Article

Simultaneous Optimization of a Multiple-Aircraft Family

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Abstract

Multidisciplinary design optimization is considered in the context of designing a family of aircraft. A framework is developed in which multiple aircraft, each with different missions but sharing common parts, can be optimized simultaneously.The new framework is used to gain insight to the effect of design variable scaling on the optimization algorithm. Results are presented for a two-member family whose individual missions differ signii cantly. Both missions can be satiss ed with common designs. Moreover, optimizing both airplanes simultaneously rather than following the traditional baseline plus derivative approach vastly improves the common solution. A cost modeling framework is outlined that allows the value of commonality to be quantii ed for design and manufacturing costs. A notional example is presented to show the cost bene t that may be achieved by designing a common family of aircraft.

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... Two scale-based approaches are used in the industry for designing passenger aircraft families: sequential and simultaneous [3]. In the sequential approach, a baseline aircraft is designed first, and the variants are designed later, whereas in the simultaneous approach, baseline aircraft and the variants are designed together. ...
... Researchers have presented methods for sequential development of aircraft families by introducing reserves into the baseline aircraft and using change propagation to develop new variants [4][5][6]. Willcox and Wakayama [3] compared the two approaches in the context of a design study of blended wingbody (BWB) aircraft families. The authors claimed that about 1% of the structural weight could be saved when the simultaneous approach is used. ...
... Most existing scale-based methods for designing passenger aircraft families employ parametric optimization-based approach. Willcox and Wakayama [3] developed a multidisciplinary design optimization framework and demonstrated its use for designing blended wing-body (BWB) aircraft family consisting of two variants. Cabral and Paglione [7] developed a multi-objective optimization tool for the conceptual design of passenger aircraft families using genetic algorithms (GAs). ...
Article
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Presented is a method for the design of passenger aircraft families. Existing point-based methods found in the literature employ sequential approaches in which a single design solution is selected early and is then iteratively modified until all requirements are satisfied. The challenge with such approaches is that the design is driven toward a solution that, although promising to the optimizer, may be infeasible due to factors not considered by the models. The proposed method generates multiple solutions at the outset. Then, the infeasible solutions are discarded gradually through constraint satisfaction and set intersection. The method has been evaluated through a notional example of a three-member aircraft family design. The conclusion is that point-based design is still seen as preferable for incremental (conventional) designs based on a wealth of validated empirical methods, whereas the proposed approach, although resource-intensive, is seen as more suited to innovative designs.
... In general, a product family is a group of related products that share a collection of common elements to satisfy a variety of market niches [3]. In aviation areas, a product family usually comprises two or more products with similar or dissimilar missions that share some parts, systems, or large sections [4]. ...
... Developing derivatives is the traditional and typical way, in which a baseline aircraft is designed first and subsequently modified to produce a number of derivatives to satisfy different missions, like the Boeing B747 family and the Airbus A320 family [9]. This approach can often result in substantial modifications and suboptimal performance [4]. The second approach is to design all aircraft family members simultaneously, and their missions can be similar or significantly different. ...
... One is the one-stage approach, which treats the aircraft family problem as a standard constrained nonlinear programming problem. Willcox and Wakayama [4] adopted sequential quadratic programming (SQP) in the blended-wing/body aircraft family problem. D'Souza and Simpson [15] applied a genetic algorithm to a general aviation aircraft family problem. ...
... Yet another interesting effort was reported by Wilcox et. al [5] where the aim was to design optimum aircrafts for various mission requirements with several common design features (family of aircrafts). ...
... In all the above MDO studies, the aircraft configuration [1][2][3][4] and the base design for different missions [5] were decided a priori and were held fixed throughout the optimization process. Such a scheme restricts the evolution of various configurations at the onset, some of which could be better. ...
Conference Paper
At the conceptual phase of an aircraft design process, the aim is to determine the set of design features such as configuration arrangement, planform geometry, wing area, engine configuration and weight that meet various performance characteristics. Multidisciplinary design optimization (MDO) at this phase allows the designer to consider various options via simultaneous interactions of aerodynamics, propulsion, structures, stability and flight mechanics to arrive at better designs. Earlier attempts with MDO seek to optimize a design for a predetermined aircraft configuration or optimize a base design for different mission profiles. In this paper, we propose a MDO framework for conceptual aircraft design that considers different aircraft configurations simultaneously. The advantage of this approach is to allow the evolution of various aircraft configurations. The optimization algorithm used in the framework is based on computational intelligence which is a stochastic, zero-order, population based algorithm, especially suitable for multi-objective, constrained optimization problems involving computationally expensive functions. The work is aimed at providing insights in how different mission requirements dictate configuration choices. In the present work we study the evolution of different two-seater, propeller driven aircraft configurations for different mission requirements and we limit it to two configurations namely, conventional wing-tail and canard configurations.
... In order to meet many constraints and design variables, the logical and systematic aircraft design process has been developed to get accurate optimum configuration. 2,20 In C.P. Van Dam's paper for high-lift device, there is discussion about design objectives and constraints of the Federal Airworthiness Regulations (FAR) Part 25 regulation such as 'the liftoff speed must be at least 1.1 times the minimum liftoff or unstick speed and 1.05 times when one engine out.' 3 In this paper also there are several constraints for KAS-VLA such as the speed of stall when flap deflected in landing stage must not exceed 20m/s. There are design constraints such as the stall angle of attack have to over 9~10 degree and about the takeoff and landing distance. ...
... 20 . The airworthiness compliance and user-requirement check are satisfied with the optimum flap configuration. ...
Conference Paper
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The flap deflection, overlap, and gap are considered as main and significant effects to the increment of maximum lift coefficient which indirectly influences on the Very Light Aircraft (VLA) takeoff, landing distance, and stall condition. Therefore, the overall flap design optimization process is proposed to obtain the most effective flap configuration with the accurate and reliable increment in lift coefficient versus flap deflection by implementing a Computational Fluid Dynamic (CFD) analysis tool, ANSYS Fluent® 13.0.0. The flap design optimization problem is formulated in which the objective function is to maximize the maximum lift coefficient (Clmax) while constrained by the stall angle of attack. The optimum flap configuration is obtained by Sequential Quadratic Programming (SQP) method which searches on flap design space created by the large number of CFD analysis case results. Subsequently, the optimum flap configuration is integrated into the in-house Aircraft Design Synthesis Program (ADSP) to analyze the entire VLA performance parameters including takeoff distance, landing distance, maximum rate of climb, service ceiling, and rotation speed which will be checked for the compliance with the airworthiness and requirement constraints. The proposed overall flap design process demonstrated the robustness and reliability for enhancing to entire VLA performance analysis results.
... Wakayama [14], Jansen et al. [47], Mariens et al. [48], and Elham and van Tooren [32,49]. ...
... 14: Surface sensitivity for the baseline RAE2822 aerofoil. ...
Thesis
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Computational fluid dynamics (CFD) has become the method of choice for aerodynamic shape optimisation of complex engineering problems. To date, however, the sensitivity of the optimal solution to numerical parameters has been largely underestimated. Meanwhile, aerodynamic shape optimisation based on high-fidelity CFD remains a computationally expensive task. The thesis consists of two research streams aimed at addressing each of the challenges identified, namely revisiting the optimal solution and developing an efficient optimisation framework. This work primarily focuses on the assessment of optimal design sensitivity and computational efficiency in gradient-based optimisation of aeronautical applications. Two benchmark cases for NACA0012 and RAE2822 aerofoil optimisation are investigated using the open-source SU2 code. Hicks-Henne bump functions and free-form deformation are employed as geometry parameterisation methods. Gradients are computed by the continuous adjoint approach. The optimisation results of NACA0012 aerofoil exhibit strong dependence on virtually all numerical parameters investigated, whereas the optimal design of RAE2822 aerofoil is insensitive to those parameter settings. The degree of sensitivity reflects the difference in the design space, particularly of the local curvature on the optimised shape. The closure coefficients of Spalart-Allmaras model affect the final optimisation performance, raising the importance of quantifying uncertainty in turbulence modelling calibration. Non-unique flow solutions are found to exist for both cases, and hysteresis occurs in a narrow region near the design point. Wing twist optimisations are conducted using two aerodynamic solvers of different levels of fidelity. A multi-fidelity aerodynamic approach is proposed, which contains three components: a linear vortex lattice method solver, an infinite swept wing solver, and a coupling algorithm. For reference, three-dimensional data are obtained using SU2. Two optimisation cases are considered, featuring inviscid flow around an unswept wing and viscous flow around a swept wing. A good agreement in terms of lift distribution and aerodynamic shape between the multi-fidelity solver and high-fidelity CFD is obtained. The numerical optimisation using the multi-fidelity approach is performed at a negligible computational cost compared to the full three-dimensional CFD solver, demonstrating the potential for use in early phases of aircraft design.
... This scenario captures some of the important characteristics of designing a product family. In the literature, Willcox and Wakayama [50] considered designing multiple aircrafts, each with a different mission but sharing a common wing. In this scenario, the overall goal is , z) i.e., min η(x i , z)) + w 2 * Mass normalized (x i , z)) (16) where m is the number of motors, x i denotes the local design parameters of the ith motor, and z denotes the common design parameters. ...
... In the experiments, we set the communication cost to pop num * NP and the communication interval range to [1,50]. The MaxFEs was set to 2e5, and the specified number of generations in both NDCC-SS and CCDM was set to MaxFEs/(pop num * NP + cost) . ...
Article
As a well-known engineering practice, concurrent engineering (CE) considers all elements involved in a product’s life cycle from the early stages of product development, and emphasises executing all design tasks simultaneously. As a result, there exist various complex design problems in CE, which usually have many design parameters or require different disciplinary knowledge to solve them. To address these problems and enable concurrent design, different methods have been developed. The original problem is usually divided into small subproblems so that each subproblem can be solved individually and simultaneously. However, good decomposition, optimisation and communication strategies among subproblems are still needed in the field of CE. This paper attempts to study and analyse cooperative coevolution (CC) based design optimisation in concurrent engineering by employing a parallel CC framework. Furthermore, it aims to develop new concurrent design methods based on parallel CC to solve different kinds of CE problems. To achieve this goal, a new novelty-driven CC is developed for design problems with complex structures and a novel concurrent design method is presented for quasi-separable multidisciplinary design optimisation problems. The efficacy of the new methods is studied on universal electric motor design problems and a general multidisciplinary design optimisation problem, and compared to that of some existing methods. Additionally, this paper studies how the communication frequency among subpopulations affects the performance of the proposed methods. The optimal communication frequencies under different communication costs are reported as experimental results for both proposed methods on the test problems. Based on this study, an effective self-adaptive method is proposed to be used in both optimisation schemes, which is able to adapt the communication frequency during the optimisation process.
... Meanwhile, population-based evolutionary algorithms, such as bio-inspired genetic algorithms (GAs) [16] and differential evolution (DE) [17], can be used to solve MDO problems conveniently. Historically, MDO methodologies were first proposed for the purpose of designing aircraft components [18,19]. Later research has extended the application of MDO into other types of machines, such as wind turbines whose blade and tower sizes were optimized to reduce the cost of generated energy [20]. ...
Article
Full-text available
Additive manufacturing (AM) techniques are ideal for producing customized products due to their high design flexibility. Despite the previous studies on specific additive manufactured customized products such as biomedical implants and prostheses, the simultaneous optimization of components, materials, AM processes, and dimensions remains a challenge. Multidisciplinary design optimization (MDO) is a research area of solving complex design problems involving multiple disciplines which usually interact with each other. The objective of this research is to formulate and solve an MDO problem in the development of additive manufactured products customized for various customers in different market segments. Three disciplines, i.e. the customer preference modeling, AM production costing, and structural mechanics are incorporated in the MDO problem. The optimal selections of components, materials, AM processes, and dimensional parameters are searched with the objectives to maximize the functionality utility, match individual customers’ personal performance requirements, and minimize the total cost. A multi-objective genetic algorithm with the proposed chromosome encoding pattern is applied to solve the MDO problem. A case study of designing customized trans-tibial prostheses with additive manufactured components is presented to illustrate the proposed MDO method. Clusters of multi-dimensional Pareto-optimal design solutions are obtained from the MDO, showing trade-offs among the objectives. Appropriate design decision can be chosen from the clusters based on the manufacturer's market strategy.
... Moreover, MDO can ensure that additional information on properties such as robustness, adaptability, flexibility, scalability, and safety are also delivered by using suitable inputs to the problem like for example probabilistic and uncertainty constraints (Gavel et al., 2008). Finally, considering logistics and marketing is also a further possibility, and it can be seen that designing families of aircraft is one example which shows how modularity and scalability can be effectively included in the MDO framework (Willcox and Wakayama, 2003). ...
