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Full-Text Articles in Engineering
Trajectory Optimization Of Evtol And Conventional Aircraft: A Comparative Analysis Of Vortex Particle Method And Vortex Lattice + Blade Element Momentum Theory, Andrew Tagg, Ryan Anderson, Cibin Joseph, Andrew Ning
Trajectory Optimization Of Evtol And Conventional Aircraft: A Comparative Analysis Of Vortex Particle Method And Vortex Lattice + Blade Element Momentum Theory, Andrew Tagg, Ryan Anderson, Cibin Joseph, Andrew Ning
Faculty Publications
Trajectory optimization of aircraft transition maneuvers can significantly influence the design of these systems, particularly when making decisions about aircraft geometry, propulsion sizing, and control system design. This paper presents the trajectory optimization of air vehicles including electric vertical takeoff and landing (eVTOL) as well as conventional aircraft. The study evaluates the influence of fidelity in trajectory design by comparing the use of two aerodynamic methods in the context of trajectory optimization. The mid-fidelity method utilizes a vortex lattice method (VLM) to model lifting surfaces while employing blade element momentum theory (BEMT) to model rudimentary rotor-wing interactions. The high-fidelity approach …
Transfer-Learning-Enhanced Regression Generative Adversarial Networks For Optimal Evtol Takeoff Trajectory Prediction, Shuan Tai Yeh, Xiaosong Du
Transfer-Learning-Enhanced Regression Generative Adversarial Networks For Optimal Evtol Takeoff Trajectory Prediction, Shuan Tai Yeh, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Electric vertical takeoff and landing (eVTOL) aircraft represent a crucial aviation technology to transform future transportation systems. The unique characteristics of eVTOL aircraft include reduced noise, low pollutant emission, efficient operating cost, and flexible maneuverability, which in the meantime pose critical challenges to advanced power retention techniques. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimizations, however, adopt high-fidelity simulation models in an iterative manner resulting in a computationally intensive mechanism. In this work, we implement a surrogate-enabled inverse mapping optimization architecture, i.e., directly predicting optimal designs from design requirements (including …
Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang
Review Of Computational Models For Large-Scale Mdao Of Urban Air Mobility Concepts, Darshan Sarojini, Marius L. Ruh, Jiayao Yan, Luca Scotzniovsky, Nicholas C. Orndorff, Ru Xiang, Han Zhao, Joshua J. Krokowski, Michael Warner, Sebastiaan Pc Van Schie, Ashley Cronk, Alexandre T. R. Guibert, Jeffrey T. Chambers, Lauren Wolfe, Rachel Doring, Robin Despins, Cibin Joseph, Ryan Anderson, Andrew Ning, Hyunjune Gill, Seongkyu Lee, Zeyu Cheng, Zhi Cao, Chunting Mi, Y Shirley Meng, Christopher Silva, Jiun-Shyan Chen, H. Alicia Kim, John T. Hwang
Faculty Publications
The advent of Urban Air Mobility (UAM) has necessitated a paradigm shift in aircraft design from traditional regression methods to physics-based analysis and the use of modern computational methods. This paper explores the intricacies of UAM aircraft design, acknowledging the limitations of historical empirical equations and advocating for the use of physics-based tools in the early stages of the design process. It underscores the importance of Multidisciplinary Design, Analysis, and Optimization (MDAO) as a means to integrate physics-based tools for conceptual design, facilitating decisions on configuration and sizing. The paper presents a comprehensive survey and review of computational models across …
Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du
Optimal Tilt-Wing Evtol Takeoff Trajectory Prediction Using Regression Generative Adversarial Networks, Shuan Tai Yeh, Xiaosong Du
Mechanical and Aerospace Engineering Faculty Research & Creative Works
Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of …