The Experts below are selected from a list of 189429 Experts worldwide ranked by ideXlab platform

Hamsa Balakrishnan - One of the best experts on this subject based on the ideXlab platform.

  • aircraft engine performance study using Flight Data recorder archives
    2013 Aviation Technology Integration and Operations Conference, 2013
    Co-Authors: Yashovardhan Sushil Chati, Hamsa Balakrishnan
    Abstract:

    Aircraft emissions are a significant source of pollution and are closely related to engine fuel burn. The onboard Flight Data Recorder (FDR) is an accurate source of information as it logs operational aircraft Data in situ. The main objective of this paper is the visualization and exploration of Data from the FDR. The Airbus A330 223 is used to study the variation of normalized engine performance parameters with the altitude profile in all the phases of Flight. A turbofan performance analysis model is employed to calculate the theoretical thrust and it is shown to be a good qualitative match to the FDR reported thrust. The operational thrust settings and the times in mode are found to differ significantly from the ICAO standard values in the LTO cycle. This difference can lead to errors in the calculation of aircraft emission inventories. This paper is the first step towards the accurate estimation of engine performance and emissions for different aircraft and engine types, given the trajectory of an aircraft.

  • estimation of aircraft taxi fuel burn using Flight Data recorder archives
    Transportation Research Part D-transport and Environment, 2012
    Co-Authors: Harshad Khadilkar, Hamsa Balakrishnan
    Abstract:

    Abstract This paper builds a model for estimating the fuel consumption of a taxiing aircraft using Flight Data recorder information from operational aircraft. The taxi fuel burn is modeled as a linear function of several potential explanatory variables including the taxi time, number of stops, number of turns and number of acceleration events, and the coefficients are estimated using least-squares regression. The statistical significance of each potential factor is investigated. Our analysis shows that in addition to the taxi time, the number of acceleration events is a significant factor in determining taxi fuel consumption. Since the model parameters are estimated using Data from operational aircraft, they provide more accurate estimates of fuel burn than methods that use idealized physical models of fuel consumption based on aircraft velocity profiles, or the baseline fuel consumption estimates provided by the International Civil Aviation Organization.

Sarah Yenson - One of the best experts on this subject based on the ideXlab platform.

  • human systems integration design process of the air traffic control tower Flight Data manager
    Journal of Cognitive Engineering and Decision Making, 2013
    Co-Authors: Hayley Davison J Reynolds, Kiran Lokhande, Maria Kuffner, Sarah Yenson
    Abstract:

    A user-friendly system that yields operational benefit results from Data-driven prototype evaluations and benefits analyses that iteratively feed back into the prototype design and development. In this study, initial requirements development and field evaluations were conducted using a shadow operations technique at the center tower backup Dallas-Fort Worth International Airport air traffic control tower (ATCT). Results are discussed in reference to the design process of the Tower Flight Data Manager (TFDM) prototype. Nonintrusive measures for quantitatively validating human-systems design issues were identified for this study, including visual gaze analysis and verbal command sequence analysis. Behavioral validation of design issues simplifies the process to prioritize beneficial design changes. The iterative process used resulted in an interim TFDM prototype that was rated by active air traffic controllers as both beneficial and usable in an operational ATCT environment. Language: en

  • a field demonstration of the air traffic control tower Flight Data manager prototype
    Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2011
    Co-Authors: Hayley Davison J Reynolds, Maria Kuffner, Sarah Yenson
    Abstract:

    The development and evaluation process of the Tower Flight Data Manager prototype at Dallas Ft. Worth airport is described. Key results from the first field evaluation are presented, including lessons learned about making electronic Flight information acceptable to controllers. Iteration of the field evaluation methods are discussed for practitioner benefit.

Hayley Davison J Reynolds - One of the best experts on this subject based on the ideXlab platform.