... The approach is to determine common characteristics that optimize the value or performance across the entire family of aircraft simultaneously as opposed to developing derivative aircraft by perturbing a baseline designed without consideration of the family evolution. Willcox and Wakayama indicate that a "way to reduce costs is to conceive of a family of aircraft that share common parts and characteristics, such as planform and systems, but each aircraft satisfies a different mission requirement" [19]. They employ multidisciplinary optimization to a family of aircraft that share design variables. ...
Article
Aircraft with modular airframe components may offer significant flexibility in mission performance by enabling reconfiguration between sorties. This paper introduces an approach for optimizing a family of aircraft variants defined by a library of interchangeable components such as wings, tails, engines, and payloads. First, the combinatorial problem of composing interchangeable components into feasible aircraft variants and assigning the variants to missions is posed. Next, two methods are presented to determine optimal reconfigurable family designs. The methods are then applied to an example problem to define optimal families of modular unmanned aerial vehicles consisting of interchangeable wings and engines. The results indicate a rich trade space of family architectures and aircraft configurations that depends strongly on the type and diversity of the required missions.
... The solution chosen to progress to the preliminary design stage is usually one that satisfies all the constraints and optimizes some figure of merit, related to performance, 3-5 cost, 6 revenue or combinations of these. [7][8][9][10][11] To compute these metrics and make design decisions based on them, the design system needs to integrate the various strands of multidisciplinary analysis into an iterative process, often driven by an optimization engine. The reader interested in the precise nature of the workflow within such systems may consult the detailed descriptions of various MDO (Multidisciplinary Optimization) frameworks (see, e.g., Sobieski's BLISS 12 ) or some of the relevant surveys. ...
... The goal of modern product-family methods is to design aircraft with a significant variation in performance to serve multiple market segments (i.e., domestic and transatlantic routes). Such a motivation is discussed in the study by [1] to design a family of two blended-wing-body aircraft with a capacity of 272 and 475 passengers with built-in commonality. Other noteworthy investigations include the use of decomposition-based methods [2] and genetic-algorithm techniques [3] for aircraft family design. ...
Article
The benefits of a family of macroscale reconfigurable unmanned aerial vehicles to meet distinct flight requirements are readily evident. The reconfiguration capability of an unmanned-aerial-vehicle family for different aerial tasks offers a clear cost advantage to end users over acquiring separate unmanned aerial vehicles dedicated to specific types of missions. At the same time, it allows the manufacturer the opportunity to capture distinct market segments, while saving on overhead costs, transportation costs, and after-market services. Such macroscale reconfigurability can be introduced through effective application of modular product-platform-planning concepts. This paper advances and implements the Comprehensive Product Platform Planning framework to design a family of three reconfigurable twin-boom unmanned aerial vehicles with different mission requirements. The original Comprehensive Product Platform Planning method was suitable for scale-based product-family design. In this paper, important modifications to the commonality matrix and the commonality constraint formulation in Comprehensive Product Platform Planning are performed. These advancements enable the Comprehensive Product Platform Planning to design an optimum set of distinct unmanned-aerial-vehicle modules, different groups of which could be assembled to configure twin-boom unmanned aerial vehicles that provide three different combinations of payload capacity and endurance. The six key modules that participate in the platform planning are 1) the fuselage/pod, 2) the wing, 3) the booms, 4) the vertical tails, 5) the horizontal tail, and 6) the fuel tank. The performance of each unmanned aerial vehicle is defined in terms of its range per unit fuel consumption (miles/gallon). It is found that, when the average unmanned-aerial-vehicle performance (miles/gallon) and the commonality among the unmanned-aerial-vehicle variants are simultaneously maximized, a one-third reduction in the number of unique modules is accomplished at a 66% compromise in performance. On the other hand, when simultaneously maximizing performance and minimizing costs, the best tradeoff unmanned-aerial-vehicle-family designs provide a remarkable 26% reduction in cost for a 6% compromise in performance. In this case, the cost savings are attributed to both material reduction and increased module sharing across the three unmanned-aerial-vehicle variants. It is also observed that, among the best tradeoff unmanned-aerialvehicle families, the individual unmanned aerial vehicles are most likely to share the horizontal tail and tail booms, and are least likely to share the wing. © Copyright 2015 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
... This approach is named quasi-three-dimensional (Q3D) analysis. Examples of Q3D wing aerodynamic analysis and optimization can be found in the works of Drela (2010a), van Dam et al. (2001), Elham and van Tooren (2014a, b), Mariens et al. (2014), Willcox and Wakayama (2003) and Jansen et al. (2010). ...
Article
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This paper presents a method for wing aerostructural analysis and optimization, which needs much lower computational costs, while computes the wing drag and structural deformation with a level of accuracy comparable to the higher fidelity CFD and FEM tools. A quasi-three-dimensional aerodynamic solver is developed and connected to a finite beam element model for wing aerostructural optimization. In a quasi-three-dimensional approach an inviscid incompressible vortex lattice method is coupled with a viscous compressible airfoil analysis code for drag prediction of a three dimensional wing. The accuracy of the proposed method for wing drag prediction is validated by comparing its results with the results of a higher fidelity CFD analysis. The wing structural deformation as well as the stress distribution in the wingbox structure is computed using a finite beam element model. The Newton method is used to solve the coupled system. The sensitivities of the outputs, for example the wing drag, with respect to the inputs, for example the wing geometry, is computed by a combined use of the coupled adjoint method, automatic differentiation and the chain rule of differentiation. A gradient based optimization is performed using the proposed tool for minimizing the fuel weight of an A320 class aircraft. The optimization resulted in more than 10 % reduction in the aircraft fuel weight by optimizing the wing planform and airfoils shape as well as the wing internal structure.
... The latter implies the presence of multiple equivalent designs for similar objective performance. Such solutions are of relevance to DMs involved in, e.g., design of re-configurable product families [41,42]. It is desirable to have options for replacing a given design with another one to achieve similar performance in case the former becomes infeasible/impractical.. ...
