This study investigates the mechanical properties of cementitious composites with 3D-printed auxetic lattices, featuring negative Poisson's ratios (auxetic behavior) in multiple directions. These lattices were fabricated using vat photopolymerization 3D printing, and three base materials with varying stiffness and deformation capacities were analyzed to determine their impact on the composites’ mechanical behavior. To unravel the reinforcing mechanisms of multidirectional auxetic lattices, which exhibit auxetic behavior in both planar and out-of-plane directions, X-ray computed tomography (X-ray CT) was utilized to analyze composite damage evolutions under different strain levels. The micro-CT characterization reveals that auxetic lattices more effectively constrain crack growth and dissipate energy by distributing stress evenly within the cement matrix. In contrast, due to lack of lateral confinement, the non-auxetic lattice reinforced composites primarily dissipate energy through extensive crack propagation and interfacial damage, leading to lower peak strength. When strain exceeding 5%, although the confinement from the auxetic behavior diminished with crack propagation, the lattice can still maintain the composite's structural integrity, resulting in 1.7 times higher densification energy than conventional cement-based materials. These findings provide valuable insights for designing auxetic lattice-reinforced cementitious composites with enhanced load-bearing capacity and improved dissipation capabilities.

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A novel highly compressible auxetic cementitious composite (ACC) is developed in this work. Contrary to conventional cementitious materials, such as plain concrete and fiber reinforced concrete, the ACC shows strain-hardening behavior under uniaxial compression: the stress continuously increases with strain up to approximately 40 % strain. On one hand, in the early compression stage, the ACC exhibit highly recoverable deformability of 10 % strain under cyclic loading (20 times higher than the constituent cementitious material). In addition, the ACC shows fatigue damage until the stiffness/strength and energy dissipation plateau values are reached after 500 cycles. At 2.5 % strain amplitude, the plateau stiffness/strength is approximately 120 MPa/3 MPa, while these values are only 25 MPa/1.2 MPa at 5 % strain amplitude. In contrast, the energy dissipation plateau of the ACC is independent from the amplitude and remains at 0.05 J/cm3. On the other hand, due to the strain-hardening behavior, the ACC exhibits significantly improved energy dissipation capacity compared to both the conventional cementitious materials and the auxetic frame. This behavior is achieved by a tailored composite action: integrating cementitious mortar with 3D printed thermoplastic polyurethane (TPU) auxetic frame. A rotating-square auxetic mechanism was designed for the TPU frame for the ACC to achieve the tailored cracking behavior. The horizontal ACC cells enable large deformability by enlarging the crack width under the confinement of the auxetic frame, while the vertical cells work as stiffening phase to ensure load resistance. Owing to the outstanding mechanical properties, the ACC shows great potential to be applied in engineering practice where high compressive deformability is required, for instance yielding elements for squeezing tunnel linings.

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Polyvinyl alcohol fiber reinforced engineered cementitious composite (ECC) using piezoelectric polymer film has attracted significant interest due to its energy harvesting potential. This work provides a theoretical model for evaluating the energy harvesting of bendable ECC using surface-mounted polyvinylidene fluoride (PVDF). In the mechanical part, concrete damage plasticity model based on the explicit dynamic analysis was utilized to simulate the dynamic flexural behavior of ECC beam under different dynamic loading rates. The mechanism of force transfer through the bond layer between the PVDF film and ECC specimen was simulated by a surface-surface sliding friction model wherein the PVDF film was simplified as shell element to reduce computational cost. Then, the electromechanical behavior of the piezoelectric film was simulated by a piezoelectric finite element model. A simplified model was also given for a quick calculation. The theoretical model was verified with the experimentally measured mechanical and electrical results from the literature. Finally, a parametric analysis of the effects of electromechanical parameters on the efficiency of energy harvesting was performed. The verified theoretical model can provide a useful tool for design and optimization of cementitious composite systems for energy harvesting application.@en

