Perspectives for flood risk assessment and management for mega-city metro system

In addition to materials, labor, equipment, and method, construction cost depends on many other factors such as the project locality, type, construction duration, scheduling, and the extent...

Novel Machine-Learning Model for Estimating Construction Costs Considering Economic Variables and Indexes

Coupled seepage-damage effect in fractured rock masses: model development and a case study

Structural health monitoring (SHM) and damage assessment of civil engineering infrastructure are complex tasks. Structural health and strength of structures are influenced by various factors, such as the material production stage, transportation, placement, workmanship, formwork removal, and concrete curing. Technological advancements and the widespread availability of Wi-Fi networks has resulted in SHM shifting from traditional wire-based methods to Internet of Things (IoT)-based real-time wireless sensors. Comprehensive structural health assessment can be performed through the efficient use of real-time test data on structures obtained from various types of IoT sensors, which monitor several health parameters of structures, available on cloud-based data storage systems. The sensor data may be subsequently used for various applications, such as forecasting masonry construction deterioration, predicting the early-stage compressive strength of concrete, forecasting the optimum time for the removal of formwork, vibration and curing quality control, crack detection in buildings, pothole detection on roads, determination of the construction quality, corrosion diagnosis, identification of various damage typologies and seismic vulnerability assessment. This review paper summarizes the applications of the wireless IoT technology in the monitoring of civil engineering infrastructure. In addition, several case studies on real structures and laboratory investigations for monitoring the structural health of civil engineering constructions are discussed. 

Structural health monitoring of civil engineering structures by using the internet of things: A review

An IFC-inspection process model for infrastructure projects: Enabling real-time quality monitoring and control

Comprehensive and effective risk analysis is significant for studying construction simulation of diversion tunnel. Existing tunnel risk simulation approaches mainly analyze ordinary risk factors, and cannot quantitatively study risk events considering their causes. Additionally, in other tunnel probabilistic risk analysis methods, although some studies have made full probabilistic estimates of tunnel schedule, risk factors are unable to be studied considering cyclic construction characteristics and occurrence probability of risk events cannot be determined quantitatively. To address the issues, a probabilistic risk analysis approach of diversion tunnel construction simulation is proposed. Based on hierarchical simulation model, risk factors can be analyzed at operation level of tunnel construction. Moreover, Bayesian network is embedded into simulation program to quantitatively calculate probability of risk events in each simulation cycle, considering geology, design, construction, and management conditions and their mutual dependence.

Probabilistic Risk Analysis of Diversion Tunnel Construction Simulation

Real-time monitoring for vibration quality of fresh concrete using convolutional neural networks and IoT technology

A complete scheme for solving the key scientific problems associated with high-standard, high-intensity continuous construction of high arch dams was presented. First, based on a coupling analysis of construction system decomposition and coordination for a high arc dam, a mathematical model for real-time control of construction quality and progress that considers complex constraints was developed. Second, a method of progress control was proposed based on a dynamic simulation. Third, a dynamic quality control mechanism was established based on construction information collected using a PDA. Fourth, a system for integrating collected information, progress simulation and quality control analyses under a network environment was developed. Finally, these methods were applied to a practical project to show that each aspect of a construction process can be managed effectively and that real-time monitoring and feedback control can be realized. Our methods provide new theoretical principles and technical measures for quality and progress control in the high arc dam construction process.

Theory on real-time control of construction quality and progress and its application to high arc dam

Seepage is a vital reason that may bring many adverse consequences such as subsidence, inclination and fracture to the channel, and is harmful to the safety and stability of the channel. Thus, a 3D visualization model is established for the engineering geological information of the research channel section by using NURBS-TIN-BRep hybrid data structure. Coupled with the VOF (volume of fluid) method, the N-S (Navier-Stokes) equations are applied to seepage simulation of the research channel section. Then the stability of the channel is studied coupled with the seepage simulation results, to comprehensively analyze the stress and displacement conditions of the channel under the impact of different factors such as seepage and underground goafs. The results of this study illustrate that the channel seepage has great influence on its stability, especially on the displacement field: it will lead to a significant sedimentation to the foundation. Therefore, during the practical construction, it is suggested that the certain part of the channel should be reinforced and effective seepage control measures should be taken.

Study on coupled 3D seepage and stress fields of the complex channel project

The productivity analysis of cable crane transportation in the construction field is of great significance to improve crane equipment management and reduce operation costs. However, the tra...

Bingyu Ren

Papers

Probabilistic Risk Analysis of Diversion Tunnel Construction Simulation

Real-time monitoring for vibration quality of fresh concrete using convolutional neural networks and IoT technology

Theory on real-time control of construction quality and progress and its application to high arc dam

Study on coupled 3D seepage and stress fields of the complex channel project

Vision-Based Productivity Analysis of Cable Crane Transportation Using Augmented Reality–Based Synthetic Image