Article
In multi/many-objective optimization, a decision maker (DM) may often be interested in examining only a small set of solutions instead of the entire Pareto optimal front (PF). Such solutions are referred to as solutions of interest (SOI) in some recent studies. A number of methods have been proposed to identify SOIs in an offline or online setting using measures based on reflex angle, bend angle, expected marginal utility, etc. However, these measures only account for the desirable trade-offs in the objective space. On the other hand, the variable space information is often critical in practical scenarios as it relates directly to the implemented design. For example, a DM may additionally require that the obtained solutions are robust, i.e., insensitive to variable perturbations, or look significantly different in the variable space, thereby offering multiple equivalent designs to achieve similar performance. These require formulation of new measures and search strategies that simultaneously consider both objective and variable spaces while identifying SOIs. In this paper, we develop an approach that can identify a given number of SOIs for DM’s consideration for three different scenarios: (a) purely based on objective space, (b) simultaneous consideration of objectives and robustness, and (c) simultaneous considerations of objectives and equivalent designs. Towards this end, we first define the relevant quantitative measures and illustrate their use for offline selection for a few 2-3 objective test problems. Thereafter, we design an online algorithm that can identify the SOIs and bias the search towards the SOIs based on the scenarios listed above. Lastly, we also present results on two practical examples: a 2-objective welded beam and a 5-objective wind-turbine design problem.
... Therefore, it is of great interest to find a fast way to calculate the primary aerodynamic forces with sufficient accuracy . An interesting way for establishing such an approach is by combining (two-dimensional) viscous airfoil data with an inviscid three-dimensional wing lift calculation [2,10111231]. This approach is named quasi-three-dimensional (Q3D) analysis. ...
Article
A quasi-three-dimensional method for wing aerodynamic analysis for drag prediction is presented. This method can predict the wing drag with a level of accuracy similar to higher fidelity three-dimensional CFD analysis, with a much lower computational cost. A tool has been developed based on the proposed method and the outputs of the tool have been validated using a higher fidelity CFD tool. Another advantage of the mentioned method (and the tool developed based on that) is to compute the derivatives of any function of interest, such as the wing drag, lift, or pitching moment, with respect to the design variables, mainly the wing geometry, using analytical methods. The tool uses a combination of the Adjoint method, the chain rule for differentiation, and the automatic differentiation to compute the sensitivities. The quasi-three-dimensional aerodynamic solver is used for a multi-fidelity wing aerodynamic shape optimization. A trust region algorithm is used to connect the low fidelity aerodynamic solver to a high fidelity CFD tool for wing drag prediction. The derivatives of the objective function are computed using the low fidelity solver, and the high fidelity solver is used to calibrate the results of the low fidelity one.
... Different algorithms are adopted to deal with the problem of the degree and uniformity of the solution set. In this paper, the concepts of Rank and Density in the literature are introduced (Willcox and Wakayama, 2003), and the mathematical expression of density can be improved to represent the degree of the evolution of genetic algorithm. Mutual distance, so that the non-dominated solution can be approximated to the real optimal solution set, and the uniform distribution is maintained on the Pareto interface(Yuan Xu and Huifeng Xue, 2016). ...
Article
In order to improve the aerodynamic optimization design efficiency and using multi-objective optimization algorithm solving non-inferior solutions sets efficiency, a multi-objective optimization method is developed to solve the multi-objective problem of aerodynamic design for aircraft, and then an optimization algorithm for the aerodynamic system is proposed based on the characteristics of the Pareto method. At last, the integrated optimization design of aerodynamic and stealth characteristics is given. The results show that the aerodynamic performance of the wing is improved by the optimized design, to achieve the purpose of optimization design, and the optimized wing design method is feasible.
... Then, for other parameter settings, approximate surrogate models of the simulation-based function are assembled (using no additional simulations) and minimized, resulting in an approximate optimal solution for each parameter setting; see also Fig. 2. The algorithm presented in this paper can-besides the tyre design problem-be used in other applications in which a number of similar computationally expensive optimization problem instances are to be solved. Examples include the design of freight aircraft to be used for several types of transport missions (Willcox and Wakayama 2003), and the optimization of the charge of melting with respect to the quality of various products and which needs to be done in real time (Dupačová and Popela 2005). ...
Article
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This paper concerns the solution of a class of mathematical optimization problems with simulation-based objective functions. The decision variables are partitioned into two groups, referred to as variables and parameters, respectively, such that the objective function value is influenced more by the variables than by the parameters. We aim to solve this optimization problem for a large number of parameter settings in a computationally efficient way. The algorithm developed uses surrogate models of the objective function for a selection of parameter settings, for each of which it computes an approximately optimal solution over the domain of the variables. Then, approximate optimal solutions for other parameter settings are computed through a weighting of the surrogate models without requiring additional expensive function evaluations. We have tested the algorithm’s performance on a set of global optimization problems differing with respect to both mathematical properties and numbers of variables and parameters. Our results show that it outperforms a standard and often applied approach based on a surrogate model of the objective function over the complete space of variables and parameters.
... After the definition of a fitness function that expresses the "suitability" of a configuration to the mission, several techniques can be applied to find the minimum of this function that represents the best (optimal) design point: gradientbased techniques and heuristic algorithms are tools often used in MDO. Numerical techniques based on gradient and Hessian matrices, like the sequential quadratic programming (SQP) [9], can handle the optimization of multiple parameters, even with nonlinear functions; also in the paper [10] dealing with the aerodynamic and structural optimization of an unmanned aerial vehicle, the SQP method has been applied. As an alternative to gradient methods, in the present study, heuristic optimization is applied to solve the tradeoff problem and to integrate all the design aspects in a feasible solution [11]. ...
Article
This paper describes the multidisciplinary optimization of an airship with unconventional configuration. The shape of the airship is based upon two semi-ellipsoids, whose axis ratios can be altered for optimization purpose. The parameters to optimize are volume, ratio between longitudinal and lateral semi-axis, ratio between vertical and lateral semi-axis, percentage of the top surface covered by photovoltaic films, and dimension of the tail. The objective of the optimization is to reduce the mass of the airship by keeping the equilibrium between buoyancy and weight as a constraint, reaching the design speed while maintaining the static longitudinal stability of the vehicle. The mathematical model developed to evaluate airship features includes the computation of the ballonet volume, a weight breakdown, considerations about the energy storage for night operations, the power system, and the stability. Six heuristic optimization strategies have been applied to achieve the best solution; some case studies have been developed, and the final optimal configurations found by algorithms have been analyzed to validate the optimization framework. The approach demonstrates that the heuristic optimization strategies used are good tools for the conceptual design of unconventional airship since this problem requires a multidisciplinary approach and several parameters including aerodynamics, propulsion, mass breakdown, aerostatics, and stability. These parameters are strongly dependent on each other and they must be considered together to obtain an optimum and balanced design.
... In literature, a number of different approaches to address these problems are proposed, 38,39 spanning from layered design, 40,41 to component-based approaches, [42][43][44] and from model-based development 35,43,45 to the V-model. [46][47][48][49] Layered design copes with complexity by focusing on those aspects of the system pertinent to supporting the design activities at the corresponding level of abstraction. ...
