PSI - Issue 78

Han Liu et al. / Procedia Structural Integrity 78 (2026) 1759–1766

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These include reduced labor demands, improved cost e ffi ciency, accelerated fabrication, enhanced quality control, and increased design flexibility enabled by complex geometries and sustainable mix designs Buswell et al. (2018); Zhang et al. (2019); Khan et al. (2021); Xiao et al. (2021). Despite these advantages, challenges such as inconsistency qual ity throughout each print, monitoring of layer adhesion, material variabilit, reinforcement embedment, and ensuring overall structural performance continue to impede its widespread adoption Siddika et al. (2019); Raphael et al. (2023). To address these limitations, the use of structural health monitoring (SHM) techniques has been explored to pro vide in-situ assessment of the performance and integrity of 3D-printed structures Lynch et al. (2016); Mishra et al. (2022). While conventional sensors, such as strain gauges Yoon et al. (2022), acoustic emission transducers Van Steen et al. (2024), piezoelectric elements Gomasa et al. (2023), and fiber-optic systems Alwis et al. (2021) can o ff er valu able data, they often present integration challenges in printed structures due to their fragility, complex wiring, signal interpretation di ffi culties, and the intrusive nature of installation. As a result, recent research has shifted toward the development of self-sensing materials, particularly cementitious composites engineered to respond to mechanical stimuli by intrinsically altering their electrical properties, enabling embedded sensing without the need for discrete transducers Laflamme et al. (2023). Our prior work demonstrated that incorporating small amounts of conductive fillers, such as graphite (G) and car bon microfibers (CMF), into a cementitious matrix can impart a significant piezoresistive response to strain Birgin et al. (2021). These functionalized composites exhibit changes in electrical resistance that correlate with strain lev els under mechanical loading, enabling their use for real-time structural monitoring. This sensing principle has been demonstrated in various applications, including smart pavements Gupta et al. (2021); Gulisano et al. (2024), conduc tive cementitious sensors Han et al. (2020); Bekzhanova et al. (2021), and smart masonry units Wi et al. (2021); Meoni et al. (2022). More recently, we have found that such functionalized cementitious composites can be 3D printed, al lowing the creation of self-sensing nodes that can be embedded within structural components to monitor strain in real time during and after fabrication Laflamme and Ubertini (2020); Liu et al. (2024). The aim of this work is to investigate the integration of self-sensing nodes into structural cementitious elements using additive manufacturing, and demonstrate the technology on a 3D printed reinforced concrete beam. Specifically, we proposed self-sensing nodes made of cementitious mixes doped with G and CMF, using Sikacrete powder as the primiary binder. The beam is printed with a functionally graded design, wherein the bottom layers are made from the conductive Sikacrete composite to form the self-sensing layers, transitioning continuously to a normal Sikacrete composite at the top. These printed self-sensing layers act as strain-sensitive interfaces capable of capturing strain fields through the monitoring of electrical resistance. Commercial carbon steel drop-in anchors are embedded as electrodes to create stable and reliable electrical connections to external data acquisition systems. Percolation behavior was characterized to determine the optimal filler content in Sikacrete, and a series of dynamic tests were conducted to evaluate the strain-sensing performance of the fabricated smart beam. The rest of the paper is organized as follows. Section 2 provides the background on 3D printed self-sensing cemen titious specimens including the material properties, the fabrication process, and the derivation of the electromechan imal model. Section 3 describes the experimental methodology. Section 4 presents and discusses results from the experimental investigation. Section 5 concludes the paper.

2. Background

2.1. Materials

The conductive cementitious composite was formulated by incorporating G powder (Fisher Chemical APS 7-11 micron, 99%), milled carbon microfiber (MCMF) (SGL Carbon C M150-4.0 / 240-UN), and chopped carbon microfiber (CCMF) (SGL Carbon C M150-4.0 / 240-G100) into commercially available Sikacrete ® -752 3D powder, which is a 1-part micro-concrete specifically for use with 3D robot or gantry printers and served as the primary binder for the 3D printing process in this study. These materials were selected based on prior research findings, which demonstrated that combining these two forms of carbon microfibers in a hybrid configuration e ff ectively imparts piezoresistive behavior to cement-based composites Birgin et al. (2021); Liu et al. (2024).