Publications

Please see Dr. San's Google Scholar profile for a current list of publications.

2020

  1. Pawar, S., Ahmed, S. E., San, O., Rasheed, A. and Navon I. M. Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows. Physics of Fluids, 32, 076606, 2020.

  2. Pawar, S., Ahmed, S. E., San, O. and Rasheed, A. An evolve-then-correct reduced order model for hidden fluid dynamics. Mathematics, 8(4), 570, 2020.

  3. Ahmed, S. E., San, O., Rasheed, A. and Iliescu, T. A long short-term memory embedding for hybrid uplifted reduced order models. Physica D: Nonlinear Phenomena, 409, 132471, 2020.

  4. Maulik, R. and San, O. Numerical assessments of a parametric implicit large eddy simulation model. Journal of Computational and Applied Mathematics, 376, 112866, 2020.

  5. 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.

  6. Pawar, S., Ahmed, S. E., San, O. and Rasheed, A. Data-driven recovery of hidden physics in reduced order modeling of fluid flows. Physics of Fluids, 32, 036602, 2020.

  7. Meyer, E., Robinson, H., Rasheed, A., and San, O. Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning. IEEE Access, 8, 41466--41481, 2020.

  8. Ahmed, S. E. and San, O. Breaking the Kolmogorov barrier in model reduction of fluid flows. Fluids, 5, 26, 2020.

  9. 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.

  10. Rasheed, A., San, O. and Kvamsdal, T. Digital twin: values, challenges and enablers from a modeling perspective. IEEE Access, 8, 21980-22012, 2020.

  11. Pawar, S., San, O., Rasheed, A. and Vedula, P. A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence. Theoretical and Computational Fluid Dynamics, accepted, 2020.

  12. Vaddireddy, H., Rasheed, A., Staples, A. E. and San, O. Feature engineering and symbolic regression methods for detecting hidden physics from sparse sensor observation data. Physics of Fluids, 32, 015113, 2020.

2019

  1. Ahmed, S. E., Rahman, S. M., San, O., Rasheed, A. and Navon, I. M. Memory embedded non-intrusive reduced order modeling of non-ergodic flows. Physics of Fluids, 31, 126602, 2019.

  2. Rahman, S. M., Pawar, S., San, O., Rasheed, A. and Iliescu, T. Nonintrusive reduced order modeling framework for quasigeostrophic turbulence. Physical Review E, 100, 053306, 2019.

  3. Pawar, S., Rahman, S. M., Vaddireddy, H. , San, O., Rasheed, A. and Vedula, P. A deep learning enabler for non-intrusive reduced order modeling of fluid flows. Physics of Fluids, 31, 085101, 2019.

  4. Pawar, S. and San, O. CFD Julia: A learning module structuring an introductory course on computational fluid dynamics. Fluids, 4(3), 159, 2019.

  5. Vaddireddy, H. and San, O. Equation discovery using fast function extraction: a deterministic symbolic regression approach. Fluids, 4(2), 111, 2019.

  6. 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.

  7. 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.

  8. 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.

  9. Rahman, S. M. and San, O. A relaxation filtering approach for two-dimensional Rayleigh–Taylor instability-induced flows. Fluids, 4(2), 78, 2019.

  10. 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.

  11. 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.

2018

  1. Maulik, R., San, O., Rasheed, A. and Vedula, P. Data-driven deconvolution for large eddy simulations of Kraichnan turbulence. Physics of Fluids, 30, 125109, 2018.

  2. Rahman, S. M., San, O. and Rasheed, A. A hybrid approach for model order reduction of barotropic quasi-geostrophic turbulence. Fluids, 3(4), 86, 2018.

  3. Ahmed, M. and San, O. Stabilized principal interval decomposition method for model reduction of nonlinear convective systems with moving shocks. Computational and Applied Mathematics, 37(5), 6870-6902, 2018.

