Annals of Civil Engineering and Management(ACEM)

Department of Chemical Engineering, Dalhousie University, Canada

Publications

• Review Article   
  AI-Guided Predictive Carbonation Mapping for Ultra-Low-Emission Cement Manufacturing Facilities
  Author(s): Chinenye Elizabeth Onumadu*
  
  Carbonation curing can transform cement manufacturing from a CO2 source to a CO2 sink, but its industrial adoption is limited by unpredictable outcomes arising from feedstock variability, fluctuating flue gas compositions, and inhomogeneous chamber conditions. Current control strategies rely on static lookup tables that fail to account for real- time process dynamics, leading to underperformance or batch rejection. Here we develop and validate an AI-guided predictive carbonation mapping system that forecasts four key performance indicators simultaneously: CO2 absorbed (wt%), carbonation depth (mm), 28-day compressive strength (MPa), and porosity reduction (%). Using a dataset of 10,800 production batches from a pilot carbonation chamber operating over 12 months (24 input features including raw meal XRF, chamber temperature, relative humidity, pCO2, and curing duration), we trained a h.. Read More»
  

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