One particularly interesting class of mechanical metamaterials are those having a negative Poisson's ratio, which are referred to as ‘auxetics’. Because of their geometrical complexity, auxetic designs cannot always be easily created. However, Additive Manufacturing (AM) methods like material extrusion in 3D printing present the opportunity to construct auxetic structures. Nevertheless, extruded 3D printed material can be highly anisotropic. Before 3D printed auxetics manufactured through material extrusion can be used in engineering applications, it is important to generate powerful simulation tools that can reliably reproduce and foretell their mechanical characteristics irrespective of their form and intricacy. In view of this, the current work proposes printing path-dependent models based on an experimentally validated multi-scale modelling scheme using the Lattice Beam Model (LBM). This is done by first representing idealized microstructures of extruded 3D printed polymers through geometric models and simulating these on the material scale. The aim is to explicitly model the inter-layer and intra-layer bonds that exist in material extruded 3D printed parts by assigning experimentally obtained interface properties that significantly differ from the bulk material. On the auxetic structure scale, two planar auxetic designs are modelled using the determined material scale relationships as input: Re-Entrant (RE) and Rotating Square (RS). In terms of mechanical response, the experimentally and numerically obtained force displacement curves agree reasonably well: the stiffness of the modelled auxetic designs fit well with the experimentally measured ones while the LBM simulations generally provide a good estimation in strength. Finally, it has been shown on both the material and auxetic structure scales that incorporation of the interfacial bond strengths in simulations of extruded 3D printed polymers is important, because neglecting these results in significant overestimation of the strength.

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This paper presents a state-of-the-art review on the application of additive manufacturing (AM) in self-healing cementitious materials. AM has been utilized in self-healing cementitious materials in three ways: (1) concrete with 3D-printed capsules/vasculatures; (2) 3D concrete printing (3DCP) with fibers or supplementary cementitious materials (SCMs); and (3) a combination of (1) and (2). 3D-printed capsules/vascular systems are the most extensively investigated, which are capable of housing larger volumes of healing agents. However, due to the dimension restraints of printers, most of the printed vasculatures/capsules are in small scale, making them difficult for upscaling. Meanwhile, 3DCP shows great potential to lower the environmental footprint of concrete construction. Incorporation of fibers and SCMs helps improve the autogenous healing performance of 3DCP. Besides, 3D-printed concrete with hollow channels as the vasculature could further improve the autonomous healing and scalability of self-healing cementitious materials. Finally, possible directions for future research are discussed.

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3D printed polymeric reinforcement has been found able to improve the ductility of cementitious materials. However, due to the hydrophobic nature of commonly used 3D printing polymers, the bonding strength between the 3D printed polymers and cementitious matrix is extremely weak, which potentially hinders the mechanical performance of the reinforced composites. This work aims to improve the bonding properties by applying surface modifications on the 3D printed reinforcement, and eventually enhance the mechanical performance of the reinforced cementitious composites. Three types of surface coatings ingredients: epoxy resin (EP), sand sprinkled epoxy (SA) and short steel fibers sprinkled epoxy (SF) were used. Pull-out experiments are performed to study the bonding properties of the 3D printed reinforcement with different coatings. Then, uniaxial tensile and four-point-bending experiments are used to investigate the mechanical performance of the reinforced cementitious composites. A lattice type numerical model is applied to simulate the pull-out and tensile tests. The pull-out experiments indicate that the SA and SF reinforcement achieved approximately two times higher bonding strength than the uncoated and EP reinforcement. The tensile and flexural results suggest that the cementitious composites with SA and SF reinforcement achieved significantly better ductility (manifested by strain-hardening and deflection-hardening behavior) than the composites with uncoated and EP reinforcement. The numerical simulation results highly agree with the experimental findings, and further confirmed that the improved reinforcement-mortar bonding strength is the determinative factor that enhanced the composites mechanical performance. The findings of this work suggest that the sand and steel fiber surface coatings can effectively enhance the ductility of cementitious composites reinforced by 3D printed polymers.@en