Article
New technologies and complex systems are being developed in commercial aviation to meet strict requirements regarding fuel consumption, emissions and noise constraints. This motivates the development of multidisciplinary environments to efficiently manage the increasing complexity of the design process. Under the Clean Sky 2 initiative, the ModellIng and Simulation tools for Systems IntegratiON on Aircraft (MISSION) project aims to develop an integrated framework to holistically support the aircraft design, development and validation processes. Within the MISSION framework, this paper proposes a methodology to handle the integration between the aircraft level and the system level in the early phase of aircraft design. The methodology is demonstrated for the case of the Landing Gear System in the rejected take-off scenario.
... 10 It is a common practice to derive fuselagelengthened or fuselage-shortened type from baseline aircraft so as to reduce Research and Development (R&D) costs, shorten R&D cycles, improve the adaptability of aircraft routes and airports, and expand the market coverage of aircraft products. [11][12][13][14] Commonality, an important concept in the product family, refers to the reuse and sharing of assets (components, manufacturing processes, architectures, interfaces and infrastructure) across members in a product family, representing a potential strategy for improving the company's profitability. 15 The challenge of designing a product family is to resolve the trade-off between commonality and distinctiveness: if commonality is too high, products will lack distinctiveness, and their individual performance will not be optimal; in contrast, if commonality is too low, manufacturing costs will increase. ...
Article
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Commercial aircraft family design can reduce development costs, shorten development cycles, and expand the market coverage of aircraft. Commercial aircraft family development has become one of the most important features of modern aircraft design. This paper explores the effects of commonality on different aircraft models in a commercial aircraft family. The existing product commonality indexes are summarized and their limitations in the application to aircraft design are discussed. Then a new component commonality index is proposed based on the component decomposition structure. A model for calculating the aircraft program value is established, which considers development costs, manufacturing costs, sale price, operation costs and residual costs. The effects of aircraft commonality on time and economic costs of both development and manufacturing, and on sale price, are analyzed and quantified. The commonality evaluation strategy is obtained, which features comprehensive consideration of the aircraft program value and time costs. The break-even analysis of aircraft is proceeded on the basis of costs and price data. By using a real option method, the strategy considers the uncertainty of the aircraft program and the flexibility of the manufacturer. This strategy proves to be rational and applicable to aircraft design based on the calculation of three examples and the analysis of parameter sensitivity. Keywords: Aircraft cost, Aircraft family, Aircraft program value, Commonality index, Real option method
... Comparisons with panel methods such as those in Refs. [18,19,40,45] are considered to be beyond the scope of this paper. This paper is structured, such that the reader is first given the details of the use case: the AX-1 large civil transport aircraft configuration. ...
Article
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Verification and validation of simulation models are critical steps in engineering. This paper aims at verifying the suitability of reduced order aerodynamic models used in an aeroservoelastic framework designed to analyze the flight dynamics of flexible aircraft, known as the Cranfield Accelerated Aircraft Loads Model. This framework is designed for rapid assessment of aircraft configurations at the conceptual design stage. Therefore, it utilizes or relies on methods that are of relatively low fidelity for high computational speeds, such as modified strip theory coupled with Leishmann–Beddoes unsteady aerodynamic model. Hence, verification against higher order methods is required. Although low fidelity models are widely used for conceptual design and loads assessments, the open literature still lacks a comparison against higher fidelity models. This work focuses on steady-trimmed flight conditions and investigates the effect of aerodynamic wing deformation under such loads on aerodynamic performance. Key limitations of the reduced order models used, namely fuselage and interference effects, are discussed. The reasons for the overall agreement between the two approaches are also outlined.
... Also, until now, there are no studies in the literature considering the minimization of aircraft development and production costs taken into the integrated aircraft and network optimization framework. However, in an interesting research paper, Wilcox and Wakayama[141] used a monolithic framework to design a family of aircraft in a common framework, sharing parts of selected mission requirements, where design and manufacturing costs are considered in the objective function. ...
Thesis
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The determination of optimal aerial transport networks and their associated flight frequencies is crucial for the strategic planning of airlines, as well as for carrying out market research, and for aircraft and crew rostering. In addition, optimum airplane types for the selected networks are crucial to improve revenue and to provide reduced operating costs. The present research proposes an innovative Multidisciplinary Design Optimization (MDO) framework with the objective to optimize a highly detailed airplane design simultaneously with the associated airline network, for a given area of operations and associated demand, in a multiobjective-multivariable problem. In this framework, the aircraft design and network computation modules are executed independently in sequenced blocks and wrapped into a genetic algorithm in the optimization process. Two sets of objective functions were studied, according to the optimization scope: airline operations optimization (considering Network Profit and Network Direct Operational Cost as objective functions) and airline/aircraft manufacturer optimization (considering Network Profit and manufacturer´s Cash Flow Net Present Value as objective functions). In the aircraft design module, several design parameters are used to represent the airplane in finest detail with accurate aerodynamic, stability and control, and propulsion characteristics, necessary for the mission analysis of each route segment considered in each leg of the network. The accurate calculation of a realistic mission operational profile was performed thanks to the application of an Artificial Neural Network for aerodynamic coefficient estimation and a robust generic turbofan propulsion model. In the network computation module, disciplines related to network optimization, mission performance and airline economics are integrated. The network optimization module is performed in a sub-optimization framework using an elaborated gravitational demand model to predict passenger flows between city-pairs. Under this scope, four types of simulation scenarios, considering major Brazilian airports, were evaluated in order to apply the above described methodology: determination of the optimum aircraft design in a given five airports network, determination of the optimum five airports network for a given aircraft design, simultaneous optimization of aircraft design and network (five and ten airports) and simultaneous optimization of a fleet of three aircraft and a network of twenty airports. Results demonstrated significant financial advantages for airlines on using the mentioned objective functions instead of the conventional minimization of Direct Operational Costs approach.
... As a final element for this optimization introduction, it is necessary to mention the optimization algorithms that are going to be used. For this particular problem gradient methods are not usable, or at least not the pure ones, maybe a modified version of them could be implemented but in general for problems in which the main design variables are not continuous genetic algorithms (GA) are recommended [21,22]. Genetic algorithms are also known as heuristic methods. ...
... Constraints were imposed on the variables ranges and on the wing section's thickness and camber, all of them being geometrical constraints. The authors adopted ARMOGA 13 , and the aerodynamic evaluation of the design solutions, was done by high-fidelity Navier-Stokes CFD simulations. No aeroelastic analysis was performed, which considerably reduced the total computational cost. ...
