Seismic Hazard Visualization from Big Simulation Data: Construction of a Parallel Distributed Processing System for Ground Motion Simulation Data

Takahiro Maeda; Hiroyuki Fujiwara

doi:10.20965/jdr.2016.p0265

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JDR Vol.11 No.2 pp. 265-271

(2016)

doi: 10.20965/jdr.2016.p0265

Paper:

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Seismic Hazard Visualization from Big Simulation Data: Construction of a Parallel Distributed Processing System for Ground Motion Simulation Data

Takahiro Maeda and Hiroyuki Fujiwara

National Research Institute for Earth Science and Disaster Prevention (NIED)
3-1 Tennodai, Tsukuba, Ibaraki 305-0006, Japan

Received:

October 2, 2015

Accepted:

January 3, 2016

Online released:

March 18, 2016

Published:

March 1, 2016

Keywords:

seismic hazard, visualization, simulation, parallel distributed processing

Abstract

We have developed a data mining system of parallel distributed processing system which is applicable to the large-scale and high-resolution numerical simulation of ground motion by transforming into ground motion indices and their statistical values, and then visualize their values for the seismic hazard information. In this system, seismic waveforms at many locations calculated for many possible earthquake scenarios can be used as input data. The system utilizes Hadoop and it calculates the ground motion indices, such as PGV, and statistical values, such as maximum, minimum, average, and standard deviation of PGV, by parallel distributed processing with MapReduce. The computation results are being an output as GIS (Geographic Information System) data file for visualization. And this GIS data is made available via the Web Map Service (WMS). In this study, we perform two benchmark tests by applying three-component synthetic waveforms at about 80,000 locations for 10 possible scenarios of a great earthquake in Nankai Trough to our system. One is the test for PGV calculation processing. Another one is the test for PGV data mining processing. A maximum of 10 parallel processing are tested for both cases. We find that our system can hold the performance even when the total tasks is larger than 10. This system can enable us to effectively study and widely distribute to the communities for disaster mitigation since it is built with data mining and visualization for hazard information by handling a large number of data from a large-scale numerical simulation.

Cite this article as:

T. Maeda and H. Fujiwara, “Seismic Hazard Visualization from Big Simulation Data: Construction of a Parallel Distributed Processing System for Ground Motion Simulation Data,” J. Disaster Res., Vol.11 No.2, pp. 265-271, 2016.

Data files:

References

[1] K. Irikura and H. Miyake, “Prediction of strong ground motions for scenario earthquakes,” Journal of Geography, Vol.110, pp. 849-875, 2001 (in Japanese with English abstract).
[2] Earthquake Research Committee, “Strong Ground Motion Prediction Method (“Recipe”) for Earthquakes with Specified Source Faults,” 2009 (in Japanese), http://www.jishin.go.jp/main/ chousa/09textunderscore yosokuchizu/gtextunderscore furoku3.pdf [accessed March 4, 2016]
[3] T. Maeda, N. Morikawa, A. Iwaki, S. Aoi, and H. Fujiwara,“Finite-Difference Simulation of Long-Period Ground Motion for the Nankai Trough Megathrust Earthquakes,” JDR, Vol.8, No.5, pp. 912-925, 2013.
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[5] A. Thusoo, J. S. Sarma, N. Jain, Z. Shao, P. Chakka, S. Anthony, H. Liu, P. Wyckoff, and R. Murthy, “Hive – A Warehousing Solution Over a Map-Reduce Framework,” In Proc. of Very Large Data Bases, Vol.2 No.2, pp. 1626-1629, August 2009.
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[9] T. G. Addair, D. A. Dodge, W. R. Walter, and S. D. Ruppert, “Large-scale seismic signal analysis with Hadoop,” Comput. Geosci. Vol.66, pp. 145-154, doi: 10.1016/j.cageo.2014.01.014, 2014.
[10] T. Maeda, N. Morikawa, S. Aoi, and H. Fujiwara, “Long-period ground motion evaluation for the Nankai Trough megathrust earthquakes,” In Proc. of JpGU, SSS23-13, 2014.
[11] Earthquake Research Committee, “On the long-term evaluation of earthquakes in the Nankai Trough (2^nd edition),” 2013 (in Japanese), http://www.jishin.go.jp/main/chousa/13may textunderscore nankai/index.htm [accessed March 4, 2016]
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[14] P. Wessel and W. H. F. Smith, “New version of the Generic Mapping Tools released,” Eos Transactions, American Geophysical Union, Vol.76, p. 329, 1995.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] K. Irikura and H. Miyake, “Prediction of strong ground motions for scenario earthquakes,” Journal of Geography, Vol.110, pp. 849-875, 2001 (in Japanese with English abstract).

