Electrical characteristics and conductivity mechanism of self-sensing asphalt concrete

The existing conductive asphalt concrete is not suitable for self-sensing of asphalt concrete structural damage. In order to realize the perception of electrical signals on the structural damage of asphalt pavement, A self-sensing asphalt concrete is designed, and the relationship between condition change and resistance change of asphalt pavement is established by adding multi-conductive phase materials to ordinary asphalt concrete. The influence of different amounts of conductive additives on the volumetric parameters, electrical properties, and mechanical properties of asphalt concrete has been studied, the influence of volume parameter changes on the electrical properties and variability of conductive asphalt concrete was clarified, and the correlation analysis between volume of air voids (VV) and resistivity has been established. Nano-CT scanning, the distribution of conductive phase materials in asphalt concrete was characterized, and its long-short synergistic conduction mechanism was revealed, which provided a theoretical basis for the application of self-sensing asphalt concrete. Results indicate that the failure spacing of conductive particles of single-doped graphite is 2 µm, and the volume content of graphite should not be less than 0.68% to have weak conductivity. Considering the volume parameters, electrical properties and mechanical properties of asphalt concrete, the composite modification method of graphite and steel fiber is proposed, the recommended graphite content of conductive phase material is 0.68%, and the content of steel fiber is 0.9–1.1%. The internal structure failure of asphalt concrete is mainly manifested in the change of volume of air voids (VV), the electrical properties of conductive asphalt concrete show a negative correlation with the VV of concrete, and the change of resistivity of asphalt concrete can be used to predict the damage state inside the pavement structure

A Practical Monitoring System for the Structural Safety of Mega-Trusses Using Wireless Vibrating Wire Strain Gauges

Sensor technologies have been actively employed in structural health monitoring (SHM) to evaluate structural safety. To provide stable and real-time monitoring, a practical wireless sensor network system (WSNS) based on vibrating wire strain gauges (VWSGs) is proposed and applied to a building under construction. In this WSNS, the data measured from each VWSG are transmitted to the sensor node via a signal line and then transmitted to the master node through a short-range wireless communication module (operating on the Industrial, Scientific, and Medical (ISM) band). The master node also employs a long-range wireless communication module (Code Division Multiple Access—CDMA) to transmit the received data from the sensor node to a server located in a remote area, which enables a manager to examine the measured data in real time without any time or location restrictions. In this study, a total of 48 VWSGs, 14 sensor nodes, and seven master nodes were implemented to measure long-term strain variations of mega-trusses in an irregular large-scale building under construction. Based on strain data collected over a 16-month period, a quantitative evaluation of the construction process was performed to determine the aspects that exhibit the greatest influence on member behavior and to conduct a comparison with numerical simulation results. The effect of temperature stress on the structural elements was also analyzed. From these observations, the feasibility of a long-term WSNS based on VWSGs to evaluate the structural safety of an irregular building under construction was confirmed

