This study examines the fresh and flushing water pump installations for high-rise residential buildings in Hong Kong in terms of system availability, mean time to failure, mean time between failures and restoration time. Together with some reliability data published elsewhere, it applies Bayesian analysis to improve our understanding of the downtime characteristics of water pump installations. For three consecutive years (2005)(2006)(2007), water pump failures in 46 typical high-rise residential buildings were recorded to determine the component failure rates. In order to study the failure patterns, Monte Carlo simulations were performed for the operations of 100 parallel pump sets over a period of 10 years. The mean time to failure, total downtime, failure counts and system availability estimated for the fresh water pump installations were 1.24 years, 8990 h, 709 and 90% while those estimated for the flushing seawater pump installations were 0.46 years, 4049 h, 2081 and 78%, respectively. The results are useful in the calculation of water supply availability for highrise residential buildings while keeping the balance between maintenance cost and system reliability. This study also demonstrates a method for reliability modelling of water supply for high-rise residential buildings. Practical applications: This study demonstrates a method for reliability modelling of building services systems. With the use of Bayesian analysis, example estimates of the mean time to failure, total downtime, failure counts and system availability were determined for the fresh and flushing water pump installations for high-rise residential buildings in Hong Kong.
Urban forest ecosystems are being developed to provide various environmental services (e.g., the preservation of urban trees) to urban inhabitants. However, some trees are deteriorated asymptomatically without exhibiting an early sign of tree displacement, which results in a higher vulnerability under dynamic wind loads, especially during typhoon seasons, in the subtropical and tropical regions. As such, it is important to understand the tilt and sway behaviors of trees to cope up with the probability of tree failure and to improve the efficacy of tree management. Tree behaviors under wind loads have been broadly reviewed in the past literature, yet thorough discussions on the measurement methods for tree displacement and its analysis of broadleaf specimens are lacking. To understand the behavioral pattern of both broadleaf and conifer species, this paper presents a detailed review of sway behavior analysis from the perspectives of the aerial parts of the individual tree, including tree stem, canopy, and trunk, alongside a highlighted focus on the root–plate movement amid the soil-root system. The analytical approaches associated with the time-space domain and the time-frequency domain are being introduced. In addition to the review of dynamic tree behaviors, an integrated tree monitoring framework based on geographic information systems (GIS) to detect and visualize the extent of tree displacement using smart sensing technology (SST) is introduced. The monitoring system aims to establish an early warning indicator system for monitoring the displacement angles of trees over the territory of Hong Kong’s urban landscape. This pilot study highlights the importance of the monitoring system at an operational scale to be applicable in the urban areas showcasing the practical use of the Internet of Things (IoT) with an in-depth understanding of the wind-load effect toward the urban trees in the tropical and subtropical cities.
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