Evaluation of Multidisciplinary Optimization (MDO) Techniques Applied to a Reusable Launch Vehicle
AE 8900 MS Special Problems ReportOptimization of complex engineering systems has always been an integral part of design. Due to the size and complexity of aerospace systems the design of a whole system is broken down into multiple disciplines ...
Brown, Nichols
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Analysis of Logistics Linkage by Digital Twins Technology and Lightweight Deep Learning. [PDF]
Qiao L, Cheng Y.
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Poly(vinylidene fluoride) Intestinal Sleeve Implants for the Treatment of Obesity and Type 2 Diabetes. [PDF]
Chang HM, Zhan WP, Tsai HC, Yang MR.
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Conceptual design and optimization methodology for box wing aircraft [PDF]
A conceptual design optimization methodology was developed for a medium range box wing aircraft. A baseline conventional cantilever wing aircraft designed for the same mis- sion and payload was also optimized alongside a baseline box wing aircraft.
Jemitola, Paul Olugbeji
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Evolutionary Mahalanobis Distance-Based Oversampling for Multi-Class Imbalanced Data Classification. [PDF]
Yao L, Lin TB.
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Multi-Criteria Conceptual Design Analysis of Single Stage Suborbital Launch Vehicle
This paper presents the design analysis of a suborbital launch vehicle by performing a multidisciplinary optimization analysis. The design problem consists of establishing the optimized launch scenario using the interior point optimization method.
Hemza Layachi +3 more
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Multidisciplinary Design Optimization of Unmanned Aerial Vehicle under Uncertainty
Uncertainty-based multidisciplinary design optimization considers probabilistic variables and parameters and provides an approach to account for sources of uncertainty in design optimization.
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Kick Solid Rocket Motor Multidisciplinary Design Optimization Using Genetic Algorithm
http://dx.doi.org/10.5028/jatm.v5i3.225 In this paper, a multidisciplinary design optimization (MDO) approach of a solid propellant kick rocket motor is considered. A genetic algorithm optimization method has been used.
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Fuzzy optimal control of multilayer coverage based on radon exhalation dynamics in uranium tailings. [PDF]
Zhang M, Dai J.
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An Automated Hybrid Deep Learning-based Model for Breast Cancer Detection using Mammographic Images [PDF]
Gandhi O, Rao SNT, Prasad MHMK.
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