Lego-inspired reconfigurable modular blocks for automated construction of engineering structures

This paper presents an intelligent photo interpretation approach to automatically monitor and characterize dense interconnected microcracks in strain-hardening cementitious composite (SHCC) featuring unique crack patterns in terms of crack number and crack width. The presented approach employs a stereo vision system that integrates binocular and monocular cameras for automatic detection, ranging, and quantification of cracks as well as characterization of crack patterns. The presented approach was implemented into evaluation of SHCC in flexural tests and direct tension tests . Dense microcracks were detected and ranged by the stereo vision system, segmented by an encoder-decoder approach, and quantified by an efficient computer vision approach. Evolution of the cracks was traced throughout the loading process until failure, and a statistical analysis revealed that the crack width was retained while the crack number monotonically increased. The interpretation time was shorter than 0.4 s for each photo, making the approach promising for monitoring of SHCC. The proposed system can be deployed for automated assessment of cementitious composites with complex crack patterns in material research and engineering structures. • Complex cracks in strain-hardening cementitious composites are intelligently characterized. • Ranging is incorporated to enable automatic photo interpretation without human intervention. • Real-time assessment of crack width and crack number is achieved. • The proposed approach showed high accuracy in crack detection and quantification. 

Monitoring and automatic characterization of cracks in strain-hardening cementitious composite (SHCC) through intelligent interpretation of photos

Lightweight ultra-high-performance concrete (UHPC) with expanded glass aggregate: Development, characterization, and life-cycle assessment

Abstract High-performance fiber-reinforced cementitious composites (HPFRCC) have shown benefits in improving infrastructure resilience but often compromises sustainability due to the higher upfront cost and carbon footprint compared with conventional concrete. This paper presents a framework to optimize HPFRCC for improving bridge resilience and sustainability. This research considers ultra-high-performance concrete and strain-hardening cementitious composite featuring high mechanical properties, ductility, and damage tolerance. This paper establishes links between resilience, sustainability, mechanical properties of HPFRCC, and HPFRCC mixtures. The investigated mechanical properties include the first crack stress, ultimate tensile strength, and ultimate tensile strain. With the established links, sustainability is maximized while resilience is retained by optimizing HPFRCC mixtures. The framework is implemented into a case study of a bridge that collapsed during construction. Results show that use of HPFRCC enhances resilience, and HPFRCC mixtures can be engineered to minimize the material cost and carbon footprint while retaining high resilience. 

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Optimizing high-performance fiber-reinforced cementitious composites for improving bridge resilience and sustainability

Orthogonal experimental and theoretical study on mechanical properties of fiber-reinforced recycled powder concrete

Upcycling of waste concrete in eco-friendly strain-hardening cementitious composites: Mixture design, structural performance, and life-cycle assessment

Xiuling Li

Papers

Upcycling of waste concrete in eco-friendly strain-hardening cementitious composites: Mixture design, structural performance, and life-cycle assessment