Abstract

Portland Cement (PC) is responsible for about 8% of global CO2 emissions and is mainly used as a binder in concrete, which is a basic material for all types of load-bearing structures. Due to its versatile usage (precast or ready-mix concrete) and availability almost all over the world, concrete is used in a wide range of applications. When looking at possible pathways to reduce the carbon footprint four measures emerge: 1. 2. 3. 4. Use of renewable energy for PC production (mainly clinker burning process) CO2 capture during PC production. Use of supplementary cementitious materials to reduce the amount of PC. Optimization of PC efficiency within the concrete to reduce the amount of PC needed. To optimize the efficiency of PC, particle packing methods can be used, see e.g. [1], [2]. A well-established geometrical particle packing model is the compressible packing model (CPM) [3], which was extended to the compressible interaction packing model (CIPM) to account for colloidal interactions [4]. Based on the CIPM a so-called cement-spacing-factor (CSF) is calculated [2], [4] by dividing the PC volume in concrete by the maximum packing density (PD). CSF is then used to optimize PC efficiency, i.e., strength of PC based materials. However, CSF calculated based on PD is only an auxiliary parameter (i.e., particle saturation on a volume base), which at best qualitatively describes PC spacing in a particle arrangement and does not take the spread of the PC spacing into account. In this paper, a DEM-based enriched particle packing algorithm is developed that accounts for particle type (i.e., inert particles or PC) and distribution of PC particle distance. The results are compared to strength tests on PC-based pastes and the correlation to the calculated distribution of PC particle distance is shown. Based on PD calculations and the enriched DEM particle packing algorithm an optimization of PC efficiency in concrete can be performed.