线性弹性模型中摩擦问题的灵敏度分析和优化控制

IF 1.6 2区 数学 Q2 MATHEMATICS, APPLIED Applied Mathematics and Optimization Pub Date : 2024-08-01 DOI:10.1007/s00245-024-10156-z
Loïc Bourdin, Fabien Caubet, Aymeric Jacob de Cordemoy
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引用次数: 0

摘要

本文在没有任何正则化程序的情况下,研究了线性弹性模型中涉及(非光滑)特雷斯卡摩擦定律的机械摩擦问题的敏感性分析。为此,我们采用了基于凸分析和变分分析先进工具的最新方法。确切地说,我们通过与相应的特雷斯卡摩擦函数相关的近算子来表达所谓的特雷斯卡摩擦问题的解。然后,利用两次表微分的扩展版本,我们证明了参数化特雷斯卡摩擦问题解的可微分性,将其导数表征为涉及切向西格诺里尼单边条件的边界值问题解。最后,我们利用这一结果研究并数值求解了与特雷斯卡摩擦模型相关的最优控制问题。
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Sensitivity Analysis and Optimal Control for a Friction Problem in the Linear Elastic Model

This paper investigates, without any regularization procedure, the sensitivity analysis of a mechanical friction problem involving the (nonsmooth) Tresca friction law in the linear elastic model. To this aim a recent methodology based on advanced tools from convex and variational analyses is used. Precisely we express the solution to the so-called Tresca friction problem thanks to the proximal operator associated with the corresponding Tresca friction functional. Then, using an extended version of twice epi-differentiability, we prove the differentiability of the solution to the parameterized Tresca friction problem, characterizing its derivative as the solution to a boundary value problem involving tangential Signorini’s unilateral conditions. Finally our result is used to investigate and numerically solve an optimal control problem associated with the Tresca friction model.

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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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