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Strong Stability Preserving Multistage Integration Methods [PDF]
Mathematical Modelling and Analysis, 2015 In this paper we systematically investigate explicit strong stability preserving (SSP) multistage integration methods, a subclass of general linear methods (GLMs), of order p and stage order q ≤ p.
Giuseppe Izzo, Zdzislaw Jackiewicz
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Strong Stability Preserving Runge–Kutta and Linear Multistep Methods
Bulletin of the Iranian Mathematical Society, 2022 AbstractThis paper reviews strong stability preserving discrete variable methods for differential systems. The strong stability preserving Runge–Kutta methods have been usually investigated in the literature on the subject, using the so-called Shu–Osher representation of these methods, as a convex combination of first-order steps by forward Euler ...
Zdzislaw Jackiewicz, Giuseppe Izzo
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On the stability of strong-stability-preserving modified Patankar–Runge–Kutta schemes
ESAIM: Mathematical Modelling and Numerical Analysis, 2023 In this paper, we perform a stability analysis for classes of second and third order accurate strong-stability-preserving modified Patankar–Runge–Kutta (SSPMPRK) schemes, which were introduced in Huang and Shu [J. Sci. Comput. 78 (2019) 1811–1839] and Huang et al. [J. Sci. Comput.
Juntao Huang +4 more
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Strong Stability Preserving Integrating Factor Runge--Kutta Methods [PDF]
SIAM Journal on Numerical Analysis, 2018 Strong stability preserving (SSP) Runge-Kutta methods are often desired when evolving in time problems that have two components that have very different time scales. Where the SSP property is needed, it has been shown that implicit and implicit-explicit methods have very restrictive time-steps and are therefore not efficient.
Leah Isherwood +2 more
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Strong Stability Preserving Two-step Runge–Kutta Methods [PDF]
SIAM Journal on Numerical Analysis, 2011 We investigate the strong stability preserving (SSP) property of two-step Runge-Kutta (TSRK) methods. We prove that all SSP TSRK methods belong to a particularly simple subclass of TSRK methods, in which stages from the previous step are not used. We derive simple order conditions for this subclass.
David I Ketcheson +2 more
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Strong Stability Preserving Two-Derivative Two-Step Runge-Kutta Methods
MathematicsIn this study, we introduce the explicit strong stability preserving (SSP) two-derivative two-step Runge-Kutta (TDTSRK) methods. We propose the order conditions using Albrecht’s approach, comparing to the order conditions expressed in terms of rooted ...
Xueyu Qin, Zhenhua Jiang, Chao Yan
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A Static-to-Temporal Framework for Interpretable Camera Lens Soiling Severity Estimation in Autonomous Driving [PDF]
SensorsCamera lens soiling can severely degrade visual perception in autonomous driving, making reliable soiling severity estimation essential for camera-health monitoring and downstream perception safety.
Fan Yang +3 more
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Strong Stability Preserving Runge-Kutta Methods Applied to Water Hammer Problem
Trends in Computational and Applied Mathematics, 2022 The characteristic method of lines is the most used numerical method applied to the water hammer problem. It transforms a system of partial differential equations involving the independent variables time and space in two ordinary differential equations ...
D. F. G. Santiago +3 more
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Krylov SSP Integrating Factor Runge–Kutta WENO Methods
Mathematics, 2021 Weighted essentially non-oscillatory (WENO) methods are especially efficient for numerically solving nonlinear hyperbolic equations. In order to achieve strong stability and large time-steps, strong stability preserving (SSP) integrating factor (IF ...
Shanqin Chen
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Robust Prediction of Sea Surface Temperature Based on SSPGAN
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Sea surface temperature (SST) is an important parameter for monitoring ocean phenomena. Driven by ocean satellite Big Data, deep neural networks have achieved state-of-the-art performance in forecasting fields of oceanic phenomena.
Xiaofang Yao +4 more
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