Multidisciplinary Design of an Efficient Supersonic Air Vehicle (ESAV)

The Efficient Supersonic Air Vehicle (ESAV) is an aircraft concept designed to meet the ever-growing Air Force requirements for mission capability, combat survivability, and lifetime sustainability of future military aircraft. The supersonic/tailless, low-observable, and embedded-engine configuration inherently requires a multidisciplinary design and analysis approach. This approach makes it possible to achieve these requirements while capturing the complex, often coupled, physical phenomena present in its operating environment and flight regime (such as nonlinear aeroelastic, aerodynamic, and thermal-structural effects). In addition, it also allows researchers to exploit those complex physical effects and their interactions to achieve advanced aircraft capabilities and configurations otherwise unattainable.

Concept visual of aircraft Notional Efficient Superonic Air Vehicle (ESAV) Concept

Together Wright State University, the Air Force Research Laboratory's Multidisciplinary Science and Technology Center (MSTC) at Wright-Patterson AFB, and Virginia Tech have formed the Collaborative Center for Multidisciplinary Sciences (CCMS) to conduct research in advanced aircraft design methods. By employing structural design optimization methods and advanced uncertainty quantification techniques, CEPRO researchers, working within CCMS, seek to improve the ESAV design while accounting for uncertainties throughout structural parameters, uncertain operating environments, and advanced modeling processes.

Current CEPRO research efforts on the ESAV platform include:

  • transonic aeroelastic analysis for tailless aircraft
  • reliability-based design optimization for thermal environments
  • uncertainty quantification to address modeling uncertainties throughout the analysis process
  • integration of reliability-based design optimization methods in a novel collaborative design environment

Reliability-Based Design of ESAV Exhaust Structures

One common feature of modern low observability aircraft designs is embedded-engine integration. Designing an aircraft such that its engines are located inside the airframe allows for a smooth outer mold line and cooler exhaust gases and also prevents direct line of sight to hot engine components. This reduces the vehicle's observability by decreasing both radar and infrared detectability. While such a configuration affords tremendous tactical capabilities, it also creates a challenging structural design space. In addition to placing large heat sources inside the aircraft, embedded engines require a carefully designed nozzle through which high temperature exhaust gases are passed to the rear of the vehicle. Such a configuration results in a region of the aircraft located adjacent to and aft of the embedded engines that experiences an extreme structural loading environment characterized by elevated temperatures, acoustic effects, and aeroelastic flight loading. The structures that make up the exhaust nozzle and surrounding support in this region are known as engine exhaust-washed structures (EEWS). Their structural response varies depending on material selection, but is often characterized by non-linear behavior resulting from temperature dependent materials properties and large geometric displacements, in addition to both spatial and temporal temperature gradients.

To design these structures, size and topology optimization concepts are employed to increase structural life of engine exhaust-washed components. Parametric uncertainties, both aleatory and epistemic, in design parameters are also accounted for using modern uncertainty quantification techniques including Polynomial Chaos Expansion, Spectral Stochastic FEM, and Dempster's Theory of Evidence. This provides system-level effects of variability in the design and allows for a reduction of the design space through sensitivity analysis and lower-order simulations to gain a better understanding of the structural behavior inside an extreme exhaust-washed environment.

Exhaust-Washed Component on a B-2 Spirit

 

Transonic Aeroelastic Analysis and Design of Supersonic Tailless Air Vehicle Configurations

The transonic flight regime introduces a critical aeroelastic condition due to the aerodynamic nonlinearities prevalent in transonic flow. Thus, transonic aeroelastic analysis becomes an important factor in supersonic tailless air vehicle configurations. It has been shown from experience that in high-speed, long range aircraft designs, the nonlinear and complex flutter mechanisms give rise to dynamic aeroelastic instabilities such as flutter "chimneys" and limit cycle oscillations. These transonic aeroelastic concerns have arisen specifically in the upper transonic regime near Mach 1 for such designs. Limited knowledge and research exists in the upper transonic regime for aircraft designs of Mach 2 or higher. Therefore, the purpose of this research is to explore and predict the transonic aeroelastic behavior of supersonic tailless air vehicle configurations. Through this effort, the physics driving the configuration can be identified. As a result, delaying the occurrence of dynamic instabilities through optimization becomes feasible.

First and second bending mode and first and second torsion mode flutter diagrams

 

Quantification of Modeling Uncertainty in Aeroelastic Design

Traditional uncertainty quantification techniques in engineering design concentrate on the quantification of parametric uncertainties (uncertainties of the input design variables). In problems with a high degree of uncertainty associated with the modeling methodology, the uncertainties induced by the modeling process itself—model-form uncertainty—can become a significant source of uncertainty to the problem. This is the case with complex aeroelastic simulations, particularly in the transonic region of the design space. Thus, in addition to simply quantifying the parametric uncertainty in transonic problems, this work aims to include both model-form and predictive uncertainty. By developed and utilizing a complete modeling uncertainty framework, the results of the models can serve to be the driving force in identifying the necessity and parameters of any additional model validation measures such as wind tunnel testing or full scale design. This will ultimately lead to a more complete quantification of all the uncertainties in an aeroelastic design problem while minimizing the need for blanket experimental validation.

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