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1
Understanding Complex Design Models Through Bayesian Networks and Network Theory
Understanding Complex Design Models Through Bayesian Networks and Network Theory
Wincott, Claire Marie. | University of Michigan | 2021
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A Novel Framework Utilizing Bayesian Networks Structured as Logical Syllogisms to Determine Sufficiency of Early Stage Ship Design Knowledge Queries
A Novel Framework Utilizing Bayesian Networks Structured as Logical Syllogisms to Determine Sufficiency of Early Stage Ship Design Knowledge Queries
Taylordean, Samantha Bunting. | University of Michigan | 2021
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3
Early-Stage Ship Design Operational Considerations as a Thin Abstraction Enabled by a Grid-Supported Markov Decision Process Directional Decision Ensemble Framework
Early-Stage Ship Design Operational Considerations as a Thin Abstraction Enabled by a Grid-Supported Markov Decision Process Directional Decision Ensemble Framework
Yuan, Hao. | University of Michigan | 2021
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4
High-Fidelity Hydrostructural Optimization of Composite Hydrodynamic Lifting Surfaces
High-Fidelity Hydrostructural Optimization of Composite Hydrodynamic Lifting Surfaces
Liao, Yingqian. | University of Michigan | 2021
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5
Physics-Informed Data-Driven Models for Ship Response Prediction Using Global Wave Data
Physics-Informed Data-Driven Models for Ship Response Prediction Using Global Wave Data
Schirmann, Matthew L. | University of Michigan | 2021
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6
A Quantitative Weld Sizing Criterion for Welded Connections in Lightweight Shipboard Structures: Modeling, Validation, and Structural Applications
A Quantitative Weld Sizing Criterion for Welded Connections in Lightweight Shipboard Structures: Modeling, Validation, and Structural Applications
Lu, Hanqing. | University of Michigan | 2021
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