A Computational Sketch-Based Approach Towards Optimal Product Design Solutions
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| Publicado en: | Applied Sciences vol. 15, no. 5 (2025), p. 2413 |
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| Autor principal: | |
| Publicado: |
MDPI AG
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2076-3417 | ||
| 024 | 7 | |a 10.3390/app15052413 |2 doi | |
| 035 | |a 3176306262 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231338 |2 nlm | ||
| 100 | 1 | |a Charalampous, Paschalis | |
| 245 | 1 | |a A Computational Sketch-Based Approach Towards Optimal Product Design Solutions | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This paper presents a numerical sketch-based methodology to achieve optimal product design solutions, bridging the gap between initial conceptual sketches and advanced engineering analyses. The proposed approach enables the transformation of simple hand-drawn sketches into digital models suitable for complex computational simulations and design optimization. Using computer vision algorithms, sketches are processed to generate digital design components that serve as inputs for Finite Element Analysis (FEA). In order to further enhance the overall design process, topology optimization (TO) is also performed, iteratively refining the geometry to achieve optimal material distribution for improved structural performance. Additionally, Adaptive Mesh Refinement (AMR) techniques are applied to ensure computational efficiency and accuracy by dynamically refining the mesh in regions of high complexity or stress concentration. The synergy of sketch-based modeling, FEA, TO, and AMR demonstrates significant potential in reducing design cycles while maintaining high-performance standards. Finally, it should be noted that the proposed pipeline consists of a fully automated procedure, hence it could reduce the learning curve for the designers, enabling companies to onboard employees faster and integrate advanced design techniques into their workflows without extensive training. The above-mentioned modules render the introduced approach particularly suitable for applications in product design development that can be utilized in several industries like mechanical, manufacturing, and furniture. | |
| 653 | |a Load | ||
| 653 | |a Simulation | ||
| 653 | |a Design optimization | ||
| 653 | |a Physics | ||
| 653 | |a Fluid dynamics | ||
| 653 | |a Open source software | ||
| 653 | |a Computer aided design--CAD | ||
| 653 | |a Neural networks | ||
| 653 | |a Methods | ||
| 653 | |a Automation | ||
| 653 | |a Designers | ||
| 653 | |a Performance evaluation | ||
| 653 | |a Boundary conditions | ||
| 653 | |a Generative artificial intelligence | ||
| 653 | |a Product design | ||
| 653 | |a Computer aided engineering--CAE | ||
| 653 | |a Efficiency | ||
| 653 | |a Algorithms | ||
| 773 | 0 | |t Applied Sciences |g vol. 15, no. 5 (2025), p. 2413 | |
| 786 | 0 | |d ProQuest |t Publicly Available Content Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3176306262/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3176306262/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3176306262/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |