Predicting extreme events : the role of big data in quantifying risk in structural development
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2014
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| Online Access: | http://hdl.handle.net/1721.1/90028 |
| _version_ | 1826197814825189376 |
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| author | Newth, Oliver Edward |
| author2 | Pierre Ghisbain and Jerome J. Connor. |
| author_facet | Pierre Ghisbain and Jerome J. Connor. Newth, Oliver Edward |
| author_sort | Newth, Oliver Edward |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014. |
| first_indexed | 2024-09-23T10:53:33Z |
| format | Thesis |
| id | mit-1721.1/90028 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:53:33Z |
| publishDate | 2014 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/900282019-04-11T05:43:16Z Predicting extreme events : the role of big data in quantifying risk in structural development Newth, Oliver Edward Pierre Ghisbain and Jerome J. Connor. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Civil and Environmental Engineering. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2014. Cataloged from PDF version of thesis. Includes bibliographical references (pages 71-73). Engineers are well-placed when calculating the required resistance for natural and non-natural hazards. However, there are two main problems with the current approach. First, while hazards are one of the primary causes of catastrophic damage and the design against risk contributes vastly to the cost in design and construction, it is only considered late in the development process. Second, current design approaches tend to provide guidelines that do not explain the rationale behind the presented values, leaving the engineer without any true understanding of the actual risk of a hazard occurring. Data is a key aspect in accurate prediction, though its sources are often sparsely distributed and engineers rarely have the background in statistics to process this into meaningful and useful results. This thesis explores the existing approaches to designing against hazards, focussing on natural hazards such as earthquakes, and the type of existing geographic information systems (GIS) that exist to assist in this process. A conceptual design for a hazard-related GIS is then proposed, looking at the key requirements for a system that could communicate key hazard-related data and how it could be designed and implemented. Sources for hazard-related data are then discussed. Finally, models and methodologies for interpreting hazard-related data are examined, with a schematic for how a hazard focussed system could be structured. These look at how risk can be predicted in a transparent way which ensures that the user of such a system is able to understand the hazard-related risks for a given location. by Oliver Edward Newth. M. Eng. 2014-09-19T21:35:19Z 2014-09-19T21:35:19Z 2014 2014 Thesis http://hdl.handle.net/1721.1/90028 890138627 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 73 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Civil and Environmental Engineering. Newth, Oliver Edward Predicting extreme events : the role of big data in quantifying risk in structural development |
| title | Predicting extreme events : the role of big data in quantifying risk in structural development |
| title_full | Predicting extreme events : the role of big data in quantifying risk in structural development |
| title_fullStr | Predicting extreme events : the role of big data in quantifying risk in structural development |
| title_full_unstemmed | Predicting extreme events : the role of big data in quantifying risk in structural development |
| title_short | Predicting extreme events : the role of big data in quantifying risk in structural development |
| title_sort | predicting extreme events the role of big data in quantifying risk in structural development |
| topic | Civil and Environmental Engineering. |
| url | http://hdl.handle.net/1721.1/90028 |
| work_keys_str_mv | AT newtholiveredward predictingextremeeventstheroleofbigdatainquantifyingriskinstructuraldevelopment |