Auxetic cementitious cellular composites (ACCCs) exhibit desirable mechanical properties (e.g., high fracture resistance and energy dissipation), due to their unique deformation characteristics. In this study, a new type of cementitious auxetic material, referred to as peanut shaped ACCC, has been designed and subsequently architected using additive manufacturing techniques. Two peanut shaped ACCCs specimens with different pseudo-minor axes have been tested under uniaxial compression with Digital Image Correlation (DIC) to assess their compressive behavior, peak strength, Poisson's ratio, and energy dissipation capacity. Additionally, cyclic tests were conducted to investigate their compressive resilience properties, further elucidated through microstructural analysis using a digital optical microscope. The mechanical test results were also compared with those of previously developed elliptical-shaped ACCCs. Furthermore, a numerical model was used to simulate the mechanical behavior of peanut shaped ACCCs under uniaxial compression, and showed a good agreement with the experimental data. The auxetic behavior observed in peanut shaped ACCCs arises from the rotation of sections facilitated by fiber bridging at the ligament of adjacent holes within the cementitious unit cell. In comparison to elliptical-shaped ACCCs, peanut shaped ACCCs can exhibit a slightly more negative Poisson's ratio and mitigate stress concentration. The reduction of stress concentration enables peanut shaped ACCCs to dissipate substantial energy, showcasing enhanced ductility and toughness. In cyclic tests, peanut shaped ACCCs exhibit superior recoverable deformation elasticity, attributed to robust fiber bridging capacity. The exceptional mechanical properties exhibited by peanut shaped ACCCs offer a scalable solution for developing energy-absorbent and multifunctional cementitious materials for smart infrastructure.

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Vascular self-healing concrete (SHC) has great potential to mitigate the environmental impact of the construction industry by increasing the durability of structures. Designing concrete with high initial mechanical properties by searching a specific arrangement of vascular structure is of great importance. Herein, an automatic optimization method is proposed to arrange vascular configuration for minimizing the adverse influence of vascular system through a reinforcement learning (RL) approach. A case study is carried out to optimize a concrete beam with 3 pores (representing a vascular network) positioned in the beam midspan within a design space of 40 possibilities. The optimization is performed by the interaction between RL agent and Abaqus simulation environment with the change of target properties as a reward signal. The results illustrates that the RL approach is able to automatically enhance the vascular arrangement of SHC given the fact that the 3-pore structures that have the maximum target mechanical property (i.e., peak load or fracture energy) are accessed for all of the independent runs. The RL optimization method is capable of identifying the structure with high fracture energy in the new optimization task for 4-pore concrete structure.

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A composite can have properties much better than the components it is made of. This work proposes a three-dimensional auxetic cementitious-polymeric composite structure (3D-ACPC) which incorporates 3D printed polymeric shell with cementitious mortar. Uniaxial compression experiments are performed on the 3D-ACPC to study their quasi-static stress-strain response. Experimental results show that the created composite structure can simultaneously overcome the brittleness of conventional cementitious material and the low compressive strength of 3D printed polymeric cellular shell. Therefore, the 3D-ACPC exhibit compressive strain-hardening behavior ensuring high energy absorption ability. In addition, it is found that structural anisotropy and the shell printing direction have significant impact on the stress-strain response of the 3D-ACPC. Moreover, due to the lightweight cellular structure, the 3D-ACPC shows significantly enhanced specific energy absorption compared to conventional cementitious materials and polymeric cellular materials. To this end, the developed 3D-ACPC has great potential to be used in engineering practice, such as protective structures.

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Additively manufactured vascular networks have great potential for use in autonomous self-healing of cementitious composites as they potentially allow multiple healing events to take place. However, the existence of a vascular tube wall may impede with the healing efficiency if it does not rupture timely to release the healing agent. The issue of vascular material design has therefore been a major topic of research. To overcome this, dissolvable Polyvinyl Alcohol (PVA) filament is adopted in this study to fabricate the vascular networks. Fabricated networks are coated with wax, placed in cementitious mortar and removed upon hardening, thereby leaving a network of hollow channels. Different printing directions were expected to affect the dissolvability of printed structures and were therefore fabricated and tested. Different shapes (i.e., 2D and 3D) of vascular networks were printed and embedded in the cementitious mortar. Four-point bending tests and permeability tests were performed to investigate the healing efficiency. Multiple healing cycles were applied in the cracked specimens. The results show that the vertically printed PVA tubes with wax coating have good dissolution behaviour. As expected, the existence of vascular networks decreases the initial flexural strength of the specimens. In terms of healing efficiency, excellent mechanical and water tightness recovery were achieved when using epoxy resin as the healing agent. The mechanical recovery after the first healing process is higher than the following healing process. The watertightness of the cracked samples keeps decreasing with the increase of healing cycles. Specimens embedded with 3D vascular networks have higher healing potential than those utilizing 2D vascular networks.

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Auxetic cementitious composites (ACCs) with improved mechanical properties are created, by casting 3D printed polymeric auxetic reinforcement structures inside cementitious mortar. Four types of ACCs incorporating reinforcement with different auxetic mechanisms were prepared: “re-entrant” (RE), “rotating-square” (RS), “chiral” (CR) and “missing-rib” (MR). Experiments and finite element models were used to study the compressive behavior of the ACCs. The results indicate that all ACCs have high compressive ductility. Specifically, the RE shows the highest ductility, manifested by 853% and 708% higher energy absorption than the reference mortar and the auxetic structure itself, respectively. In addition, the RE and RS are found to exhibit stronger crack-arresting effect under compression. Therefore, they achieved comparable compressive strength to the reference mortar, which is considerably higher than CR and MR. Furthermore, decreasing the volumetric ratio of the auxetic structure by half, the ductility of the RS reduces by 32.2%, while decreasing the water-to-binder ratio of the cementitious matrix from 0.4 to 0.3 only increases the compressive strength by 18.5%. Moreover, the two-dimensional finite element analyses used herein show a good match with experiments but become less accurate at high strain levels, due to their inability to capture the out-of-plane failure of the ACCs.

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Direct ink writing of cementitious materials can be an alternative way for creating vascular self-healing concrete by intentionally incorporating hollow channels in the cementitious matrix. In this study, a 3D-printable fibre reinforced mortar was first developed. Three groups of specimens were fabricated using direct ink writing, where the two top and bottom printing layers were printed with different printing directions. The macrostructure of the hardened specimens was studied using CT scanning. Four-point bending tests were carried out to investigate the initial flexural strength and the strength recovery after healing with injected epoxy resin. Furthermore, water permeability test was used to evaluate the healing potential of the samples. The results from CT scanning show that printing direction influences the actual volumes of hollow channels and the volume of small pores which are a consequence of the deposition process. The hollow channels of all samples were squeezed by the upper layers during the printing process, and the longitudinally printed samples were the most affected. When printing direction changes from longitudinal to transverse, the initial flexural strength decreases. Similarly, the average permeability of the cracked samples increases when the printing direction changes from longitudinal to transverse. Although the healing effectiveness regarding flexural strength is remarkable for all specimens, it was only possible to perform a single healing process as hollow channels were then blocked by the epoxy resin. The rough surface of the hollow channels is inferred to make it difficult to extract the epoxy resin out of the specimens.

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In this study, an experimental setup to characterize the early-age creep of 3D printable mortar was proposed. The testing protocol comprises quasi-static compressive loading-unloading cycles, with 180-s holding periods in between. An analytical model based on a double power law was used to predict creep compliance with hardening time and loading duration as inputs. Subsequently, this analytical model was validated by comparison to uniaxial compression tests in which loading is increased incrementally, i.e., in steps, showing a good quantitative agreement. Minor differences between the two results were noted, most notably at the beginning of the test. This is because the determination of creep compliance for 3D printable mortar at fresh stage depends on the load level. In the end, the volumetric strain of tested samples from uniaxial compressive test is used to explain why the compressive loading affects the creep deformation.

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Compared with other self-healing mechanisms, embedding vascular networks in cementitious matrix enables repairing wider cracks and performing multiple healing cycles. For vascular-based self-healing cementitious composites, additive manufacturing (AM) allows fabricating vascular structures with complex geometry. For Fused Filament Fabrication (FFF), printing direction has great influences on the properties of the 3D-printed vascular network. To timely release the healing agent when cracks occur, selecting the proper printing direction for the vascular network in self-healing concretes is necessary. In this work, two commercial printing filaments, i.e., polylactic acid (PLA) and polyvinyl alcohol (PVA), are used to create the vascular structures. The influence of printing direction on the dissolution of 3D-printed PVA structure is investigated. Besides, the flexural strength and water tightness of samples with PLA vascular printed in different printing directions are compared. After the 4-point bending tests, epoxy resin is manually injected into the vascular networks to seal the cracks. It is found that the strength recovery and the permeability of the cracked specimens are influenced by the printing direction due to the different crack closure after unloading.@en

