The Experts below are selected from a list of 50085 Experts worldwide ranked by ideXlab platform

Aneli Bongers - One of the best experts on this subject based on the ideXlab platform.

  • learning and forgetting in the jet fighter Aircraft industry
    PLOS ONE, 2017
    Co-Authors: Aneli Bongers
    Abstract:

    A recent strategy carried out by the Aircraft industry to reduce the total cost of the new generation fighters has consisted in the development of a single airframe with different technical and operational specifications. This strategy has been designed to reduce costs in the Research, Design and Development phase with the ultimate objective of reducing the final unit price per Aircraft. This is the case of the F-35 Lightning II, where three versions, with significant differences among them, are produced simultaneously based on a single airframe. Whereas this strategy seems to be useful to cut down pre-production sunk costs, their effects on production costs remain to be studied. This paper shows that this strategy can imply larger costs in the production phase by reducing learning acquisition and hence, the total effect on the final unit price of the Aircraft is indeterminate. Learning curves are estimated based on the flyaway cost for the latest three fighter Aircraft Models: The A/F-18E/F Super Hornet, the F-22A Raptor, and the F-35A Lightning II. We find that learning rates for the F-35A are significantly lower (an estimated learning rate of around 9%) than for the other two Models (around 14%).

  • learning and forgetting in the jet fighter Aircraft industry
    Research Papers in Economics, 2017
    Co-Authors: Aneli Bongers
    Abstract:

    A recent strategy carried out by the Aircraft industry to reduce the total cost of new generation fighter has consisted in the development of a single airframe with different technical and operational specifications. This strategy has been designed to reduce costs in the Research, Design, and Development phase with the aim of reducing the final unitary price of Aircraft. This is the case of the F-35 Lightning II, where three versions, with significant differences among them, are produced simultaneously based on a single airframe. Whereas this strategy seems to be useful to reduce pre-production sunk costs, remains key to study their effects on production costs. This paper shows that this strategy can imply larger costs in the production phase by reducing learning acquisition and hence, the total effect on the final unitary price of the Aircraft is indeterminate. Learning curves are estimated based on the flyaway cost for the latest three fighter Aircraft Models: The A/F-18E/F Super Hornet, F-22A Raptor, and the F-35A Lightning II. We find that learning rates for the F-35A are significantly lower (an estimated learning rate around 9%) than for the other two Models (around 14%).

Thomas w. Gilligan - One of the best experts on this subject based on the ideXlab platform.

  • Lemons and Leases in the Used Business Aircraft Market
    Journal of Political Economy, 2004
    Co-Authors: Thomas w. Gilligan
    Abstract:

    Given adverse selection, durable goods that trade infrequently depreciate quickly. Consistent with this prediction I find an inverse relationship between depreciation and trading volume for less reliable brands of used business Aircraft. Additionally, recent theoretical analyses suggest that leasing, by increasing the average quality of used goods, may reduce adverse selection in durable goods markets. Indeed, I find a direct relationship between depreciation and trading volume for Aircraft Models with relatively high lease rates. Together these findings suggest that adverse selection is a prominent feature of the contemporary used business Aircraft market and that leasing mitigates the consequences of adverse selection.

Thomas W Gilligan - One of the best experts on this subject based on the ideXlab platform.

  • lemons and leases in the used business Aircraft market
    Journal of Political Economy, 2004
    Co-Authors: Thomas W Gilligan
    Abstract:

    Given adverse selection, durable goods that trade less frequently depreciate more quickly. Consistent with this prediction, I find an inverse relationship between depreciation and trading volume for less reliable brands of used business Aircraft. Additionally, recent theoretical analyses suggest that leasing, by increasing the average quality of used goods offered for sale, may reduce adverse selection in durable goods markets. Indeed, I find an increase in the direct relationship between depreciation and trading volume for Aircraft Models with relatively high lease rates. Together these findings suggest that adverse selection is a prominent feature of the market for contemporary used business Aircraft and that leasing mitigates the consequences of asymmetric information about the quality of used durable goods.

Michael O'neill - One of the best experts on this subject based on the ideXlab platform.

  • Evolving parametric Aircraft Models for design exploration and optimisation
    Neurocomputing, 2014
    Co-Authors: Jonathan Byrne, Philip Cardiff, Anthony Brabazon, Michael O'neill
    Abstract:

    Traditional CAD tools generate a static solution to a design problem. Parametric systems allow the user to explore many variations on that design theme. Such systems make the computer a generative design tool and are already used extensively as a rapid prototyping technique in architecture and aeronautics. Combining a design generation tool with an analysis software and an evolutionary algorithm provides a methodology for optimising designs. This work combines [email protected]?s parametric Aircraft design tool (OpenVSP) with a fluid dynamics solver (OpenFOAM) to create and analyse Aircraft. An evolutionary algorithm is then used to generate a range of Aircraft that maximise lift and reduce drag while remaining within the framework of the original design. Our approach allows the designer to automatically optimise their chosen design and to generate Models with improved aerodynamic efficiency. Different components on three Aircraft Models are varied to highlight the ease and effectiveness of the parametric model optimisation.

Hyotae Kim - One of the best experts on this subject based on the ideXlab platform.

  • efficient radar target recognition using the music algorithm and invariant features
    IEEE Transactions on Antennas and Propagation, 2002
    Co-Authors: Kyungtae Kim, Dongkyu Seo, Hyotae Kim
    Abstract:

    An efficient technique is developed to recognize target type using one-dimensional range profiles. The proposed technique utilizes the Multiple Signal Classification algorithm to generate superresolved range profiles. Their central moments are calculated to provide translation-invariant and level-invariant feature vectors. Next, the computed central moments are mapped into values between zero and unity, followed by a principal component analysis to eliminate the redundancy of feature vectors. The obtained features are classified based on the Bayes classifier, which is one of the statistical classifiers. Recognition results using five different Aircraft Models measured at compact range are presented to assess the effectiveness of the proposed technique, and they are compared with those of the conventional range profiles obtained by inverse fast Fourier transform.