Aircraft Conceptual Design Using Multidisciplinary Optimisation Engineering Essay

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The purpose of this literature review is review the past research activities on the aircraft design at conceptual level using multidisciplinary optimization in order to satisfy the objectives like cost & weight optimization, aircraft robust design optimization. Optimization means the determination of a minimum or maximum of one or more objective functions such that no constraints are violated Aircraft designers have always tried to make their newest design the "best ever" at the time of concept level. During the concept level, the optimization of the design to provide the desired capabilities at a minimum cost is of paramount importance. Aircraft are very expensive compared to almost any other man-made item. Specific technologies that can reduce cost, such as improved engines, lightweight structures, and advanced control systems. Another way that an improved design process can reduce aircraft cost is in the early identification of the best possible balance between the disparate desires of the various design disciplines such as The aerodynamics department generally prefers a thinner wing to reduce drag, whereas the structures department prefers a thicker one to reduce weight. Identification of the best balance must be done in the context of the aircraft's roles and missions, and has the potential for a substantial overall cost savings. To better optimize an aircraft at the conceptual level, additional design parameters such as fuselage fineness ratio, wing design lift coefficient (or camber), and engine bypass ratio or propeller diameter could be included in a simultaneous optimization. One could attempt to simultaneously optimize all of these and many more, and also have the computer optimally change the actual shape of the design including wing platform breaks, nacelle locations, and tail locations, and perhaps optimize the airfoils at the same time. The main importance of the project is aircraft conceptual design with the help of multidisciplinary optimization and trade study between multidisciplinary.


Figure 1 aircraft conceptual design using multidisciplinary optimization [13]

Above figure shows the conceptual design layout

There are three major phase in design

Conceptual design: in conceptual design included market determination, rough "outline" of the design with some supporting concept wise calculation.

Preliminary: "detailed" aero shape, structure, propulsion detail calculation with final dimension.

Detailed: actual drawings of every part in the aircraft ready to cut

But in our project we are concentrating on the conceptual design.

Key elements of conceptual design are as under

Comprehensive set of requirements / constraints

Inputs variables

Goals and objectives


According to National Research Council Canada web site " " If we design new and complex aircraft vehicles a reality is high levels of integration are needed between multidisciplinary, such as aerodynamics, heat transfer, propulsion, controls, and electromagnetics. Because these disciplines are mutually interactive and coupled, they must all be fully considered in predicting responses and in design optimization of aerospace and aircraft vehicles. Multidisciplinary design and optimization is a new technology for design of engineering systems that coherently exploits the synergism of mutually interacting phenomena. The integrated design process will improve the design quality and reduce the design cycle time and cost.

Figure 2 Multidisciplinary optimization [11]

With the help of above discussion integration are needed between main disciplines such as aerodynamics, structure, propulsion and control.

Corke.T.C (2005) 'Design of aircraft' India : Pearson Education Pte. Ltd. in the above book Thomas corke mentioned following chapters of aircraft conceptual design.

preliminary estimate of take-off weight

wing loading selection

main wing design

fuselage design

horizontal and vertical tail design

engine selection

enhanced lift design

structural design and material selection

static stability and control

He mentioned in his finding a crucial aspect of the design was the selection of "principle design drivers".

This step acknowledged that although objective was to optimize every part of the performance of the aircraft, optimizing one often had an adverse effect on another. There were many examples where this occurred, such as having a high wing loading to improve cruise efficiency also increased take-off and landing distance or having a large wing sweep angle to lower the drag in high-speed flight also greatly reduced the effectiveness of the lift-enhancing devices (flaps and slats). Therefore, the final design has many features that are the outcome of the initial selection of a few principle design drivers. The first step in the conceptual design was proposal. This defined the types of aircraft and its performance objectives. On the bases of above literature review Thomas corke are focus on the principle design drivers in the aircraft conceptual design but he did not use any multidisciplinary optimization methods or techniques. He was used trade study in his book. He examined the impact of individual parameters on the total design which referred as a trade study. An example of this would be to evaluate how wing loading, range or payload might affect the unit cost of a conceptual aircraft. He was included some trade study in his book, such as the thrust to weight ratio affect the range and payload because it affects the thrust specific fuel consumption. A higher thrust to weight ratio increases the amount of fuel used for the mission. For the same take-off weight, the added fuel weight has to be traded for a reduced range or a reduced payload. In either case, the outcome will be very dramatic, owing to an exponential dependence of both of these on the thrust specific fuel consumption. Second example of the trade study was for a specified take-off weight, the value of the wing loading sets the wing area S. As the wing area increases, the viscous drag increases. For high aspect-ratio wing, this can be a significant part of the total drag on the wing. The higher drag then requires an increase in the required thrust and, thereby, an increase in the fuel weight, which then must be traded off with the payload or range. Author took the SSBJ aircraft trade study for better explanation. He was used all the traditional method for design. However, which were very useful in the particular our project. But Raymer introduced the multidisciplinary optimization methods which was changed the view point of the design

