Multidisciplinary Optimization of a Hovering Wing with a Service-Oriented Framework and Experimental Model Validation

Structural Technology Evaluation and Analysis Program (STEAP). Delivery Order 0049: Computational Prototyping of Micro Air Vehicles

“…As a result, the force inputs associated with maintaining orbital position, hover, are inherited in the control design. This eliminates the need to prescribe an additional design constraint related to lift required in a similar optimization study reported by Bryson et al 15 Five different optimization cases were considered for various gust scenarios and different sets of design variables.…”

Multidisciplinary Design Optimization of Aerial Vehicles: A Review of Recent Advancements

“…A common application of MDF in aircraft design is the decomposition of coupled disciplines, and the most typical example of this is the concurrent evaluation of the mission performance (fuel requirements) and the estimation of the total weight [12,16,25,37,45,50,109]. Accordingly, further uses of the MDF architecture include the decoupling between performance and propulsion [12,18,51], aerodynamics and stability [12,61], and lastly, structures and loads which is a very common requirement when an accurate aeroelastic state must be determined [32,35,36,45,60,88,90,92,110].…”

“…An alternative that can increase the efficiency of the framework when the local hardware is already at its limits is to distribute the calculations over several computational units [2,11,17,93]. Provided that the optimization includes processes that can be executed in parallel, it becomes possible to take advantage of additional resources and thus make significant time savings by performing some of the analyses simultaneously [36,39,44,46,64,91,94,106,110]. Furthermore, this approach facilitates the decentralization of the framework, and therefore, it also enables to perform an optimization by using models which were developed independently by geographically separated teams of experts [18,82,96,110,112,115].…”

“…Provided that the optimization includes processes that can be executed in parallel, it becomes possible to take advantage of additional resources and thus make significant time savings by performing some of the analyses simultaneously [36,39,44,46,64,91,94,106,110]. Furthermore, this approach facilitates the decentralization of the framework, and therefore, it also enables to perform an optimization by using models which were developed independently by geographically separated teams of experts [18,82,96,110,112,115]. Nevertheless, parallelization can often have many disadvantages, and in fact, the final efficiency can often be limited by the network or data exchange speeds which are often the bottleneck [36].…”

“…On the whole, a validation process can insure the reliability of the design and provide supplementary confidence regarding the optimization [41,50], but on the downside, it is also expected to increase the overall process time and require the input of additional teams like, for example, simulation or prototyping experts [63]. According to this review, there are three possible methods for validating the results of the MDO process, and to this end, the most common approaches are to either use high-fidelity simulations [21,30,33,37,40,41,46,50,58,59,77,109,112]; physical prototypes [34,40,55,63,68,86,97,110,116]; or data from similar aircraft [12,17,21,25,26,79,85,91,92,101]. As far as prototyping is concerned, it can be seen that MDO and additive manufacturing techniques can be easily coupled, and it has been shown that this approach can be a promising combination for both the validation of the results and for establishing a solid foundation towards further subscale tests [34,40,97,116].…”