Flight loads calculations play a fundamental role in the development and certification of an aircraft and have an impact on the structural sizing and weight. The number of load cases required by the airworthiness regulations is in the order of tens of thousands and the analysis must be repeated for each design iteration. On large aircraft, CS-25 explicitly requires taking into account for loads prediction, airframe flexibility, unsteady aerodynamics and interaction of systems and structure, leading to computationally expensive numerical models. Thus there is a clear benefit in speeding-up this calculation process. This paper presents a methodology aiming to significantly reduce the computational time to predict loads due to gust and maneuvers. The procedure is based on Model Order Reduction, whose goal is the generation of a Reduced Order Model (ROM) able to limit the computational cost compared to a full analysis whilst retaining accuracy. The method is applied to a commercial transport aircraft modeled with beam elements, unsteady aerodynamics based on Doublet Lattice Method and servo-hydraulic actuators for the control surfaces. The aeroelastic equations of motion are formulated in the time-domain, through the Rational Function Approximation and application of the Balanced Truncation method. The results obtained with the reduced model shows a very good accuracy with respect to the full model and a significant saving in computational time. The impact of flexibility on the gust load factor is also highlighted, comparing it with the quasi-static analysis by Pratt's formula, current standard for Part 23 aircraft.


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    Title :

    Reduced Order Model Approach for Efficient Aircraft Loads Prediction


    Additional title:

    Sae Int. J. Aerosp


    Contributors:

    Conference:

    SAE 2015 AeroTech Congress & Exhibition ; 2015


    Published in:

    Publication date :

    2015-09-15


    Size :

    9 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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