Real-time generative design of diverse, "truly" optimized structures with controllable structural complexities Article Swipe
Zongliang Dua
,
Xinyu Ma
,
Wenyu Hao
,
Liang Yuan
,
Xiaoyu Zhang
,
Hongzhi Luo
,
Xu Guo
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.08981
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2401.08981
Compared with traditional design methods, generative design significantly attracts engineers in various disciplines. In thiswork, howto achieve the real-time generative design of optimized structures with various diversities and controllable structural complexities is investigated. To this end, a modified Moving Morphable Component (MMC) method together with novel strategies are adopted to generate high-quality dataset. The complexity level of optimized structures is categorized by the topological invariant. By improving the cost function, the WGAN is trained to produce optimized designs with the input of loading position and complexity level in real time. It is found that, diverse designs with a clear load transmission path and crisp boundary, even not requiring further optimization and different from any reference in the dataset, can be generated by the proposed model. This method holds great potential for future applications of machine learning enhanced intelligent design.
Related Topics
Concepts
Generative grammar
Computer science
Generative Design
Generative model
Path (computing)
Function (biology)
Component (thermodynamics)
Boundary (topology)
Artificial intelligence
Machine learning
Engineering
Mathematics
Thermodynamics
Metric (unit)
Mathematical analysis
Evolutionary biology
Physics
Programming language
Operations management
Biology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2401.08981
- https://arxiv.org/pdf/2401.08981
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391013242
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391013242Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2401.08981Digital Object Identifier
- Title
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Real-time generative design of diverse, "truly" optimized structures with controllable structural complexitiesWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-01-17Full publication date if available
- Authors
-
Zongliang Dua, Xinyu Ma, Wenyu Hao, Liang Yuan, Xiaoyu Zhang, Hongzhi Luo, Xu GuoList of authors in order
- Landing page
-
https://arxiv.org/abs/2401.08981Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2401.08981Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2401.08981Direct OA link when available
- Concepts
-
Generative grammar, Computer science, Generative Design, Generative model, Path (computing), Function (biology), Component (thermodynamics), Boundary (topology), Artificial intelligence, Machine learning, Engineering, Mathematics, Thermodynamics, Metric (unit), Mathematical analysis, Evolutionary biology, Physics, Programming language, Operations management, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.invariant. | 64 |
| abstract_inverted_index.strategies | 46 |
| abstract_inverted_index.structural | 29 |
| abstract_inverted_index.structures | 23, 58 |
| abstract_inverted_index.categorized | 60 |
| abstract_inverted_index.diversities | 26 |
| abstract_inverted_index.intelligent | 137 |
| abstract_inverted_index.topological | 63 |
| abstract_inverted_index.traditional | 2 |
| abstract_inverted_index.applications | 132 |
| abstract_inverted_index.complexities | 30 |
| abstract_inverted_index.controllable | 28 |
| abstract_inverted_index.disciplines. | 12 |
| abstract_inverted_index.high-quality | 51 |
| abstract_inverted_index.optimization | 109 |
| abstract_inverted_index.transmission | 100 |
| abstract_inverted_index.investigated. | 32 |
| abstract_inverted_index.significantly | 7 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4000000059604645 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile |