ANALYSIS OF HIGH PRESSURE ZONE ATTRIBUTES FROM TACTILE PRESSURE SENSOR FIELD DATA

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1 Proceedings of the ASME rd International Conference on Ocean, Offshore and Arctic Engineering OMAE2014 June 8-13, 2014, San Francisco, California, USA OMAE ANALYSIS OF HIGH PRESSURE ZONE ATTRIBUTES FROM TACTILE PRESSURE SENSOR FIELD DATA Martin Richard C-CORE Ice Engineering St. John s, NL, Canada Rocky S. Taylor 1, 2 1 Memorial University of Newfoundland, 2 C-CORE Centre for Arctic Resource Development St. John s, NL, Canada ABSTRACT Tactile sensor data collected during the Japan Ocean Industries Association (JOIA) medium-scale field indentation test program provide detailed information about spatial and temporal distributions of contact pressures during ice crushing. The localization of contact into high pressure zones (hpzs) through which the majority of loads are transmitted to the structure is an important feature of these data. For all but the slowest interaction rates, non-simultaneous failure is observed, with linear distributions of hpzs comprising a total contact area on the order of 10% of the nominal interaction area (structure width x ice thickness). To improve understanding of the nature of individual hpzs during compressive ice failure, a new approach to analyzing tactile sensor data has been developed. Analysis algorithms developed for automatic hpz detection and tracking are discussed. Issues associated with pressure threshold value definition and selection are considered. Probabilistic descriptions of high pressure zone attributes based on analysis of JOIA field measurements are presented. The development of a probabilistic ice load model based on these hpz data is detailed in a companion paper. INTRODUCTION In the design of offshore structures for ice environments one is interested, amongst other things, in modeling extreme ice actions. In the case of vertical-walled structures, pressures associated with ice crushing failure are a dominant consideration. The general observation of decreasing pressure with increasing interaction area has important implications for load estimation and a high degree of focus has been placed on understanding pressure-area relationships (see for example (Sanderson, 1988; Jordaan et al., 2005; Masterson et al., 2007; Palmer et al., 2009; Timco and Sudom, 2013). Traditional pressure-area relationships provide good general guidance, but do not explicitly account for statistical exposure effects. Such curves often correspond to a curve of best fit to the data representing the mean peak pressure plus three standard deviations. Structures experiencing very infrequent interactions would be expected to experience smaller extreme loads than those exposed to many annual interactions. Probabilistic methods of extreme ice pressure analysis, such as the event maximum method, also show very clear scale effects but provide an approach in which design exposure and exceedence probability are explicitly accounted for (Jordaan et al., 1993; Taylor et al., 2010). Such an approach allows the designer to more clearly link estimated design loads with target safety levels based on the operational profile of the vessel or structure. Such probabilistic methods are very well suited to the analysis of local panel pressure data, where ice loads are measured over structural panels of fixed areas. High resolution tactile pressure sensor data, such as that made available by the Japan Ocean Industries Association (JOIA) medium-scale field indentation program, provide opportunities to study and model pressures at the scale of the fundamental element of compressive ice failure: the high pressure zone. High pressure zones are regions of localized contact through which the ice transmits intense local pressures to the structure during an ice-structure interaction (Jordaan, 2001). Individual hpzs have high temporal and spatial variability and collectively all hpzs present during an interaction are responsible for the majority of loads transmitted to the structure. 1 Copyright 2014 by ASME

2 For structures interacting with level sea ice, linear patterns of hpzs or line-loads are typically observed across the width of the interaction area (Riska, 1991; Sodhi et al., 2001; Frederking, 2004; Taylor et al., 2008). The ice feature geometry plays an important role in the shape of the contact pressure distribution, as was recognized in the geometrical model of Spencer and Masterson (1993). For the case of level ice interactions, the shape of the spatial distribution of hpzs is influenced by the occurrence of spalling fractures which extend to the top and bottom surfaces of the ice sheet and tend to concentrate hpzs near the centre of thickness of the ice sheet. Observations from the JOIA tactile pressure sensor dataset suggest that the total contact area (combined area of all hpzs) during crushing events is on average only about 10% of the nominal interaction area (Frederking, 2004; Taylor et al., 2008). During ship-ice ramming events with multi-year ice pressures as high as 70 MPa have been measured (Glen and Blount, 1984). Similarly, very intense local pressures have been measured during medium-scale indentation tests on multi-year sea ice and pressures as high as 60 MPa (Masterson et al., 1993) and 80 MPa (Frederking et al., 1990) have been reported. From small-scale indentation tests on polycrystalline freshwater ice at -10 o C pressures greater than 100 MPa have been reported for areas of a few mm 2, while pressures on the order of 35MPa on areas of a few hundred mm 2 have been reported (see for example, Mackey et al., 2007; Wells et al., 