A framework for state-based time-series analysis and prediction

Time-series analysis and prediction play an important role in state-based systems that involve dealing with varying situations in terms of states of the world evolving with time. Generally speaking, the world in the discourse persists in a given state until something occurs to it into another state. This paper introduces a framework for prediction and analysis based on time-series of states. It takes a time theory that addresses both points and intervals as primitive time elements as the temporal basis. A state of the world under consideration is defined as a set of time-varying propositions with Boolean truth-values that are dependent on time, including properties, facts, actions, events and processes, etc. A time-series of states is then formalized as a list of states that are temporally ordered one after another. The framework supports explicit expression of both absolute and relative temporal knowledge. A formal schema for expressing general time-series of states to be incomplete in various ways, while the concept of complete time-series of states is also formally defined. As applications of the formalism in time-series analysis and prediction, we present two illustrating examples.

More than a nuisance: personal injury under Rylands

Discusses, by reference to case law, whether damages for personal injury are recoverable under Rylands v Fletcher liability. Considers the issue by reference to a hypothetical scenario in which a claimant suffers personal injury as a result of a chemical leak from a factory for which the factory owner is not at fault. Considers claims based on diminution in amenity and for consequential loss.

Prediction of reinforcement corrosion in concrete and its effects on concrete cracking and strength reduction

Based on extensive research on reinforcing steel corrosion in concrete in the past decades, it is now possible to estimate the effect of the progression of reinforcement corrosion in concrete infrastructure on its structural performance. There are still areas of considerable uncertainty in the models and in the data available, however This paper uses a recently developed model for reinforcement corrosion in concrete to improve the estimation process and to indicate the practical implications. In particular stochastic models are used to estimate the time likely to elapse for each phase of the whole corrosion process: initiation, corrosion-induced concrete cracking, and structural strength reduction. It was found that, for practical flexural structures subject to chloride attacks, corrosion initiation may start quite early in their service life. It was also found that, once the structure is considered to be unserviceable due to corrosion-induced cracking, there is considerable remaining service life before the structure can be considered to have become unsafe. The procedure proposed in the paper has the potential to serve as a rational tool for practitioners, operators, and asset managers to make decisions about the optimal timing of repairs, strengthening, and/or rehabilitation of corrosion-affected concrete infrastructure. Timely intervention has the potential to prolong the service life of infrastructure.