Research Papers: Polar and Arctic Engineering

A Statistical Analysis of First-Year Level Ice Uniaxial Compressive Strength in the Svalbard Area

[+] Author and Article Information
Lucie Strub-Klein

Arctic Technology Department,
The University Centre on Svalbard (UNIS),
P.O. Box 156,
Longyearbyen 9170, Norway;
Department of Civil and Transport Engineering,
The Norwegian University of
Technology (NTNU),
Trondheim 7491, Norway
e-mail: lucie.sk@gmail.com

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received February 20, 2012; final manuscript received August 13, 2016; published online October 18, 2016. Assoc. Editor: Arne Gürtner.

J. Offshore Mech. Arct. Eng 139(1), 011503 (Oct 18, 2016) (23 pages) Paper No: OMAE-12-1017; doi: 10.1115/1.4034526 History: Received February 20, 2012; Revised August 13, 2016

This paper proposes a methodology for a statistical analysis of uniaxial compressive strength and applies it to full-scale data collected in the Svalbard area from 2005 to 2011. A total of 894 samples were compressed over 7 years of field investigation. The ice was mainly from frozen fjords on Svalbard and also from the Barents Sea and the Arctic Ocean. The analysis consisted in determining the most appropriate distribution for level ice strength according to the sample orientation, the time of the year (which would then relate to the brine configuration in the ice), and the failure mode. Six groups (horizontal, vertical, early, late, brittle, and ductile) were defined, and the gamma, two-parameter Weibull, and lognormal distributions were compared for each group. The Weibull parameters (shape and scale) were estimated with the method of moments and the method of maximum likelihood. The two methods agreed well. A visual observation of quantiles–quantiles plots (QQ-plots) combined with a linear regression and a Kolmogorov–Smirnov (KS) test were conducted to determine the best fitting distribution. Neither the season nor the failure mode appeared to influence the determination of a statistical distribution, contrary to the sample orientation. However, it appeared that the lognormal distribution was a best fit for the failure mode and season groups, whereas the gamma and the Weibull were the best candidates for the vertical and horizontal samples, respectively.

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Fig. 1

Estimation of β with the MML

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Fig. 4

Box plots for the different groups

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Fig. 5

Typical QQ-plots, here for horizontal samples, gamma, and Weibull distributions

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Fig. 6

QQ-plots of the gamma and the lognormal distribution for the late samples

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Fig. 7

QQ-plots for the ductile samples

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Fig. 8

QQ-plots for the horizontal samples

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Fig. 11

QQ-plots for the late samples

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Fig. 12

QQ-plots for the brittle samples

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Fig. 13

QQ-plots for the ductile samples

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Fig. 9

QQ-plots for the vertical samples

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Fig. 10

QQ-plots for the early samples

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Fig. 3

(a) Transportable uniaxial compression rig, (b) vertically loaded samples, and (c) horizontally loaded samples

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Fig. 2

Sampling sites (indicated by dots) on Van Mijenfjorden and in the Barents Sea: AF—Adventfjorden; AO—Arctic Ocean, BS—Barents Sea; BN—Barrynesset; SB—Svea Bukta; KA—Kapp Amsterdam; A—Akseløya; and VKF—Van Keulenfjorden




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