Journal Articles – Hybrid Modelling

2022

Blakseth, S.S., Rasheed, A., Kvamsdal, T. and San, O., Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach, Applied Soft Computing, 128, 109533, 2022
Robinson H., Pawar, S., Rasheed, A., San, O., Physics guided neural networks for modelling of non-linear dynamics, Neural Networks, 154, 333-345, 2022
San, O., Pawar, S., Rasheed, A., Prospects of federated machine learning in fluid dynamics. AIP Advances, 2022
Heiberg, A., Larsen, T.N., Meyer, E., Rasheed, A., San, O., Varagnolo, D., Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning, Neural Networks, 152, 17-33, 2022
Gupta, P., Rasheed, A., Steen, S., Ship Performance Monitoring using machine-learning, Ocean Engineering, 254, 111094, 2022
Pawar, S., San, O., Vedula, P., Rasheed, A., Kvamsdal, T., Multi-fidelity information fusion with concatenated neural networks, Scientific Report, 12, 5900, 2022

2021

Blakseth, S.S., Rasheed, A., Kvamsdal, T., San, O. Deep neural network enabled corrective source term approach to hybrid analysis and modeling, Neural Networks, 146, 181-199, 2021
Alshantti, A.A.S., Rasheed, A. Self-organising map based framework for investigating accounts sus- pected of money laundering, Frontiers in Artificial Intelligence, 2021
Ahmed, S. E., San, O., Rasheed, A. and Iliescu, T. Nonlinear proper orthogonal decomposition for convection-dominated flows, Physics of Fluids, 33, 121702, 2021.
Larsen, T.N., Teigen, H.Ø., Laache, T., Varagnolo, D., and Rasheed, A., Comparing Deep Reinforcement Learning Algorithms’ Ability to Safely Navigate Challenging Waters, Frontiers in Robotics and Artificial Intelligence, 8, 287, 2021
Lundby, E.T.B., Rasheed, A., Gravdahl, J.T., Halvorsen, I.J., A novel hybrid analysis and modeling approach applied to aluminum electrolysis process, Journal of Process Control, 105, 62–77, 2021.
Gupta, P., Taskar, B., Steen, S., Rasheed, A., Statistical modeling of Ship’s hydrodynamic performance indicator, Applied Ocean Research, 111, 102623, 2021.
Ahmed, S., Pawar, S., San, O., Rasheed, A., Iliescu, T., and Noack, B., On closures for reduced order models – a spectrum of first-principle to machine-learned avenues, Physics of Fluids, 33, 091301, 2021.
Pawar, S., San, O., Rasheed, A., Navon, I.M., A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations, International Journal of Geomathematics, 12, 17, 2021
Pawar, S., San, O., Aditya, N., Rasheed, A., Kvamsdal, T., Model fusion with physics-guided machine learning: projection based reduced order modeling, Physics of Fluids, 33, 067123, 2021. (Editor’s Pick)
San, O., Rasheed, A., Kvamsdal, T. Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution, GAMM Mitteilungen, 44, e202100007, 2021.
Sundby, T., Graham, J. M., Rasheed, A., Tabib, M., San, O., Geometric change detection in digital twins, Digital, 1 (2), 111-129, 2021.
Ahmed, S. E., Pawar, S., San, O., Rasheed, A., Tabib, M., A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction, Computers and Fluids, 221, 104895, 2021.
Stavelin, H., Rasheed, A., San, O., Hestnes, A. J., Applying object detection to marine data and exploring explainability of a fully convolutional neural network using principal component analysis, Ecological Informatics, 62, 101269, 2021.
Ahmed, S. E., San, O., Kara, K., Younis, R., Rasheed, A., Multifidelity computing for coupling full and reduced order models, PLOS ONE, 16(2), e0246092, 2021.
Havenstrøm, S. T., Rasheed, A., San, O. Deep reinforcement learning controller for 3D path following and collision avoidance by autonomous underwater vehicles, Frontiers in Robotics and AI, 7, 566037, 2021.
Pawar, S., San, O., Aksoylu, B., Rasheed, A., Kvamsdal, T. Physics guided machine learning using simplified theories, Physics of Fluids, 33, 011701, 2021.
Pawar, S. and San, O. Data assimilation empowered neural network parameterizations for subgrid processes in geophysical flows. Physical Review Fluids, accepted, 2020.
Mou, C., Koc, B., San, O. , Rebholz, L. G. and Iliescu, T. Data-driven variational multiscale reduced order models. Computer Methods in Applied Mechanics and Engineering, 373, 113470, 2021.

