A wireless system for crack monitoring in concrete structures

The formation of cracks in concrete is a normal phenomenon. However, effective control and prevention of the formation of cracks is the key for successful life of concrete structures. Specifically, cracks represent a path of least resistance for moisture and corrosive ionic agents from de-icing salts to reach embedded steel in concrete. Commercial wireless sensor networks utilizing crack gauge sensors can be applied for crack monitoring in the common concrete structure. The crack sensors circuits\u27 boards, which are used to stimulate the cracks, are currently unavailable for the SG-Link module platform. The SG-Link module is an ultra-low-power module for use in sensor networks, monitoring applications and rapid application prototyping. Therefore, a crack sensor circuit board for the SG-Link module platform has been developed. The development of a smart wireless sensor network for the crack monitoring system is divided into four parts: a crack gauge sensor, signal conditioning, the SG-Link module, and a base station unit. The signal conditioning module consists of a crack gauge sensor, a wheatstone bridge, an amplifier, and a filter. The SG-Link module consists of an analog to digital converter (ADC), a microcontroller unit (MCC), and a transmitter with an antenna. The base station unit includes an antenna and a receiver module connected to the base station or computer. In this study, cracks are monitored based on the change of the electrical resistance between the sensor\u27s two terminals that are taken from the simulation model of the crack sensor board consisting of a crack gauge sensor and signal conditioning. This thesis looked at the effectiveness of a wireless system for crack monitoring in concrete structures. Tests were conducted in a laboratory to monitor the cracks in the structures and explore the validity and reliability of the monitoring mechanism and data transmission

Identify and manage productivity risks in construction processes

In the construction industry, the project managers’ role is to complete the project on time, within budget, and meet the predetermined standard of quality. At site level, the project manager (PM) breakdowns the project into construction processes. Traditionally, PM selects the suitable method of procuring construction works based on his/her intuition and past experience. In fact, misjudgment of the strategy and technical uncertainty may lead to failure of the activity. Therefore, it is very important to anticipate risks and degree of uncertainty while deploying the suitable technique to carry out construction process. The purpose of this study is to develop a decision-making model based on fuzzy logic to evaluate the performance of construction processes. The model aims to predict the probability of cost of failure due the risk impact on construction processes performance. The model provides the project managers with control tools to implement, modify, or update construction techniques and methods effectively and efficiently. In addition, the model provides project managers with a planning tool that might help in identifying critical risks associated with the construction processes that might contribute to the failures of the process. The model has been tested statistically by comparing the actual probability of cost of failure to predicted probability. The model is considered to be practical and its accuracy and consistency has been approved