Amadori.K, Jouannet.C & Krus P (2008) "Aircraft conceptual design optimization" paper published in 26TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES with the use of CAD, framework & simulation methodology. The paper represents the multiple disciplines with different design stages involved in the design of the aircraft. The aircraft design to be optimized at the conceptual level which will minimize possibility of the error in the design at preliminary & detail stage. During the conceptual design phase of a new aircraft designers will evaluate a large number of different concepts, searching for the one that meets the requirements in the best way. This means that they need to iteratively cycle through sketching a concept, analyze it and evaluate and compare its performances. In the paper the framework, simulation tools and cad tools are used in a multidisciplinary optimization for defining and refining aircraft designs in terms of aerodynamics, performance, weight, stability and control.

In this paper author also included a framework architecture that focuses on flexibility of application, has been outlined. Author suggested use of analytical tools instead of semi empirical or statistical equation during the conceptual phase of aircraft design. For the aerodynamics, a high order panel code - PANAIR - has been employed. PANAIR may not represent the most advanced tool for aerodynamic analysis, but it served the purpose of illustrating the process. Clearly any other panel code or CFD software could equally be used instead. A CAD model has also been included as one module in the framework, where geometric calculations, as well as structural analysis are performed.

Figure 3 improvement using optimization [12]

According to above figure if we introduced optimization at conceptual level than we can remove the any error at conceptual early and reduced the cost. Potential improvement we can see after the optimization.

Raymer D, (2002) 'Enhancing aircraft conceptual design using multidisciplinary optimization', published doctoral thesis was included the improvement of the Aircraft Conceptual Design process by the application of Multidisciplinary Optimization (MDO). He was used the aircraft conceptual design analysis codes into a variety of optimization methods including Orthogonal Steepest Descent, Monte Carlo, a mutation-based Evolutionary Algorithm and three variants of the Genetic Algorithm with numerous options. Four aircraft concepts such as an advanced fighter, a commercial airliner, an asymmetrical light twin, and a tactical UAV were used to evaluate the optimum solution with the help of above optimization methods. Each design variation was completely analyzed as to aerodynamics, weights, performance, cost, and mission sizing, and evaluated as to performance and geometric constraints. In his research he was found that aircraft conceptual design can be improved by the proper application of Multidisciplinary Optimization techniques. MDO techniques can reduce the weight and cost of an aircraft by fairly minor changes to the key design variables at the time of conceptual design stage. He also included that MOD techniques are superior compare to the traditional carpet plots used in the aircraft conceptual design process for many decades. According to him different MDO methods for aircraft design optimization gives the reasonable results. For a smaller number of variables the deterministic Orthogonal Steepest Descent searching method provides a slightly better final result with about the same number of case evaluations. For more variables, evolutionary/genetic methods seem superior. The Breeder Pool approach defined herein seems to provide the best convergence in the fewest number of case evaluations. The Net Design Volume approach defined herein to assure sufficient volume for fuel and internal equipment appears to work well and improves the design realism with little user effort.

According to authors in the past we were used traditional optimize methods such as carpet plot and traditional methods. But in the present thesis he used the some advanced optimization techniques which are very useful in the our design project

Figure 4: Traditional optimization method optimum fineness ratio [12]

In the above (figure 4) illustrate the how to find the optimum fineness ratio (fineness ratio f = l/d maximum length to diameter) with the help of the traditional optimization method. L and D both are variable and the design drag is constrained. It's one type of trade study.

Figure:5 Orthogonal Steepest Descent Full-Factorial Stepping Search[12]

According to (Figure 5) advanced optimization method orthogonal steepest decent full-factorial stepping search method we can also find the optimize fineness ratio. We can find optimum value with the use of two different variable and measure of merit. In our project aircraft conceptual design with the use of multidisciplinary optimization some of advanced optimization method will give the more accurate and cost effective design.

