MDO at Predesign Stage

Guenov, Marin D.; Fantini, Paolo; Balachandran, L. K.; Maginot, Jeremy; Padulo, Mattia

doi:10.2514/5.9781600867279.0017.0071

Cited by 4 publications

(1 citation statement)

References 28 publications

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“…Another work studies the influence of the system design variables with a satellite optimization as the benchmark case [186]. Finally, some studies, [187,188], address the current state of the art in MDO at predesign stage and space launchers.…”

Section: Multidisciplinary Design Optimizationmentioning

confidence: 99%

RPAS Design : an MDO Approach

Aliaga-Aguilar¹

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Unmanned aircraft and, particularly, RPAS (Remotely Piloted Aircraft Systems) are nowadays experiencing great growth both in the military and civil industries. This is due to the fact that removing the need to be manned has enabled the improvement of their endurance, range, and overall performance while, at the same time, reducing the risk to which human lives were exposed. In addition, RPAS can be made much smaller. This decrease of mass and size increases the variety of missions they can perform. However, the design process to manufacture such aircraft is often long and costly, which prevents small companies from undertaking it. Multidisciplinary Design Optimization (MDO) is an engineering field whose focus is to solve highly complex problems by the means of optimization techniques. It has been used in the design of commercial aircraft for a long time, but integrating the various engineering disciplines that take part in designing an RPAS within an MDO to simplify the design process is a challenge. In addition, there is an ample variety of architectures for MDO projects and, the reasons to choose a particular one, have to be discussed on a case by case basis. During the last years, distributed architectures have become widespread, given that they can take advantage of parallel computing (even with graphical platforms) and reduce computing time. Adapting the formulation of a problem to a particular vii Dissertation Overview Chapter 1: This is the introduction to the thesis. It presents the evolution of RPAS and the current state of the art both in MDO and in RPAS design methodologies. Chapter 2 introduces the Generic Parameter Penalty Architecture (GPPA): a new, flexible MDO architecture, oriented towards the solution of engineering problems that present different levels of complexity. Chapter 3 introduces the RPAS Advanced MDO Platform (RAMP). A new MDO environment aimed at the design of small RPAS. Chapters 4-7 present RAMP's main analysis models: aerodynamics, structure, economy and pricing, propulsion, and performance. Chapter 8 presents an application case of RAMP to a real-world mission. Chapter 8 does so by limiting RAMP's configuration availability to just classical. This provides the opportunity to compare its results to most commercially available RPAS, while Chapter 9 unleashes RAMP's full capabilities to also consider Blended Wing Body (BWB) and Canard configurations. Chapter 9 presents results for the various tests and hypothesis that are presented in the thesis, while Chapter 10 serves to give shape to the conclusions of the thesis and the future lines of research.

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Section: Multidisciplinary Design Optimizationmentioning

confidence: 99%

RPAS Design : an MDO Approach

Aliaga-Aguilar¹

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Realizing collaborative systems design for missile seekers by combining design margin analysis with multi-disciplinary optimization

Cross¹,

Mulford

2015

Concurrent Engineering

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Collaborative design is a recursive process, wherein multiple engineering disciplines iteratively pursue targeted goals. The collaborative process mandates the sharing of information, enabling performance assessments for negotiation of requirement trade-offs. A layered architecture supports collaboration across the missile's subsystems allowing for optimization of critical product parameters. The multidisciplinary optimization expedites trades between performance and product resources such as mission performance, system cost, computational throughput, and memory capacity. We propose an innovative process for missile design using collaborative system design margin analysis with multidisciplinary optimization. A core principle of design margin analysis is the disciplined allocation of performance margins to critical parameters at the system level. This paradigm assures consistent performance and reliability while optimizing key metrics, especially cost. Critical to attaining that core principle is the ready access and traceability of all critical parameters at each subsystem level and for all hardware, software, and firmware components. Additionally, the collaborative system design margin analysis with multidisciplinary optimization framework analyzes and re-allocates design margins to optimize performance parameters in a collaborate manner. This article proposes to demonstrate engineering methods for rigorous evaluation and effective communication of system performance between design disciplines. Communication begins with consistent terminology throughout the design process. Our demonstration will consist of two focus areas: reliable performance measurement and robust design evaluation. Specifically, the article will show collaborative system design margin analysis with multidisciplinary optimization effectivity using signal processing examples. Prior robust design methodologies by Taguchi in conjunction with a common view of system performance lay a framework for collaborative design margin with a constrained optimization approach. Each critical engineering decision is viewed with a perspective of overall system performance, quality, and cost. The following design trades are used for demonstration; probability of target acquisition, as a function of seeker complexity and target classification capability; signal processing distortion, as a function of computational complexity; and using phase noise margin to optimize the signal processing electronics. Currently, the authors have developed a collaborative design infrastructure to demonstrate collaborative system design margin analysis with multidisciplinary optimization principles and their efficacy. The analyses and trade results of each of the design examples will highlight design options with acceptable performance as a function of applicable resources.

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Fast Nonlinear Static Aeroelasticity Method for High-Aspect-Ratio Wings at Different Mach Regimes

Chandre-Vila

Boin

Barriety

et al. 2023

Journal of Aircraft

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A low-computational-cost method is proposed in this paper to predict steady-state nonlinear aeroelastic response for high-aspect-ratio wings. This fast nonlinear static aeroelasticity method relies on a simple but robust mathematical approach. The work presented in this paper evaluates the accuracy of a nonlinear aerodynamic method on a large range of Mach numbers for a geometry representative of a typical industrial high-aspect-ratio-wing aircraft. The robustness of the method relies on the accurate estimation of the local pressure field based on an aerodynamic database using a local incidence estimated with a vortex lattice method. The database can be filled with flight test, wind tunnel test, or high-fidelity numerical simulation. The structural deformation is provided by a coupled aeroelastic high-fidelity numerical simulation, and so this paper focuses mainly on the development and validation of the aerodynamic model. Then, the flexible coefficients of the wing are compared to the high-fidelity aeroelastic numerical simulations for a set of Mach numbers ranging from subsonic to transonic conditions. The results presented in this paper show that the present method is very accurate for low-Mach-number regimes (error is lower than 1% on lift), and it is also adapted to transonic flow regimes because the error on lift is lower than 5%. For high Mach numbers, the current solution commits larger errors on drag and pitching moment coefficients.

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MDO at Predesign Stage

Cited by 4 publications

References 28 publications

RPAS Design : an MDO Approach

RPAS Design : an MDO Approach

Realizing collaborative systems design for missile seekers by combining design margin analysis with multi-disciplinary optimization

Fast Nonlinear Static Aeroelasticity Method for High-Aspect-Ratio Wings at Different Mach Regimes

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