Technical Report
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The coupling schemes take us to the essential subject of Multi-Disciplinary Optimization (MDO). The interdisciplinary coupling inherent in MDO tends to present additional challenges beyond those encountered in a single-discipline optimization . It increases computational burden, and it also increases complexity and creates organizational challenges for implementing the necessary coupling in software systems. The increasing complexity of engineering systems has sparked increasing interest in multi-disciplinary optimization (MDO). The two main challenges of MDO are computational expense and organizational complexity. Accordingly the survey is focused on various ways different researchers use to deal with these challenges. The survey is organized by a breakdown of MDO into its conceptual components. Accordingly, the survey includes sections on Mathematical Modeling, Design-oriented Analysis, Approximation Concepts, Optimization Procedures, System Sensitivity, and Human Interface. With the increasing acceptance and utilization of MDO in industry, a number of software frameworks have been created to facilitate integration of application software, manage data, and provide a user interface with various MDO-related problem-solving functionalities.
... The research on the parametric design method of aircraft family has attracted the attention of many scholars. Willcox et al. studied the shape design of Blended-Wing-Body aircraft family by using the simultaneous optimization method [12]. Allison et al. applied a decomposition-based method to determine the overall parameters of the aircraft family [13]. ...
... Initially, another part of the work that should have been done during this study was to perform aircraft sizing not only for one new configuration, but to design an aircraft family whose members share some components. Indeed, one way to reduce costs is to conceive a family of aircraft which share common parts and characteristics, satisfying different mission requirements [Willcox and Wakayama, 2002]. Traditionally, this has been achieved through the use of derivatives. ...
Article
Aircraft sizing studies consist in determining the main characteristics of an aircraft starting from a set of requirements. These studies can be summarized as global constrained optimisation problems with typically one thousand parameters and almost as many constraints. The constraints express physical feasibility and the requirements to be satisfied, and the objectives are market driven performances of the aircraft. Moreover, aircraft sizing is typically a multicriteria optimisation problem because of some competing objectives. The aim of this thesis is to introduce new mathematical methods that can be useful in a future project sizing tool to treat the aircraft configuration optimisation problem. We contributed in improving the optimisation methods that are currently used in the Airbus Future Project Office. By using genetic algorithms, we made the mono-criterion optimisation process more robust. Then, we introduced multicriteria optimisation methods because we had several conflicting criteria to consider. As the calculation times became important, we decided to substitute the aircraft model by a surrogate model. We implemented radial basis functions to approximate the constraint and the objective functions. Finally, we propagated the model uncertainty to assess the robustness of the optimisation results and we proposed a possible outcome of the integration of these different techniques in order to yield the engineers a global and operational perception of the design space.
Conference Paper
A quasi-three-dimensional aerodynamic solver is connected to a finite beam element model for wing aerostructural optimization. In a quasi-three-dimensional approach an inviscid incompressible vortex lattice method is coupled with a viscous compressible airfoil analysis code for drag prediction of a three dimensional wing. The proposed quasi-three-dimensional method in this paper can compute the wing drag with an accuracy comparable to the accuracy of high fidelity CFD methods, but with much lower computational cost. A finite beam model is used for wingbox structural analysis. The wing structural deformation as well as the stress distribution in the wingbox structure is computed using that method. The Newton method is used to solve the coupled system. The sensitivities of the outputs, for example the wing drag, with respect to the inputs, for example the wing geometry, is computed by a combined use of the coupled adjoint method, automatic differentiation and the chain rule of differentiation. A gradient based optimization is performed using the proposed tool for minimizing the fuel weight of an A320 class aircraft. The optimization resulted in more than 8% reduction in the aircraft fuel weight by optimizing the wing planform and airfoils shape as well as the wing internal structure.
Article
Flying wings are one of the most promising concepts regarding the ever-increasing air traffic demand. Furthermore, they help improving economic efficiency and are environmentally friendly, both in terms of emissions and noise. In the first place, the paper deals about the initial design of a medium size C-type flying wing, of the 300-seat class, showing that the aircraft is operationally efficient, and can beat conventional airplanes of similar capacity. It specifically exhibits some considerable gains in field and cruise performances. Second, the paper addresses the potential of some emerging technologies, such as laminar flow control, vectored thrust, and active stability, which provide additional improvements and allow the simplification of the original configuration to a U-type arrangement. A preliminary assessment of emergency evacuation is included.
Article
Flying wings in various layouts (blended wing body, C-wing, tail-less aircraft, etc.) are among the most promising concepts in the foreseeable scenario of air traffic increase and very demanding noise and emission regulations. Published literature shows that these aircraft will exhibit considerable gains in field length and cruise performance with respect to conventional airplanes and could be less harmful in terms of emissions and noise. The objective of this study is to present the beneficial effects that blended wing bodies would have on the air transportation system: specifically, on four relevant aspects of airport capacity, community noise, air space capacity, and emissions.
Conference Paper
Reconfigurable systems are a class of systems that can be transformed into different configurations, generally to perform unique functions or to maintain operational efficiency under distinct conditions. In this paper, we perform the conceptual design of a new offline- reconfigurable Unmanned Aerial Vehicle (UAV) platform that can take up both a quadrotor UAV (QR-UAV) configuration and a fixed-wing UAV (FW-UAV) configuration. Potential uses of such an offline reconfigurable UAV, which provides both VTOL/hovering capabilities and long-endurance/range capabilities, include hazard-critical survey applications in remote locations (e.g., surveying wildfires). This UAV platform is comprised of modules that can be assembled/re-assembled to form the FW and QR configurations (as needed). The entire set of modules are designed to be as light as possible (allowing to be carried in backpacks), and the FW and QR configurations are required to satisfy different endurance specifications (60 mins and 15 mins). A novel combination of exploratory 3D CAD modeling and modular product platform planning is adopted for the conceptual design of the offline reconfigurable FW-QR UAV. Conceived through the 3D CAD modeling process, the QR configuration comprises four ducted rotors, a central pod (with onboard electronics), and a battery; in addition to all the components in the QR configuration, the FW configuration includes flying wing and tail sections, with the ducted rotors mounted under the wing. The modules are attached using a robust lock-pin mechanism, conceived through the 3D CAD modeling process. The modular platform planning process promote the sharing of the maximum number of modules without compromising the performances of the individual configurations, and while minimizing the net weight and net cost of all the modules. The UAV modules are defined in terms of 15 design variables, and the subsequent mixed-integer non-linear optimization is performed using the mixed-discrete Particle Swarm algorithm. Significant design improvements of 41% weight reduction and 38% cost reduction are accomplished through optimization.
