## 1 Introduction
[PERSON] [32] presented a numerical procedure to evaluate the compressive strength development of high-volume fly ash concrete, which is valid for concrete with different water-to-binder ratios and different fly ash contents. [PERSON] [33] used a genetic programming model to study the effect of specimen size and shape on compressive strength of concrete containing fly ash. Limestone flour is usually assumed to be an inert filler [21] and used as a partial replacement of cement in concrete [34; 35; 36], which mainly provides a filling effect and micro-aggregate effect in the concrete [37]. The fact that limestone flour does not participate in the chemical reaction is confirmed from both thermal analysis and backscattering scanning electron image analysis [35]. Besides, other studies also find that limestone flour has low reactivity [38; 39]. Although limestone flour is deemed to be an inert material, it can still improve the very early-age compressive strength of concrete, workability, and stability of fresh concrete due to its micro-aggregate effect [40; 41]. However, a few researchers have reported that limestone flour has been successfully used in conjunction with cement as an accelerator [42; 43]. [PERSON] et al. [1] illustrate the influence of limestone flour's particle size on hydration and mechanical properties of cement pastes. In a word, the influence of limestone flour on concrete compressive strength is still unclear. There are numerous studies about the influence of each supplementary cementitious material on the compressive strength of concrete, such as slag [8], fly ash [24], and limestone flour [41]. Some studies demonstrate the influence of two or more kinds of supplementary cementitious materials on the concrete compressive strength [1; 4; 44]. However, most of these studies are specific to a certain engineering or a certain experiment [1; 4; 8; 24], which cannot reveal the nature of the influence of supplementary cementitious materials on the concrete compressive strength. Moreover, the research about the influence of two or more kinds of supplementary cementitious materials on concrete compressive strength is still unclear. Furthermore, there is a lack of clarity on the optimum proportion of one or more certain cementitious materials in a practical engineering or experiment. In order to identify the nature of the influence of supplementary cementitious materials on concrete compressive strength, it is necessary to conduct comprehensive and quantitative research, which would require a lot of experimental and engineering data instead of just using certain engineering or experimental data. To solve these problems, it requires a model with explicit expression and ability to adapt new data, which can fit and predict concrete compressive strength. There are two main types of models, conventional models and artificial intelligence models [45; 46], to predict the compressive strength of concrete mixed with supplementary cementitious materials. Generally, conventional models are developed with a fixed equation with a limited amount of data and parameters [47]. If new data is different from the original data, then it is necessary to update not only the coefficients in the model but also the form of its equation. On the other hand, artificial intelligence models require a large training data set due to their \"black-box\" techniques [48], and always having no explicit expression. Both aforementioned models are flawed. The concrete compressive strength development over time (CCSDOT) model [49] generates explicit formulas that provide important advantages to reveal the nature of influence of the supplementary cementitious materials on concrete compressive strength. Therefore, it is adopted in this study. The inbuilt optimization algorithms make the CCSDOT model more adaptable to new data than conventional models. This study employs 239 groups of mix proportions from 18 practical engineering experiments and lab reports to explore the nature of the proposed three supplementary cementitious materials.