NTU Testbed for Digital Construction
This project is aimed to develop a multi-purpose reconfigurable testbed (aka, NTU Testbed) to support the design, analysis, deployment, and validation of interdisciplinary solutions for digital construction and automation in Singapore. Particularly, built upon the facilities at PE Lab, we will collect spaces/slopes for both building construction demo and underground construction demo. In addition, we will setup a framework for data collection and visualization, built upon a network of wireless/wired sensor/cameras surrounding the lab for both situational awareness and project demonstration. It is designed as a focal point among research, industry and education fields, attracting top researchers, students, and engineers in Singapore for both current and future (next-generation) digital construction development.
AI SINGAPORE
The objective of this project is to develop and implement novel artificial intelligence (AI) techniques on smart sensing systems to detect, diagnose and predict potential faults in high-risk underground transportation infrastructure. We focus on railroad tunnels, as they are critical components of the underground infrastructure, and their main faults include cracks, seepages, concrete spalling, and tunnel joint failures. The proposed AI-based smart sensing system will address the needs of tunnel owners and engineering services companies by providing actionable and timely condition assessment of tunnels under both sudden events (e.g., ground tremors or nearby construction) and long-term deterioration (e.g., ground deformation). Achieving accurate and reliable diagnosis/prognosis of various source fault information from a massive amount of low-quality multivariate data is a primary challenge. Our key innovation lies in context-aware data imputation to reconstruct the missing/noisy data and explainable deep learning models to diagnose/predict tunnel faults.
System of Systems Modeling and Testbed for the Resilient Design of Deep Space Habitats
As NASA, ESA, and private sectors (e.g., SpaceX) make plans for space settlement on the Moon or Mars, developing smart habitats is of vital importance to enable sustainable long-term presence in deep space. The futuristic infrastructure must be resilient, functioning as intended under continuous extreme conditions (e.g., meteoroid impacts, vibrations, etc.). The mission of the Resilient ExtraTerrestrial Habitats institute (RETHi) is to develop next-generation technologies, that will anticipate and adapt to extreme conditions, actively detect and diagnose habitat faults, and rapidly recover from disruptions using autonomous robots. As one of key personnel, my main responsibilities are to simulate the integrated deep space habitat as a system of systems, capturing the emergent dynamic behavior and cascading events subjected to multi-hazard environment. In parallel, I am coordinating the development of a multi-physics cyber-physical testbed to enable unprecedented testing of resilient strategies at scale.
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Fu, Y., Montoya, H., Maghareh, A., Dyke, S. “Modular Coupled Virtual Testbed: A Real-time Platform for Cyber-physical Testing of Extraterrestrial Habitat Systems”, (in preparation).
Fault Detection and Diagnostics for Meteorite Impacts on Deep Space Habitats
Due to their unpredictable nature, many impact events (e.g., overheight vehicles striking on bridges) go unnoticed or get reported many hours later. However, they can induce structural failures or hidden damage that accelerates the structure's long-term degradation. Therefore, prompt impact detection and localization strategies are essential for early warning of impact events and rapid maintenance of structures. In particular, due to the harsh environment, structural impact localization must be robust to a limited number of sensors and multi-source errors (e.g., measurement errors). In this study, an effective impact localization strategy is proposed to identify impact locations using a limited number of vibration measurements, especially in harsh environments (e.g. in deep space). Convolutional neural networks are trained for each sensor node and are fused using Bayesian theory to improve the accuracy of impact localization.
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Fu, Y., Wang, Z. Maghareh, A., Jahanshahi, M., Dyke, S. “An Effective Structural Impact Detection and Localization Technique Using Deep Learning and Information Fusion”, (in preparation).
Smart IoT System for Rapid Damage Assessment of Aging Infrastructure under Multiple Hazards
Many of the civil infrastructure damage scenarios involve unpredictable natural disasters (e.g., earthquakes) or anthropogenic hazards (e.g., blasts). An efficient monitoring system is thus critical for both early warning of hazards and rapid condition assessment for engineers to make informed decisions for maintenance, thus maximizing their contribution to environmental and social needs. We developed a smart wireless IoT system. When deployed on in-service structures, hazards of interest will be automatically assessed and reported in real-time. The key component is the demand-based wireless smart sensors, which can capture high-fidelity transient structural responses, with minimal power budget and zero latency. In addition, it addresses the challenges of remote data retrieval by integrating 4G-LTE functionality into the sensor network and completes the data pipeline with cloud-based data management. The versatile systems were installed on over ten railroad bridges of the Canadian National Railway for over one month.