Conference Paper
This paper provides an introduction to a new method for distributed optimization based on collaborative optimization, a decomposition-based method for the optimization of complex multidisciplinary designs. The key idea in this approach is to include models of the global objective and all of the subspace constraints in each subspace optimization problem while maintaining the low dimensionality of the system level (coordination) problem. Results from an analytic test case and an aircraft family design problem suggest that the new approach is robust and leads to a substantial reduction in computational eort. Collaborative optimization (CO) is a method for the design of complex, multidisciplinary systems that was originally proposed 1 in 1994. CO is one of several decomposition-based methods that divides a design problem along disciplinary (or other convenient) boundaries. The idea is to mirror the natural divisions found in aerospace design companies. In these settings, engineers are often divided into design groups by disciplinary expertise. Disciplinary analysis tools tend to be complex in nature, and it is often impractical to integrate multiple analysis codes for the purpose of multidisciplinary optimization. Rather, CO oers a means of coordinating separate analyses, even leveraging discipline-specific optimization techniques. Relative to other decomposition-based methods, CO provides the disciplinary subspaces with an unusually high level of autonomy. This enhances their ability to independently make design decisions pertinent primarily to their discipline.
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-3200.vid The Flying V is a flying-wing aircraft, which promises a 20% reduction in fuel consumption compared to a conventional twin-aisle commercial transport. The passenger cabin, cargo hold and fuel tanks are all integrated into a highly-swept, cranked wing. This study presents the conceptual design of a three-member family of Flying-V aircraft with maximal commonality between the family members. A design process is proposed to automate the synthesis process of the aircraft family comprising all relevant disciplinary analysis methods. A vortex-lattice method is employed to study the aerodynamic characteristics of the aircraft, enhanced with a viscous drag prediction method to estimate the lift-to-drag ratio. Weight of the aircraft is estimated using a combination of empirical and analytical methods. A constrained optimization algorithm is employed that minimizes fuel consumption, ensuring commonality in terms of design-variable values between family members. Comparing the resulting two largest family members to their conventional twin-aisle counterparts shows a 20% and 22% reduction fuel burn, respectively. The smaller two family members feature 100% commonality with the largest family member allowing for further reduction in fuel consumption if this constraint is relaxed. Driving parameters in Flying-V family design are the center-of-gravity excursion during flight, the wing span and the fuel tank volume.
Article
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A thermo-mechanical-electronic multifunctional structure prototype has been modelled and optimized through the use of Model Based System Engineering (MBSE) platform. The model focuses on the description of thermal and electrical phenomena, but leaves aside structural issues. It couples a 3D thermal network with representations of different possible thermal control laws, namely ON÷OFF control, proportional logic, proportional-integral-derivative strategy, and the usage of Positive Temperature Coefficient heaters. The parametric model has been already validated and correlated through a comparison with simple physical solutions, and then with the actual results of a thermal-vacuum test. A model-based approach has been used to model and properly define the main features of the overall problem. Multi-objective optimization (based on genetic algorithms) has then been used to define the best heater layout options, to identify the best control strategy in terms both of panel isothermia and energy consumption, and finally to fine-tune the parameters of the selected control strategy. In particular the main objective focused also on the use of a model-based modelling environment for the definition and set-up of an optimization problem. The study has led to the definition of an optimal thermal control solution. The optimization results show that the simultaneous adjustment of the geometrical layout, as well as the control strategy and its parameters can lead to significant energy savings.
Article
The wing component is served as a common module and sharing in every model of modern aircraft family. Due to the different mission of every model, the aerodynamic requirement of wing in the aircraft family is different. The design-ratio was inducted and the matching design optimization concept for the wing aerodynamic characteristics was presented. The corresponding models with the parameter of the model design-ratio were established. The impact of the uncertainty of the design-ratio acting on the wing aerodynamic was analyzed. The model of robust matching design optimization (RMDO) for the functional module characteristics of the aircraft family was built. RMDO for the wing aerodynamic characteristics of a transonic aircraft family with two models was accomplished. The results indicate that the wing aerodynamic difference of every model in the aircraft family and the impact of the uncertainty of the design-ratio acting on the wing aerodynamic reduce based on RMDO. And the aerodynamic performance of the aircraft is improved.
Article
There has been a pattern transform from single model to family with multiple models for the civil aircraft-developing concept. According to the strategies of modularization and generality, the aircraft family design method was developed. The design principle of the main parameters and the economic description method for the aircraft family were presented. Then the matching design model for payload and range of the aircraft family was established. The impact of the matching relationship of the payload and the range acting on the economy of the aircraft family was analyzed, too. With application of Pareto multi-objective genetic algorithm, the matching design for payload and range of a civil aircraft family was accomplished. The parameter comparison of different design schemes was carried out, and the results are satisfactory.
Article
The airliner family is a set of airliners that uses a common sub-system or components while meeting different performance or operation requirements. The airliner family can share a larger market, which is one of the key strategies for success in business. Due to the shared demand, the optimization for conceptual design of airliner family is different from that of traditional conceptual airliner design. An effective optimization method is studied for conceptual design of the airliner family. A short/medium haul airliner family is used as an example for demonstration of the method. The configurations of the airliner family are presented. A global analysis code is modified to evaluate the conceptual design. The optimization formulation for the conceptual design is presented in detail, including design variables, design constraints, and objectives. A self-adaptive evolution algorithm is used to solve the optimization problem. The results after optimization indicate that the specific design requirements for each aircraft are satisfied, and design objectives (direct operating costs) are reasonably compromised for the airliner family.
Article
An uncertainty-based approach is undertaken to deal with multipoint wing aerostructural optimization. The flight points are determined by the quadruple set of parameters: Mach number, cruise altitude, carried payload, and flight range. From this set, the payload and range are modeled as probabilistically uncertain based on U.S. flight data for the operations of an A320 aircraft. The fuel burn is selected as the performance metric to optimize. Structural failure criteria, aileron efficiency, and field performance considerations are formulated as constraints. The wing is parametrized by its planform, airfoil sections, and structural thickness. The analyses disciplines consist of an aerostructural solver and a surrogate-based mission analysis. For the optimization task, a gradient-based algorithm is used in conjunction with coupled adjoint methods and a fuel burn sensitivity analytical formula. Another key enabler is a cost-effective nonintrusive uncertainty propagator that allows optimization of an aircraft with legacy analysis codes, within a computational budget.
