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In this paper the projection hybrid FV/FE method presented in Busto et al. 2014 is extended to account for species transport equations. Furthermore, turbulent regimes are also considered thanks to the $k-\varepsilon$ model. Regarding the…

Numerical Analysis · Mathematics 2023-01-23 Saray Busto , Jose Luis Ferrin , Eleuterio F. Toro , Maria Elena Vazquez-Cendon

Convenient, easy to implement stochastic integration methods are developed on the basis of abstract one-step deterministic order $p$ integration techniques. The abstraction as an arbitrary one step map allows the inspection of easy to…

Numerical Analysis · Mathematics 2025-10-15 J. Woodfield , A. Lobbe

This paper develops a two-level fourth-order scheme for solving time-fractional convection-diffusion-reaction equation with variable coefficients subjected to suitable initial and boundary conditions. The basis properties of the new…

Numerical Analysis · Mathematics 2022-04-20 Eric Ngondiep

Splitting methods constitute a well-established class of numerical schemes for solving convection-diffusion-reaction problems. They have been shown to be effective in solving problems with periodic boundary conditions. However, in the case…

Numerical Analysis · Mathematics 2025-02-14 Thi Tam Dang , Lukas Einkemmer , Alexander Ostermann

We consider Implicit-Explicit (IMEX) Runge-Kutta (R-K) schemes for hyperbolic systems with stiff relaxation in the so-called diffusion limit. In such regime the system relaxes towards a convection-diffusion equation. The first objective of…

Numerical Analysis · Mathematics 2015-05-30 S. Boscarino , L. Pareschi , G. Russo

We introduce a class of high order accurate, semi-implicit Runge-Kutta schemes in the general setting of evolution equations that arise as gradient flow for a cost function, possibly with respect to an inner product that depends on the…

Numerical Analysis · Mathematics 2021-10-04 Alexander Zaitzeff , Selim Esedoglu , Krishna Garikipati

Exponential Runge--Kutta methods have shown to be competitive for the time integration of stiff semilinear parabolic PDEs. The current construction of stiffly accurate exponential Runge--Kutta methods, however, relies on a convergence…

Numerical Analysis · Mathematics 2020-09-29 Vu Thai Luan

We present second-order optimally stable Implicit-Explicit (IMEX) Runge-Kutta (RK) schemes with application to a modified set of shallow water equations that can be used to model the dynamics of lava flows. The schemes are optimally stable…

Numerical Analysis · Mathematics 2025-09-12 Federico Gatti , Giuseppe Orlando

Explicit Runge-Kutta (RK) integration of hyperbolic initial-boundary value problems with time-dependent Dirichlet data often displays order reduction: the observed convergence order falls below the nominal order because the stage structure…

Numerical Analysis · Mathematics 2026-04-13 Giorgio Maria Cavallazzi , Miguel Pérez Cuadrado , Alfredo Pinelli

This work constructs and analyzes new efficient high-order two-derivative diagonally implicit Runge--Kutta (TDDIRK) schemes with optimized phase errors. Specifically, we present a convergence result for TDDIRK methods and investigate their…

Numerical Analysis · Mathematics 2025-12-18 Julius Ehigie , Vu Thai Luan

In this paper, we perform stability analysis for a class of second and third order accurate strong-stability-preserving modified Patankar Runge-Kutta (SSPMPRK) schemes, which were introduced in [4,5] and can be used to solve convection…

Numerical Analysis · Mathematics 2022-05-05 Juntao Huang , Thomas Izgin , Stefan Kopecz , Andreas Meister , Chi-Wang Shu

We develop two new sets of stable, rank-adaptive Dynamically Orthogonal Runge-Kutta (DORK) schemes that capture the high-order curvature of the nonlinear low-rank manifold. The DORK schemes asymptotically approximate the truncated singular…

Numerical Analysis · Mathematics 2023-08-08 Aaron Charous , Pierre F. J. Lermusiaux

A high-order accurate adjoint-based optimization framework is presented for unsteady multiphysics problems. The fully discrete adjoint solver relies on the high-order, linearly stable, partitioned solver introduced in [1], where different…

Numerical Analysis · Mathematics 2019-01-01 Daniel Z. Huang , Per-Olof Persson , Matthew J. Zahr

We introduce an automatic variationally stable analysis (AVS) for finite element (FE) computations of scalar-valued convection-diffusion equations with non-constant and highly oscillatory coefficients. In the spirit of least squares FE…

Numerical Analysis · Mathematics 2019-04-16 Victor M. Calo , Albert Romkes , Eirik Valseth

This article shows how to develop an efficient solver for a stabilized numerical space-time formulation of the advection-dominated diffusion transient equation. At the discrete space-time level, we approximate the solution by using…

Numerical Analysis · Mathematics 2023-06-30 Marcin Łoś , Paulina Sepulveda-Salas , Maciej Paszyński

A time discretization method is called strongly stable, if the norm of its numerical solution is nonincreasing. It is known that, even for linear semi-negative problems, many explicit Runge--Kutta (RK) methods fail to preserve this…

Numerical Analysis · Mathematics 2019-12-30 Zheng Sun , Chi-Wang Shu

This article is devoted to the construction of a new class of semi-Lagrangian (SL) schemes with implicit-explicit (IMEX) Runge-Kutta (RK) time stepping for PDEs involving multiple space-time scales. The semi-Lagrangian (SL) approach fully…

Numerical Analysis · Mathematics 2021-07-16 Walter Boscheri , Maurizio Tavelli , Lorenzo Pareschi

High-order adaptive time-stepping algorithms are of significant practical value and theoretical interest for accelerating long-time fluid-flow simulations and resolving complex dynamical behaviors. While several high-order implicit-explicit…

Numerical Analysis · Mathematics 2026-05-08 Hong-lin Liao , Xiaoming Wang , Xuping Wang , Cao Wen

This paper proposes an implicit family of sub-step integration algorithms grounded in the explicit singly diagonally implicit Runge-Kutta (ESDIRK) method. The proposed methods achieve third-order consistency per sub-step and thus the…

Numerical Analysis · Mathematics 2025-06-05 Jinze Li , Hua Li , Kaiping Yu , Rui Zhao

Sampling with Markov chain Monte Carlo methods often amounts to discretizing some continuous-time dynamics with numerical integration. In this paper, we establish the convergence rate of sampling algorithms obtained by discretizing smooth…

Machine Learning · Statistics 2020-02-04 Xuechen Li , Denny Wu , Lester Mackey , Murat A. Erdogdu