A measurement-based statistical model to evaluate uncertainty in long-range noise assessments: Dissertation
Panu Maijala
Research output: Thesis › Dissertation › Monograph
Carefully validated long-range sound propagation measurements with extensive meteorological instrumentation were continued for 612 days without interruption, around the clock, resulting in a database with millions of files, terabytes of sound and environmental data, and hundreds of pages of documentation. More than 100 environmental variables were analysed by statistical means, and many statistically highly significant dependencies linked to excess attenuation were found. At a distance of 3 km from the source, excess attenuation was spread over a dynamic range of 80 dB, with differences of 10 dB between individual quarters of the year; also, negative excess attenuation at frequencies below 400 Hz existed. The low frequencies were affected mainly by the stability characteristics of the atmosphere and the lapse rate. Humidity; lapse rate; sensible heat flux; and longitudinal, transverse, and vertical turbulence intensities explain excess attenuation at higher frequencies to a statistically highly significant extent. Through application of a wide range of regression analyses, a set of criteria for frequency-dependent uncertainty in sound propagation was created. These criteria were incorporated into a software module, which, together with a state-of-the-art physical sound propagation calculation module, makes it possible to perform environmental noise assessments with known uncertainty. This approach can be applied to the shortterm measurements too and it was shown that some of the most complex meteorological variables, among them atmospheric turbulence, can be taken into account. Comparison with two standardised noise modelling methods showed that the statistical model covers well a range of uncertainty notmatched with the standardisedmethods and themeasured excess attenuation fit within the limits of predicted uncertainty.
Doctor Degree
Tampere University of Technology (TUT)
Halttunen, Jouko, Supervisor, External person
Kuivanen, Risto, Advisor
Electronic ISBNs
G4 Doctoral dissertation (monograph)
acoustic wave propagation
atmospheric acoustics
environmental acoustics
noise assessments
statistical model
http://www.vtt.fi/inf/pdf/science/2013/S48.pdf
Dive into the research topics of 'A measurement-based statistical model to evaluate uncertainty in long-range noise assessments: Dissertation'. Together they form a unique fingerprint.
sound propagation Earth & Environmental Sciences 100%
turbulence Earth & Environmental Sciences 36%
environmental noise Earth & Environmental Sciences 31%
sensible heat flux Earth & Environmental Sciences 26%
environmental data Earth & Environmental Sciences 25%
documentation Earth & Environmental Sciences 22%
instrumentation Earth & Environmental Sciences 21%
state of the art Earth & Environmental Sciences 20%
Maijala, P. (2013). A measurement-based statistical model to evaluate uncertainty in long-range noise assessments: Dissertation. VTT Technical Research Centre of Finland. http://www.vtt.fi/inf/pdf/science/2013/S48.pdf
Maijala, Panu. / A measurement-based statistical model to evaluate uncertainty in long-range noise assessments : Dissertation. Espoo : VTT Technical Research Centre of Finland, 2013. 196 p.
@phdthesis{24219e7550f44df184f0a5f89570846d,
title = "A measurement-based statistical model to evaluate uncertainty in long-range noise assessments: Dissertation",
abstract = "Carefully validated long-range sound propagation measurements with extensive meteorological instrumentation were continued for 612 days without interruption, around the clock, resulting in a database with millions of files, terabytes of sound and environmental data, and hundreds of pages of documentation. More than 100 environmental variables were analysed by statistical means, and many statistically highly significant dependencies linked to excess attenuation were found. At a distance of 3 km from the source, excess attenuation was spread over a dynamic range of 80 dB, with differences of 10 dB between individual quarters of the year; also, negative excess attenuation at frequencies below 400 Hz existed. The low frequencies were affected mainly by the stability characteristics of the atmosphere and the lapse rate. Humidity; lapse rate; sensible heat flux; and longitudinal, transverse, and vertical turbulence intensities explain excess attenuation at higher frequencies to a statistically highly significant extent. Through application of a wide range of regression analyses, a set of criteria for frequency-dependent uncertainty in sound propagation was created. These criteria were incorporated into a software module, which, together with a state-of-the-art physical sound propagation calculation module, makes it possible to perform environmental noise assessments with known uncertainty. This approach can be applied to the shortterm measurements too and it was shown that some of the most complex meteorological variables, among them atmospheric turbulence, can be taken into account. Comparison with two standardised noise modelling methods showed that the statistical model covers well a range of uncertainty notmatched with the standardisedmethods and themeasured excess attenuation fit within the limits of predicted uncertainty.",
keywords = "acoustic wave propagation, aeroacoustics, atmospheric acoustics, environmental acoustics, environmental noise, noise assessments, uncertainty, statistical model",
author = "Panu Maijala",
isbn = "978-951-38-8109-2 ",
series = "VTT Science",
school = "Tampere University of Technology (TUT)",
Maijala, P 2013, 'A measurement-based statistical model to evaluate uncertainty in long-range noise assessments: Dissertation', Doctor Degree, Tampere University of Technology (TUT), Espoo. <http://www.vtt.fi/inf/pdf/science/2013/S48.pdf>
A measurement-based statistical model to evaluate uncertainty in long-range noise assessments : Dissertation. / Maijala, Panu.