  • human systems integration design process of the air traffic control tower Flight Data manager
    Journal of Cognitive Engineering and Decision Making, 2013
    Co-Authors: Hayley Davison J Reynolds, Kiran Lokhande, Maria Kuffner, Sarah Yenson
    Abstract:

    A user-friendly system that yields operational benefit results from Data-driven prototype evaluations and benefits analyses that iteratively feed back into the prototype design and development. In this study, initial requirements development and field evaluations were conducted using a shadow operations technique at the center tower backup Dallas-Fort Worth International Airport air traffic control tower (ATCT). Results are discussed in reference to the design process of the Tower Flight Data Manager (TFDM) prototype. Nonintrusive measures for quantitatively validating human-systems design issues were identified for this study, including visual gaze analysis and verbal command sequence analysis. Behavioral validation of design issues simplifies the process to prioritize beneficial design changes. The iterative process used resulted in an interim TFDM prototype that was rated by active air traffic controllers as both beneficial and usable in an operational ATCT environment. Language: en

  • cognitive workload and visual attention analyses of the air traffic control tower Flight Data manager tfdm prototype demonstration
    Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2012
    Co-Authors: Kiran Lokhande, Hayley Davison J Reynolds
    Abstract:

    This paper presents two methods of analyzing air traffic controller activity: cognitive workload measurement through the novel comparison of controller-pilot verbal communications, and visual attention quantification through manual eye gaze analysis. These analyses were performed as part of an evaluation of the Tower Flight Data Manager (TFDM) prototype system. Cognitive workload analyses revealed that, when comparing participant controllers utilizing TFDM to a control group utilizing existing air traffic control (ATC) equipment, participants issued commands sooner than the control, and thus were perceived to have a lower workload. While visual attention Data were not available for the control group, analyses of participant gaze Data revealed 81.9% of time was spent in a head-down position, and 17.2% of time was spent head-up. Results are related back to system inefficiencies to find potential areas of improvement in design. Language: en

  • a field demonstration of the air traffic control tower Flight Data manager prototype
    Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 2011
    Co-Authors: Hayley Davison J Reynolds, Maria Kuffner, Sarah Yenson
    Abstract:

    The development and evaluation process of the Tower Flight Data Manager prototype at Dallas Ft. Worth airport is described. Key results from the first field evaluation are presented, including lessons learned about making electronic Flight information acceptable to controllers. Iteration of the field evaluation methods are discussed for practitioner benefit.

J A Gregor - One of the best experts on this subject based on the ideXlab platform.

  • a mathematical cross correlation for time alignment of cockpit voice recorder and Flight Data recorder Data
    Journal of Accident Investigation, 2006
    Co-Authors: J A Gregor
    Abstract:

    A new method is described for performing timing correlations between Flight Data recorder (FDR) and cockpit voice recorder (CVR) information. This method involves the use of the cross-correlation function to search the typically larger FDR Data file for a best match to the event pattern present in the CVR Data file. The results of this search give a first-order estimate of the time differential between identical events as recorded on both units. A simple curve fit may then be employed to obtain a general conversion from time as represented in the CVR and time as represented in the FDR.

Harshad Khadilkar - One of the best experts on this subject based on the ideXlab platform.

  • estimation of aircraft taxi fuel burn using Flight Data recorder archives
    Transportation Research Part D-transport and Environment, 2012
    Co-Authors: Harshad Khadilkar, Hamsa Balakrishnan
    Abstract:

    Abstract This paper builds a model for estimating the fuel consumption of a taxiing aircraft using Flight Data recorder information from operational aircraft. The taxi fuel burn is modeled as a linear function of several potential explanatory variables including the taxi time, number of stops, number of turns and number of acceleration events, and the coefficients are estimated using least-squares regression. The statistical significance of each potential factor is investigated. Our analysis shows that in addition to the taxi time, the number of acceleration events is a significant factor in determining taxi fuel consumption. Since the model parameters are estimated using Data from operational aircraft, they provide more accurate estimates of fuel burn than methods that use idealized physical models of fuel consumption based on aircraft velocity profiles, or the baseline fuel consumption estimates provided by the International Civil Aviation Organization.