## 3 Printing Information Model for Additive Manufacturing of Concrete Structures
### Verification of the Printing Information
#### 3.3.2 Competency Questions
The printing system is a robot concrete printer with a printing area of 2500 mm \(\times\) 3000 mm \(\times\) 4000 mm (L \(\times\) W \(\times\) H), a nozzle size of 25.4 mm, and a printing speed range between 3000 mm/min and 48,000 mm/min. Based on the nozzle size of the printing system, a layer height of 15 mm and an extrusion width of 30 mm are defined as slicing parameters. Toolpath parameters include a spiral layer-by-layer strategy with a boundary thickness of two adjacent filaments. A printing speed of 5000 mm/min is chosen as a machine setting with a layer interval time of 0.31 min. The material-related information is described based on the material model presented in [44]. Early-age concrete is modeled as a cohesive material with a Mohr-Coulomb failure criterion. The temporal behavior of early-age concrete regarding yield stress (i.e., green strength) is modeled using time-dependent parameters, such as cohesion and Young's modulus, as well as constant parameters, such as internal friction angle, Poisson's ratio, and dilatancy angle. The concrete printing process is simulated by gradually adding layers and updating the yield stress over time. Border conditions include free radial deformation, a fixed support at the bottom layer, and self-weight loading conditions. The input parameters are fed into the finite element model for further analysis. The finite element model is used to perform a deformation analysis to determine the maximum build height that can be achieved with the defined printing strategy and machine settings. The validation example case demonstrates that the PIM model is suitable for designing and planning concrete printing projects using BIM models, representing components to be printed as inputs. With the PIM tool, information from BIM models can be processed, enabling model updates. User-defined parameters are used as a basis to execute algorithms and generate the information necessary for simulating the build-up process. Hence, BIM

Figure 8: Validation process of the PIM model. Simulation parameters include printing speed \(v_{print}\), layer interval time \(t_{layer\ internal}\), cohesion \(C(t)\), and Young’s modulus \(E(t)\). models are extended to include material-related information, such as temporal behavior, and process-related information, such as profiles for each layer. The PIM model has therefore been shown to be suitable to describe parameters and material-process interactions in concrete printing for simple components. Even though the PIM tool can be coupled with BIM platforms, limitations regarding complex structures and data transferability are observed during validation. On the one hand, the algorithms in the PIM tool perform satisfactorily for structures with simple geometries, but errors in toolpath planning may occur for structures with complex geometries. On the other hand, data cannot be transferred directly to FEA software tools, so a work-around is presented in this study by storing the data as files. In the following section, the results of this study are discussed. ## 4 Discussion of the Results

The PIM model has been conceptualized, formalized, verified, and validated as a metamodel for the AM of concrete structures. The PIM model has been conceptualized to abstract the information exchange requirements identified in the system and process analysis by categorizing concepts into entities and attributes in a semiformal representation. The formalization of the PIM model into the PIM-O has provided a higher level of abstraction, where knowledge from various domains contained in existing ontologies can be integrated, queried, and reasoned with to further advance concrete printing towards automation. Together, the formal and semiformal representations of the PIM model have provided a comprehensive data schema for data integration and software development following object-oriented modeling concepts. The PIM model has been evaluated as a metamodel in terms of requirements and purpose satisfaction.