IHS ESDU Example of statistical analysis of wet runway friction: ground-test machine data. 00018

Description
ESDU 00018 is the third of a series of examples of the application of a method for representing - and, if necessary, relating - the braking performances of aircraft and ground-test machines in wet conditions. The method, which is given in ESDU 99015, is essentially statistical and implies there is a clearly-defined level of probability that can be deduced from test runs of an aircraft (or ground-test machine) in a given set of wetness conditions on a particular runway. If the runway macro-texture depth is known, then the parameter that defines the variation of effective coefficient of braking friction in the given conditions can be readily calculated from a pre-determined Friction Data Base. The concept of a Friction Data Base is explained in ESDU 99015. This example uses data for the 'Mu-Meter' ground-test machine operating both on wetted runways and in self-wetting mode. The background to the tests is described, the method of analysis is summarised and results are presented. Mu-Meter friction measurements are available from widely differing test series - to the extent that the suitability of the various results for use in predicting aircraft stopping performance can be assessed as a function of the ranges of runway wetness conditions used. The first example, for an aircraft where an extensive set of data is available, is given in ESDU 99016. The second example, for an aircraft where only a limited set of data is available, is given in ESDU 99017. If the method of ESDU 99015 is to be used to relate the braking performances of a given combination of aircraft and ground-test machine, the procedure is comprised of two distinct phases. The first is the establishment of separate Friction Data Bases for the aircraft and for the ground-test machine. The second is to predict operational braking performance of the aircraft from day-to-day measurements from the ground-test machine.
Description
ESDU 00018 is the third of a series of examples of the application of a method for representing - and, if necessary, relating - the braking performances of aircraft and ground-test machines in wet conditions. The method, which is given in ESDU 99015, is essentially statistical and implies there is a clearly-defined level of probability that can be deduced from test runs of an aircraft (or ground-test machine) in a given set of wetness conditions on a particular runway. If the runway macro-texture depth is known, then the parameter that defines the variation of effective coefficient of braking friction in the given conditions can be readily calculated from a pre-determined Friction Data Base. The concept of a Friction Data Base is explained in ESDU 99015. This example uses data for the 'Mu-Meter' ground-test machine operating both on wetted runways and in self-wetting mode. The background to the tests is described, the method of analysis is summarised and results are presented. Mu-Meter friction measurements are available from widely differing test series - to the extent that the suitability of the various results for use in predicting aircraft stopping performance can be assessed as a function of the ranges of runway wetness conditions used. The first example, for an aircraft where an extensive set of data is available, is given in ESDU 99016. The second example, for an aircraft where only a limited set of data is available, is given in ESDU 99017. If the method of ESDU 99015 is to be used to relate the braking performances of a given combination of aircraft and ground-test machine, the procedure is comprised of two distinct phases. The first is the establishment of separate Friction Data Bases for the aircraft and for the ground-test machine. The second is to predict operational braking performance of the aircraft from day-to-day measurements from the ground-test machine.

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Example of statistical analysis of wet runway friction: ground-test machine data. - 00018 - IHS ESDU
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Example of statistical analysis of wet runway friction: ground-test machine data.
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Example of statistical analysis of wet runway friction: ground-test machine data. 00018
ESDU 00018 is the third of a series of examples of the application of a method for representing - and, if necessary, relating - the braking performances of aircraft and ground-test machines in wet conditions. The method, which is given in ESDU 99015, is essentially statistical and implies there is a clearly-defined level of probability that can be deduced from test runs of an aircraft (or ground-test machine) in a given set of wetness conditions on a particular runway. If the runway macro-texture depth is known, then the parameter that defines the variation of effective coefficient of braking friction in the given conditions can be readily calculated from a pre-determined Friction Data Base. The concept of a Friction Data Base is explained in ESDU 99015. This example uses data for the 'Mu-Meter' ground-test machine operating both on wetted runways and in self-wetting mode. The background to the tests is described, the method of analysis is summarised and results are presented. Mu-Meter friction measurements are available from widely differing test series - to the extent that the suitability of the various results for use in predicting aircraft stopping performance can be assessed as a function of the ranges of runway wetness conditions used. The first example, for an aircraft where an extensive set of data is available, is given in ESDU 99016. The second example, for an aircraft where only a limited set of data is available, is given in ESDU 99017. If the method of ESDU 99015 is to be used to relate the braking performances of a given combination of aircraft and ground-test machine, the procedure is comprised of two distinct phases. The first is the establishment of separate Friction Data Bases for the aircraft and for the ground-test machine. The second is to predict operational braking performance of the aircraft from day-to-day measurements from the ground-test machine.

ESDU 00018 is the third of a series of examples of the application of a method for representing - and, if necessary, relating - the braking performances of aircraft and ground-test machines in wet conditions. The method, which is given in ESDU 99015, is essentially statistical and implies there is a clearly-defined level of probability that can be deduced from test runs of an aircraft (or ground-test machine) in a given set of wetness conditions on a particular runway. If the runway macro-texture depth is known, then the parameter that defines the variation of effective coefficient of braking friction in the given conditions can be readily calculated from a pre-determined Friction Data Base. The concept of a Friction Data Base is explained in ESDU 99015. This example uses data for the 'Mu-Meter' ground-test machine operating both on wetted runways and in self-wetting mode. The background to the tests is described, the method of analysis is summarised and results are presented. Mu-Meter friction measurements are available from widely differing test series - to the extent that the suitability of the various results for use in predicting aircraft stopping performance can be assessed as a function of the ranges of runway wetness conditions used. The first example, for an aircraft where an extensive set of data is available, is given in ESDU 99016. The second example, for an aircraft where only a limited set of data is available, is given in ESDU 99017. If the method of ESDU 99015 is to be used to relate the braking performances of a given combination of aircraft and ground-test machine, the procedure is comprised of two distinct phases. The first is the establishment of separate Friction Data Bases for the aircraft and for the ground-test machine. The second is to predict operational braking performance of the aircraft from day-to-day measurements from the ground-test machine.

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  IHS ESDU
Product Category Standards and Technical Documents
Product Number 00018
Product Name Example of statistical analysis of wet runway friction: ground-test machine data.
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