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Fu, Y., Hoang, T., Mechitov, K., Spencer Jr, B.F., Kim, J. (2018). “Sudden Event Monitoring of Civil Infrastructure using Demand-based Wireless Smart Sensors”, Sensors, 18(12), 4480.
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Fu, Y., Hoang, T., Mechitov, K., Spencer Jr, B.F. “xShake: Intelligent Wireless System for Cost-effective Real-time Seismic Monitoring”, Smart Structures and Systems, (accepted).
Instability Monitoring of Space Grid Structures under Blizzards
Space grid structures have been widely used as important large-scale public buildings, which are now increasingly applied for railway stations in China, such as Hangzhou East Railway Station. However, in history, a series of space grid structures collapsed under blizzards, initiating from the sudden buckling of individual members and developing into progressive collapse in seconds. Therefore, the conditions of space grid structures should be timely monitored and reliably assessed under blizzards, such that instability can be detected and emergency response can be made before collapse occurs. In this study, two early warning strategies are proposed for instability monitoring of space grid structures based on local/global vibration information, such that an alert will be sent to the maintenance crew before buckling occurs. The result shows that the strategies are able to predict and identify dangerous members and hence send early warning of instability in space grid structures before buckling occurs.
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Fu, Y., Gomez, F., Spencer Jr, B.F. (2018). “Instability Monitoring of Space Grid Structures under Blizzards”, Proc. 7th World Conference on Structural Control and Monitoring, Qingdao, China.
Research on the Performance of CFRP-strengthened Tubular Gap K-joints
An efficient technique of Carbon Fiber Reinforced Polymer (CFRP) application was proposed to promote the joint capacity of general tubular K-joints fabricated from Circular Hollow Section (CHS) members. Using this technique, in order to understand the static performance of CFRP-strengthened CHS joints, a systematic investigation was carried out by means of both experiments and the finite element method. Three CHS gap K-joints strengthened with CFRP sheets were tested under static axial force in braces, whilst one additional joint was served as a reference joint without CFRP. A series of finite element models were developed and validated for the joints with and without CFRP reinforcement. A parametric study was conducted to evaluate the effect of variables (length, layers, and mechanical properties of CFRP) on load-bearing capacity. Finally, formulas were proposed for calculating the ultimate load-bearing capacity of CHS gap K-joints with CFRP composites, and their calculation results matched well with the experimental and numerical results respectively
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Fu, Y., Tong, L., He, L., Zhao, X.L. (2016). “Experimental and Numerical Investigation on Behavior of CFRP-Strengthened Circular Hollow Section Gap K-Joints.” Thin-Walled Structures, 102, 80-97.
Study on the Innovative Application of Bamboo-Cable Composite Structures
In the 2010 Shanghai Expo, people were deeply impressed by the Sun Valley. However, due to large energy and labor consumption, the Valley is not consistent with the Expo slogan of sustainability. What if the steel is replaced with bamboo? Possessing excellent mechanical properties, bamboo has been nowadays recognized as one of the most sustainable potential structural materials. However, the irregularity in cross-sections and the inefficient joint configuration could be bottlenecks in developing future large-span bamboo structures. A novel spatial composite structure is proposed with the methodology of bamboo-cable structural systems which consist of bamboo, steel elements, and adhesive construction materials. Meanwhile, key technical difficulties involved with this application are carefully investigated and analyzed, which we target to address in the near future. Additionally, several tentative structural styles are presented in order to explore the application of this bamboo-composite structure.
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Fu, Y., Hu, L., Hu, Y., He, X., (2014). “Study on the Innovative Application of Bamboo-Cable Composite Structures.” XXV International Union of Architects World Congress, Durban, South Africa.