In the above method neither derivatives nor finite differences use to find the direction of maximum local improvement to the objective function. Instead, the region around the current best is investigated only along the variables' axes, and a step of pre-determined size is made in the best direction found.

Raymer are focus on the variable, constrain and measure of merit in conceptual design which are important for aircraft conceptual/preliminary MDO. However, some parameters have great importance like number of wing spars, but it was missing from this list. But he mentioned the impact of dependent variables on conceptual design. Design variable and constrains are as follows.

Independent Design Variables in the MDO

The basic six variables

(1)T/W or P/W (unless fixed-size engine)

(2)W/S (area)

(3)Aspect Ratio

(4)Taper Ratio


(6)Airfoil t/c (constant or averaged)

Fuselage variable

(1)Length / diameter ratio ("fineness ratio") or diameter alone

(2)Volume distribution (optimize wave drag)

(3)Number of seats

Engine variable

(1)Bypass Ratio (BPR)

(2)Overall Pressure Ratio (OPR)

(3)Turbine Inlet Temperature (TIT)

(4) Capture Area

(5)Inlet lip radius

(6)Auxiliary door presence / size

(7)Inlet type

(8)Ramp or Cone angles (supersonic)

(9)Exhaust type

(10)Engine locations

Design constrains

Stall & approach speed

Maximum speed

Climb rate or time to climb

Sustained & instantaneous turn rate

Ps at given conditions

Acceleration time/distance

Glide ratio / sink speed

Descent rate / time / distance

Takeoff / landing distances

Hugh.H.T and Perez.R.E (2004),"Evaluation of Multidisciplinary Optimization Approaches for Aircraft Conceptual Design" published the paper. The paper was present the some optimization methods like Multi-Disciplinary Feasible, Individual Discipline Feasible, Collaborative Optimization, Concurrent Subspace Optimization and Bi-Level Integrated Synthesis System. The selection of the above method are depends upon evolution matrix result. Author was used simplicity, Transparency, Portability, Efficiency, Accuracy as an evolution metrics. He used example of supersonic business jet subjected to individual disciplinary constrain. The goal is to maximize the range of a supersonic business jet. Four coupled disciplinary systems are used. Representing structures, aerodynamic, propulsion, and performance. The first three disciplines are fully coupled since they share common variables and exchange computed states. The fourth discipline (performance) receives information from the others to evaluate the range performance of the design. Structures and weights are coupled to aerodynamic and propulsion. This is expected since aerodynamic loads cause changes in aircraft structural deflection that in turn changes the aerodynamics characteristics of the aircraft. Similarly, the propulsion and weights are coupled. The thrust required is dependent on the total aircraft weight, including the engine weight, which is also the function of thrust. .

Figure 6 Design Optimizations using multi disciplinary [9]

Author presented an extended evaluation of MDO methods. With the help of supersonic business jet author try to evaluate the five MDO methods. The evaluation is based on above metrics, which take into account formulation and the algorithm considerations. The quantitative description of the metrics provides a systematic approach in evaluating the MDO methods. He used all above five optimization method in his research.

Forth.S.A, Padulo.M and Marin.D presents a paper on "Robust Aircraft Conceptual Design using Automatic Differentiation in Mat lab" This paper shows the need for robust optimization in aircraft conceptual design & for that the design parameters were assumed stochastic, was introduced. They highlighted at the time of optimization we have to consider the Robustness of the design. We can not ignore Robustness because of the safety is our main concern in the design. In the present paper two approaches were highlighted, first-order method of moments (IMM) and Sigma-Point (SP) reduced quadrate, to estimate the mean and variance of the design's outputs. The method of moments requires the design model's differentiation and here, since the model is implemented in Mat lab, is performed using the Automatic Differentiation tool MAD. Gradient-based constrained optimization of the stochastic model is shown to be more efficient using AD-obtained gradients than finite-differencing. A post-optimality analysis, performed using AD enabled third-order method of moments and Monte-Carlo analysis, confirms the attractiveness of the Sigma-Point technique for uncertainty propagation. Author was demonstrated the benefits of using AD in robust optimization of a Mat lab implemented. He took the example of Minimize Maximum Take-Off Weight.

Author demonstrates the benefits AD may give to robust optimization for aircraft conceptual design. They performed robust optimizations of an industrially relevant, Mat lab-implemented aircraft sizing problem using the AD tool MAD. He used two robust design strategies:

(1) First strategy exploits automatic differentiation obtained first order sensitivities of the original function to approximate the robust objective and constraints using the method of moments and second order sensitivities to calculate their gradients.