Advanced microwave embedded sensors for infrastructure health monitoring

Microwave sensor systems have been widely investigated for many applications due to their ability to provide non-destructive, noncontact, one-sided and wireless testing. Among these applications infrastructure health monitoring of bridges, building, and dams using microwave sensors, which are mounted on or embedded in composite structures of infrastructure has been attracting an increasing interest. One of the current needs of infrastructure health monitoring includes the detection and monitoring of disbonding and gaps in concrete-based structures, which are also required for simultaneous characterization of concrete. A recently proposed microwave sensor technique exploiting a relatively simple waveguide sensor embedded in a concrete-metal structure such as a concrete-filled steel tube exhibited great potential. However, it suffers from a few drawbacks that need to be solved. This thesis aims to develop and investigate advanced microwave embedded sensors to solve main problems in the current microwave sensory technique including characterization of concrete in concrete-based structures at different stage of its life, size of the interface under inspection, detection and monitoring of a small gap between concrete and dielectric material surfaces and sensitivity to gaps. To achieve this aim the following five research contributions have been made: The first contribution is the methodology for the determination of the complex dielectric permittivity of concrete using both measurement data and simulation results at different stages (fresh, early-aged and dry) of its life. Firstly, it is developed and tested for a single flanged open-ended waveguide sensor with a hardened concrete specimen, and then the methodology is modified for the developed sensors embedded in concrete-based composite structures with fresh, early-age and dry concrete. Modern computational tool CST Microwave Studio and a performance network analyser are used for simulation and measurement, respectively, throughout this research work. The second contribution is a dual waveguide sensor, which is proposed, designed and applied for the detection and monitoring of a small gap in concrete-metal composite structures. It consists of two waveguide sections and a metal plate and uses the transmission of electromagnetic waves along gap when it occurs between the metal plate and concrete surfaces. It provides more measurement data than the single waveguide sensor for characterising concrete-metal structures such as transmission properties of guided waves along the gap and reflection properties of the metal–concrete interface at two different places at the same stage of concrete. As a result, the proposed sensor increases the size of the interface under inspection and sensitivity to the gap using the magnitude of reflection coefficient and magnitude of transmission coefficient together and/or independently. The third contribution is the design and application of a dual waveguide sensor with rectangular dielectric insertions that is proposed and tested for the characterisation of concrete–metal structures at different stages of the concrete life including its fresh stage. The dielectric insertions are designed and implanted in the waveguide sections in such a way that they create the resonant response of the sensor and prevent water and concrete entering the sections. The resonant properties of the sensor allow long-term monitoring of the concrete hydration, including the detection of the transition from fresh to hardened concrete on its first day. The proposed sensor along with the modified algorithm provides the determination of the complex dielectric permittivity of fresh concrete. The fourth contribution is a dual waveguide sensor with tapered dielectric insertions. Each tapered dielectric insertion is designed with a tapered part and rectangular part to reduce wave reflection from the insertions over an entire frequency band. The proposed sensor has improved performance at the resonant responses of a quarter-wavelength resonator formed by an open end at the tapered part and shorted end at the rectangular part of each insertion. The last contribution is the development of dual waveguide sensors with attached dielectric layer and their application for the detection and monitoring of gap between dielectric materials and concrete in metal-dielectric layer-concrete composites as well as the determination of complex dielectric permittivity of concrete at different stages of its life. One of the most attractive designs is the sensor with empty waveguide sections due to its simplicity and robustness, and capability of the layer for preventing penetration of the obstacles and water, and for optimization of the sensor. On the other hand, the sensors with dielectric insertions and the layer demonstrate a significantly higher magnitude of transmission coefficient. The proposed DWSs can be applied to characterise fresh concrete in a dielectric mould or on-line, and to investigate the shrinkage of different categories of concrete

Development of BIM-based Automated Methods for Building Management and Structural Safety Assessment

Despite the progress made in modern project management methods, there is still a lack of appropriate automated tools that support digital integration over the project life cycle. There is considerable demand for fully embracing the latest technological opportunities such as Building Information Modeling (BIM), Internet of Things (IoT), Structural Health Monitoring (SHM), and prefabrication to support that digital transformation in construction. The aim of this study is to develop a set of automated management solutions and related tools to address the issues highlighted above. The thesis is presented as a collection of manuscripts of five peer-reviewed journal articles authored based on the present research. The first development is of a BIM-based method for 3D model visualization of buildings and their non-structural elements and their corresponding seismic risk levels and locations. It supports automated assessment of seismic risk of these elements. The second focuses on the development of a novel data-driven SHM technique to monitor the structural behavior of individual building modules to detect possible damages during their transportation. It consists of two main components, a sensor-based data acquisition (DAQ) and storage module, and an automated data analysis module that uses unsupervised machine learning techniques to identify damages during transportation using onboard captured acceleration data. It can be used to ascertain the safety of delivered modules before their assembly on site. The third accounts for the development of an automated BIM-based framework to facilitate effective data management and representation of sensory components of the SHM tool used in buildings. It allows for visualization of damages in building components based on the interpretation of the captured sensor data. It is designed to facilitate effective visualization capabilities for a rapid and efficient structural condition assessment. The fourth development is designed to dynamically update the thermal comfort data in monitored buildings by integrating their BIM models with captured sensor data. The default range utilized in this development is based on the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard. It is expected to provide a robust and practical tool for data collection, analysis, and visualization to facilitate intelligent monitoring of the thermal condition in buildings and help decision-makers take needed timely data-driven decisions. The fifth and last development is designed to alert IoT companies of malfunctioning of deployed sensors utilizing a BIM platform and a cloud database to process and transfer related actionable information