Icing Events Research Articles

Risk Assessment and Value of Action Analysis for Icing Conditions of Wind Turbines Close to Highways

The paper presents research results from the Marie Skłodowska-Curie Innovative Training Network INFRASTAR in the field of reliability approaches for decision-making for wind turbines and bridges. This paper addresses the application of Bayesian decision analysis for installation of heating systems in wind turbine blades in cases where an ice detection system is already installed in order to allow wind turbines to be placed close to highways. Generally, application of ice detection and heating systems for wind turbines is very relevant in cases where the wind turbines are planned to be placed close to urban areas and highways, where risks need to be considered due to icing events, which may lead to consequences including human fatality, functional disruptions, and/or economic losses. The risk of people being killed in a car passing on highways near a wind turbine due to blades parts or ice pieces being thrown away in cases of over-icing is considered in this paper. The probability of being killed per kilometer and per year is considered for three cases: blade parts thrown away as a result of a partial or total failure of a blade, ice thrown away in two cases, i.e., of stopped wind turbines and of wind turbines in operation. Risks due to blade parts being thrown away cannot be avoided, since low strengths of material, maintenance or manufacturing errors, mechanical or electrical failures may result in failure of a blade or blade part. The blade (parts) thrown away from wind turbines in operation imply possible consequences/fatalities for people near the wind turbines, including in areas close to highways. Similar consequences are relevant for ice being thrown away from wind turbine blades during icing situations. In this paper, we examine the question as to whether it is valuable to put a heating system on the blades in addition to ice detection systems. This is especially interesting in countries with limited space for placing wind turbines; in addition, it is considered if higher power production can be obtained due to less downtime if a heating system is installed.

An Assessment of LEWICE Roughness and Convection Enhancement Models

<div class="section abstract"><div class="htmlview paragraph">During aircraft design and certification, in-flight ice accretions are simulated using ice prediction codes. LEWICE, the ice accretion prediction code developed by NASA, employs a time-stepping procedure coupled with a thermodynamic model to calculate the location, size and shape of an ice accretion. LEWICE has been extensively validated for a wide range of icing conditions. However, continuing improvements to LEWICE predictive capabilities require better understandings of 1) the fundamental physics of turbulent flow generated by ice accretion roughness during an icing event and 2) the mechanisms responsible for convective enhancement of real ice accretion roughness. Recent experiments in the Icing Research Tunnel (IRT) at NASA Glenn Research Center have enabled significant insights into the nature of ice accretion roughness spatial and temporal variations. Other recent investigations have employed scans from the IRT to generate scaled test surfaces to investigate convection enhancement and skin friction interactions of flow over the surfaces with real ice roughness. For this investigation, the measurements of ice roughness characteristics, skin friction, and convection heat transfer enhancement are compared directly to predictions calculated using the LEWICE models. Issues associated with the LEWICE model for predicting laminar-to-turbulent transition are also addressed. The comparisons show that while the LEWICE models significantly overestimate equivalent sand-grain roughness heights and the local skin friction, the resulting LEWICE predictions of convection heat transfer generally agree within 25% of the experimental values for surfaces constructed with low thermal conductivity materials. At each step of the LEWICE model, methods to improve the predictions are provided.</div></div>

A Continuing Investigation of Diurnal and Location Trends in an Ice Crystal Icing Engine Event Database

<div class="section abstract"><div class="htmlview paragraph">Due to ongoing efforts by the aviation industry, much has been learned over the last several years regarding jet engine power loss and compressor damage events caused by the ingestion of high concentrations of ice crystal particles into the core flow path. Boeing has created and maintained a database of such ice crystal icing (ICI) events to aid in analysis and further study of this phenomenon. This article provides a general update on statistics derived from the Boeing event database, and provides more details on specific event clusters of interest. A series of three flight campaigns have, over the past five years, collected in-situ data in deep convective clouds that will be used for the assessment of the new FAA CFR Part 33 ice crystal environmental envelope Appendix D, and the equivalent EASA CS-25 Appendix P. The most recent Boeing engine event study in 2015 focused on oceanic cloud systems that caused events in Southeast Asia, a region expected to have similar cloud properties as the first flight campaign in Darwin, Australia. The current study will examine ICI engine events over South America and Africa, which are caused by large deep convective continental clouds of the type that were not the main focus of the three Appendix D/P flight campaigns. Continental event clouds are compared to the previously studied oceanic event clouds, in order to ascertain whether any systematic differences exist that should be considered when assessing the representativeness of the flight campaign datasets. The results may also be useful to those developing nowcasting algorithms identifying high ice concentration regions using satellite measurements.</div></div>

