Physics-constrained generative adversarial networks for rapid optimal takeoff trajectory designs

Samuel Sisk; Xiaosong Du

doi:10.1007/s00158-026-04358-y

Physics-constrained generative adversarial networks for rapid optimal takeoff trajectory designs

Samuel Sisk
, Xiaosong Du

Mechanical and Aerospace Engineering

Missouri University of Science and Technology

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	160
Journal	Structural and Multidisciplinary Optimization
Volume	69
Issue number	6
DOIs	https://doi.org/10.1007/s00158-026-04358-y
State	Published - Jun 2026

ASJC Scopus Subject Areas

Software
Control and Systems Engineering
Computer Science Applications
Computer Graphics and Computer-Aided Design
Control and Optimization

Keywords

Electric vertical takeoffand landing aircraft
Feasible space exploitation
Generative adversarial networks
Multidisciplinary analysis and optimization
Physics-constrained generative adversarial networks

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10.1007/s00158-026-04358-y

Cite this

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title = "Physics-constrained generative adversarial networks for rapid optimal takeoff trajectory designs",

keywords = "Electric vertical takeoffand landing aircraft, Feasible space exploitation, Generative adversarial networks, Multidisciplinary analysis and optimization, Physics-constrained generative adversarial networks",

author = "Samuel Sisk and Xiaosong Du",

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language = "English",

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AU - Sisk, Samuel

AU - Du, Xiaosong

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Y1 - 2026/6

KW - Electric vertical takeoffand landing aircraft

KW - Feasible space exploitation

KW - Generative adversarial networks

KW - Multidisciplinary analysis and optimization

KW - Physics-constrained generative adversarial networks

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Physics-constrained generative adversarial networks for rapid optimal takeoff trajectory designs

ASJC Scopus Subject Areas

Keywords

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