bow echoes, tornadic vortex signatures, and the impacts of climate change on severe weather. His work integrates advanced numerical modeling with observational data from field campaigns like BAMEX and VORTEX, utilizing Doppler radar systems including WSR-88D and Doppler On Wheels (DOW). His publication record demonstrates consistent research output from 1995-2007, with recent work emphasizing telescoping model approaches for evaluating severe convective storms under future climate scenarios. Key methodological contributions include objective analysis techniques for weather radar data and multi-platform observational strategies for severe thunderstorms. Trapp maintains active research collaboration through the National Center for Supercomputing Applications, leveraging computational resources for atmospheric modeling. His work bridges fundamental atmospheric dynamics with practical severe weather forecasting applications. Professional service includes leadership roles as Director and Department Head, indicating significant administrative responsibilities alongside research activities. His scholarly contributions appear primarily in conference proceedings and peer-reviewed journals focused on meteorology and atmospheric science.

• Turbulent Combustion
• Numerical Simulation
• Heat Transfer
• +۳ مورد دیگر

Ronan Vicquelin is a University Professor (1st Class) at CentraleSupélec, Paris-Saclay University, affiliated with the EM2C Laboratory (CNRS). He serves as Head of the Department of Aeronautics, Space and Transport and co-supervises the High Performance Computing Mésocentre. His academic appointments include previous roles as University Professor (2nd class) and Head of Aerospace programs. Education includes Habilitation (University of Rouen Normandy, 2018), PhD in Energetics (École Centrale Paris, 2010), M.Sc. in Mechanical Engineering & Aerospace (École Centrale Paris, 2006), and Engineering Diploma (École Centrale Paris, 2006). Research focuses on turbulent reacting flows with emphasis on: numerical simulation of combustion systems, LES/DNS methodologies, uncertainty quantification, hydrogen combustion dynamics, conjugate heat transfer, and radiative energy transfer. Current investigations explore flame stabilization mechanisms, multi-physics coupling, and high-performance computing applications for aerospace propulsion systems. Publications predominantly address combustion science, with recent works (2021-2025) emphasizing hydrogen flame dynamics, NOx emission control, advanced numerical methods for reactive flows, and experimental validation of turbulent combustion models. Thermal radiation effects and multi-phase flow interactions constitute emerging themes. Advises multiple PhD candidates with projects funded by ANR, EU programs (ACHIEVE, SOPRANO), and industry partnerships (Safran, Air Liquide). Research grants include PEPR OXY3C, ANR HyMaX, and ANR OXYTEC focusing on zero-emission combustion technologies. Leads experimental and computational research at EM2C Laboratory, coordinating teams working on turbulent combustion diagnostics, high-fidelity simulations, and development of the Mésocentre HPC infrastructure for large-scale CFD.

Robert Moserمشاهده پروفایل

استاد

• Turbulence physics
• Direct numerical simulation and spectral methods
• Large-eddy simulation
• +۲ مورد دیگر

Dr. Robert D. Moser is a Professor at the University of Texas at Austin and holds the W.A. "Tex" Moncrief, Jr. Chair in Computational Engineering and Sciences I. He is affiliated with the Thermal and Fluid Systems program, the Institute for Computational Engineering and Sciences (ICES), and serves as Director of the DOE-funded Center for Predictive Engineering and Computational Sciences (PECOS). Ph.D. in Mechanical Engineering from Stanford University (1984) His research focuses on computational methods for turbulence modeling, cardiovascular fluid mechanics, and uncertainty quantification in complex physical simulations. He develops large-eddy simulation techniques for aerospace applications and biological flow analysis, while pioneering methods to characterize uncertainties in reentry vehicle simulations and turbulence modeling. Dr. Moser leads interdisciplinary research at PECOS and ICES, combining computational engineering with biomedical applications. His work spans theoretical turbulence physics, numerical methods for Navier-Stokes equations, and practical implementations for aerodynamic and medical device design.

Elizabeth Yankovskyمشاهده پروفایل

استادیار

• Physical Oceanography
• Climate Modeling
• Ocean Turbulence
• +۳ مورد دیگر

Elizabeth Yankovsky is an Assistant Professor in the Yale Department of Earth and Planetary Sciences, affiliated with the Atmosphere, Oceans, Climate Dynamics Group. She holds a PhD from Princeton University and conducted postdoctoral research at New York University's Courant Institute. Her research focuses on physical oceanography, climate modeling, and the role of ocean turbulence in shaping large-scale ocean dynamics and climate. She collaborates with [C]Worthy on marine Carbon Dioxide Removal (mCDR) projects, particularly studying ocean alkalinity enhancement and regional ocean modeling. Her work emphasizes understanding mesoscale and submesoscale eddies, dense water formation in the Arctic, and improving climate models through parameterization of unresolved processes. Key contributions include developing parameterizations for symmetric instability in abyssal flows and analyzing eddy vertical structure using high-resolution models. She has also explored river plume dynamics and estuarine processes using nonhydrostatic simulations. Dr. Yankovsky teaches courses on ocean physics and climate dynamics, integrating pedagogical strategies learned through Princeton's Teaching Transcript Program. Her outreach activities include STEM education initiatives for K-12 students, such as workshops on Arctic oceanography and climate science.

Marco Colomboمشاهده پروفایل

مدرس

• Multiphase flows
• Nuclear thermal hydraulics
• Boiling heat transfer
• +۴ مورد دیگر

Marco Colombo is a Lecturer in Fluid Mechanics at the Department of Mechanical Engineering, University of Sheffield, School of Mechanical, Aerospace and Civil Engineering. He joined the university in late 2021 and focuses on computational fluid dynamics (CFD) for multiphase flows in nuclear systems. BSc: Energy Engineering, Politecnico di Milano MSc: Nuclear Engineering, Politecnico di Milano PhD: Politecnico di Milano (2013) His research specializes in Thermo-fluid dynamics of multiphase flows , particularly nuclear thermal hydraulics , boiling heat transfer , passive cooling systems , and two-phase flow instabilities . He employs advanced CFD techniques, including Eulerian-Eulerian and LES models, to study bubbly flows and reactor cooling dynamics. Recent publications highlight his work on Morphology-adaptive multifluid CFD for bubbly flows Generalized multiphase modeling (GEMMA) for multiscale flows Benchmarking turbulence closures in nuclear reactor applications Frictional pressure drop correlations in helical tubes Scientific achievements include an EPSRC Fellowship to address gas-liquid flow regime modeling. Collaborators span institutions such as the University of Leeds and Politecnico di Milano.