Evaluation of ESSENCE Syndromic Definitions for ED Visits Related to Falls in Icy Weather

ObjectiveThis project evaluated and compared two ESSENCE syndromic surveillance definitions for emergency department (ED) visits related to injuries associated with falls in icy weather using 2016-2017 data from two hospitals in Douglas County, Nebraska. The project determined the validity of the syndromic surveillance definition as applied to chief complaint and triage notes and compared the chief complaint data alone to chief complaint plus triage notes definitions to find the most reliable definition for ED visits resulting from fall-related injuries.IntroductionIcy weather events increase the risk for injury from falls on untreated or inadequately treated surfaces. These events often result in ED visits, which represents a significant public health and economic impact1.The goal of this project was to start the process toward an evaluation of the public health impact and the economic impact of falls associated to icy weather in Douglas County, NE for the ultimate purpose of designing and implementing injury prevention related public health protection measures. Additionally, the validated definition will be used by NE DHHS Occupational Health Surveillance Program to identify work related ice-related fall injuries that were covered by workers compensation. To achieve the goal, the first step was to identify a valid and reliable syndromic surveillance. Specifically, this project looked at the applicability of the ESSENCE syndromic surveillance definitions related to injuries associated with falls. Two syndromic surveillance definitions were compared, one that includes triage note and chief complaint search terms, and another that only includes chief complaint. The hypothesis was that the ESSENCE syndromic surveillance definition that includes triage note and chief complaint search terms, rather than the syndromic surveillance definition that only includes chief complaint, would be more effective at identifying ED visits resulting from fall-related injuries.MethodsThis project included 751 EDs visits from two hospitals located in Douglas County Nebraska, during ice events on December 16-18, 2016, January 10-12, 2017, and January 15-18, 2017.Two ESSENCE syndromic surveillance definitions, “Chief Complaint or Triage Note” and “Chief Complaint Only,” were used to identify fall-related ED visits from two participating EDs in Douglas County, NE. In the chief complaint and the triage note fields, the keywords selected were: fall, fell, or slip. In that the ESSENCE time series analysis indicated the increase in the number of falls were associated with ice events from baseline, an assumption was made that the increase was a result of the weather. Then, the Syndromic Surveillance Event Detection of Nebraska database was used to find the patient and visit identification numbers. These two identification numbers were used to identify the EHRs needed for a gold standard review. Chart data was used to evaluate the reliability and validity of the two syndromic surveillance definitions for the detection of falls on the study dates. This analysis was used to find the sensitivity, specificity and predictive value.ResultsThe sensitivity, specificity and positive predictive value for the “Chief Complaint Only” definition yielded 71.7%, 100%, and 100% respectively. The “Chief Complaint or Triage Note” definition results were 90.9%, 98.8%, and 95.5% for these analyses. Negative predictive value for both definitions was 97.5%.ConclusionsThe sensitivity indicates both definitions are unlikely to give false positives, and the positive predictive value indicates both definitions successfully identify most of the true positives found in the visits. However, the “Chief Complaint Only” definition resulted in a minimally higher specificity and positive predictive value. Therefore, the results indicate that although both definitions have similar specificity and positive predictive value, the “Chief Complaint or Triage Note” definition is more likely than the “Chief Complaint Only” definition to correctly identify ED visits related to falls in icy weather.

