Fifth-Order A-WENO Schemes Based on the Adaptive Diffusion Central-Upwind Rankine-Hugoniot Fluxes

Bao-Shan Wang , Wai Sun Don , Alexander Kurganov , Yongle Liu

Communications on Applied Mathematics and Computation ›› 2021, Vol. 5 ›› Issue (1) : 295 -314.

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Communications on Applied Mathematics and Computation ›› 2021, Vol. 5 ›› Issue (1) : 295 -314. DOI: 10.1007/s42967-021-00161-2
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Fifth-Order A-WENO Schemes Based on the Adaptive Diffusion Central-Upwind Rankine-Hugoniot Fluxes

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Abstract

We construct new fifth-order alternative WENO (A-WENO) schemes for the Euler equations of gas dynamics. The new scheme is based on a new adaptive diffusion central-upwind Rankine-Hugoniot (CURH) numerical flux. The CURH numerical fluxes have been recently proposed in [Garg et al. J Comput Phys 428, 2021] in the context of second-order semi-discrete finite-volume methods. The proposed adaptive diffusion CURH flux contains a smaller amount of numerical dissipation compared with the adaptive diffusion central numerical flux, which was also developed with the help of the discrete Rankine-Hugoniot conditions and used in the fifth-order A-WENO scheme recently introduced in [Wang et al. SIAM J Sci Comput 42, 2020]. As in that work, we here use the fifth-order characteristic-wise WENO-Z interpolations to evaluate the fifth-order point values required by the numerical fluxes. The resulting one- and two-dimensional schemes are tested on a number of numerical examples, which clearly demonstrate that the new schemes outperform the existing fifth-order A-WENO schemes without compromising the robustness.

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Bao-Shan Wang, Wai Sun Don, Alexander Kurganov, Yongle Liu. Fifth-Order A-WENO Schemes Based on the Adaptive Diffusion Central-Upwind Rankine-Hugoniot Fluxes. Communications on Applied Mathematics and Computation, 2021, 5(1): 295-314 DOI:10.1007/s42967-021-00161-2

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Funding

National Natural Science Foundation of China(1201101343)

Ocean University of China(201712011)

National Natural Science Foundation of China(11771201)

Guangdong Provincial Key Laboratory of Computational Science and Material Design(2019B030301001)

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