The high deformation capacity of auxetic cementitious cellular composites (ACCCs) makes them promising for strain-based energy harvesting applications in infrastructure. In this study, a novel piezoelectric energy harvester (PEH) with ACCCs and surface-mounted PVDF film based on strain-induced piezoelectric mechanisms has been designed, fabricated, and experimentally tested. Furthermore, a numerical model for simulating the energy harvesting of ACCC-PVDF system undergoing repeated mechanical loading has been established and validated against the experimental data. The mechanical behavior of ACCCs was simulated by the concrete damage plasticity model during the preloading stage, which was converted to the second-elasticity model during cyclic loading stage. Based on the mechanical responses, analytical formulas for piezoelectric effects were developed to calculate the output voltage of the PVDF film. The output voltages of the ACCCs-PVDF system under different loading amplitudes and loading frequencies were assessed. The experimental results and models of the ACCCs-PVDF energy harvester lay a solid foundation for utilizing architected cementitious composites in energy harvesting applications to supply self-power electronics in infrastructure.

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In this paper, optimization of vascular structure of self-healing concrete is performed with deep neural network (DNN). An input representation method is proposed to effectively represent the concrete beams with 6 round pores in the middle span as well as benefit the optimization process. To investigate the feasibility of using DNN for vascular structure optimization (i.e., optimization of the spatial arrangement of the vascular network), structure optimization improving peak load and toughness is first carried out. Afterwards, a hybrid target is defined and used to optimize vascular structure for self-healing concrete, which needs to be healable without significantly compromising its mechanical properties. Based on the results, we found it feasible to optimize vascular structure by fixing the weights of the DNN model and training inputs with the data representation method. The average peak load, toughness and hybrid target of the ML-recommended concrete structure increase by 17.31%, 34.16% and 9.51%. The largest peak load, toughness and hybrid target of the concrete beam after optimization increase by 0.17%, 14.13%, and 3.45% compared with the original dataset. This work shows that the DNN model has great potential to be used for optimizing the design of vascular system for self-healing concrete.

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Extrusion-based 3D concrete printing (3DCP) results in deposited materials with complex microstructures that have high porosity and distinct anisotropy. Due to the material heterogeneity and rapid growth of cracks, fracture analysis in these air-void structures is often complex, resulting in a high computational cost. This study proposes a convolutional neural network (CNN)-based methodology for fracture analysis using air-void structures as input. More specifically, the lattice fracture model is used to build a dataset that comprises input air-void structures as well as output fracture information, including the crack patterns and crack-width curves. To establish the relationship between crack morphology and associated microstructures, a U-net convolutional neural network is first presented. With the obtained crack pattern as input, the principal component analysis (PCA) and CNN are then integrated to predict the stress-crack width curves. The predicted results from the CNN model demonstrate a quantitative agreement with lattice numerical analyses, with 0.85 Intersection over Union for crack patterns prediction and 0.75 R2 for the stress-crack width curves prediction. This indicates that CNN models can be used as an alternative to traditional numerical analysis. The feature maps during the convolutional or deconvolutional process are given to explain why the proposed CNN models perform well on fracture analysis of the air-void system. Moreover, the model generalization is discussed using transfer learning with fine-tuning to show the model potential on microstructures expressing varied pore information. In the end, the microstructures cropped from XCT are created to explore the further application of CNN models on fracture analysis of 3D printed materials.@en

