Multidisciplinary design optimization is considered in the context of designing a family of aircraft Aframework is developed in which multiple aircraft, each with different missions but sharing common parts, can be optimized simultaneouslyThenewframeworkisusedtogaininsighttotheeffectofdesignvariablescalingontheoptimization algorithm Results are presented for a two-member family whose individual missions differ signie cantly Both missions can be satise 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 quantie ed for design and manufacturing costs A notional example is presented to show the cost benee t that may be achieved by designing a common family of aircraft

/pdf/simultaneous-optimization-of-a-multiple-aircraft-family-3e78egclo9.pdf

Simultaneous Optimization of a Multiple-Aircraft Family

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design

New methods for rapid front-end development of complex systems are introduced. New tradespace exploration techniques, advances in integrated concurrent engineering, and application of risk analysis methods early in the design process allow rapid progress from poorly defined user needs to fairly detailed conceptual designs. An overview is provided of the methods. A process is described that allows thousands of system architecture alternatives to be quickly and quantitatively assessed vs user needs. The result is an understanding of the tradespace, including its key constraints and sensitivities, as well as an optimum architecture. This architecture is used to specify needs for space vehicles, which are designed using integrated concurrent engineering techniques. Research in risk and uncertainty, policy impacts, and information technology methods allows quantitative consideration of these factors, resulting in designs that are robust to uncertainties and policy impacts and potentially more versatile and flexible. Eight systems designed to date using the method are briefly reviewed. Key literature and a number of companion papers that go into depth on various aspects of the method are cited.

New Methods for Rapid Architecture Selection and Conceptual Design

An overview of the deployment of multidisciplinary-optimization technologies in an industrial environment is presented herein. This capability is being developed in a multilevel framework in line with the aircraft design stages within the engineering organization. At every design stage, the appropriate problem formulation, level of detail, analysis tools, and optimization strategy are implemented to meet the design objectives within the design-cycle time frame. The multidisciplinary-optimization technologies are deployed incrementally as an evolution of existing engineering methods, with subject-matter experts contributing to the problem setup and validation of the framework. A description of the multilevel strategy and sample results are provided.

Development of a Multilevel Multidisciplinary-Optimization Capability for an Industrial Environment

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.

http://aero.stanford.edu/Reports/AIAA-2008-5841.pdf

Enhanced Collaborative Optimization: Application to an Analytic Test Problem and Aircraft Design

This research considers the commercial aircraft design process from the perspective of program value. Whereas traditionally, the conceptual design of aircraft has often focused on minimum weight, or sometimes minimum cost, this approach demonstrates the feasibility and usefulness of design based on maximum value to the aircraft manufacturer. A program valuation tool is developed and demonstrated that measures the overall program value associated with a set of either one or two new aircraft concepts. The tool is based on a combination of a performance model; a development and manufacturing cost model; a revenue model; and a dynamic programming-based algorithm that accounts for uncertainty in future market conditions and the program’s ability to cope with such uncertainty through real-time decision-making. The cost model, using a component-based representation of the aircraft, allows for the consideration of the effects of part commonality on development and production costs. The revenue model, based on an analysis of existing commercial aircraft, estimates a market price and demand forecast for a new aircraft based on several key characteristics. The dynamic programming algorithm, used to find program value, treats annual aircraft quantity demanded as a stochastic process, evolving unpredictably with time. The algorithm borrows from Real Options theory to discount future cash flows using riskneutral expectations and models the aircraft program as an actively managed project with real-time decision-making to maximize expected program value. Several examples are drawn from the Blended-Wing-Body aircraft concept to demonstrate the operation of the program valuation tool. The results suggest that the value of part commonality between aircraft may be strongly sensitive to the weight penalty and increased fuel burn resulting from a common derivative design. More generally, the example results illustrate the usefulness of the explicit consideration of flexibility in program valuation and the feasibility of a conceptual aircraft design tool based on the metric of program value. Thesis Supervisor: Karen Willcox Title: Assistant Professor, Aeronautics and Astronautics

/pdf/valuation-techniques-for-commercial-aircraft-program-design-421y4kpqmf.pdf

Jacob Markish

Papers

Valuation techniques for commercial aircraft program design