Prediction of ice accumulation on bridge cables during freezing rain: A theoretical modeling and experimental study

Accreted ice falling from bridge cables is a hazard to vehicles crossing the bridge. The falling ice can startle drivers, cause accidents, and break windshields. Therefore, predicting ice accretion on bridge cables is vital in determining the severity of the event and making decisions concerning bridge or lane closure. In this study, a simple ice accumulation model for freezing rain on bridge cables was developed that accounts for the cable inclination and determines the accretion orientation and shape. Indoor experiments in an icing wind tunnel were conducted on stainless steel cylindrical specimen with various inclinations. It was found that the inclination of the cables affected the ice thickness and prevalence of icicles. The model was evaluated by two icing events on the Veterans' Glass City Skyway Bridge in Toledo, Ohio. The modeled ice results were consistent with the observations. The model can be a valuable tool for ice accumulation prediction on bridge cables using forecasted weather data.

Aircraft Icing Study Using Integrated Observations and Model Data

Abstract Light (LGT) to moderate (MOD) aircraft icing (AI) is frequently reported at Cold Lake, Alberta, but forecasting AI has been a big challenge. The purpose of this study is to investigate and understand the weather conditions associated with AI based on observations in order to improve the icing forecast. To achieve this goal, Environment and Climate Change Canada in cooperation with the Department of National Defence deployed a number of ground-based instruments that include a microwave radiometer, a ceilometer, disdrometers, and conventional present weather sensors at the Cold Lake airport (CYOD). A number of pilot reports (PIREPs) of icing at Cold Lake during the 2016/17 winter period and associated observation data are examined. Most of the AI events were LGT (76%) followed by MOD (20%) and occurred during landing and takeoff at relatively warm temperatures. Two AI intensity algorithms have been tested based on an ice accumulation rate (IAR) assuming a cylindrical shape moving with airspeed υa of 60 and 89.4 m s−1, and the Canadian numerical weather prediction model forecasts. It was found that the algorithms IAR2 with υa = 89.4 m s−1 and IAR1 with υa = 60 m s−1 underestimated (overestimated) the LGT (MOD) icing events, respectively. The algorithm IAR2 with υa = 60 m s−1 appeared to be more suitable for forecasting LGT icing. Over all, the hit rate score was 0.33 for the 1200 UTC model run and 0.6 for 0000 UTC run for both algorithms, but based on the individual icing intensity scores, the IAR2 did better than IAR1 for forecasting LGT icing events.

Field analysis, modeling and characterization of wind turbine hot air ice protection systems

In the rapidly expanding market of wind energy, sites in cold climates are becoming popular because of their high wind potential. However, several challenges are associated with energy production in those sites. Such challenges not only include low temperature and high winds, but also multiple icing events. To cope with the negative impacts of icing, wind turbine manufacturers nowadays include ice protection systems (IPS) to their products. It has been observed that the performances of those systems can be greatly influenced by the ambient conditions. In many occasions, under harsh conditions, turbines IPS may not able to prevent ice formation on the blades nor to remove ice that is already formed. Multiple numerical analysis were made on the IPS performance but none of them relies on actual field data. In this paper, the relationship between the turbine stoppage time, wind speed and ambient temperature was studied on a wind farm of over 80 turbines in eastern Canada. The test site is subject to harsh weather and long recovery time and can therefore provide interesting data on icing events. A simplified 1-D heat transfer model of the blades during recovery time has been developed and then compared to the field data. The model was used to generate IPS performance envelopes to delimit, on a temperature vs. wind speed chart, the conditions where the IPS are expected to operate successfully. This analysis showed the importance of having an IPS adapted to the conditions encountered in a given site. To help wind turbine manufacturers design their IPS, a set of distributions of the most relevant meteorological parameters is presented. This set of data has been retrieved using a custom made meteorological conditions monitoring station (MCMS) installed on one of the wind turbines' nacelle. Wind turbine designers, developers and operators can greatly benefit from the data presented in this paper.

