Computer Methods in Applied Mechanics and Engineering, Год журнала: 2024, Номер 432, С. 117439 - 117439
Опубликована: Окт. 9, 2024
Язык: Английский
Computer Methods in Applied Mechanics and Engineering, Год журнала: 2024, Номер 432, С. 117439 - 117439
Опубликована: Окт. 9, 2024
Язык: Английский
Computer Methods in Applied Mechanics and Engineering, Год журнала: 2025, Номер 436, С. 117713 - 117713
Опубликована: Янв. 4, 2025
Язык: Английский
Процитировано
1International Journal of Mechanical Sciences, Год журнала: 2024, Номер unknown, С. 109732 - 109732
Опубликована: Сен. 1, 2024
Язык: Английский
Процитировано
6Engineering Optimization, Год журнала: 2025, Номер unknown, С. 1 - 27
Опубликована: Янв. 3, 2025
In this article, an evolutionary isogeometric topology optimization method for elastoplastic materials while minimizing compliance is proposed. The material and constitutive models are grounded in the framework of finite strain nonlinear isotropic hardened plasticity, yield surfaces undergo updates through explicit numerical scheme elastic prediction/plasticity correction. application analysis intended to meet requirements high-order continuity between adjacent elements during transitional states. For evolutionary-based optimization, adjoint sensitivity expressions developed under displacement-loaded control, realization performed. Numerical results demonstrate that proposed performs well with different effective scenarios various specifications. comparison element shows technique yields fast yet accurate solutions.
Язык: Английский
Процитировано
0Thin-Walled Structures, Год журнала: 2025, Номер unknown, С. 112937 - 112937
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Computers and Geotechnics, Год журнала: 2025, Номер 180, С. 107104 - 107104
Опубликована: Янв. 23, 2025
Язык: Английский
Процитировано
0Computer Methods in Applied Mechanics and Engineering, Год журнала: 2025, Номер 437, С. 117789 - 117789
Опубликована: Янв. 30, 2025
Язык: Английский
Процитировано
0Advances in Engineering Software, Год журнала: 2025, Номер 203, С. 103886 - 103886
Опубликована: Фев. 16, 2025
Язык: Английский
Процитировано
0International Journal of Mechanical Sciences, Год журнала: 2025, Номер unknown, С. 110086 - 110086
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0Advanced Theory and Simulations, Год журнала: 2025, Номер unknown
Опубликована: Фев. 28, 2025
Abstract Crystal growth, particularly silicon, is pivotal in the semiconductor industry. It serves as foundation for electronic devices, solar cells, and various advanced technologies. The Czochralski method a prominent technique producing large single silicon crystals, well‐known its complexity due to precise control required over temperature gradients, interface dynamics, impurity incorporation— all critical factors growing uniform, high‐quality crystals. This paper proposes hybrid SyMO (Symbolic regression Multi‐objective Optimization) framework that combines Computational Fluid Dynamics (CFD), machine learning, mathematical optimization techniques investigate effects of process parameters, furnace geometries, radiation shield material properties on key crystal quality metrics. data set created from axisymmetric CFD simulations used fit symbolic models effectively capture complex nonlinear relationships, ensuring accurate deflection ratio predictions. SR equations are integrated into multi‐objective model simultaneously optimizes efficiency. obtained results validated through additional confirm accuracy solution. demonstrated successfully generalizes dependencies across parameters provides robust, solutions.
Язык: Английский
Процитировано
0Sustainability, Год журнала: 2025, Номер 17(6), С. 2463 - 2463
Опубликована: Март 11, 2025
The increasing demand for efficiency, brand consistency, and sustainability in automotive design has led to the exploration of innovative methods. This study investigated impact V-shaped Dynamic Morphology Curve (VDMC) on outcomes automobile wheel design. A total 24 designers took part, divided into an experimental group using VDMC a control traditional CAD uses parametric modeling accelerate iterations while maintaining identity. completed task 31.5% faster, achieved significantly higher consistency (9.1/10 vs. 7.8/10), reduced number by 53.2% compared group. Furthermore, made 50.9% fewer changes, indicating stability. These results show that improves efficiency reducing both time resource consumption ensuring greater alignment with guidelines. highlights potential transform practices offers notable benefits creative processes environmental impact. suggest integrating workflows could lead significant improvements industry beyond.
Язык: Английский
Процитировано
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