Theory of Information in Construction – Implementation in Critical Infrastructures exposed to Extreme events

Abstract

The Theory of Information in Construction based on the hypothesis that failures in critical infrastructures (C.I.) are the result of loss of control in the information system of the CI as a result of information overflow of the system. The theory is established on four phases: (I) Statistical analyses: Probability Density Function of incoming events (PDF), Cumulative Distribution Function (CDF), Power function expressing the magnitude of events, and Scatter analysis; (II) Information Constraint (IC) expressing the capacity if the system, (III) Control circuits (feed-back loops), and (IV) Artificial Intelligence, Machine learning, Artificial Neural Network. The hypothesis of the theory is that failures, deficiencies, accidents and cascading failures are the result of an overflow of information in the system beyond the system's Information Constraint (IC). A similar hypothesis also refers to the performance of critical infrastructures, exposed to extreme abnormal events, caused by extreme events such as climate change, terrorism and seismic events. The events put the critical infrastructures in an extreme situation causing high risk to the continuity of performance of the CI, affecting vital services to civil society. This paper proposes a novel method for multi-hazard risk assessment of overhead transmission lines (OTL) grid. The main objective is to estimate the annual risk using failure rates estimated from historical failure data and modify them by reanalysis data and a dynamic Bayesian scheme. For this purpose, a comprehensive database of power grid supply failures is gathered. ANN is implemented to predict the incoming events, assess the risk and propose preventive activities.