Deterioration modeling
 | This page is currently being created It is a new Wikipedia article developing through collaboration and successive edits.To help avoid edit conflicts and other confusion, the creator asks that for a short time this page not be edited unnecessarily, or nominated for deletion during this early stage of development.
|
Deterioration modeling is the process of modeling and prediction of the physical health of structures or infrastructure. Deterioration models are instrumental to infrastructure asset management and are the basis for maintenance and rehabilitation decision-making.[1][2] The condition of all physical infrastructure degrade over time. A deterioration model can help decision-makers to understand how fast the condition drops or violates a certain threshold.
Types of deterioration models
Deterioration models are either deterministic or probabilistic. Deterministic models cannot entertain probabilities. Probabilistic models, however, can predict both the future condition and the probability of being in that certain condition.[3]
Deterministic models
Deterministic models are simple and ineligible, but cannot incorporate probabilities. Deterioration curves developed based on age are an example of deterministic deterioration models.
Probabilistic models
Examples of probabilistic deterioration models are the models developed based on reliability theory, Markov chain and machine learning.[4][3]
References
- ^ Piryonesi, S. M.; El-Diraby, T. E. (2020) [Published online: December 21, 2019]. "Data Analytics in Asset Management: Cost-Effective Prediction of the Pavement Condition Index". Journal of Infrastructure Systems. 26 (1). doi:10.1061/(ASCE)IS.1943-555X.0000512.
{{cite journal}}: CS1 maint: url-status (link) - ^ "The IAM: Asset Management - an Anatomy".
{{cite web}}: CS1 maint: url-status (link) - ^ a b Piryonesi, S. M.; El-Diraby, T. (2018). "Using Data Analytics for Cost-Effective Prediction of Road Conditions: Case of The Pavement Condition Index:[summary report]". United States. Federal Highway Administration. Office of Research, Development, and Technology. FHWA-HRT-18-065 – via National Transportation Library Repository & Open Science Access Portal.
{{cite web}}: CS1 maint: url-status (link) - ^ Ford, K., Arman, M., Labi, S., Sinha, K.C., Thompson, P.D., Shirole, A.M., and Li, Z. 2012. NCHRP Report 713 : Estimating life expectancies of highway assets. In Transportation Research Board, National Academy of Sciences, Washington, DC. Transportation Research Board, Washington DC.