Unprecedented Vessel-Icing Climatology Based on Spray-Icing Modelling and Reanalysis Data: A Risk-Based Decision-Making Input for Arctic Offshore Industries

Marine icing is considered a major concern for vessels operating in the Arctic Ocean. Interaction between vessels and waves is the major source of sea spray that, under certain conditions, can lead to ice accretion on the vessels and thus create hazardous situations. Various models have been developed for the estimation of ice accretion rate using meteorological and oceanographic parameters. Various data sets are also available containing observations of spray icing events for different Arctic offshore regions. However, there is limited climatological information that can be used for providing decision-makers with the necessary information on optimal options and solutions in advance for assessing, managing, and mitigating the risks imposed by spray icing. In this study, a Marine-Icing model for the Norwegian Coast Guard (MINCOG) is adapted to study and analyze ice accretion on vessels operating in sea areas between Northern Norway and Spitsbergen, their temporal and spatial variations, as well as their statistical distributions over the region. This study uses NOrwegian ReAnalysis 10 km data (NORA10) of atmosphere and ocean parameters as input to the icing model from 1980 to 2012. The developed spray icing maps representing spatial and temporal variation of icing severity and spray-ice accretion rate, as well as the probability of the occurrence of icing events at different junctures and periods, can be used for risk-based decision-making tasks involved in industrial activities including shipping and offshore logistics operations in these sea areas.

The 2017–18 design and construction of ice composite structures in Harbin

This paper will focus on the design and construction of two large thin shell structures with ice composites in the winter of 2017–18: the Flamenco Ice Tower and THRICE. Both structures were unique with regard to the application of ice composites. In this paper there will be a special focus on the structural behavior of the fiber-reinforced ice shell and membrane moulding. The ice composite had limited structural capacity and the material was pushed to its limits. Ice can be reinforced by adding (cellulose) fibers such as wood and paper. These fibers make the ice up to three times stronger and increase the ductility, thus creating a reliable building material. This sustainable, fully recyclable building material might be a solution for temporary constructions in cold areas, ice events, the Olympic Winter Games or possibly even Mars missions. HIT in cooperation with IASS Workgroup 21 invited several universities to design and construct architectural ice structures. In this paper the two most interesting structures that have been realized will be described. The technique used might also be interesting for architectural shell structures in other materials such as concrete and polymer composites. The Flamenco Ice Tower was the world record for the largest thin shell structure in ice and achieved the WA design award for most innovative architectural experiment in China.

Weather situation during observed ship-icing events off the coast of Northern Norway and the Svalbard archipelago

Ship icing may lead the ship and crew in great jeopardy. Usually, predictions of such ice build-up are based on the modelling of the heat fluxes capable of freezing sea water originated from wave-ship interactions. This study, on the other hand, follows a different and more general approach by investigating the relationship between the weather situation and icing both using observed parameters from 17 ships operating in Arctic-Norwegian waters from 1980 to 2006, and by applying upper-air parameters derived from NOrwegian ReAnalysis 10 km data (NORA10). In the atmosphere, the memory aloft is larger than that near the surface providing capability of medium-range icing predictions based on such upper-air parameters. It is demonstrated that cold-air outbreak from the ice-covered ocean areas is the dominant weather situation during icing. However, around 10% of the icing events arise in cold-air outbreak mountain-wave situations with downslope windstorms near the coastlines of Northern Norway and Svalbard. It is shown that snow showers and frontal snow, mostly in combination with sea spray, increase the risk of icing. Finally, a simple model applying the temperature and temperature anomaly at 850 hPa is found to be more accurate than methods based on temperature and wind close to the surface. The model is further improved by including wind at 850 hPa.

An Analysis of the Reliability of a New Dataset of Transmission Line Icing Thickness in Southern China

AbstractBased on ERA-Interim data, gauge observations, transmission line icing observational data, and hindcasted predictors from a numerical forecast system of transmission line icing, a new transmission line icing thickness (TLIT) dataset was constructed to solve the problem of limited historical data. The reliability of the dataset was analyzed using case studies and climate data. The results showed that the descriptions of three icing events in southern China by the TLIT were consistent with the actual observational data, and the icing thickness differences were less than 2 mm. The spatial distribution of annual icing days and icing thickness calculated using meteorological observation station icing data (OIT) and the TLIT data had a similar pattern, with small differences in the numerical values. A rotated empirical orthogonal function (REOF) decomposition was conducted for 67 transmission line icing events. It was found that the spatial distributions of the first three characteristic vectors of the TLIT and OIT data were similar, and the correlation coefficients for the time coefficients of the first three characteristic vectors were 0.801, −0.443, and 0.576, respectively. Three key areas were identified based on the first three patterns of REOF, and the average icing thickness of 67 events in southern China and the three key areas was calculated. The correlation coefficients of icing thickness calculated by the TLIT and OIT data for these areas were 0.648, 0.384, 0.565, and 0.599, respectively. The results illustrate that the TLIT data can reflect the temporal and spatial variations of ice thickness in southern China.

