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20192025
most citedThe generalized scalar auxiliary variable approach (G-SAV) for gradient flows

7 citations · 12 across the 6 of their papers we have counts for

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8 papers · 1 filter

math.NA2025

Adaptive time-stepping and maximum-principle preserving Lagrangian schemes for gradient flows

Qianqian Liu, Wenbin Chen, Jie Shen +1

We develop in this paper an adaptive time-stepping approach for gradient flows with distinct treatments for conservative and non-conservative dynamics. For the non-conservative gra…

math.NA20241 cited

Unique solvability and error analysis of the Lagrange multiplier approach for gradient flows

Qing Cheng, Jie Shen, Cheng Wang

The unique solvability and error analysis of the original Lagrange multiplier approach proposed in [8] for gradient flows is studied in this paper. We identify a necessary and suff…

math.NA20212 cited

A new Lagrange multiplier approach for constructing structure-preserving schemes, II. bound preserving

Qing Cheng, Jie Shen

In the second part of this series, we use the Lagrange multiplier approach proposed in the first part \cite{CheS21} to construct efficient and accurate bound and/or mass preserving…

math.NA2021

Modeling and simulation of nuclear architecture reorganization process using a phase field approach

Qing Cheng, Pourya Delafrouz, Jie Liang +2

We develop a special phase field/diffusive interface method to model the nuclear architecture reorganization process. In particular, we use a Lagrange multiplier approach in the ph…

math.NA20207 cited

The generalized scalar auxiliary variable approach (G-SAV) for gradient flows

Qing Cheng

We establish a general framework for developing, efficient energy stable numerical schemes for gradient flows and develop three classes of generalized scalar auxiliary variable app…

math.NA20192 cited

Global constraints preserving SAV schemes for gradient flows

Qing Cheng, Jie Shen

We develop several efficient numerical schemes which preserve exactly the global constraints for constrained gradient flows. Our schemes are based on the SAV approach combined with…