  4. Kholikov, K., Ilhom, S., Sajjad, M., Smith, M. E., Monroe, J. D., San, O. and Er, A. O. Improved singlet oxygen generation and antimicrobial activity of sulphur-doped graphene quantum dots coupled with methylene blue for photodynamic therapy applications. Photodiagnosis and Photodynamic Therapy, 24, 7-14, 2018.

  5. Rahman, S. M., Rasheed, A. and San, O. A hybrid analytics paradigm combining physics-based modeling and data-driven modeling to accelerate incompressible flow solvers. Fluids, 3(3), 50, 2018.

  6. San, O. and Maulik, R. Stratified Kelvin–Helmholtz turbulence of compressible shear flows. Nonlinear Processes in Geophysics, 25, 457-476, 2018.

  7. San, O. and Maulik, R. Extreme learning machine for reduced order modeling of turbulent geophysical flows. Physical Review E, 97, 042322, 2018.

  8. San, O. and Maulik, R. Neural network closures for nonlinear model order reduction. Advances in Computational Mathematics, 44(6), 1717-1750, 2018.

  9. Maulik, R., San, O. and Behera, R., An adaptive multilevel wavelet framework for scale-selective WENO reconstruction schemes. International Journal for Numerical Methods in Fluids, 87(5), 239-269, 2018.

  10. Ilhom, S., Seyitliyev, D., Kholikov, K., Thomas, Z., Er, A. O., Li, P., Karaca, H. E. and San, O. Laser shock wave-assisted patterning on NiTi shape memory alloy surfaces. Shape Memory and Superelasticity, 4(1), 224-231, 2018.

  11. Ilhom, S., Kholikov, K., Li, P., Ottman, C., Sanford, D., Thomas, Z., San, O., Karaca, H. E. and Er, A. O. Scalable patterning using laser-induced shock waves. Optical Engineering, 57(4), 041413, 2018.

  12. San, O. and Maulik, R. Machine learning closures for model order reduction of thermal fluids. Applied Mathematical Modelling, 60, 681-710, 2018.

  13. Maulik, R. and San, O. A dynamic closure modeling framework for large eddy simulation using approximate deconvolution: Burgers equation. Cogent Physics, 5, 1464368, 2018.

  14. San, O. and Vedula, P. Generalized deconvolution procedure for structural modeling of turbulence. Journal of Scientific Computing, 75(2), 1187-1206, 2018.

  15. Maulik, R. and San, O. Explicit and implicit LES closures for Burgers turbulence. Journal of Computational and Applied Mathematics, 327, 12-40, 2018.

2017

  1. Maulik, R. and San, O. A neural network approach for the blind deconvolution of turbulent flows. Journal of Fluid Mechanics, 831, 151-181, 2017.

  2. Seyitliyev, D., Kholikov, K., Grant, B., San, O. and Er, A. O. Laser-induced hydrogen generation from graphite and coal. International Journal of Hydrogen Energy, 42, 26277-26288, 2017.

  3. Maulik, R. and San, O. A novel dynamic framework for subgrid scale parametrization of mesoscale eddies in quasigeostrophic turbulent flows. Computers & Mathematics with Applications, 74, 420-445, 2017.

  4. Benosman, M., Borggaard, J., San, O. and Kramer, B. Learning-based robust stabilization for reduced-order models of 2D and 3D Boussinesq equations. Applied Mathematical Modelling, 49, 162-181, 2017.

  5. Maulik, R. and San, O. Resolution and energy dissipation characteristics of implicit LES and explicit filtering models for compressible turbulence. Fluids, 2(14), 14, 2017.

  6. Maulik, R. and San, O. A dynamic framework for functional parameterisations of the eddy viscosity coefficient in two-dimensional turbulence. International Journal of Computational Fluid Dynamics, 31(2), 69-92, 2017.

  7. Maulik, R. and San, O. A stable and scale-aware dynamic modeling framework for subgrid-scale parameterizations of two-dimensional turbulence. Computers & Fluids, 158, 11-38, 2017.

