Polymorphic uncertainty modeling ofa 3D printing process of concrete

在过去的几十年里，建筑业的数字化取得了长足的进步。它已经融入了从设计和规划到结构的终身监测和维护的各种过程。增加的自动化和合理化节省了成本和时间，同时还提高了工作空间的安全性。与传统的、即主要是减法或成形的生产方法相比，添加制造技术实现了设计驱动的制造过程，从而可以制造出具有高度复杂性、设计自由度和功能性的结构。目前的研究热点是开发3D打印技术，并对其进行优化，并将其应用于日常实践中，以获得性能定义良好、在不同荷载下具有可靠性能的结构。对于大多数材料和印刷技术来说，不确定因素主导着工艺，这是很常见的。例如，在混凝土的3D挤压打印过程中，泵送的新鲜混凝土的粘度可能会发生变化，影响结构的几何形状、硬化和最终性能。应该接受的是，在一个过程中，参数是随机变化的，但是在该过程中存在自相关。这些相关性并不是完全已知的，这促使了模糊随机变量的应用，以同时涵盖任意和认知的不确定性。此外，表示3D打印过程的模型的一些输入参数可能表现出与其他参数的交叉相关，这应该被考虑在内。同样，对于具有模糊互相关的输入参数，应该考虑模糊随机变量。综上所述，该项目导致了基于瞬时有限元的混凝土3D打印过程的多态不确定性描述，其中交叉和自相关的随机过程被转换为相互关联的随机场，即结果结构的空间和随机变化的材料特性。由于模型中包含了精确的不确定性描述，因此可以进一步用于工艺的可靠性分析，其中考虑了不同的失效模式(基于强度的失效、几何要求、屈曲和层界面强度)。最后，该模型可以用于在严格考虑所有类型的不确定性的情况下对3D打印过程进行优化指导。

Over the past few decades, the digitization in the construction industry has been progressed considerably. It has been integrated into processes ranging from design and planning to lifetime monitoring and maintenance of structures. The increased automation and rationalization save costs and time, while improving the workspace safety, additionally. In comparison to conventional, i.e. mostly subtractive or forming, production methods, additive manufacturing techniques enable a design-driven manufacturing process so that structures with a high degree of complexity, design freedom and functionality can be produced. Current research focus aims at developing 3D printing techniques, optimizing them and applying them in daily practice in order to obtain structures with well-defined properties and reliable behavior under different loads. For most materials and printing techniques it is common, that uncertainties dominate the processes. For instance, during 3D extrusion printing of concrete, the viscosity of the pumped fresh concrete may vary, affecting the geometry, the hardening and the final properties of the structure. It should be accepted that parameters during a process vary randomly, where however auto-correlations during the process are present. These correlations are not fully known, motivating the application of fuzzy-random variables to cover aleatoric and epistemic uncertainties simultaneously. Furthermore, some input parameters of a model representing a 3D printing process may exhibit cross-correlations with other parameters, which should be accounted for. Again, for the input parameters with vaguely known cross-correlation, fuzzy-random variables should be considered. Taking this together, the project results in a polymorphic uncertainty description of a transient finite element-based 3D printing process of concrete, where cross- and auto-correlated random processes are converted into cross-correlated random fields, namely the spatially and randomly varying material properties of the resulting structures. Having a precise uncertainty description included in the model, this can be further taken for reliability analysis of the process, where different failure modes are to be considered (strength-based failure, geometric requirements, buckling and layer interface strength).Finally, the model can be used to steer a 3D printing process optimally under a rigorous consideration of all types of uncertainties.