2009; Taylor et al., 2013). Given the important role of high pressure zones in determining the loads transmitted to a structure during an icestructure interaction, understanding the nature of hpzs and associated mechanics is key to developing improved models of local and global ice pressures. To provide insights into the behavior of hpzs during the compressive failure of first-year sea ice, a detailed analysis of the tactile pressure data from the JOIA program has been undertaken and a new ice load model based on extracted hpz data has been developed. In the present paper, a description of the data analysis and a summary of results have been provided; the probabilistic hpz-based ice load model is described in a companion paper. OVERVIEW OF DATA The medium-scale field indentation program (MS-FIT) consisted of more than thirty tests carried out between 1996 and 2000 which were conducted in the harbor of Notoro Lagoon in Hokkaido, Japan (44 o 05 N, 144 o 10 E). During this program the indentation apparatus was mounted on the side of a dock in the harbor so as to allow it be moved to different test locations along the length of the wharf. Movement of the apparatus was accomplished using a 65-ton mobile crane. In some cases the tests were conducted using the naturally grown ice, while in other cases the natural ice cover was removed and a refrozen ice sheet was grown. Natural ice in the harbor consisted of brackish first-year ice, which sometimes had a layer of snow ice. This snow ice was not present on refrozen sheets (Takeuchi et al., 1997). Throughout the test program the average air temperature was about -3 o C and the average ice thickness was on the order of 30 cm; see Kaimo et al. (2000) for a detailed description of ice conditions and physical properties of the ice during the program. In the present work, tests from the 1998 series of experiments have been considered. In this set of tests the indenter structure consisted of a 150 cm wide by 40 cm deep instrumented beam. This indenter was instrumented with fifteen contiguous 10 cm wide segmented load panels. For many of these tests Tekscan tactile pressure sensors were mounted on the front of the load panels so as to provide detailed measurement of pressure distributions at the ice-indenter interface (Sodhi et al., 2001). The tactile sensors used in this program consisted of a 44x176 array of sensor elements (sensels) that had a resolution of mm x mm (element area of mm 2 ). The reader is referred to Takeuchi et al. (1997); Matsushita and Takawaki (1997); Kaimo et al. (2000); Matsushita et al. (2000); Takeuchi et al. (2000); Akagawa et al. (2000) for additional detail about the JOIA program. ANALYSIS TOOLS To aid in the analysis of the JOIA tactile sensor data, a set of numerical tools and a Graphical User Interface (GUI) were developed in Matlab to facilitate easier exploration, analysis, processing, filtering and analysis of the raw JOIA data. This work included an overall assessment of the dataset to examine general observations of ice failure behavior under different loading conditions. Screenshots of the GUI developed for analyzing these data are shown in Figure 1. Figure 1: Screenshot of the graphical user interface of the JOIA analysis tool developed to assist in the analysis of the tactile sensor dataset. From an initial analysis of the tactile sensor data, it was evident that there are regions of surrounding background pressure, such as the regions shown in blue in Figure 2, which can make it difficult to discriminate between contact areas associated with individual hpzs. 2 Copyright 2014 by ASME

3 To address this issue, several different techniques for identifying and delimiting hpzs were explored. The selected technique was based on a combination of a threshold-based contact area definition and an hpz centroid tracking algorithm. For each time-step contour lines corresponding to regions defined by areas having pressures above a specified threshold pressure were extracted from the tactile sensor data. To track the hpz evolution in time it was assumed that if the centroid of a given hpz area did not shift by a distance of more than half the area width during subsequent time steps, then these areas could be assumed to correspond to the same hpz. Shifts in the centroid that were greater than half the hpz width were taken as an indicator of the death of one hpz and the birth of a new hpz. Upon detection each hpz was assigned an ID number and it was tracked in time until it died (either due to pressure everywhere within the hpz dropping below the threshold pressure, or due to a major failure event that resulted in a centroid shifting greater than half the hpz width). Figure 3: Plot of total percentage of force carried by all hpzs as a function of pressure threshold. RESULTS Based on the approach outlined above an automated algorithm for identifying and tracking individual hpzs from the tactile sensor dataset was developed. This algorithm was subsequently implemented to extract a database of time series data for individual hpzs such as the ones shown in Figure 4. Figure 2: Spatial and temporal details of sample individual hpzs identified and tracked using the automated algorithms. It is important to note that in using a threshold-based approach to isolate hpzs, the total force gets divided into two components: (1) the load carried by all hpzs (areas above the pressure threshold) and (2) a small, but non-negligible, amount of total force associated with the background pressure regions that are below the specified threshold pressure levels. Since these low pressure regions will contribute some small percentage of force to the