Application of MDO to large subsonic transport aircraft

Velden, Alexander Van der; Kokan, David; Kelm, Roland; Mertens, J.

doi:10.2514/6.2000-844

Cited by 14 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is consistent with previous work we have found on the subject, which we hope to improve upon in part with the layout of a detailed methodology. 3 Once an optimized family of airfoils is created, a surrogate must be made that can be used to generate airfoil properties (drag in this case) in conditions that have not been explicitly calculated. To do this, a special fit is used as described below to create a surrogate for drag results.…”

Section: A General Methodsmentioning

confidence: 99%

Increasing Conceptual Design Fidelity with Prebuilt Airfoil Databases

MacDonald

Alonso

2018

2018 Multidisciplinary Analysis and Optimization Conference

View full text Add to dashboard Cite

Due to time and monetary constraints, the conceptual design process for new aircraft is typically limited to inexpensive low-fidelity methods. Unfortunately, these methods generally only provide the fidelity necessary to confidently go forward with a new design when they have been fitted to previous aircraft of the same type. The conceptual design process has difficulty producing accurate estimates of performance in unconventional aircraft. To remedy this, new methods must be developed that can produce higher fidelity results without a significant increase in cost. Here we present a method to do this in the aerodynamic analysis. First, we generate a large database of airfoils that are optimized using CFD to minimize drag in a variety of flight conditions that are likely to be seen on the wing of a subsonic transport aircraft. We then present methods to integrate these airfoils along an arbitrary wing to find the minimum possible drag. This process is meant to mimic the "expert designer" often pointed to in current correlation equations for determining the drag of a wing. Since the airfoils are generated before hand in a manner that is easy to parallelize, this process is not substantially more expensive than other methods for determining the aerodynamic properties of an aircraft at the conceptual level.

show abstract

Section: A General Methodsmentioning

confidence: 99%

Increasing Conceptual Design Fidelity with Prebuilt Airfoil Databases

MacDonald

Alonso

2018

2018 Multidisciplinary Analysis and Optimization Conference

View full text Add to dashboard Cite

show abstract

“…The flight fuel for a complete mission profile is defined as the release fuel (total fuel) less the summation of quantities devoted to block maneuvering, hold, and diversion. Adhering to this fuel balance relationship, the fractional change in & flt is ◃& flt ◃& rfl man ◃& man hld ◃& hld div ◃& div 1 man hld div (9) where the partial fractions are referenced to the seed as…”

Section: Integrated Range Modelmentioning

confidence: 99%

“…Morris and Gantois [8] described a European Union funded research program into MDO, which involved the majority of the European aircraft industry together with university and research organizations. Van der Velden et al [9] also developed a successful MDO methodology for the preliminary design of the Airbus A3XX, by integrating the FAME-W weight model from DASA-Airbus (Hamburg) and the Globair aerodynamics model from DASA-Airbus (Bremen) into the POINTER TM MDO framework from Synaps, Inc. (now part of Engineous Software, Inc.).…”

