Average spectral acceleration as an intensity measure for collapse risk assessment

284 indexed citations

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This paper, published in 2015, received 284 indexed citations. Written by Laura Eads, Eduardo Miranda and Dimitrios G. Lignos covering the research area of Civil and Structural Engineering. It is primarily cited by scholars working on Civil and Structural Engineering (282 citations), Building and Construction (42 citations) and Geophysics (26 citations). Published in Earthquake Engineering & Structural Dynamics.

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doi.org/10.1002/eqe.2575 →

Countries where authors are citing Average spectral acceleration as an intensity measure for collapse risk assessment

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This map shows the geographic impact of Average spectral acceleration as an intensity measure for collapse risk assessment. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Average spectral acceleration as an intensity measure for collapse risk assessment with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Average spectral acceleration as an intensity measure for collapse risk assessment more than expected).

Fields of papers citing Average spectral acceleration as an intensity measure for collapse risk assessment

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Average spectral acceleration as an intensity measure for collapse risk assessment. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Average spectral acceleration as an intensity measure for collapse risk assessment.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1002/eqe.2575.

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