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Mathematical and Computational Applications, Volume 28, Issue 4

August 2023 - 14 articles

Cover Story: To determine buckling loads in cracked Euler–Bernoulli columns within a Winkler elastic medium, the utilized beam can be modelled as two continuous segments connected by a massless rotational spring at the cracked section, whose rotation discontinuity is proportional to the bending moment transmitted through this section. By solving the differential equations for the buckling behavior by considering the corresponding boundary conditions, as well as compatibility and jump conditions at the cracked section, the buckling load is calculated. These loads vary as a function of the support type, soil stiffness, crack position, and initial crack length. Comparison with existing partial approaches highlights the interaction between the parameters on the buckling loads. View this paper

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Article

1 Citations

2,008 Views

12 Pages

Effect of Chrome and Vanadium on the Behavior of Hydrogen and Helium in Tungsten

Meicong Li,
Zheng Zhang,
Yangyang Li,
Qiang Zhao,
Mei Huang and
Xiaoping Ouyang

Math. Comput. Appl.2023, 28(4), 81;https://doi.org/10.3390/mca28040081

3 July 2023

Tungsten is a promising material for nuclear fusion reactors, but its performance can be degraded by the accumulation of hydrogen (H) and helium (He) isotopes produced by nuclear reactions. This study investigates the effect of chrome (Cr) and vanadi...

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Article

5 Citations

2,070 Views

20 Pages

Vehicle Make and Model Recognition as an Open-Set Recognition Problem and New Class Discovery

Diana-Itzel Vázquez-Santiago,
Héctor-Gabriel Acosta-Mesa and
Efrén Mezura-Montes

Math. Comput. Appl.2023, 28(4), 80;https://doi.org/10.3390/mca28040080

3 July 2023

One of the main limitations of traditional neural-network-based classifiers is the assumption that all query data are well represented within their training set. Unfortunately, in real-life scenarios, this is often not the case, and unknown class dat...

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Article

2,576 Views

12 Pages

Solve High-Dimensional Reflected Partial Differential Equations by Neural Network Method

Xiaowen Shi,
Xiangyu Zhang,
Renwu Tang and
Juan Yang

Math. Comput. Appl.2023, 28(4), 79;https://doi.org/10.3390/mca28040079

24 June 2023

Reflected partial differential equations (PDEs) have important applications in financial mathematics, stochastic control, physics, and engineering. This paper aims to present a numerical method for solving high-dimensional reflected PDEs. In fact, ov...

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Article

5 Citations

3,963 Views

16 Pages

A New Method for Improving Inverse Finite Element Method Material Characterization for the Mooney–Rivlin Material Model through Constrained Optimization

John Dean Van Tonder,
Martin Philip Venter and
Gerhard Venter

Math. Comput. Appl.2023, 28(4), 78;https://doi.org/10.3390/mca28040078

24 June 2023

The inverse finite element method is a technique that can be used for material model parameter characterization. The literature shows that this approach may get caught in the local minima of the design space. These local minimum solutions often fit t...

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