Data-Driven Modeling of Aircraft Engine Performance
Yashovardhan Sushil Chati

Citation
Yashovardhan Sushil Chati. "Data-Driven Modeling of Aircraft Engine Performance". Talk or presentation, 4, November, 2015.

Abstract
The fuel flow rate is an important aspect of aircraft engine performance. The accurate estimation of the fuel flow rate during flight enables the development of fuel burn inventories. The objective of our research is to develop models of engine performance using operational flight data from Flight Data Recorders (FDRs) in combination with insights from the physical principles governing the operation of an aircraft engine. In this talk, we use hierarchical Bayesian Multiple Linear Regression to model the fuel flow rate as a function of the aircraft pressure altitude, ground speed, vertical speed, and aircraft mass. A two-layer hierarchical model of an Airbus A320-200 aircraft in cruise is built: the lower layer consists of a regression model of the fuel flow rate for each flight, while the upper level estimates the regression parameters corresponding to the particular type of aircraft. Posterior distributions of the aircraft type regression coefficients are used to develop posterior predictive distributions of the fuel flow rate on an unseen test dataset. This model predictive performance is also compared with that of models developed using non Bayesian methods. We present preliminary ideas for extending the approach to other phases of flight and aircraft types.

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  • HTML
    Yashovardhan Sushil Chati. <a
    href="http://www.cps-forces.org/pubs/98.html"
    ><i>Data-Driven Modeling of Aircraft Engine
    Performance</i></a>, Talk or presentation,  4,
    November, 2015.
  • Plain text
    Yashovardhan Sushil Chati. "Data-Driven Modeling of
    Aircraft Engine Performance". Talk or presentation,  4,
    November, 2015.
  • BibTeX
    @presentation{Chati15_DataDrivenModelingOfAircraftEnginePerformance,
        author = {Yashovardhan Sushil Chati},
        title = {Data-Driven Modeling of Aircraft Engine Performance},
        day = {4},
        month = {November},
        year = {2015},
        abstract = {The fuel flow rate is an important aspect of
                  aircraft engine performance. The accurate
                  estimation of the fuel flow rate during flight
                  enables the development of fuel burn inventories.
                  The objective of our research is to develop models
                  of engine performance using operational flight
                  data from Flight Data Recorders (FDRs) in
                  combination with insights from the physical
                  principles governing the operation of an aircraft
                  engine. In this talk, we use hierarchical Bayesian
                  Multiple Linear Regression to model the fuel flow
                  rate as a function of the aircraft pressure
                  altitude, ground speed, vertical speed, and
                  aircraft mass. A two-layer hierarchical model of
                  an Airbus A320-200 aircraft in cruise is built:
                  the lower layer consists of a regression model of
                  the fuel flow rate for each flight, while the
                  upper level estimates the regression parameters
                  corresponding to the particular type of aircraft.
                  Posterior distributions of the aircraft type
                  regression coefficients are used to develop
                  posterior predictive distributions of the fuel
                  flow rate on an unseen test dataset. This model
                  predictive performance is also compared with that
                  of models developed using non Bayesian methods. We
                  present preliminary ideas for extending the
                  approach to other phases of flight and aircraft
                  types.},
        URL = {http://cps-forces.org/pubs/98.html}
    }
    

Posted by Carolyn Winter on 4 Nov 2015.
Groups: forces
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