overall interaction, it is important to quantify this effect. As shown in Figure 3, the percent of total load carried by all hpzs decreases with increasing threshold pressure, since higher thresholds exclude more area from the analysis. In the present work a background pressure threshold of 1MPa has been used, which yields hpz areas which contain approximately 80% of the total load transmitted to the structure. This detail is very important to understand in the context of building ice load models based on this hpz data, since neglecting to account for the additional component of load due to the background pressure may result in an under-conservative load estimate. Damage Failure Spalling Failure Figure 4: Illustration of: (top) hpz area evolution over time; and (bottom) associated area, pressure and force versus time plots for the selected hpz over its lifetime. 3 Copyright 2014 by ASME

4 From the pressure, area and force data for these hpzs, such as that shown in Figure 4, it is evident that both damage and fracture types of failures can be distinctly identified. Damage induced crushing events are characterized by events wherein load drops occur due to pressure softening and extrusion (without appreciable area loss), while spalling events tend to be characterized by load drops associated with significant reductions in area (due to removal of discrete pieces of ice). These observations are consistent with earlier analyses of tactile sensor data for the JOIA program (Taylor et al., 2008) and small-scale laboratory tests (Wells et al., 2009; Taylor et al., 2013) and are important in linking observed trends in the data with the physical mechanisms responsible for their occurrence. From this database of empirical hpzs characteristics of individual hpzs were extracted including geometric attributes such as areas, widths, heights, aspect ratios, and hpz centroid positions (x, y), as well as pressure attributes including means, maximums and standard deviations of hpz pressure. To assess the spatial and temporal behavior of individual hpzs, the mean trajectory (path traced in space-time by the centroid of each hpz over its lifetime) has been plotted in Figure 5. This result shows that the size of individual, independent hpzs are significantly smaller (on the order of 5x10-4 m 2 ) and the spatial density of hpzs are higher when compared with values estimated from pressure panel data (e.g. Johnston et al., 1998; Spencer, 2013). indicates that for the ice conditions in the JOIA program, such panel areas are loaded by contact regions comprised of many small independently varying zones distributed throughout the measurement area rather than a single large hpz, as might be inferred if loads were measured by a single panel. This has important implications for the development of theoretical models, since it is important to understand if correlations arise from failure processes in the ice or if apparent correlations are a consequence of pressure averaging over the measurement area. It is noted that the above observations regarding hpz sizes and densities are consistent with the conditions required to achieve the short characteristic correlation lengths for panel pressures reported from earlier correlation analysis of the JOIA segmented panel pressure data; see Figure 6. Another important feature of data for tests carried out at rates above 0.1 cm/s (brittle domain) is that the distribution of maximum indentation depth associated with the failure of each hpz indicates that there may be a consistent, characteristic duration for a large portion of the high pressure zones. This observation is consistent with damage layer theory (e.g. Jordaan, 2001) and may correspond to hpzs that only survive one crushing cycle. Another subset of the hpz population has a significantly longer duration, the length of which tends to be more random in nature. This is an important aspect of hpz behavior and is the subject of ongoing research. Additional detail of hpz attributes based on this analysis will be described in a separate paper. Figure 5: Plot of mean indentation trajectories of individual hpzs showing both spatial distribution (represented by horizontal location) and indentation depth, which also indicates the duration of each hpz (represented by length of the line). DISCUSSION While these data provide additional detail in terms of the size of independent failure zones than could be inferred from pressure panel measurements alone, these observations do not necessarily conflict with prior knowledge of hpzs. High pressure zone information inferred from the analysis of panel data results in estimates of hpz sizes that reflect the total area covered by all hpzs acting on the measurement area. The present analysis Figure 6: Plot of correlation as a function of distance for segmented local panel pressure data from the JOIA program (modified after Taylor and Jordaan, 2011). It is important to highlight that the ice conditions for the dataset used in this work correspond to thin first-year sea ice. It is recognized that differences in ice conditions (e.g. thickness and ice type) between the conditions of interest for design and those corresponding to the present work are an important consideration. 4 Copyright 2014 by ASME

