Vehicle Design and Optimization Model for Urban Air Mobility

2020 ◽  
Vol 57 (6) ◽  
pp. 1003-1013
Author(s):  
Arthur Brown ◽  
Wesley L. Harris
Author(s):  
Emilio M. Botero ◽  
Andrew Wendorff ◽  
Timothy MacDonald ◽  
Anil Variyar ◽  
Julius M. Vegh ◽  
...  

2014 ◽  
Vol 686 ◽  
pp. 160-163
Author(s):  
Xu Yin ◽  
Ming Juan Zhu ◽  
Ai Min Ji

Taking rectangular beam as an example, an integrated analytical method was proposed based on optimization software ISIGHT and finite element software ANSYS. First of all, in order to obtain the parameters of beam, the paper used ANSYS to establish the corresponding model and perform the simulation. Then, the optimization model was integrated with ISIGHT. At last, the model was optimized with NLPQL algorithm and the lightest weight of beam under specified constraints was obtained.


2019 ◽  
Vol 78 ◽  
pp. 101385 ◽  
Author(s):  
Jorge A. Sefair ◽  
Mónica Espinosa ◽  
Eduardo Behrentz ◽  
Andrés L. Medaglia

Author(s):  
Anthony M. Gjessing ◽  
Rafiqul I. Noorani

Abstract This paper describes the design, analysis and optimization of a Mini Baja off-road vehicle which will be used to compete with other schools of the nation. The project is undertaken by a group of mechanical engineering students of Loyola Marymount University. The finite element software package used for the optimization is COSMOS/M from SAC in Santa Monaco, CA. Suggestions on how to best use the software to support design decisions is also given. The optimization is made based on material and weight of the vehicle.


2015 ◽  
Vol 137 (4) ◽  
Author(s):  
Benjamin M. Geller ◽  
Thomas H. Bradley

System design tools including simulation and component optimization are an increasingly important component of the vehicle design process, placing more emphasis on early stages of design to reduce redesign and enable more robust design. This study focuses on the energy use and power management simulations used in vehicle design and optimization. Vehicle performance is most often evaluated in simulation, physical testing, and certification using drive cycle cases (also known as dynamometer schedules or drive schedules). In vehicle optimization studies, the information included in each drive cycle has been shown to influence the attributes of the optimized vehicle, and including more drive cycles in simulation optimizations has been shown to improve the robustness of the optimized design. This paper aims to quantitatively understand the effect of drive cycles on optimization in vehicle design and to specify drive cycles that can lead to robust vehicle design with minimal simulation. Two investigations are performed in service of this objective; investigation 1 tests how different combinations of drive cycles affect optimized vehicle performance and design variables (DV); investigation 2 evaluates the use of stochastic drive cycles for improving the robustness of vehicle designs without adding computational cost to the design and optimization process.


2021 ◽  
Author(s):  
Prajwal S. Prakasha ◽  
Patrick Ratei ◽  
Nabih Naeem ◽  
Björn Nagel ◽  
Oliver Bertram

2021 ◽  
Author(s):  
Bernardo Pacini ◽  
Anil Yildirim ◽  
Behdad Davoudi ◽  
Joaquim R. Martins ◽  
Karthikeyan Duraisamy
Keyword(s):  

2019 ◽  
Author(s):  
Michiel J. Schuurman ◽  
Borrdephong Rattanagraikanakorn ◽  
Christos Kassapoglou ◽  
Roeland De Breuker

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