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Measurements and Modeling of Frost Depth in Railway Tracks

Tutkimustuotosvertaisarvioitu

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Measurements and Modeling of Frost Depth in Railway Tracks. / Pylkkänen, Kari; Nurmikolu, Antti; Guthrie, W. Spencer; Argyle, Hillary M.

Proceedings of the International Conference on Cold Regions Engineering: 16th International Conference on Cold Regions Engineering 2015. American Society of Civil Engineers ASCE, 2015. s. 123-134.

Tutkimustuotosvertaisarvioitu

Harvard

Pylkkänen, K, Nurmikolu, A, Guthrie, WS & Argyle, HM 2015, Measurements and Modeling of Frost Depth in Railway Tracks. julkaisussa Proceedings of the International Conference on Cold Regions Engineering: 16th International Conference on Cold Regions Engineering 2015. American Society of Civil Engineers ASCE, Sivut 123-134, Iso-Britannia, 13/10/15. https://doi.org/10.1061/9780784479315.012

APA

Pylkkänen, K., Nurmikolu, A., Guthrie, W. S., & Argyle, H. M. (2015). Measurements and Modeling of Frost Depth in Railway Tracks. teoksessa Proceedings of the International Conference on Cold Regions Engineering: 16th International Conference on Cold Regions Engineering 2015 (Sivut 123-134). American Society of Civil Engineers ASCE. https://doi.org/10.1061/9780784479315.012

Vancouver

Pylkkänen K, Nurmikolu A, Guthrie WS, Argyle HM. Measurements and Modeling of Frost Depth in Railway Tracks. julkaisussa Proceedings of the International Conference on Cold Regions Engineering: 16th International Conference on Cold Regions Engineering 2015. American Society of Civil Engineers ASCE. 2015. s. 123-134 https://doi.org/10.1061/9780784479315.012

Author

Pylkkänen, Kari ; Nurmikolu, Antti ; Guthrie, W. Spencer ; Argyle, Hillary M. / Measurements and Modeling of Frost Depth in Railway Tracks. Proceedings of the International Conference on Cold Regions Engineering: 16th International Conference on Cold Regions Engineering 2015. American Society of Civil Engineers ASCE, 2015. Sivut 123-134

Bibtex - Lataa

@inproceedings{d1b5afe1505b489896399b59e438fb4c,
title = "Measurements and Modeling of Frost Depth in Railway Tracks",
abstract = "In Finland, increases in the maximum allowable operating speed on railways have led to stricter smoothness requirements for rails. Despite continuous rehabilitation of the track structures, decreased speed limits have been required due to seasonal frost action. To improve the understanding of frost action phenomena in railway structures, a real-time in-situ monitoring system was installed at 14 sites within the Finnish railway track network for the purpose of measuring temperatures in the track structures and vertical displacements of selected railway sleepers. Based on 5 years of data collected from 2009 to 2013, during which time the maximum frost depth was observed to range from 0.9 m to 2.4 m, multivariable regression models for predicting the maximum frost depth at the instrumented sites were developed. Several factors were shown to influence the maximum frost depth, including latitude, longitude, air-freezing index, rainfall, elevation, and ditch depth. With comparatively high R2 values of 0.73 and 0.87, the resulting regression models may provide satisfactory utility for predicting maximum frost depth at sites similar to those that were instrumented for this research. When considered with other information such as track structure thickness, predictions of maximum frost depth can be useful for development of site-specific reasons for observed frost problems in railways.",
keywords = "Air-freezing index, Frost depth, Railway track structures, Seasonal frost action, Train speed",
author = "Kari Pylkk{\"a}nen and Antti Nurmikolu and Guthrie, {W. Spencer} and Argyle, {Hillary M.}",
year = "2015",
doi = "10.1061/9780784479315.012",
language = "English",
pages = "123--134",
booktitle = "Proceedings of the International Conference on Cold Regions Engineering",
publisher = "American Society of Civil Engineers ASCE",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Measurements and Modeling of Frost Depth in Railway Tracks

AU - Pylkkänen, Kari

AU - Nurmikolu, Antti

AU - Guthrie, W. Spencer

AU - Argyle, Hillary M.

PY - 2015

Y1 - 2015

N2 - In Finland, increases in the maximum allowable operating speed on railways have led to stricter smoothness requirements for rails. Despite continuous rehabilitation of the track structures, decreased speed limits have been required due to seasonal frost action. To improve the understanding of frost action phenomena in railway structures, a real-time in-situ monitoring system was installed at 14 sites within the Finnish railway track network for the purpose of measuring temperatures in the track structures and vertical displacements of selected railway sleepers. Based on 5 years of data collected from 2009 to 2013, during which time the maximum frost depth was observed to range from 0.9 m to 2.4 m, multivariable regression models for predicting the maximum frost depth at the instrumented sites were developed. Several factors were shown to influence the maximum frost depth, including latitude, longitude, air-freezing index, rainfall, elevation, and ditch depth. With comparatively high R2 values of 0.73 and 0.87, the resulting regression models may provide satisfactory utility for predicting maximum frost depth at sites similar to those that were instrumented for this research. When considered with other information such as track structure thickness, predictions of maximum frost depth can be useful for development of site-specific reasons for observed frost problems in railways.

AB - In Finland, increases in the maximum allowable operating speed on railways have led to stricter smoothness requirements for rails. Despite continuous rehabilitation of the track structures, decreased speed limits have been required due to seasonal frost action. To improve the understanding of frost action phenomena in railway structures, a real-time in-situ monitoring system was installed at 14 sites within the Finnish railway track network for the purpose of measuring temperatures in the track structures and vertical displacements of selected railway sleepers. Based on 5 years of data collected from 2009 to 2013, during which time the maximum frost depth was observed to range from 0.9 m to 2.4 m, multivariable regression models for predicting the maximum frost depth at the instrumented sites were developed. Several factors were shown to influence the maximum frost depth, including latitude, longitude, air-freezing index, rainfall, elevation, and ditch depth. With comparatively high R2 values of 0.73 and 0.87, the resulting regression models may provide satisfactory utility for predicting maximum frost depth at sites similar to those that were instrumented for this research. When considered with other information such as track structure thickness, predictions of maximum frost depth can be useful for development of site-specific reasons for observed frost problems in railways.

KW - Air-freezing index

KW - Frost depth

KW - Railway track structures

KW - Seasonal frost action

KW - Train speed

U2 - 10.1061/9780784479315.012

DO - 10.1061/9780784479315.012

M3 - Conference contribution

SP - 123

EP - 134

BT - Proceedings of the International Conference on Cold Regions Engineering

PB - American Society of Civil Engineers ASCE

ER -