5 The scaling of hpz mechanics is essential for extending the present work and this is an area of ongoing research. To this end, high resolution pressure distribution data is needed for thicker ice specimens, as well as for multi-year and glacial ice, to improve understanding of ice failure processes for these conditions. CONCLUSIONS New techniques have been developed to aid in the analysis of tactile pressure sensor data to facilitate the identification, tracking and extraction of data for individual hpzs. These techniques have been incorporated into a Matlab algorithm and used to analyze data from the JOIA medium-scale field indentation test program. A database of individual hpzs has been compiled and studied to improve understanding of the nature of hpzs. For the dataset considered in this study it was determined that individual hpzs tend to be small in areal extent, have a high spatial density and to be concentrated near the centre of the ice sheet thickness. It was also noted that the hpz population tends to be comprised of one subset of hpzs that exhibit a consistent, characteristic indentation depth and another subset which exhibits longer, more random durations. Research is presently underway to further understand these observations and links with physical processes of fracture and damage. Additional field-scale testing to provide pressure distribution data at adequately fine resolution to fully resolve and track hpz behavior (as in the JOIA program) is recommended for thicker ice and different ice types. Through improved understanding of the nature of field-scale hpzs, their ensemble behavior, and associated scaling issues, researchers will be better equipped with information needed to guide the development of physicsbased methods for design ice load estimation. ACKNOWLEDGEMENTS The authors would like to acknowledge the Japan Ocean Industries Association (JOIA) for making these data available and also Dr. Robert Frederking of the National Research Council of Canada and Dr. Ian Jordaan of Memorial University for their help during the initial processing and analysis of these data. Financial support from the Research Development Corporation of Newfoundland and Labrador (RDC) is gratefully acknowledged. REFERENCES Akagawa, S., Nakazawa, N., Sakai, M., Ice failure mode predominantly producing peak-ice-load observed in continuous ice load records. Proceedings of the 10th International Offshore and Polar Engineering Conference p Dunwoody, A.B., (1991) Non-simultaneous ice failure. A report to Amoco Production,Tulsa, OK. 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6 Matsushita, H., Kamio, Z., Sakai, M., et al., Consideration of failure mode of a sea ice sheet. Proceeding of 10th International Offshore and Polar Engineering Conference. p Palmer, A.C., Dempsey, J.P, and D.M. Masterson. (2009). A Revised pressure-area curve and a fracture mechanics explanation. Cold Regions Science and Technology 56, pp Riska, K Observations of the Line-like Nature of Ship-Ice Contact. 11th International Conference on Port and Ocean Engineering under Arctic Conditions, Proceedings, Vol 2, St. John's, Canada, September 24 28, 1991, pp Sanderson, T.J.O., Ice mechanics: risks to offshore structures. p Graham & Trotman, London. Sodhi, D.S., Takeuchi, T., Kawamura, M., Nakazawa, N., Akagawa, S., Measurement of ice forces and interfacial pressures during medium-scale indentation tests in Japan. POAC '01. p Spencer, P.A. and D. M. Masterson,(1993) "A Geometrical Model for Pressure Aspect-Ratio Effects in Ice-Structure Interaction", Proceedings of the 12th International Conference on Offshore Mechanics and Arctic Engineering, OMAE '93, Glasgow, Scotland, June 1993, Vol. 4, pp Spencer, P.A., Morrison, T.B., (2012), High Pressure Zones, Statistics and Pressure-Area Effects. Proceedings of Icetech Paper No. ICETECH RF. Spencer P.A, (2013). Unifying local and global ice crushing pressures. Proceedings of the 22nd International Conference on Port and Ocean Engineering under Arctic Conditions, June 9-13, 2013, Espoo, Finland. Takeuchi, T., Masaki, T., Akagawa, S., et al., Medium-scale indentation tests (MSFIT) - ice failure characteristics in Ice/Structure interactions. Proceedings of 7th International Offshore and Polar Engineering Conference. Vol. 2. p Takeuchi, T., Akagawa, S., Kawamura, M., et al., Examination of factors affecting total ice load using medium field indentation test data. Proceedings of 10th International Offshore and Polar Engineering Conference. p Taylor, R.S., Frederking, R.F. and Jordaan, I.J The nature of high pressure zones in compressive ice failure. Proceedings of the 19th IAHR International Symposium on Ice, Vancouver, BC. Taylor, R.S., Jordaan, I.J., Li., C., Sudom, D., (2010). Local Design Pressures for Structures in Ice: Analysis of Full- Scale Data. AMSE Journal of Offshore Mechanics and Arctic Engineering, Vol. 132, Issue 3; also presented at the 28th Offshore Mechanics and Arctic Engineering Conference, Honolulu, Hawaii, May Taylor R., and Jordaan I., (2011), The effects of nonsimultaneous failure, pressure correlation and probabilistic averaging on global ice load estimates. Proceedings of the International Offshore and Polar Engineering Conference pp Taylor, R.S., Browne, T., Jordaan, I., Gürtner, A., (2013). Fracture and Damage during Dynamic Interactions between Ice and Compliant Structures at Laboratory Scale. Proceedings of Offshore Mechanics and Arctic Engineering Conference, Nantes, France, June Timco, G., and Sudom, D. (2013). Revisiting the Sanderson pressure area curve: Defining parameters that influence ice pressure. Cold Regions Science and Technology 95 (2013) Wells, J., Jordaan, I., Derradji-Aouat, A. and Taylor, R Small-scale laboratory experiments on the indentation failure of polycrystalline ice in compression: Main results and pressure distribution. Cold Regions Science and Technology, Vol. 65, No. 3, pp Zou, B., (1996). Ships in ice: the interaction process and principles of design. PhD Thesis, Memorial University of Newfoundland Copyright 2014 by ASME