activity
20182026
most citedPhysically-Constrained Data-Driven, Filtered Reduced Order Modeling of Fluid Flows

75 citations · 76 across the 12 of their papers we have counts for

collaborators

13 papers

math.NA2026

An Efficient Second-Order-in-Time Penalty-Projection Ensemble Eddy Viscosity Method for Parameterized Navier-Stokes Flows

Md Mahmudul Islam, Muhammad Mohebujjaman, Jahrul Alam

We propose a novel, robust, and second-order-accurate parameterized penalty-projection ensemble algorithm for incompressible Navier--Stokes flow problems. The resulting linearized…

math.AP2026

On higher-order derivative ratios in turbulent flows

Zoran Grujić, Muhammad Mohebujjaman

A computational study of higher-order derivative ratios on a time interval leading to the enstrophy peak is presented in the case of the 3D Taylor-Green vortex, a benchmark problem…

math.NA2025

Efficient and Optimally Accurate Numerical Algorithms for Stochastic Turbulent Flow Problems

Brandiece N. Berry, Md Mahmudul Islam, Muhammad Mohebujjaman +1

In this paper, we first propose a filter-based continuous Ensemble Eddy Viscosity (EEV) model for stochastic turbulent flow problems. We then propose a generic algorithm for a fami…

math.NA2025

Efficient, Accurate, and Robust Penalty-Projection Algorithm for Parameterized Stochastic Navier-Stokes Flow Problems

Neethu Suma Raveendran, Md. Abdul Aziz, Sivaguru S. Ravindran +1

This paper presents and analyzes a fast, robust, efficient, and optimally accurate fully discrete splitting algorithm for the Uncertainty Quantification (UQ) of parameterized Stoch…

math.NA2025

A simple-to-implement nonlinear preconditioning of Newton's method for solving the steady Navier-Stokes equations

Muhammad Mohebujjaman, Mengying Xiao, Cheng Zhang

The Newton's method for solving stationary Navier-Stokes equations (NSE) is known to convergent fast, however, may fail due to a bad initial guess. This work presents a simple-to-i…

math.NA2024

Two Robust, Efficient, and optimally Accurate Algorithms for parameterized stochastic navier-stokes Flow Problems

Neethu Suma Raveendran, Md Abdul Aziz, Muhammad Mohebujjaman

This paper presents and analyzes two robust, efficient, and optimally accurate fully discrete finite element algorithms for computing the parameterized Navier-Stokes Equations (NSE…

math.NA2023

A Penalty-projection based Efficient and Accurate Stochastic Collocation Method for Magnetohydrodynamic Flows

Muhammad Mohebujjaman, Julian Miranda, Md. Abdullah Al Mahbub +1

We propose, analyze, and test a penalty projection-based efficient and accurate algorithm for the Uncertainty Quantification (UQ) of the time-dependent Magnetohydrodynamic (MHD) fl…

math.NA2021

An efficient algorithm for simulating ensembles of parameterized MHD flow problems

Muhammad Mohebujjaman, Hongwei Wang, Leo G. Rebholz +1

In this paper, we propose, analyze, and test an efficient algorithm for computing ensemble average of incompressible magnetohydrodynamics (MHD) flows, where instances/members corre…

math.NA2021

High order efficient algorithm for computation of MHD flow ensembles

Muhammad Mohebujjaman

In this paper, we propose, analyze, and test a new fully discrete, efficient, decoupled, stable, and practically second-order time-stepping algorithm for computing MHD ensemble flo…

math.NA2018★ 1 cited

Nonintrusive Stabilization of Reduced Order Models for Uncertainty Quantification of Time-Dependent Convection-Dominated Flows

M. Gunzburger, T. Iliescu, M. Mohebujjaman +1

In this paper, we propose a nonintrusive filter-based stabilization of reduced order models (ROMs) for uncertainty quantification (UQ) of the time-dependent Navier-Stokes equations…

math.NA2018

Commutation Error in Reduced Order Modeling of Fluid Flows

Birgul Koc, Muhammad Mohebujjaman, Changhong Mou +1

For reduced order models (ROMs) of fluid flows, we investigate theoretically and computationally whether differentiation and ROM spatial filtering commute, i.e., whether the commut…

math.NA2018★ 75 cited

Physically-Constrained Data-Driven, Filtered Reduced Order Modeling of Fluid Flows

M. Mohebujjaman, L. G. Rebholz, T. Iliescu

In our earlier work, we proposed a data-driven filtered reduced order model (DDF-ROM) framework for the numerical simulation of fluid flows, which can be formally written as \begin…

math.NA2018

Second order ensemble simulation for MHD flow in Elsässer variable with noisy input data

Muhammad Mohebujjaman

We propose, analyze and test a fully discrete, efficient second-order algorithm for computing flow ensembles average of viscous, incompressible, and time-dependent magnetohydrodyna…