DeepGeo: Deep Geometric Mapping for Automated and Effective Parameterization in Aerodynamic Shape Optimization Article Swipe
Zhen Wei
,
Aobo Yang
,
Jichao Li
,
Michaël Bauerheim
,
Rhea P. Liem
,
Pascal Fua
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2514/6.2024-3839
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.2514/6.2024-3839
Aerodynamic shape optimization (ASO) is a key technique in aerodynamic designs, aimed at enhancing an object's physical performance while adhering to specific constraints. Traditional parameterization methods for ASO often require substantial manual tuning and are only limited to surface deformations. This paper introduces the Deep Geometric Mapping (DeepGeo) model, a fully automatic neural-network-based parameterization method for complex geometries. DeepGeo utilizes its universal approximation capability to provide large shape deformation freedom with global shape smoothness, while achieving effective optimization in high-dimensional design spaces. Additionally, DeepGeo integrates volumetric mesh deformation, simplifying the ASO pipeline. By eliminating the need for extensive datasets and hyperparameter tuning, DeepGeo significantly reduces implementation complexity and cost. Multiple case studies that use the same parameterization settings, including the two-dimensional circle-to-airfoil optimization, the three-dimensional CRM wing optimization and the Blended-Wing-Body aircraft optimization, demonstrate DeepGeo's effectiveness compared to state-of-the-art free-form deformation methods. This research highlights DeepGeo's potential to automate ASO, making it more accessible and efficient.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.2514/6.2024-3839
- OA Status
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4402689547Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2514/6.2024-3839Digital Object Identifier
- Title
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DeepGeo: Deep Geometric Mapping for Automated and Effective Parameterization in Aerodynamic Shape OptimizationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-27Full publication date if available
- Authors
-
Zhen Wei, Aobo Yang, Jichao Li, Michaël Bauerheim, Rhea P. Liem, Pascal FuaList of authors in order
- Landing page
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https://doi.org/10.2514/6.2024-3839Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://infoscience.epfl.ch/handle/20.500.14299/208896.2Direct OA link when available
- Concepts
-
Aerodynamics, Computer science, Artificial intelligence, Aerospace engineering, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.datasets | 98 |
| abstract_inverted_index.designs, | 10 |
| abstract_inverted_index.methods. | 141 |
| abstract_inverted_index.object's | 15 |
| abstract_inverted_index.physical | 16 |
| abstract_inverted_index.research | 143 |
| abstract_inverted_index.specific | 21 |
| abstract_inverted_index.utilizes | 59 |
| abstract_inverted_index.(DeepGeo) | 47 |
| abstract_inverted_index.DeepGeo's | 134, 145 |
| abstract_inverted_index.Geometric | 45 |
| abstract_inverted_index.achieving | 75 |
| abstract_inverted_index.automatic | 51 |
| abstract_inverted_index.effective | 76 |
| abstract_inverted_index.enhancing | 13 |
| abstract_inverted_index.extensive | 97 |
| abstract_inverted_index.free-form | 139 |
| abstract_inverted_index.including | 118 |
| abstract_inverted_index.pipeline. | 91 |
| abstract_inverted_index.potential | 146 |
| abstract_inverted_index.settings, | 117 |
| abstract_inverted_index.technique | 7 |
| abstract_inverted_index.universal | 61 |
| abstract_inverted_index.accessible | 153 |
| abstract_inverted_index.capability | 63 |
| abstract_inverted_index.complexity | 106 |
| abstract_inverted_index.efficient. | 155 |
| abstract_inverted_index.highlights | 144 |
| abstract_inverted_index.integrates | 84 |
| abstract_inverted_index.introduces | 42 |
| abstract_inverted_index.volumetric | 85 |
| abstract_inverted_index.Aerodynamic | 0 |
| abstract_inverted_index.Traditional | 23 |
| abstract_inverted_index.aerodynamic | 9 |
| abstract_inverted_index.deformation | 68, 140 |
| abstract_inverted_index.demonstrate | 133 |
| abstract_inverted_index.eliminating | 93 |
| abstract_inverted_index.geometries. | 57 |
| abstract_inverted_index.performance | 17 |
| abstract_inverted_index.simplifying | 88 |
| abstract_inverted_index.smoothness, | 73 |
| abstract_inverted_index.substantial | 30 |
| abstract_inverted_index.constraints. | 22 |
| abstract_inverted_index.deformation, | 87 |
| abstract_inverted_index.optimization | 2, 77, 127 |
| abstract_inverted_index.Additionally, | 82 |
| abstract_inverted_index.approximation | 62 |
| abstract_inverted_index.deformations. | 39 |
| abstract_inverted_index.effectiveness | 135 |
| abstract_inverted_index.optimization, | 122, 132 |
| abstract_inverted_index.significantly | 103 |
| abstract_inverted_index.hyperparameter | 100 |
| abstract_inverted_index.implementation | 105 |
| abstract_inverted_index.two-dimensional | 120 |
| abstract_inverted_index.high-dimensional | 79 |
| abstract_inverted_index.parameterization | 24, 53, 116 |
| abstract_inverted_index.state-of-the-art | 138 |
| abstract_inverted_index.Blended-Wing-Body | 130 |
| abstract_inverted_index.circle-to-airfoil | 121 |
| abstract_inverted_index.three-dimensional | 124 |
| abstract_inverted_index.neural-network-based | 52 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/13 |
| sustainable_development_goals[0].score | 0.5799999833106995 |
| sustainable_development_goals[0].display_name | Climate action |
| citation_normalized_percentile.value | 0.80901406 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |