Forthcoming and Online First Articles

International Journal of Risk Assessment and Management

International Journal of Risk Assessment and Management (IJRAM)

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

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International Journal of Risk Assessment and Management (2 papers in press)

Regular Issues

  • A bibliometric analysis of the climate risk literature: 2000-2021   Order a copy of this article
    by Richard Gregory 
    Abstract: This paper presents a bibliometric review of the last two decades' research in climate risk, providing a general picture of the research field regarding classification by paper, author, journal, and publisher. The main objectives of this study are to identify the most relevant research in this field and uncover the newest trends from the information in the Web of Science database. An analysis of the most influential journals, the most cited papers, and the most productive and influential authors are made. Climate risk as a new field of study has undergone tremendous growth in research and popularity but still offers open challenges.
    Keywords: climate risk; bibliometrics.

  • Risk-stratify power transformers based on health index condition utilising asset management   Order a copy of this article
    by Khamis Salim, David Baglee, Derek Dixon 
    Abstract: Recently, a cumulative records of power transformer are aging. The power transformer ageing argues necessity of a massive replacement budget. The money has become the main driver towards implementing the capital plan and reducing the asset management replacement cost. According to the statistical analysis in Python programming language, the age factor was the most correlated factor with Health Index (HI) value. This is counted as a reliable risk investigator that examine health condition of the large fleet of power transformer. HI utilized to define faulty transformers. Regression model developed in R programming language. Probability failure analysis is mapped to HI condition score and the expected degradation outcomes. The risk assessment is based on HI method applied to 1177 power transformers dataset for electrical utility. The results prove the practicality of this approach to identifying the risk condition of the transformer to ensure fast concrete maintenance decision are made.
    Keywords: R programming language; health index; apparent age; failure rate; power transformer; risk matrix; python programming language; asset management; risk index.
    DOI: 10.1504/IJRAM.2024.10067329
     

 

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