Cracking is one of the main causes for deterioration of concrete structures. Self-healing concrete with 3D-printed vascular networks has excellent potential for autonomous self-healing. This approach is scarcely investigated: no studies have been devoted to the influence of printing parameters on the properties of vascular based self-healing concrete. In this work, three-dimensional vascular structures with complex geometry were designed and printed with 4 different sets of printing parameters. First, the influence of the four, nominally identical, vascular networks on the initial flexural strength of self-healing concretes was experimentally investigated. In parallel, numerical modeling with a concrete damaged plasticity model (CDPM) in Abaqus software is used to simulate the influence of vascular networks on the mechanical properties of the self-healing composite. After the 4-point bending tests, epoxy resin is injected into the vascular networks as the healing agent to seal the cracks. Then, flexural strength regain and watertightness recovery were also measured. Based on the obtained results, we found that vascular based self-healing concretes have lower initial flexural strengths than the reference sample, as expected. The magnitude of the strength drop is shown to depend strongly on the printing parameters: the specimens with horizontally-printed vascular networks have higher flexural strength than the vertically-printed counterparts. Furthermore, vascular networks with a smaller printing layer-height have less influence on the initial flexural strength of vascular-based self-healing concrete compared to those with the larger printing layer-height. In terms of watertightness recovery, all tested vascular based self-healing samples showed a full (100%) recovery, which means that the printing direction and printing layer-height do not have an obvious effect on the watertightness recovery in this study. Numerical simulations of the mechanical performance of the composites with the CDPM show good agreement with the experiments, although printing quality of the vascular network influences the simulation accuracy. These simulations show great potential of using numerical simulations to design vascular based self-healing concrete in order to minimize a drop in mechanical properties, without compromising the healing efficiency. Overall, the designed 3D-printed vascular self-healing concretes show remarkable strength regain and watertightness recovery and provide a good basis for further research.

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Tailoring lattice structures is a commonly used method to develop lattice materials with desired mechanical properties. However, for cementitious lattice materials, besides the macroscopic lattice structure, the multi-phase microstructure of cement paste may have substantial impact on the mechanical responses. Therefore, this work proposes a multi-scale numerical modelling method to simulate the deformation and fracture behavior of cementitious lattice materials, such that the influence of cement paste microstructure can be properly captured. On the microscale, the load–displacement response of cement paste is numerically simulated then experimentally validated. In order to rationally investigate the role of cement paste microstructure, the obtained load–displacement response was then formulated to several types of model inputs reflecting different degree of brittleness. These inputs were then used for simulating the mechanical response of macroscale cementitious lattices. By comparing the simulation to experiment, multi-linear behavior (ML) was found to an appropriate method to include the realistic pre-critical cracking and post-peak softening of cement paste in the model. Compared to ideally brittle behavior, using ML as input, the discrepancy between simulated and experimentally tested fracture energy decreases from 37.4% to 12.4%. In addition, the influence of lattice structure on the strength of cementitious lattices was also accurately captured by the proposed model. Randomized cementitious lattice has 21.6% (22.0% from simulation) lower strength than regular lattice. Moreover, the influence of fracture criterion of the proposed model is discussed and elaborated. Owning to the high simulation accuracy, the proposed multi-scale method in this work could be helpful for tailoring the fracture cementitious lattice materials for future studies.

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This research studies the impact of localized damage and deformed printing geometry on the structural failure of plastic collapse for 3D concrete printing (3DCP) using the lattice model. Two different approaches are utilized for buildability quantification: the (previously developed) load-unload method, which updates and relaxes the printing system after each analysis step and repeatedly applies the gravitational loading to the undeformed structure; and the incremental method, which keeps the load after each analysis step and applies the incremental loading to the deformed printing system. The former can consider the material yielding but cannot capture accurately the structural deformation during printing process. Compared to the load-unload method, the incremental method can not only consider deformed printing geometry but can also simulate the non-proportional loading conditions and disequilibrium force occurring during 3D printing. In this study, computational uniaxial compression tests are first conducted to compare two algorithms. The numerical results indicate the consideration of nonequilibrium force and deformed geometry affects the peak load and crack information for fracture analysis. Subsequently, the incremental method is incorporated into the lattice model to quantify buildability of 3DCP. The predictions are compared with previously published numerical results obtained using the load-unload method. The lattice model based on incremental method reproduces correct failure mode; better quantitative agreement about critical printing height also can be obtained. These numerical analyses demonstrate that the incremental solution is an approximate method for buildability quantification since it can account for the nonequilibrium force induced by the deformed printing geometry and localized damage.

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