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Measurement of atmospheric icing and droplets
RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.ORCID iD: 0000-0002-5324-002x
Mid Sweden University, Sweden.
2020 (English)In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 69, no 8, p. 5799-5809, article id 8960291Article in journal (Refereed) Published
Abstract [en]

Icing conditions including atmospheric liquid water content (LWC) and size distribution of droplets were recorded close to the top of Mt. Åreskutan, 1260-m above sea level, Sweden, a place known for frequent severe icing. The findings are comparatively analyzed. Combitech IceMonitor was used to measure the ice load, and HoloOptics T41 was used to measure the atmospheric icing rate. A method to translate the digital output from HoloOptics T41 to a value between 0 and 100 is described and used. Two instruments were used for measuring LWC and the median volume diameter (MVD). We created a model of icing intensity based on the k-nearest neighbor (KNN) using wind speed, LWC, and MVD as input. The result indicates that more learning data decrease the error. An heuristic model of erosion/ablation was added to simulate the ice load, and the result was compared with that of the standard Makkonen ice load model. The Makkonen model is suitable for estimating the ice load using a 1-h temporal resolution. With a 1-min temporal resolution, the erosion/ablation needs to be modeled and included. Our observations show that conditions can alternate between icing and erosion/ablation within 1 min during an icing event.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020. Vol. 69, no 8, p. 5799-5809, article id 8960291
Keywords [en]
Atmospheric measurements, ice, imaging, instrumentation and measurement, meteorology, weather forecasting, Drops, Erosion, Nearest neighbor search, Sea level, Wind, Atmospheric icing, Digital output, Heuristic model, Icing conditions, Icing intensity, K nearest neighbor (KNN), Liquid water content, Temporal resolution
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:ri:diva-45374DOI: 10.1109/TIM.2020.2966313Scopus ID: 2-s2.0-85087461587OAI: oai:DiVA.org:ri-45374DiVA, id: diva2:1455168
Note

Funding details: European Regional Development Fund, FEDER; Funding details: Energimyndigheten, 37268-1; Funding text 1: Manuscript received July 30, 2019; revised December 30, 2019; accepted December 31, 2019. Date of publication January 15, 2020; date of current version June 24, 2020. This work was supported in part by Swedish Energy Agency under Project 37268-1 and in part by the European Union Regional Development Fund through the SMART Project. The Associate Editor coordinating the review process was Huang-Chen Lee. (Corresponding author: Stefani Rydblom.) Stefani Rydblom is with the RISE Research Institute of Sweden, 852 30 Sundsvall, Sweden (e-mail: stefani.rydblom@ri.se).

Available from: 2020-07-22 Created: 2020-07-22 Last updated: 2021-12-22

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Rydblom, Stefani Alita Leona

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