Spectral, spatial, and temporal characteristics of underwater ambient noise in the Beaufort Sea in 1994 and 2016.

Climate induced changes in the Arctic Ocean have severely impacted underwater acoustic communication and navigation; understanding underwater noise characteristics is critical to improving the performance of these operations. Ambient noise from the Beaufort Sea recorded in experiments more than 20 years apart (SIMI94 and ICEX16) are compared to determine differences that may be attributed to the region's rapidly changing environment. Spectral comparison shows noise within 20-350 Hz is ∼30 dB louder in 1994 than 2016; however, this is likely due to higher array self noise during SIMI94. Beamforming results show ambient noise vertical directionality is focused near the horizontal during SIMI94 but more spread in elevation during ICEX16, with a robust noise notch at the horizontal. Numerical modeling demonstrates that this difference may be attributed to ambient noise during ICEX16 being dominated by surface noise sources at discrete ranges rather than the historical assumption of a continuous and uniform distribution of sources. Temporal statistics of transient ice events show more acoustic activity during SIMI94 than ICEX16 and appear to support the new proposed surface source distribution for ICEX16.

A Modeling Investigation of Northern Hemisphere Extratropical Cyclone Activity in Spring: The Linkage between Extreme Weather and Arctic Sea Ice Forcing

Arctic sea ice exhibits rapid reductions and large fluctuations during recent decades in conjunction with a warming climate. Arctic sea ice shows a prominent seasonal cycle with the maximum extent in spring and the minimum extent in fall. In this study a suite of modeling experiments, which were solely forced with observed time-varying sea-ice concentration for spring 1979 to 2008 was conducted using NCAR’s Community Atmosphere Model to identify sea ice impacts on extratropical storms and associated surface climate parameters when they at the peak of their seasonal variability. Storms are the linkage between the large-scale circulation changes, forced by Arctic sea ice and local extreme weather events through strong winds, high precipitation, and high/low air temperature. In this study, a storm identification and tracking algorithm indicates that reduced sea-ice cover enhances Arctic storm activity. As a consequence, surface climate parameters such as surface air temperature (SAT) and precipitation increases in spring over the Arctic. The changes in the Arctic have a direct and indirect effect on the extratropical storm activity over the mid-latitudes. In contrast to the Arctic, storm activity weakens over Eurasia in the years with less sea ice. Further analysis of the surface climate indicates a warmer and dryer Eurasia for years with reduced sea ice.

Measurement of Atmospheric Icing and Droplets

Icing conditions including atmospheric liquid water content (LWC) and size distribution of droplets were recorded close to the top of Mt. Areskutan, 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.

Icing events assessment of a wind park in high wind speed

Icing events assessment of a wind park in high wind speed

Machine learning-based icing prediction on wind turbines

In cold regions like Northern Europe or Northern America, formation of ice on wind turbines not only reduces the power output of the system, but also leads to wind turbine breakdowns and poses a risk to nearby vehicles and people. Economical solutions for anti-icing systems such as preventive heating are required. Purely meteorological icing predictions are not sufficient to accurately predict icing on wind turbines. Therefore, this paper proposes an icing prediction approach that uses historical weather data and data from a supervisory control and data acquisition (SCADA) system plus methods from supervised machine learning to predict the risk of icing. The first results of the prediction model show its capability to predict most of the icing events. The discussion shows that the model should consider more meteorological data that describe the icing risk such as humidity or liquid water content to achieve better prediction results. The final aim is a prediction system that will use real-time data to determine icing risks hours beforehand, allowing the operation of existing anti-icing systems more efficiently.