[2] [2] Earthquake Research Committee, “Strong Ground Motion Prediction Method (“Recipe”) for Earthquakes with Specified Source Faults,” 2009 (in Japanese), http://www.jishin.go.jp/main/ chousa/09textunderscore yosokuchizu/gtextunderscore furoku3.pdf [accessed March 4, 2016]

[3] [3] T. Maeda, N. Morikawa, A. Iwaki, S. Aoi, and H. Fujiwara,“Finite-Difference Simulation of Long-Period Ground Motion for the Nankai Trough Megathrust Earthquakes,” JDR, Vol.8, No.5, pp. 912-925, 2013.

[4] [4] A. Iwaki, N. Morikawa, T. Maeda, S. Aoi, and H. Fujiwara, “Finite-Difference Simulation of Long-Period Ground Motion for the Sagami Trough Megathrust Earthquakes,” JDR, Vol.8, No.5, pp. 926-940, 2013.

[5] [5] A. Thusoo, J. S. Sarma, N. Jain, Z. Shao, P. Chakka, S. Anthony, H. Liu, P. Wyckoff, and R. Murthy, “Hive – A Warehousing Solution Over a Map-Reduce Framework,” In Proc. of Very Large Data Bases, Vol.2 No.2, pp. 1626-1629, August 2009.

[6] [6] J. Dean and S. Ghemawat, “MapReduce: simplified data processing on large clusters,” In Proc. of the OSDI’04, 6^th Symposium on Operating Systems Design and Implementation, Sponsored by USENIX, in Cooperation with ACM SIGOPS, pp. 137–150, 2004.

[7] [7] K. Shvachko, H. Kuang, S. Radia, and R. Chansler, “The Hadoop distributed file system,” In Mass Storage Systems and Technologies (MSST), 2010 IEEE 26^th Symposium on, pages 1–10, May 2010.

[8] [8] V. K. Vavilapalli, A. C Murthy, C. Douglas, S. Agarwal, M. Konar, R. Evans, T. Graves, J. Lowe, H. Shah, S. Seth, B. Saha, C. Curino, O. O’Malley, S. Radia, B. Reed, and E. Baldeschwieler, “Apache Hadoop YARN: Yet Another Resource Negotiator,” In Proc. of the 4^th ACM Symposium on Cloud Computing (SoCC), 2013.

[9] [9] T. G. Addair, D. A. Dodge, W. R. Walter, and S. D. Ruppert, “Large-scale seismic signal analysis with Hadoop,” Comput. Geosci. Vol.66, pp. 145-154, doi: 10.1016/j.cageo.2014.01.014, 2014.

[10] [10] T. Maeda, N. Morikawa, S. Aoi, and H. Fujiwara, “Long-period ground motion evaluation for the Nankai Trough megathrust earthquakes,” In Proc. of JpGU, SSS23-13, 2014.

[11] [11] Earthquake Research Committee, “On the long-term evaluation of earthquakes in the Nankai Trough (2^nd edition),” 2013 (in Japanese), http://www.jishin.go.jp/main/chousa/13may textunderscore nankai/index.htm [accessed March 4, 2016]

[12] [12] S. Aoi, T. Hayakawa, and H. Fujiwara, “Ground motion simulator: GMS,” Butsuri Tansa. Vol.57, pp. 651–666, 2004 (in Japanese with English abstract).

[13] [13] Earthquake Research Committee, “Long-period grond motion hazard maps for Japan,” 2012 (in Japanese), http://www.jishin. go.jp/main/chousa/12textunderscore choshuki/index.htm [accessed March 4, 2016]

[14] [14] P. Wessel and W. H. F. Smith, “New version of the Generic Mapping Tools released,” Eos Transactions, American Geophysical Union, Vol.76, p. 329, 1995.