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In recent years, there has been a growing interest in exploring the application of single-photon avalanche diode (SPAD) in optical wireless communication (OWC). As a photon counting detector, SPAD can provide much higher sensitivity…

Information Theory · Computer Science 2022-02-14 Shenjie Huang , Majid Safari

The correlation and extraction of coherent structures from a turbulent flow is a principle objective of data-driven modal decomposition techniques. The Conditional space-time Proper Orthogonal Decomposition (CPOD) offers insight into…

Fluid Dynamics · Physics 2022-07-12 Spencer Stahl , Chitrarth Prasad , Hemanth Goparaju , Datta Gaitonde

We estimate the wave speed in the acoustic wave equation from boundary measurements by constructing a reduced-order model (ROM) matching discrete time-domain data. The state-variable representation of the ROM can be equivalently viewed as a…

Numerical Analysis · Mathematics 2016-10-18 Vladimir Druskin , Alexander Mamonov , Andrew E. Thaler , Mikhail Zaslavsky

High-order Discontinuous Galerkin (DG) methods offer excellent accuracy for turbulent flow simulations, especially when implemented on GPU-oriented architectures that favor very high polynomial orders. On modern GPUs, high-order polynomial…

Many unsteady flows exhibiting complex dynamics are nevertheless characterized by emergent large-scale coherence in space and time. Reduced-order models based on Galerkin projection of the governing equations onto an orthogonal modal basis…

Fluid Dynamics · Physics 2022-06-28 Jared L. Callaham , Jean-Christophe Loiseau , Steven L. Brunton

This paper investigates the spectral structure, numerical dispersion, and observability of fully discrete approximations of the one-dimensional wave equation by $P^k$ (local) discontinuous Galerkin methods. Characterizing the coupled…

Optimization and Control · Mathematics 2026-05-21 Yunzhang Li , Xiaoyang Wang , Enrique Zuazua

In particle-laden turbulence, the Fourier Lagrangian spectrum of each phase is regularly computed, and analytically derived response functions relate the Lagrangian spectrum of the fluid- and the particle phase. However, due to the periodic…

Variable-order time-fractional wave equations provide a flexible model for wave phenomena with evolving memory effects and anomalous temporal dynamics. Their numerical approximation is challenging because the variable-order fractional…

Numerical Analysis · Mathematics 2026-05-26 Lu Zhang

In this paper, we study numerically the linear damped second-order hyperbolic partial differential equation (PDE) with affine parameter dependence using a goal-oriented approach by finite element (FE) and reduced basis (RB) methods. The…

Computational Physics · Physics 2013-09-17 Khac Chi Hoang , Pierre Kerfriden , Stephane P. A. Bordas

We develop a spectral low-mode reduced solver for second-order elliptic boundary value problems with spatially varying diffusion coefficients. The approach projects standard finite difference or finite element discretization onto a global…

Numerical Analysis · Mathematics 2025-12-23 Prosper Torsu

In this paper, a stabilized proper orthogonal decomposition (POD) reduced-order model (ROM) is presented for the barotropic vorticity equation. We apply the POD-ROM model to mid-latitude simplified oceanic basins, which are standard…

Fluid Dynamics · Physics 2018-01-29 Omer San , Traian Iliescu

Discontinuous Galerkin (DG) methods for hyperbolic partial differential equations (PDEs) with explicit time-stepping schemes, such as strong stability-preserving Runge-Kutta (SSP-RK), suffer from time-step restrictions that are…

Numerical Analysis · Mathematics 2019-03-11 Pierson T. Guthrey , James A. Rossmanith

A phase proper orthogonal decomposition (Phase POD) method is demonstrated, utilizing phase averaging for the decomposition of spatio-temporal behaviour of statistically non-stationary turbulent flows in an optimized manner. The proposed…

Fluid Dynamics · Physics 2024-03-01 Yisheng Zhang , Azur Hodzic , Fabien Evrard , Berend Van Wachem , Clara M. Velte

This study presents an artificial neural network and proper orthogonal decomposition (POD)-based reduced-order model (ROM) of turbulent flow around a finite wall-mounted square cylinder. The proposed model is suitable for turbulent wake…

Fluid Dynamics · Physics 2021-09-21 Mustafa Z. Yousif , Hee Chang Lim

We present a Reduced Order Model (ROM) which exploits recent developments in Physics Informed Neural Networks (PINNs) for solving inverse problems for the Navier--Stokes equations (NSE). In the proposed approach, the presence of simulated…

Fluid Dynamics · Physics 2022-09-08 Saddam Hijazi , Melina Freitag , Niels Landwehr

In this paper we investigate the numerical solution of stochastic partial differential equations (SPDEs) for a wider class of stochastic equations. We focus on non-diagonal colored noise instead of the usual space-time white noise. By…

Numerical Analysis · Mathematics 2013-11-12 Dirk Blömker , Minoo Kamrani

This article presents a Galerkin projection-based reduced-order modelling (ROM) approach for segregated fluid-structure interaction (FSI) problems, formulated within an Arbitrary Lagrangian Eulerian (ALE) framework at low Reynolds numbers…

Numerical Analysis · Mathematics 2025-07-24 Valentin Nkana Ngan , Giovanni Stabile , Andrea Mola , Gianluigi Rozza

ADER-WENO methods have proved extremely useful in obtaining arbitrarily high-order solutions to problems involving hyperbolic systems of PDEs. For example, it has been demonstrated that for the same computational cost as a Runge-Kutta…

Computational Physics · Physics 2017-03-08 Haran Jackson

In the present study, we propose a new surrogate model, called common kernel-smoothed proper orthogonal decomposition (CKSPOD), to efficiently emulate the spatiotemporal evolution of fluid flow dynamics. The proposed surrogate model…

Fluid Dynamics · Physics 2021-01-25 Yu-Hung Chang , Xingjian Wang , Liwei Zhang , Yixing Li , Simon Mak , Chien-Fu J. Wu , Vigor Yang

We present a model reduction approach for the real-time solution of time-dependent nonlinear partial differential equations (PDEs) with parametric dependencies. The approach integrates several ingredients to develop efficient and accurate…

Numerical Analysis · Mathematics 2024-10-04 Ngoc Cuong Nguyen
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