Open AccessMultivariate Statistical Analysis (MVA) in Complimenting Building Condition Assessment as a Diagnosis Tool for Reinforced Concrete Structures Rated as Category 3, 4 and 5
Author(s) -
J. Pirah,
J. Lozitin,
N. Samshuddin,
Rodeano Roslee,
M.F. Zulkipli
Publication year - 2022
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1229/1/012003
Subject(s) - multivariate statistics , statistical analysis , multivariate analysis , guideline , medical diagnosis , engineering , descriptive statistics , reinforced concrete , computer science , forensic engineering , construction engineering , structural engineering , statistics , medicine , mathematics , machine learning , pathology
In most structural repair works or building condition assessment, structural appraisal has been done through visual inspection for tell-tale signs which highlight the possible defect. This method is extended to the standard guideline by Jabatan Kerja Raya (JKR) in their BCA format in determining the physical condition rating. Consulting engineers or structural specialists are to participate when it is determined that the structure requires material testing in order to come up with diagnoses and prognosis. The use of descriptive statistics in both reconnaissance or desktop studies as well as in standard specifications have limitation in determining the actual structural issues. This study demonstrates the advantages of using Multivariate Statistical Analysis (MVA) in summating the right diagnosis and prognosis for structural repair works.