Espoo : VTT Technical Research Centre of Finland, 2013. 196 p.
T1 - A measurement-based statistical model to evaluate uncertainty in long-range noise assessments
T2 - Dissertation
AU - Maijala, Panu
N2 - Carefully validated long-range sound propagation measurements with extensive meteorological instrumentation were continued for 612 days without interruption, around the clock, resulting in a database with millions of files, terabytes of sound and environmental data, and hundreds of pages of documentation. More than 100 environmental variables were analysed by statistical means, and many statistically highly significant dependencies linked to excess attenuation were found. At a distance of 3 km from the source, excess attenuation was spread over a dynamic range of 80 dB, with differences of 10 dB between individual quarters of the year; also, negative excess attenuation at frequencies below 400 Hz existed. The low frequencies were affected mainly by the stability characteristics of the atmosphere and the lapse rate. Humidity; lapse rate; sensible heat flux; and longitudinal, transverse, and vertical turbulence intensities explain excess attenuation at higher frequencies to a statistically highly significant extent. Through application of a wide range of regression analyses, a set of criteria for frequency-dependent uncertainty in sound propagation was created. These criteria were incorporated into a software module, which, together with a state-of-the-art physical sound propagation calculation module, makes it possible to perform environmental noise assessments with known uncertainty. This approach can be applied to the shortterm measurements too and it was shown that some of the most complex meteorological variables, among them atmospheric turbulence, can be taken into account. Comparison with two standardised noise modelling methods showed that the statistical model covers well a range of uncertainty notmatched with the standardisedmethods and themeasured excess attenuation fit within the limits of predicted uncertainty.
AB - Carefully validated long-range sound propagation measurements with extensive meteorological instrumentation were continued for 612 days without interruption, around the clock, resulting in a database with millions of files, terabytes of sound and environmental data, and hundreds of pages of documentation. More than 100 environmental variables were analysed by statistical means, and many statistically highly significant dependencies linked to excess attenuation were found. At a distance of 3 km from the source, excess attenuation was spread over a dynamic range of 80 dB, with differences of 10 dB between individual quarters of the year; also, negative excess attenuation at frequencies below 400 Hz existed. The low frequencies were affected mainly by the stability characteristics of the atmosphere and the lapse rate. Humidity; lapse rate; sensible heat flux; and longitudinal, transverse, and vertical turbulence intensities explain excess attenuation at higher frequencies to a statistically highly significant extent. Through application of a wide range of regression analyses, a set of criteria for frequency-dependent uncertainty in sound propagation was created. These criteria were incorporated into a software module, which, together with a state-of-the-art physical sound propagation calculation module, makes it possible to perform environmental noise assessments with known uncertainty. This approach can be applied to the shortterm measurements too and it was shown that some of the most complex meteorological variables, among them atmospheric turbulence, can be taken into account. Comparison with two standardised noise modelling methods showed that the statistical model covers well a range of uncertainty notmatched with the standardisedmethods and themeasured excess attenuation fit within the limits of predicted uncertainty.
KW - acoustic wave propagation
KW - aeroacoustics
KW - atmospheric acoustics
KW - environmental acoustics
KW - environmental noise
KW - noise assessments
KW - uncertainty
KW - statistical model
M3 - Dissertation
T3 - VTT Science
CY - Espoo
Maijala P. A measurement-based statistical model to evaluate uncertainty in long-range noise assessments: Dissertation. Espoo: VTT Technical Research Centre of Finland, 2013. 196 p.