2020

Ahmed, S. E., San, O., Kara, K., Younis, R., Rasheed, A., Interface learning of multiphysics and multiscale systems, Physical Review E, 102, 053304, 2020.
Ahmed, S. E., Bhar, K., San, O., Rasheed, A. Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction, Physical Review E, 102, 043302, 2020.
Meyer, E., Heiberg, A., Rasheed, A., San, O., COLREG-Compliant Collision Avoidance for Un- manned Surface Vehicle using Deep Reinforcement Learning, IEEE Access, 8, 165344-165364, 2020.
Pawar, S., Ahmed, S. E., San, O., Rasheed, A., Navon I. M., Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows, Physics of Fluids, 32, 076606, 2020.
Pawar, S., Ahmed, S. E., San, O., Rasheed, A. An evolve-then-correct reduced order model for hidden fluid dynamics, Mathematics, 8(4), 570, 2020.
Ahmed, S. E., San, O., Rasheed, A., Iliescu, T., A long short-term memory embedding for hybrid uplifted reduced order models, Physica D: Nonlinear Phenomena, 409, 132471, 2020.
Pawar, S., Ahmed, S. E., San, O., Rasheed, A., Data-driven recovery of hidden physics in reduced order modeling of fluid flows, Physics of Fluids, 32, 036602, 2020.
Meyer, E., Robinson, H., Rasheed, A., San, O., Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning, IEEE Access, 8, 41466-41481, 2020.
Rasheed, A., San, O., Kvamsdal, T., Digital twin: values, challenges and enablers from a modeling perspective, IEEE Access, 8, 21980-22012, 2020.
Pawar, S., San, O., Rasheed, A., Vedula, P., A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence, Theoretical and Computational Fluid Dynamics, 34, 429-455, 2020.
Vaddireddy, H., Rasheed, A., Staples, A. E., San, O., Feature engineering and symbolic regression methods for detecting hidden physics from sparse sensor observation data, Physics of Fluids, 32, 015113, 2020. (Editor’s Pick)
Siddiqui, M.S., Rasheed, A., Kvamsdal, T., Numerical assessment of RANS turbulence models for the development of data driven reduced order models, Ocean Engineering, 196, 106799, 2020
Ahmed, S. E., Pawar, S. and San, O. PyDA: A hands-on introduction to dynamical data assimilation with Python. Fluids, 5(4), 225, 2020.
Pawar, S., Ahmed, S. E. and San, O. Interface learning in fluid dynamics: statistical inference of closures within micro-macro coupling models. Physics of Fluids, 32, 091704, 2020. (Featured Article)
Ahmed, S. E., Pawar, S. and San, O. PyDA: A hands-on introduction to dynamical data assimilation with Python. Fluids, 5(4), 225, 2020.
Pawar, S., Ahmed, S. E. and San, O. Interface learning in fluid dynamics: statistical inference of closures within micro-macro coupling models. Physics of Fluids, 32, 091704, 2020.
Ahmed, M., Park, H., Bach, C. K. and San, O. Numerical Investigation of Air Mixer for HVAC Testing Applications (ASHRAE RP-1733). Science and Technology for the Built Environment, 26(9), 1252-1273, 2020.
Maulik, R. and San, O. Numerical assessments of a parametric implicit large eddy simulation model. Journal of Computational and Applied Mathematics, 376, 112866, 2020.
Maulik, R., San, O. and Jacob, J. D. Spatiotemporally dynamic implicit large eddy simulation using machine learning classifiers. Physica D: Nonlinear Phenomena, 406, 132409, 2020.
Ahmed, S. E. and San, O. Breaking the Kolmogorov barrier in model reduction of fluid flows. Fluids, 5, 26, 2020.
Ahmed, S. E., San, O., Bistrian, D. A. and Navon, I. M. Sampling and resolution characteristics in reduced order models of shallow water equations: intrusive vs non‐intrusive. International Journal for Numerical Methods in Fluids, 92 (8), 992-1036, 2020.