mentioning

confidence: 98%

Preliminary Aerostructural Optimization of a Large Business Jet

Piperni

Abdo

Kafyeke

et al. 2007

Journal of Aircraft

View full text Add to dashboard Cite

An overview of an industrial approach to the aerostructural optimization of a large business jet is presented herein. The optimization methodology is based on the integration of aerodynamic and structural analysis codes that combine computational, analytical, and semi-empirical methods, validated in an aircraft design environment. The aerodynamics subspace is analyzed with a three-dimensional transonic small disturbance code capable of predicting the drag of a complete, trimmed aircraft within engineering accuracy. The design of the wing structure is accomplished using a quasi-analytical method that defines the layout of the ribs and geometry of the spar webs, spar caps, and skin-stringer panels, and predicts the wing flexural properties and weight distribution. In addition, the prediction of operating economics as well as the integrated en route performance is coupled into the scheme by way of fractional change functional transformations. To illustrate the automated design system capabilities, the methodology is applied to the optimization of a large business jet comprising winglets, rear-mounted engines, and a T-tail configuration. The aircraft-level design optimization goal in this instance is to minimize a cost function for a fixed range mission assuming a constant maximum takeoff weight.Nomenclature A sk = cross-sectional area of skin, in: 2 A st = cross-sectional area of stiffener, in: 2 AR = aspect ratio C crew = hourly cost of the flight (and cabin) crew, CU=h C D = total drag coefficient C fees = landing fee charge based on maximum landing weight, CU=lb C fuel = price of fuel, CU=lb C L = operating lift coefficient C mnt = time-dependent airframe and engine maintenance cost, CU=h C mnt cyc = cyclic airframe maintenance cost, CU C mnt eng = cyclic engine maintenance component that is assumed to have a functional dependency with the engine derate level, CU E = relative or absolute error f = function; substitution parameter in modified integrated range model formulation g = acceleration due to gravity, ft=s 2 H = fuel calorific value, Btu=lb k aero = control factor used to regulate the extent of coupling (congruity or otherwise) between high-speed and intermediate-speed aerodynamic efficiency k clb = constant of proportionality required to predict all-up weight at top of climb k M = empirically derived coefficient used to establish a simplified relationship between overall power plant efficiency and Mach number k res = constant of proportionality establishing linear relationship between fractional change in total reserve fuel and fractional change in zero-fuel weight L=D = lift-to-drag ratio M = Mach number R = range, nm t = time, as in block or flight time, h V = forward speed [(knots, calibrated airspeed (KCAS) or knots, indicated airspeed (KIAS)] W= weight of a given component or assembly, all-up weight, lb x, y = arbitrary independent parameters or design variables z = arbitrary dependent parameters or objective functions = exponent, flight profile correction coefficient when useful load varies but payl...

show abstract

“…Early applications of computer-aided methods for the structural aircraft design include approaches like PrADO (Preliminary Aircraft Design and Optimization), developed at the TU Braunschweig [1], and higher fidelity tools like MIDAS (Multidisciplinary Interactive Design and Analysis System) including developments by NASA [2]. Industrial applications especially for the structural optimization include LAGRANGE by Cassidian (Airbus Defence & Space since 2014) [3] and FAME-W (Fast and Advanced Mass Estimation-Wing) by Airbus [4]. An overview of multidisciplinary design developments is provided in more detail e.g.…”

Section: Introductionmentioning

confidence: 99%

Automatic tool-based pre-processing of generic structural models for water impact simulations in the aircraft pre-design

Muñoz

Petsch

Kohlgrüber

et al. 2022

IOP Conf. Ser.: Mater. Sci. Eng.

View full text Add to dashboard Cite

The integration of automated tool capabilities for the generation of models for transient dynamic calculations in the scope of the aircraft pre-design is described in this paper. The Python-based DLR framework PANDORA, initially developed for the modelling and the sizing of aircraft structures in multidisciplinary process chains, is considered for this work. The focus lays on the generation of suitable numerical models for the water impact simulation. To enable this, the internal tool database was extended to consider additional features such as contact definitions, mesh-free formulations, enhanced connection models and specific control options. The generation of the CPACS-based FE aircraft model was extended by means of discretisation and additional structural components. The generation of the water domain was also included according to user defined inputs like pool dimensions, initial conditions and the selection of an appropriate fluid modelling approach. In addition, a feature to launch a simulation directly within the framework was included. Finally, options to retrieve and visualize results from finished water impact simulations were also integrated, allowing to display contour and time history plots.

show abstract

Application of MDO to large subsonic transport aircraft

Cited by 14 publications

References 2 publications

Increasing Conceptual Design Fidelity with Prebuilt Airfoil Databases

Increasing Conceptual Design Fidelity with Prebuilt Airfoil Databases

Preliminary Aerostructural Optimization of a Large Business Jet

Automatic tool-based pre-processing of generic structural models for water impact simulations in the aircraft pre-design

Contact Info

Product

Resources

About