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We describe an implementation of compressible inviscid fluid solvers with block-structured adaptive mesh refinement on Graphics Processing Units using NVIDIA's CUDA. We show that a class of high resolution shock capturing schemes can be…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 Peng Wang , Tom Abel , Ralf Kaehler

Water distribution systems (WDSs) are an important part of critical infrastructure becoming increasingly significant in the face of climate change and urban population growth. We propose a robust and scalable surrogate deep learning (DL)…

Neural and Evolutionary Computing · Computer Science 2025-02-19 Inaam Ashraf , André Artelt , Barbara Hammer

Grad-div stabilization is a classical remedy in conforming mixed finite element methods for incompressible flow problems, for mitigating velocity errors that are sometimes called poor mass conservation. Such errors arise due to the…

Numerical Analysis · Mathematics 2019-04-12 Mine Akbas , Alexander Linke , Leo G. Rebholz , Philipp W. Schroeder

This work introduces an optimization-based $rp$-adaptive numerical method to approximate solutions of viscous, shock-dominated flows using implicit shock tracking and a high-order discontinuous Galerkin discretization on traditionally…

Numerical Analysis · Mathematics 2025-04-22 Huijing Dong , Masayuki Yano , Tianci Huang , Matthew J. Zahr

We propose a new arbitrary high order accurate semi-implicit space-time discontinuous Galerkin (DG) method for the solution of the two and three dimensional compressible Euler and Navier-Stokes equations on staggered unstructured curved…

Numerical Analysis · Mathematics 2017-05-24 Maurizio Tavelli , Michael Dumbser

Model Predictive Control (MPC) is an optimal control strategy suited for flood control of water resources infrastructure. Despite many studies on reservoir flood control and their theoretical contribution, optimisation methodologies have…

Systems and Control · Electrical Eng. & Systems 2025-04-01 Ja-Ho Koo , Edo Abraham , Andreja Jonoski , Dimitri P. Solomatine

Deep Learning (DL) algorithms are becoming increasingly popular for the reconstruction of high-resolution turbulent flows (aka super-resolution). However, current DL approaches perform spatially uniform super-resolution - a key performance…

Precipitation nowcasting, critical for flood emergency and river management, has remained challenging for decades, although recent developments in deep generative modeling (DGM) suggest the possibility of improvements. River management…

This study develops and evaluates a novel hybridWavelet SARIMA Transformer, WST framework to forecast using monthly rainfall across five meteorological subdivisions of Northeast India over the 1971 to 2023 period. The approach employs the…

Applications · Statistics 2025-09-16 Junmoni Saikia , Kuldeep Goswami , Sarat C. Kakaty

We present a new method for numerical hydrodynamics which uses a multidimensional generalisation of the Roe solver and operates on an unstructured triangular mesh. The main advantage over traditional methods based on Riemann solvers, which…

Instrumentation and Methods for Astrophysics · Physics 2017-06-28 Sijme-Jan Paardekooper

A multigrid scheme is proposed for the pressure equation of the incompressible unsteady fluid flow equations, allowing efficient implementation on clusters of modern CPUs, many integrated core devices (MICs), and graphics processing units…

Numerical Analysis · Mathematics 2014-08-19 György Tegze , Gyula I. Tóth

During the last few years discontinuous Galerkin (DG) methods have received increased interest from the geophysical community. In these methods the solution in each grid cell is approximated as a linear combination of basis functions.…

Atmospheric and Oceanic Physics · Physics 2025-02-19 Ivo Pasmans , Yumeng Chen , Alberto Carrassi , Chris K. R. T. Jones

The evaluation of hydrological models is essential for both model selection and reliability assessment. However, simply comparing predictions to observations is insufficient for understanding the global landscape of model behavior. This is…

Geophysics · Physics 2026-02-06 Yang Yang , Joseph Janssen , Hoshin Gupta , Ting Fong May Chui

The Swift-Hohenberg equation as a central nonlinear model in modern physics has a gradient flow structure. Here we introduce fully discrete discontinuous Galerkin (DG) schemes for a class of fourth order gradient flow problems, including…

Numerical Analysis · Mathematics 2019-10-02 Hailiang Liu , Peimeng Yin

Vision-Language Latent Diffusion Models (LDMs) (Rombach et al., 2022) provide powerful generative priors for inverse problems. However, existing LDM-based inverse solvers typically require a large number of neural function evaluations…

Machine Learning · Statistics 2026-05-11 Alessio Spagnoletti , Tim Y. J. Wang , Marcelo Pereyra , O. Deniz Akyildiz

Turbulent flow simulation plays a crucial role in various applications, including aircraft and ship design, industrial process optimization, and weather prediction. In this paper, we propose an advanced data-driven method for simulating…

Fluid Dynamics · Physics 2023-06-27 Duc Minh Nguyen , Minh Chau Vu , Tuan Anh Nguyen , Tri Huynh , Nguyen Tri Nguyen , Truong Son Hy

Global climate models (GCMs), typically run at ~100-km resolution, capture large-scale environmental conditions but cannot resolve convection and cloud processes at kilometer scales. Convection-permitting models offer higher-resolution…

Atmospheric and Oceanic Physics · Physics 2026-05-12 Hungjui Yu , Lander Ver Hoef , Kristen L. Rasmussen , Imme Ebert-Uphoff

Density stratification in geophysical environments can be non-uniform, particularly in thermohaline staircases and atmospheric layer transitions. Non-uniform stratification, however, is often approximated by the average ambient density…

Fluid Dynamics · Physics 2020-11-10 G. D. Portwood , S. M. de Bruyn Kops

Friction is one of the cruxes of hydrodynamic modeling; flood conditions are highly sensitive to the Friction Factors (FFs) used to calculate momentum losses. However, empirical FFs are challenging to measure because they require laboratory…

Machine Learning · Computer Science 2024-04-04 Francisco Haces-Garcia , Vasileios Kotzamanis , Craig Glennie , Hanadi Rifai

Previous studies showed that hydro-climate processes are stochastic and complex systems, and it is difficult to discover the hidden patterns in the all non-stationary data and thoroughly understand the hydro-climate relationships. For the…

Applications · Statistics 2018-10-02 Jianhua Xu
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