  8. Maulik, R. and San, O. A dynamic subgrid-scale modeling framework for Boussinesq turbulence. International Journal of Heat and Mass Transfer, 108, 1656-1675, 2017.

2015-2009

  1. San, O. and Borggaard, J. Principal interval decomposition framework for POD reduced-order modeling of convective Boussinesq flows. International Journal For Numerical Methods in Fluids, 78, 37-62, 2015.

  2. San, O. and Iliescu, T. A stabilized proper orthogonal decomposition reduced-order model for large scale quasigeostrophic ocean circulation. Advances in Computational Mathematics, 41, 1289-1319, 2015.

  3. San, O. A novel high-order accurate compact stencil Poisson solver: application to cavity flows. International Journal of Applied Mechanics, 7, 1550006, 2015.

  4. San, O., Staples, A. E. and Iliescu, T. A posteriori analysis of low-pass spatial filters for approximate deconvolution large eddy simulations of homogeneous incompressible flows International Journal of Computational Fluid Dynamics, 29, 40-66, 2015.

  5. San, O. and Kara, K. Evaluation of Riemann flux solvers for WENO reconstruction schemes: Kelvin-Helmholtz instability. Computers & Fluids, 117, 24-41, 2015.

  6. San, O. A dynamic eddy-viscosity closure model for large eddy simulations of two-dimensional decaying turbulence. International Journal of Computational Fluid Dynamics, 28, 363-382, 2014.

  7. San, O. and Kara, K. Numerical assessments of high-order accurate shock capturing schemes: Kelvin-Helmholtz type vortical structures in high-resolutions. Computers & Fluids, 89, 254-276, 2014.

  8. San, O. and Iliescu, T. Proper orthogonal decomposition closure models for fluid flows: Burgers equation. International Journal of Numerical Analysis & Modeling, Series B, 5, 217-237, 2014.

  9. San, O. and Staples, A. E. A coarse-grid projection method for accelerating incompressible flow computations. Journal of Computational Physics, 233, 480-508, 2013.

  10. San, O. and Staples, A. E. An efficient coarse grid projection method for quasigeostrophic models of large-scale ocean circulation. International Journal For Multiscale Computational Engineering, 11, 463-495, 2013.

  11. San, O., Staples, A. E. and Iliescu, T. Approximate deconvolution large eddy simulation of a stratified two-layer quasigeostrophic ocean model. Ocean Modelling, 63, 1-20, 2013.

  12. San, O. and Staples, A. E. Stationary two-dimensional turbulence statistics using a Markovian forcing scheme. Computers & Fluids, 71, 1-18, 2013.

  13. San, O. and Staples, A. E. An improved model for reduced-order physiological fluid flows. Journal of Mechanics in Medicine and Biology, 12, 1250052, 2012.

  14. San, O. and Staples, A. E. Dynamics of pulsatile flows through elastic microtubes. International Journal of Applied Mechanics, 4, 1250006, 2012.

  15. San, O. and Staples, A. E. High-order methods for decaying two-dimensional homogeneous isotropic turbulence. Computers & Fluids, 63, 105-127, 2012.

  16. San, O., Staples, A. E., Wang, Z. and Iliescu, T. Approximate deconvolution large eddy simulation of a barotropic ocean circulation model. Ocean Modelling, 40, 120-132, 2011.

  17. San, O. and Kara, K. High-order accurate spectral difference method for shallow water equations. International Journal of Research and Reviews in Applied Sciences, 6, 41-54, 2011.

  18. San, O. and Kara, K. A multigrid accelerated high-order compact fractional-step method for unsteady incompressible viscous flows. International Journal of Research and Reviews in Applied Sciences, 5, 245-259, 2010.

  19. San, O., Bayraktar, I. and Bayraktar, T. Size and expansion ratio analysis of micro nozzle gas flow. International Communications in Heat and Mass Transfer, 36, 402-411, 2009.