2019

Ahmed, S. E., Rahman, S. M., San, O., Rasheed, A., Navon, I. M., Memory embedded non-intrusive reduced order modeling of non-ergodic flows, Physics of Fluids, 31, 126602, 2019.
Rahman, S. M., Pawar, S., San, O., Rasheed, A., Iliescu, T., Nonintrusive reduced order modeling framework for quasigeostrophic turbulence, Physical Review E, 100, 053306, 2019.
Pawar, S., Rahman, S. M., Vaddireddy, H., San, O., Rasheed, A., Vedula, P., A deep learning enabler for non-intrusive reduced order modeling of fluid flows, Physics of Fluids, 31, 085101, 2019. (Featured Article)
Maulik, R., San, O., Rasheed, A. and Vedula, P. Sub-grid modelling for two-dimensional turbulence using neural networks, Journal of Fluid Mechanics, 858, 122-144, 2019.
Siddiqui, M.S., Rasheed, A., Kvamsdal, T. Validation of the numerical simulations of flow around a scaled-down turbine using experimental data from wind tunnel, Wind and Structures, 29, 405–416, 2019
Siddiqui, M.S., Fonn, E., Kvamsdal, T., Rasheed, A., Finite Volume high-fidelity simulation com- bined with finite-element-based reduced order modeling of incompressible flow problems, Energies, 12, 1271, 2019
Fonn, E., Brummelen, H.van, Kvamsdal, T., Rasheed, A., Fast divergence-conforming reduced basis methods for steady Navier–Stokes flow, Computer Methods in Applied Mechanics and Engineering, 346, 486–512, 2019
Siddiqui, M.S., Rasheed, A., Tabib, M.V., Kvamsdal, T., Numerical investigation of modeling frame- works and geometric approximations on NREL 5MW wind turbine, Renewable Energy, 132, 1058– 1075, 2019
Pawar, S. and San, O. CFD Julia: A learning module structuring an introductory course on computational fluid dynamics. Fluids, 4(3), 159, 2019.
Vaddireddy, H. and San, O. Equation discovery using fast function extraction: a deterministic symbolic regression approach. Fluids, 4(2), 111, 2019.
Rahman, S. M., Ahmed, S. and San, O. A dynamic closure modeling framework for model order reduction of geophysical flows. Physics of Fluids, 31, 046602, 2019.
Maulik, R., San, O., Jacob, J. and Crick, C. Sub-grid scale model classification and blending through deep learning. Journal of Fluid Mechanics, 870, 784-812, 2019.
San, O., Maulik, R. and Ahmed, M. An artificial neural network framework for reduced order modeling of transient flows. Communications in Nonlinear Science and Numerical Simulation, 77, 271-287, 2019.
Rahman, S. M. and San, O. A relaxation filtering approach for two-dimensional Rayleigh–Taylor instability-induced flows. Fluids, 4(2), 78, 2019.
Rahman, S. M. and San, O. A localized dynamic closure model for Euler turbulence. International Journal of Computational Fluid Dynamics, 32(8-9), 326-378, 2019.
Sk Mashfiqur Rahman, Rasheed, Adil, and Omer San. A hybrid analytic framework for accel- erating incompressible flow solvers. Fluids, 3(3):50, 2018
Knut Nordanger, Rasheed, Adil, Knut Morten Okstad, Arne Morten Kvarving, Runar Holdahl, and Trond Kvamsdal. Numerical benchmarking of fluid-structure interaction: An isogeometric finite element approach. Ocean Engineering, 124:324–339, 2016
Knut Nordanger, Runar Holdahl, Arne Morten Kvarving, Trond Kvamsdal, and Rasheed, Adil. Simulation of airflow past a 2d naca0015 airfoil using an isogeometric incompressible navier-stokes solver with the spalart-allmaras turbulence model. Computer Methods in Applied Mechanics and Engineering, 290:183–208, 2015
Knut Nordanger, Runar Holdahl, Arne Morten Kvarving, Rasheed, Adil, and Trond Kvamsdal. Implementation and comparison of three isogeometric navier–stokes solvers applied to simulation of flow past a fixed 2d naca0012 airfoil at high reynolds number. Computer Methods in Applied Mechanics and Engineering, 284:664–688, 2014
Rasheed, Adil and Asif Mushtaq. Numerical analysis of the flying condition at the alta airport, norway. Aviation, 18:109–119, 2014
Rasheed, Adil and Karstein Sørli. Cfd analysis of terrain induced turbulence at kristiansand airport, kjevik. Aviation, 17:104–112, 2013
Rasheed, Adil and Darren Robinson. Characterization of dispersive fluxes in mesoscale models using les of flow over an array of cubes. International Journal of Atmospheric Sciences, 17:898095, 2013
Rasheed, Adil, Darren Robinson, Alain Clappier, Chidambaram Narayanan, and Djamel Lake- hal. Representing complexities in urban geometry in mesoscale modeling. International Journal of Climatology, 31:289–301, 2011