The Role of the Hungarian Defence Forces Skills in the Protection against Water Damages – The Extraordinary Flood on the Danube River 2013

The role of the Hungarian Defence Forces in the National water damage prevention is unquestionable due to the available human resources and technical preparedness. It can be stated that the Hungarian Defence Forces capabilities complement the capacity of the Hungarian Flood protection. The collaboration has always been professional and well-functioning, for example there were several flood defence and protection against ice events activities in the Hungarian Rivers that exceed the highest measured water level. In this article I present the main elements of the involvement of the Hungarian Defence Forces’ activities in the extraordinary Danube Flood in 2013.

Wind-Induced Fatigue and Asymmetric Damage in a Timber Bridge.

The transformation of a 30 m long timber pedestrian bridge into a wobbly (laterally swaying) bridge with a dramatically reduced first lateral modal frequency has been monitored by seven annual, multi-sensor surveys. This evidence, in combination with analysis of the wind record, observations of local damage and evidence of wind-induced excitations from other bridges, is used to present a multi-stage scenario of the extraordinary structural weakening of our study bridge in only a few years. Our analysis is constrained by observations of asymmetric damage (longitudinal splitting cracks around metallic connections along the south side of the deck, not explained by ordinary, essentially symmetric lateral oscillations) and over-threshold analysis of strong northerly wind events, including gusts. The proposed scenario is that an unexpected for the area icing event took advantage of construction vicissitudes and produced damage that reduced the lateral stiffness of the bridge, especially of the arch superstructure. In addition, strong winds sharing common direction with gusts produced a combination of semi-static lateral bending and of dynamic oscillations, leading to numerous cycles of asymmetric high amplitude lateral deflections producing tensile stress normal to grain, cracks localized in connections, and fatigue. The vertical stiffness of the bridge was only slightly affected.

Wind turbine blade ice accretion: A correlation with nacelle ice accretion

This paper focuses on the meteorological icing phase of typical icing events to determine the factors that affect the ice accretion rate on a wind turbine blade. The linear mass density of ice on the nacelle of a 2 MW horizontal-axis wind turbine is estimated with a camera and is compared to the linear mass density of ice on a blade evaluated by a commercial blade ice detector (e.g. a fos4X ice detector). An automated image analysis software measures the dimension of the ice on a cylindrical tube located on the nacelle and calculates the linear mass density of the ice. The fos4X ice detector estimates the total ice load on the blade by measuring variations in the vibration frequencies of the blade. The total load is then divided by the blade length to obtain the linear density. On-site results were compared to simulations for validation. The ISO 12494 method for theoretical ice accretion on a cylindrical tube was adapted to simulate ice accretion on a rotating wind turbine blade. The main results show that wind speed and turbine rotor RPM directly influence the blade ice accretion rate. A correlation is made between blade and nacelle icing, with on-site results matching the simulation. In summary, for an operating turbine, as wind speed decreases, the rate of ice accretion on the blade increases relative to the ice accretion rate on the nacelle.

Evaluating RADARSAT-2 for the Monitoring of Lake Ice Phenology Events in Mid-Latitudes

Lake ice is an important component in understanding the local climate as changes in temperature have an impact on the timing of key ice phenology events. In recent years, there has been a decline in the in-situ monitoring of lake ice events in Canada and microwave remote sensing imagery from synthetic aperture radar (SAR) is more widely used due to the high spatial resolution and response of backscatter to the freezing and melting of the ice surface. RADARSAT-2 imagery was used to develop a threshold-based method for determining lake ice events for mid-latitude lakes in Central Ontario from 2008 to 2017. Estimated lake ice phenology events are validated with ground-based observations and are compared against the Moderate Resolution Imaging Spectroradiometer (MODIS band 2). The threshold-based method was found to accurately identify 12 out of 17 freeze events and 13 out of 17 melt events from 2015–2017 when compared to ground-based observations. Mean absolute errors for freeze events ranged from 2.5 to 10.0 days when compared to MODIS imagery while the mean absolute error for water clear of ice (WCI) ranged from 1.5 to 7.1 days. The method is important for the study of mid-latitude lake ice due to its unique success in detecting multiple freeze and melting events throughout the ice season.