## 1 Introduction  
The detailed description of the pore structure of cementitious materials has a significant practical interest. The analysis of the pore structure of concrete feeds the numerical modelling of macroscopic transport properties such as permeability, diffusivity, conductivity and electrical resistivity. All these estimations need microstructural data as input. The complexity of the pore system of cementitious materials complicates the characterisation of the pore structure. Thus, the challenging description of geometry is normally limited to the assessment of the so-called pore entry size distribution, pore volume and specific surface area. However, additional information can contribute to a better understanding of the connection between the pore structure and transport processes. Pore wall roughness, pore connectivity and coordination with neighbouring throats are some of the parameters that are usually required for modelling. A wide-spread technique to describe the pore structure of cementitious systems is mercury intrusion porosimetry (MIP) [1, 2, 3, 4]. Traditionally, data from MIP is interpreted by assuming a cylindrical-shaped pore network with variable sizes. This simplification allows the determination of the pore entry size distribution but limits the efficiency of the method for describing the pore structure and for providing sensible information for modelling. The conventional three-dimensional description of the pore structure can be expanded with an additional dimension that describes the self-similarity of the pore surface. Fractal geometry analysis is a statistical method that describes irregular geometrical shapes with non-integral dimensions [5]. The fractal dimension characterises the self-similarity by the box-counting method (Equation (1)). \[D=\lim_{\delta\to\infty}-\frac{\log N(\delta)}{\log\delta}\, \tag{1}\]  
where \(D\) is the fractal dimension, \(\delta\) is the magnification factor or scale, and \(N(\delta)\) is the number of self-similar parts under the fixed magnification factor. The pore texture or irregularity can be described by considering the surface fractal dimension. Fractal analysis can contribute to more accurate models for interpreting MIP results by considering all features of the pore system. When described by electrical resistivity measurements, cementitious materials with ground granulated blast-furnace slag (GGBFS) demonstrate an increase in the tortuosity of hardened cementitious systems [2; 6]. To a lesser extent, limestone powder (LP) can increase tortuosity if its particle size distribution adequately complements the particle size distribution of cement and the packing of the system is improved. Supplementary cementitious materials (SCMs) are increasingly used in replacement of Portland cement thanks to their dual effect: (1) they have a much lower environmental impact than Portland clinker, and (2) they improve the microstructure by causing pore refinement and increased tortuosity. The impact of these SCMs on the pore structure is comprehensively depicted by MIP. A fair description is obtained by single-cycle MIP [2; 7]. However, multicycle MIP may offer additional information of the action of SCMs. This paper describes the pore structure of blended concrete mixes by the analysis of multicycle MIP. Concrete mixes containing GGBFS and LP were tested and compared to Portland cement concrete samples. The interpretation of results focuses on the additional value of multicycle MIP to describe the effect of GGBFS and LP on the pore structure of concrete, also applying fractal analysis to describe the texture of pore walls. An interesting aspect for analysis regarding the complexity of pore surfaces is the presence of GGBFS. Changes in the pore structure are confirmed with the substitution of Portland cement by GGBFS, but these are generally indicated as changes in the pore size distribution or pore volume. The texture of pore walls is also worth analysing.