Abstract In recent years, the study of high hydraulicity natural hydraulic lime (NHL5) mortars has been in the focus of many researchers, as it is considered a compatible, eco-friendly binding material, which can be used both for the restoration of culturally and historically significant structures, as well as for the construction of contemporary buildings. In the present study, artificial neural networks (ANNs) are used, aiming to simulate and map the development of NHL5 mortars' characteristics, such as compressive strength (CS), ratio of compressive to flexural strength (CS/FL) and consistency (CO), for selected mortar mix parameters, namely the binder to sand ratio (B/S), the water to binder ratio (W/B) and the maximum diameter of the aggregate (MDA) for different mortar specimen ages (AS). To this purpose, databases were developed, integrating experimental data from the international literature. Experimental verification of the developed ANN models revealed satisfactory fitting between theoretical and experimental results. This research highlights the potential of ANNs as a tool which can assist in mortar design and/or optimization, while mapping the development of mortar characteristics can assist in revealing the influence of the different mortar mix parameters on each characteristic. Furthermore, by combining the results of the three developed ANNs (CS, CO, CS/FL) targeted multi-parametric design of mortars can be assisted through a novel approach.

中文翻译：

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天然水硬石灰砂浆的测绘与整体设计

摘要 近年来，高水硬性天然水硬石灰（NHL5）砂浆作为一种相容、环保的粘结材料，既可用于文化修复，又可用于文化修复，因此受到众多研究者的关注。具有历史意义的建筑，以及现代建筑的建造。在本研究中，使用人工神经网络 (ANN) 旨在模拟和绘制 NHL5 砂浆特性的发展，例如抗压强度 (CS)、抗压与抗弯强度之比 (CS/FL) 和稠度 (CO) )，对于选定的砂浆混合参数，即不同砂浆试样年龄 (AS) 的粘合剂与砂比 (B/S)、水与粘合剂比 (W/B) 和骨料的最大直径 (MDA)。为此，开发了数据库，整合国际文献中的实验数据。开发的人工神经网络模型的实验验证表明理论和实验结果之间的拟合令人满意。这项研究强调了人工神经网络作为一种工具的潜力，可以帮助砂浆设计和/或优化，同时绘制砂浆特性的发展可以帮助揭示不同砂浆混合参数对每个特性的影响。此外，通过结合三个开发的人工神经网络（CS、CO、CS/FL）的结果，可以通过一种新颖的方法来辅助砂浆的目标多参数设计。这项研究强调了人工神经网络作为一种工具的潜力，可以帮助砂浆设计和/或优化，同时绘制砂浆特性的发展可以帮助揭示不同砂浆混合参数对每个特性的影响。此外，通过结合三个开发的人工神经网络（CS、CO、CS/FL）的结果，可以通过一种新颖的方法来辅助砂浆的目标多参数设计。这项研究强调了人工神经网络作为一种工具的潜力，可以帮助砂浆设计和/或优化，同时绘制砂浆特性的发展可以帮助揭示不同砂浆混合参数对每个特性的影响。此外，通过结合三个开发的人工神经网络（CS、CO、CS/FL）的结果，可以通过一种新颖的方法来辅助砂浆的目标多参数设计。