A remark about dimension reduction for supremal functionals: the case with convex domains
Elvira Zappale
TL;DR
This paper discusses a dimensional reduction technique for supremal functionals in the context of gradient-constrained problems, specifically focusing on 3D-2D reduction when the domain is convex.
Contribution
It provides new insights into dimensional reduction for supremal functionals in convex domains, extending previous results to this specific setting.
Findings
Dimensional reduction results are applicable to convex domains.
The paper establishes 3D-2D reduction for supremal functionals.
Results enhance understanding of gradient constrained problems in convex settings.
Abstract
An application of dimensional reduction results for gradient constrained problems is provided for 3D-2D dimension reduction for supremal functionals, in the case when the domain is convex.
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Taxonomy
TopicsAdvanced Mathematical Modeling in Engineering · Numerical methods in inverse problems · Nonlinear Partial Differential Equations