(2) Sigma Point Method (SP) which reduced quadrature to approximate the robust objective, constraints and AD for their gradients.

In the study a Monte-Carlo post-optimality analysis indicates that sigma point method more accurate for estimation of the mean but IMM more efficient with automatic differentiation gradients. In both method AD gradients significantly reduced optimization c.p.u. time compared to finite-differencing method.

Andersson.J (2001)," Multi-objective Optimization in Engineering Design" doctoral thesis published at Sweden

He presented optimization techniques in engineering design. Studied systems include a landing gear system for a civil aircraft, electro-hydrostatic actuation systems for aircraft applications as well as hydraulic actuation systems. The focus has been twofold. The first issue was to employ simulation in order to enhance our understanding of the design process, and the second to develop optimization techniques that support the design of complex systems based on simulations. The proposed method was applied to support the design of a landing gear system, which combines a mechanical structure with a hydraulic actuation system. The landing gear system was successfully optimized with the help of the Complex method. Another way to handle the multiple objectives of a design problem is to introduce the concept of Pareto optimality. The search is then not for one optimal solution but for a set of solutions that are optimal in a broader sense, i.e. they are Pareto optimal. An advantage of conducting Pareto optimization is that the arbitrariness of the decision-maker is left out of the optimization. The search is for the Pareto set, which includes all rational choices, among which the decision-maker has to select the final solution by trading the objectives against each other.

After the reviewing the above literature, understanding regarding the our project are largely improved Thomas corkes effort regarding the complete aircraft conceptual design are used in our project we can understand all the aerodynamic and design term through his book. His trade studies are also useful to trade-off between different objectives. In his book he was illustrated all major aircraft parts design. Rayner D and Andersons introduced the multi-disciplinary optimization in aircraft design and they were changed the view point of the design. They introduced the new generation design concept. Orthogonal Steepest Descent, Monte Carlo, a mutation-based Evolutionary Algorithm and three variants of the Genetic Algorithm are the method which can we use according to application of the multidisciplinary optimization. After the literature review I can conclude the Aircraft conceptual design carried out by four main disciplines (aerodynamics, structure, propulsion, control). Knowledge of major disciplines is necessary for aircraft conceptual design. With the help of advanced optimization method we can minimise the cost and increase the performance of the aircraft. Trade studies between different objectives are also necessary for optimum design.


Amadori.K, Jouannet.C & Krus P (2008) "Aircraft conceptual design optimization" published paper AT 26TH INTERNATIONAL CONGRESS OF THE AERONAUTICAL SCIENCES.

Andersson.J (2001)," Multi-objective Optimization in Engineering Design" doctoral thesis published at Sweden

Alonso J (2004),"Multidisciplinary design of complex engineering system with implications for manufacturing" published paper

Campobasso M S,Guenov M and Fantini .P(2006)," Robust Optimization of Aircraft Conceptual Design supported by MATLAB AD" published paper at uk

Corke.T.C (2005) 'Design of aircraft' India: Pearson Education Pte. Ltd

Forth.S.A, Padulo.M and Marin.D presents a paper on "Robust Aircraft Conceptual Design using Automatic Differentiation in Mat lab" published paper.

Guenov M, Maginot J and Utyuznikov S (2008) "Local Pareto approximation for multi-objective optimization" published paper at uk

Guenov M, Maginot J and Utyuznikov S (2008) "Local Pareto approximation for multi-objective optimization" published paper at uk

Hugh.H.T and Perez.R.E (2004),"Evaluation of Multidisciplinary Optimization Approaches for Aircraft Conceptual Design" published paper.

Kroo I (2004)," Distributed Multidisciplinary design and collaborative optimization" paper published at USA

National Research Council Canada official web site " " last access 14 April 2010.

Raymer D, (2002) 'Enhancing aircraft conceptual design using multidisciplinary optimization', published doctoral thesis at sweden

Raymer D " Automatic aircraft configuration redesign" published paper

Wong K.C and Whitney J (2004) " Multidisciplinary design optimization of unmanned aerial vehicles using multi-criteria evolutionary algorithms" published paper at Australia

Wong K.C and Whitney J (2006),"Multidisciplinary Aircraft Conceptual Design Optimization Using a Hierarchical Parallel Asynchronous Evolutionary Algorithm (HAPEA)" published paper at Australia