Chapter
The aim of this chapter is to offer an elementary introduction to approaches that have proven effective in conceptual design. The results of an optimization process are largely determined by the problem structure set up to carry out the automated process. This chapter begins by defining three classes of design parameters, explaining the difference between optimal control and discrete-variable optimization and between unconstrained and constrained optimization. Advantages and disadvantages of various single-objective optimization methods used in advanced aircraft design are discussed. It is argued that an efficient approach in the conceptual stage is a combination of non-complex explicit and complex multivariate optimization. The traditional optimization of a complete aircraft system consisting of sequential disciplinary activities resulted in sub-optimization and an inefficient development process. The method of multidisciplinary analysis and optimization exploits the synergism of interacting computational domains. This has thoroughly changed the way in which the design of complex engineering system is organized. Essential aspects of multidisciplinary optimization are system decomposition, multilevel and multi-objective optimization. Conditions for realistic and effective optimization in conceptual aircraft design are discussed and applied in the following chapters.
Article
A comprehensive investigation of evolvability and design reuse in new and historical civil jet transport aircraft was undertaken. The main purpose was to characterise the techniques and strategies used by aircraft manufacturers to evolve their designs. Such knowledge is essential to devise improved design methods for promoting the evolvability of new aircraft. To perform the study, jet aircraft from three large western manufacturers (Boeing, Airbus, and McDonnell Douglas) were investigated in depth. The academic and industrial literature was combed to find descriptions of design reuse and change across each major model of all three manufacturers. The causes and effects of the changes are explored, and the amenability of the different airframes to change are discussed. The evolution of the payload and range capabilities of the different aircraft was also investigated. From these studies, it was found that the initial approach to derivative designs appears somewhat ad hoc and that substantial modifications were devised in quick succession to increase both range and capacity. From the 1970s, two distinguishable patterns started to appear – a ‘leap and branch’ and a ‘Z’ pattern. The leaps correspond to major changes in both propulsion and airframe, whereas the branches are simple ‘stretches’ or ‘shrinks’. The Z pattern, also documented by other authors, is a progressive increase in range, followed by a simple stretch, and then another increase in range. Design changes were investigated further by grouping them according to the assumed payload-range objectives set for the derivatives. Finally, the maximum changes found for salient geometrical design parameters amongst all the aircraft surveyed were documented. Developing methods to support the creation of leaps (especially across configurations) appears to be one of the most promising avenues for future research.
Chapter
The aircraft family is a set of aircraft products that share common components but vary in configurations based on different mission performance and requirements. The reconfigurable UAV family using modular design can improve the efficiency of executing multiple missions and enable the acquisition cost benefits, which is one of key competitive edges in military applications. This paper aims to study an effective optimization method for conceptual design of the reconfigurable UAV family with interchangeable components that can be reconfigured between missions. First, a Flying-wing UAV family defined for combat and reconnaissance missions is used as an example for demonstration of the method, and an appropriate comprehensive analysis model is developed. Next, the optimization formulation for the conceptual design of UAV family is presented in detail, including design variables, design constraints, and objectives. A hybrid optimization strategy is then applied to solve the optimization problem of UAV family conceptual design. The results after optimization indicate that the mission performance and requirements for each configuration are satisfied, and costs are reasonably compromised for the UAV family.
Technical Report
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Aerodynamics is the study of motion of air, particularly as interaction with a solid object, such as an airplane wing. It is a sub-field of fluid dynamics and gas dynamics, and many aspects of aerodynamics theory are common to these fields. The term aerodynamics is often used synonymous with gas dynamics, the difference being that "gas dynamics" applies to the study of the motion of all gases, and is not limited to air. The formal study of aerodynamics began in the modern sense in the eighteenth century, although observations of fundamental concepts such as aerodynamic drag were recorded much earlier. Most of the early efforts in aerodynamics were directed toward achieving heavier-than-air flight, which was first demonstrated by Otto Lilienthal in 1891. Since then, the use of aerodynamics through mathematical analysis, empirical approximations, wind tunnel experimentation, and computer simulations has formed a rational basis for the development of heavier-than-air flight and a number of other technologies. Recent work in aerodynamics has focused on issues related to compressible flow, turbulence, and boundary layers and has become increasingly computational in nature.
Conference Paper
Aircraft families are effectively used in the commercial market for reducing costs and for rapidly responding to emerging market needs. A conceptual-level platform design decision support environment with cost evaluation is created for a commercial transport aircraft family through an integrated Model-Based Systems Engineering (MBSE) approach in MagicDraw and Design Space Exploration (DSE) in JMP. System elements and family requirements are represented within the MagicDraw 19.0 environment as well as their relationships to promote consistency and traceability of the model elements. Design space exploration and interactive visualizations are used to enable both the selection of platform variables and product-specific variables, balancing the trade-off between commonality and performance criteria among a set of solutions obtained through aircraft sizing and synthesis. Finally, cost analysis is performed for the aircraft family variants and the results are compared against individual designs for quantifying the value of commonality for design and manufacturing costs.
Technical Report
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Aerodynamics is the field that investigates the interrelation between moving solid objects and fluid. The physics behind aerodynamics is virtually associated with the drag coefficient CD, which is the dimensionless number that demonstrates the degree of conflict between a moving body and its surrounding fluid. Generally, we can say that the body is more aerodynamic if this conflict is as low as possible
Article
The common design of serial civil aircraft, an important strategy of modern civil aircraft research and develop-ment, minimizes the whole life cycle cost of civil aircraft through asset reuse and resource sharing. However, the existing estimating model for the R&D cost of civil aircraft ignores the effects of common design, so the value estimated by estimating derivative models is significantly inconsistent with the actual one. To solve this problem, a novel assessment method for civil aircraft commonality indicators is developed based on fuzzy set in the present study, exploiting the attributes and structural parameters of the aircraft to be assessed as input to determine the degree of membership that pertains to the commonality sub-interval as the commonality indicator. Then the BP (Back Propagation neural network) algorithm is adopted to establish the relationship between the common index and the decrease rate of the R&D cost of derivative models. The model employs over a dozen typical civil aircraft models (e.g., Boeing, Airbus, and Bombardier) as the sample data for network learning training to build a mature neural network model for estimating the R&D cost of novel derivative models. As revealed from the comparative analysis on the calculated results of the samples, the estimated results of the model given the effects of commonality in the present study exhibit higher estimation accuracy and value for future work.
Lifting Surface Design Using Multidisciplinary Optimization
  • S Wakayama