基于阿基米德对偶原理的平面曲线的离散曲率

IF 0.5 4区 数学 Q4 MATHEMATICS, APPLIED Russian Journal of Numerical Analysis and Mathematical Modelling Pub Date : 2022-04-01 DOI:10.1515/rnam-2022-0007
V. Garanzha, L. Kudryavtseva, Dmitry A. Makarov
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引用次数: 0

摘要

摘要通过构造相互对偶的折线对序列,引入平面曲线的离散曲率。对于由有限数量的具有确定(正或负)曲率的正则广义螺旋碎片组成的分段规则曲线,我们的离散曲率从下到上近似于精确的平均曲率。为了得到这些估计值,我们应该提供一个距离函数来计算平面上任意点在曲线上的最近点。通过对折线的精化,精化曲线段上的平均曲率收敛于曲率的逐点值,从而得到了曲率的良好稳定的局部逼近。对于重要的工程情况,当曲线仅由内切(原始)折线近似且无法获得精确的距离函数时,我们提供了几种允许构建双折线和离散曲率的技术的比较分析,并评估了它们创建平均曲率的下限和上限估计的能力。
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Discrete curvatures for planar curves based on Archimedes’ duality principle
Abstract We introduce discrete curvatures for planar curves based on the construction of sequences of pairs of mutually dual polylines. For piecewise-regular curves consisting of a finite number of fragments of regular generalized spirals with definite (positive or negative) curvatures our discrete curvatures approximate the exact averaged curvature from below and from above. In order to derive these estimates one should provide a distance function allowing to compute the closest point on the curve for an arbitrary point on the plane.With refinement of the polylines, the averaged curvature over refined curve segments converges to the pointwise values of the curvature and, thus, we obtain a good and stable local approximation of the curvature. For the important engineering case when the curve is approximated only by the inscribed (primal) polyline and the exact distance function is not available, we provide a comparative analysis for several techniques allowing to build dual polylines and discrete curvatures and evaluate their ability to create lower and upper estimates for the averaged curvature.
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来源期刊
CiteScore
1.40
自引率
16.70%
发文量
31
审稿时长
>12 weeks
期刊介绍: The Russian Journal of Numerical Analysis and Mathematical Modelling, published bimonthly, provides English translations of selected new original Russian papers on the theoretical aspects of numerical analysis and the application of mathematical methods to simulation and modelling. The editorial board, consisting of the most prominent Russian scientists in numerical analysis and mathematical modelling, selects papers on the basis of their high scientific standard, innovative approach and topical interest. Topics: -numerical analysis- numerical linear algebra- finite element methods for PDEs- iterative methods- Monte-Carlo methods- mathematical modelling and numerical simulation in geophysical hydrodynamics, immunology and medicine, fluid mechanics and electrodynamics, geosciences.
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