The Experts below are selected from a list of 1419 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.

Fairuz Azmi - One of the best experts on this subject based on the ideXlab platform.

  • dragon stream cipher for secure blackbox cockpit voice Recorder
    Microelectronics Systems Education, 2017
    Co-Authors: Fadira Akmal, Surya Michrandi Nasution, Fairuz Azmi
    Abstract:

    Aircraft blackbox is a device used to record all aircraft information, which consists of Flight Data Recorder (FDR) and Cockpit Voice Recorder (CVR). Cockpit Voice Recorder contains conversations in the aircraft during the Flight.Investigations on aircraft crashes usually take a long time, because it is difficult to find the aircraft blackbox. Then blackbox should have the ability to send information to other places. Aircraft blackbox must have a Data security system, Data security is a very important part at the time of information exchange process. The system in this research is to perform the encryption and decryption process on Cockpit Voice Recorder by people who are entitled by using Dragon Stream Cipher algorithm. The tests performed are time of Data encryption and decryption, and avalanche effect. Result in this paper show us time encryption and decryption are 0,85 seconds and 1,84 second for 30 seconds Cockpit Voice Recorder Data witn an avalanche effect 48,67 %.

  • analysis of cockpit voice Recorder compression reliability for airplane on demand blackbox Data transmission
    2017 International Conference on Control Electronics Renewable Energy and Communications (ICCREC), 2017
    Co-Authors: Setianto Nugroho, Surya Michrandi Nasution, Fairuz Azmi
    Abstract:

    The black box records all the important information that takes place on a flying plane. The black box is a tool used on airplanes to store all activities during Flight. The black box has a Flight Data Recorder (FDR) and a Cockpit Voice Recorder. FDR and CVR function to record and record the existing in the aircraft. The black box has recordings of information that occurs during the Flight. Data generated FDR and CVR have a very large size is very difficult to transmit in real time. For that in this research make system that can divide Data and compress Data. The sound Data in the conversion becomes binary by analog digital converter. The results of the Data in binary form will be parsed into multiple partitions. Then the Data partition into the compression process of Data directly processed to obtain an efficient Data size. The results of analysts seen from the size of Data and time. In the conversion process becomes binary and parsing Data takes about 223.4587466 seconds for 50 partitions. For time / partition takes about 4.46053 seconds. For compression takes 39614.72399 seconds for 50 partitions while for time / partition takes 792.2944798 seconds.

  • analysis of Flight Data Recorder compression reliability for airplane on demand blackbox Data transmission
    2017 International Conference on Control Electronics Renewable Energy and Communications (ICCREC), 2017
    Co-Authors: Dhipo Arsyandana Putra, Surya Michrandi Nasution, Fairuz Azmi
    Abstract:

    Currently, Blackbox records all important information that happens during the accident that is Flight Data Recorder (FDR) and Cockpit Voice Recorder (CVR). The Data is for by applying a compression method to make both of them get into transmission with on demand. This way is probably to present the Data without has to find the black box. It will make the investigator easier on the evacuation process. In this study, a program created is the conversion of Data into binary, split and merge Data and Data compression. The compression results are based on the type and size of the FDR Data. The algorithm is to make the Data size smaller and the decompression process takes a long time compared to the compression process. The results of the analysis get the result that when the compression process is faster to 1295.33 second than FDR Data recording process. and the time required decompression time longer to 3805.10 second. On the simulation FDR, from the process parsing, compression, decompression until merge all Data needed time to 5008,1316 second.

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

  • Modeling of Aircraft Takeoff Weight Using Gaussian Processes
    'American Institute of Aeronautics and Astronautics (AIAA)', 2019
    Co-Authors: Chati, Yashovardhan Sushil, Balakrishnan Hamsa
    Abstract:

    The takeoff weight of an aircraft is an important aspect of aircraft performance. However, the takeoff weight of a particular Flight is generally not available to entities outside of the operating airline. The preceding observations motivate the development of accurate takeoff weight estimates that can be used for fuel-burn estimation or trajectory prediction. This paper proposes a statistical approach based on Gaussian process regression to determine both a mean estimate of the takeoff weight and the associated prediction interval, using observed Data from the takeoff ground roll. The model development and validation are conducted using Flight Data Recorder archives, which also provide ground-truth Data. The models are found to have a mean absolute error in takeoff weight of 3.6%, averaged across nine different aircraft types, resulting in a nearly 35% smaller error than the models in the Aircraft Noise and Performance Database. Finally, the developed models are used to predict aircraft fuel flow rate during climb out and approach. For the majority of the aircraft types studied, the statistical models of takeoff weight estimation are shown to result in a similar or better fuel flow rate predictive performance as compared to the Aircraft Noise and Performance models.National Science Foundation grant (1239054

  • Estimation of Aircraft Taxi-out Fuel Burn using Flight Data Recorder Archives
    'American Institute of Aeronautics and Astronautics (AIAA)', 2018
    Co-Authors: Khadilkar, Harshad Dilip, Balakrishnan Hamsa
    Abstract:

    The taxi-out phase of a Flight accounts for a significant fraction of total fuel burn for aircraft. In addition, surface fuel burn is also a major contributor to CO 2 emissions in the vicinity of airports. It is therefore desirable to have accurate estimates of fuel consumption on the ground. This paper builds a model for estimation of on-ground fuel consumption of an aircraft, given its surface trajectory. Flight Data Recorder archives are used for this purpose. The taxi-out fuel burn is modeled as a linear function of several factors including the taxi-out time, number of stops, number of turns, and number of acceleration events. The statistical significance of each potential factor is investigated. The parameters of the model are estimated using least-squares regression. Since these 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. Our analysis shows that in addition to the total taxi time, the number of acceleration events is a significant factor in determining taxi fuel consumption. © 2011 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved

  • Statistical modeling of aircraft takeoff weight
    'The Korean Society for Heat Treatment', 2018
    Co-Authors: Chati, Yashovardhan Sushil, Balakrishnan Hamsa
    Abstract:

    The Takeoff Weight (TOW) of an aircraft is an important aspect of aircraft performance, and impacts a large number of characteristics, ranging from the trajectory to the fuel burn of the Flight. Due to its dependence on factors such as the passenger and cargo load factors as well as operating strategies, the TOW of a particular Flight is generally not available to entities outside of the operating airline. The above observations motivate the development of accurate TOW estimates that can be used for fuel burn estimation or trajectory prediction. This paper proposes a statistical approach based on Gaussian Process Regression (GPR) to determine both a mean estimate of the TOW and the associated confidence interval, using observed Data from the takeoff ground roll. The predictor variables are chosen by considering both their ease of availability and the underlying aircraft dynamics. The model development and validation are conducted using Flight Data Recorder archives, which also provide ground truth Data. The proposed models are found to have a mean TOW error of 3%, averaged across eight different aircraft types, resulting in a nearly 50% smaller error than the models in the Aircraft Noise and Performance (ANP) Database. In contrast to the ANP Database which provides only point estimates of the TOW, the GPR models quantify the uncertainty in the estimates by providing a probability distribution. Finally, the developed models are used to estimate aircraft fuel flow rate during ascent. The TOW estimated by the GPR models is used as an input to the fuel flow rate estimation. The proposed statistical models of the TOW are shown to enable a better quantification of uncertainty in the fuel flow rate as compared to the deterministic ANP models, or to models that do not use the TOW as an explicit input.National Science Foundation (U.S.) (Award 0931843

Dhipo Arsyandana Putra - One of the best experts on this subject based on the ideXlab platform.

  • analysis of Flight Data Recorder compression reliability for airplane on demand blackbox Data transmission
    2017 International Conference on Control Electronics Renewable Energy and Communications (ICCREC), 2017
    Co-Authors: Dhipo Arsyandana Putra, Surya Michrandi Nasution, Fairuz Azmi
    Abstract:

    Currently, Blackbox records all important information that happens during the accident that is Flight Data Recorder (FDR) and Cockpit Voice Recorder (CVR). The Data is for by applying a compression method to make both of them get into transmission with on demand. This way is probably to present the Data without has to find the black box. It will make the investigator easier on the evacuation process. In this study, a program created is the conversion of Data into binary, split and merge Data and Data compression. The compression results are based on the type and size of the FDR Data. The algorithm is to make the Data size smaller and the decompression process takes a long time compared to the compression process. The results of the analysis get the result that when the compression process is faster to 1295.33 second than FDR Data recording process. and the time required decompression time longer to 3805.10 second. On the simulation FDR, from the process parsing, compression, decompression until merge all Data needed time to 5008,1316 second.

  • Analisis Reliabilitas Kompresi Flight Data Recorder Untuk Transmisi On Demand Data Kotak Hitam Pesawat Terbang
    Universitas Telkom, 2017
    Co-Authors: Dhipo Arsyandana Putra
    Abstract:

    Pada saat pesawat mengalami kecelakaan, tim penyelidik akan melakukan proses pencarian terhadap korban kecelakaan dan kotak hitam. Kotak hitam memiliki rekaman seluruh informasi penting yang terjadi selama penerbangan. Kedua hal tersebut merupakan langkah utama yang harus dilakukan. Namun jika dilakukan dalam waktu yang bersamaan akan dapat mengganggu fokus kerja tim penyelidik. Untuk itu dibutuhkan solusi alternatif dalam meminimalisir pekerjaan tersebut. Pada penelitian ini, akan dibahas mengenai analisa Data yang terdapat pada kotak hitam yaitu Data Cockpit Voice Recoder (CVR) dan Flight Data Recorder (FDR) dengan menerapkan suatu metode kompresi sehingga kedua Data tersebut dapat ditransmisikan secara on demand. Hal ini memungkinkan untuk merepresentasikan Data tanpa harus menemukan bentuk fisik kotam hitam. Tentunya akan memudahkan tim penyelidik dalam proses pencarian sehingga dapat fokus untuk mencari korban kecelakaan. Diharapkan pada penelitian ini akan membantu mengurangi resiko dalam proses pencarian insiden kecelakaan pesawat. Dengan adanya penelitan ini, betujuan untuk memudahkan representasi Data secara simulasi agar tim penyelidik tidak kesulitan menemukan lokasi kotak hitam saat terjadi kecelakaan pesawat. Kata kunci : Kotak Hitam, Flight Data Recorder (FDR), Data

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