Ice Loads on a Lattice Tower Estimated by Weather Station Data

Eva Sundin Division of Water Resources Engineering, Luleå University of Technology, Lulea, Sweden

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Lasse Makkonen VTT Building Technology, Technical Research Centre of Finland, VTT, Finland

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Abstract

Atmospheric ice loads are a major design criterion of tall structures in cold regions. In this paper the possibility to derive the design ice loads using analysis of meteorological observations made routinely at a weather station is studied. Ice loads calculated by extrapolating weather station data and using simplistic ice loading and unloading models are compared with those measured on a 323-m-height lattice TV tower. The comparison is made cumulatively in 3-h intervals over seven winter periods. The results show reasonable agreement in the time of the icing events and in overall loads. In the cases where the cumulative ice loads differ, the discrepancies are mostly due to incorrectly predicted unloading events. This study points out the importance of on-site temperature data for successfully estimating cumulative ice loads over long cold periods.

Corresponding author address: Eva Sundin, Division of Water Resources Engineering, Luleå University of Technology, SE-971 87 Luleå, Sweden.

Abstract

Atmospheric ice loads are a major design criterion of tall structures in cold regions. In this paper the possibility to derive the design ice loads using analysis of meteorological observations made routinely at a weather station is studied. Ice loads calculated by extrapolating weather station data and using simplistic ice loading and unloading models are compared with those measured on a 323-m-height lattice TV tower. The comparison is made cumulatively in 3-h intervals over seven winter periods. The results show reasonable agreement in the time of the icing events and in overall loads. In the cases where the cumulative ice loads differ, the discrepancies are mostly due to incorrectly predicted unloading events. This study points out the importance of on-site temperature data for successfully estimating cumulative ice loads over long cold periods.

Corresponding author address: Eva Sundin, Division of Water Resources Engineering, Luleå University of Technology, SE-971 87 Luleå, Sweden.

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