Stochastic state sequence model to predict construction site safety states through Real-Time Location Systems

This paper addresses the challenge to design an effective method for managers to efficiently process hazardous states via recorded historical data by developing a stochastic state sequence model to predict discrete safety states – represent the hazardous level of a project or individual person over a period of time through a <i>Real-Time Location System (RTLS)</i> on construction sites. This involves a mathematical model for state prediction that is suitable for the big-data environment of modern complex construction projects. Firstly, an algorithm is constructed for extracting incidents from pre-analysis of the walk-paths of site workers based on RTLS. The algorithm builds three categories of hazardous region distribution – certain static, uncertain static and uncertain dynamic – and employs a frequency and duration filter to remove noise and misreads. Key regions are identified as either ‘hazardous’, ‘risky’, ‘admonitory’ or ‘safe’ depending on the extent of the hazard zone from the object’s boundary, and state recognition is established by measuring incidents occurring per day and classifies personal and project states into ‘normal’, ‘incident’, ‘near-miss’ and ‘accident’. A <i>Discrete-Time Markov Chain (DTMC)</i> mathematical model, focusing on the interrelationship between states, is developed to predict states on construction sites. Finally, a case study is provided to demonstrate how the system can assist in monitoring discrete states and which indicates it is feasible for the construction industry

Evaluation of road performance and micro-mechanism analysis of bentonite plastic concrete subgrade

This study evaluated the performance of bentonite plasticized concrete with good deformation coordination as a road base material, to address the poor deformation coordination of rigid base layers in roads. Through tests such as slump, strength, permeability, and scanning electron microscopy (SEM) and x-ray diffraction (XRD), the study analyzed the variations in workability, mechanical properties, and durability of plastic concrete as a base material under different bentonite and cement contents, as well as the underlying micro-mechanisms. The results showed that plastic concrete exhibited good workability, which improved with increased bentonite and cement content. The 28-day mechanical properties of the plastic concrete met the design criteria for road base layers and had features of higher load-bearing capacity, good toughness, slow strength attenuation, and overall integrity. In durability, the increase of bentonite content enhanced the concrete’s permeability, but decreased abrasivenes and shrinkage. From economic, performance, and engineering perspectives, the optimal bentonite and cement contents for the plastic concrete base were in the ranges of 90 kg m ^−3 to 120 kg m ^−3 and 110 kg m ^−3 to 150 kg m ^−3 , respectively