Coastal biogenic structures, formed by ecosystem engineering species, often feature rough surfaces characterized by intricate topographies and highly three-dimensional reliefs. Their surfaces are shaped by waves and tidal currents and reciprocally influence the ambient hydrodynamics, reflecting an equilibrium. Despite their significance, the impact of these surfaces on the ambient hydrodynamics remains underexplored due to limited knowledge of accurately replicating their complex topographies in experimental setups. The recent advent of advanced digital manufacturing presents an efficient means to manufacture highly complex, three-dimensional surrogate models for experimental modeling. This work explores the accurate replication of rough coastal biogenic structures for experimental modeling on the examples of an oyster reef and a mussel bed, utilizing a flexible design methodology and, for the first time, particle bed 3D printing with Selective Cement Activation (SCA) as a fabrication and manufacturing method. A workflow is proposed, which includes an iterative surrogate model development based on in-situ topographical features, requirements of the experimental setup, and parameters of the particle bed 3D printer with SCA. The results demonstrate the effectiveness of the methodology in achieving highly accurate surrogate surfaces of complex coastal biogenic structures by validation against a set of topographical features relevant to hydraulic roughness. Particle bed 3D printing with SCA proved to be a suitable method to manufacture complex surrogate surfaces for experimental modeling, offering advantages such as independence of production time from surface complexity. However, challenges persist in achieving exact comparability between the manufactured surrogate surface and the real coastal biogenic structures, particularly for surfaces with very high complexity. Nonetheless, the manufactured generic surrogate surfaces enable detailed investigations into the influence of complex coastal biogenic structures on the ambient hydrodynamics, thereby enhancing the understanding of the processes governing wave energy dissipation attenuation, turbulence production, and vertical mixing – critical for efficient application as a nature-based solution on coastal protection or restoration efforts.

This study aims to quantify the dimensions of an oyster reef over two years via low-cost unoccupied aerial vehicle (UAV) monitoring and to examine the seasonal volumetric changes. No current study investigated via UAV monitoring the seasonal changes of the reef-building Pacific oyster (Magallana gigas) in the German Wadden Sea, considering the uncertainty of measurements and processing. Previous studies have concentrated on classifying and mapping smaller oyster reefs using terrestrial laser scanning (TLS) or hyperspectral remote sensing data recorded by UAVs or satellites. This study employed a consumer-grade UAV with a low spectral resolution to semi-annually record the reef dimensions for generating digital elevation models (DEM) and orthomosaics via structure from motion (SfM), enabling identifying oysters. The machine learning algorithm Random Forest (RF) proved to be an accurate classifier to identify oysters in low-spectral UAV data. Based on the classified data, the reef was spatially analysed, and digital elevation models of difference (DoDs) were used to estimate the volumetric changes. The introduction of propagation errors supported determining the uncertainty of the vertical and volumetric changes with a confidence level of 68% and 95%, highlighting the significant change detection. The results indicate a volume increase of 22 m³ and a loss of 2 m³ in the study period, considering a confidence level of 95%. In particular, the reef lost an area between September 2020 and March 2021, when the reef was exposed to air for more than ten hours. The reef top elevation increased from -15.5 ± 3.6 cm NHN in March 2020 to -14.8 ± 3.9 cm NHN in March 2022, but the study could not determine a consistent annual growth rate. As long as the environmental and hydrodynamic conditions are given, the reef is expected to continue growing on higher elevations of tidal flats, only limited by air exposure. The growth rates suggest a further reef expansion, resulting in an increased roughness surface area that contributes to flow damping and altering sedimentation processes. Further studies are proposed to investigate the volumetric changes and limiting stressors, providing robust evidence regarding the influence of air exposure on reef loss.

The Pacific oyster (Magallana gigas) is an invasive species in the Wadden Sea transforming parts of it permanently. M. gigas, as an ecosystem engineer, builds reef structures that are characterized by highly complex and variable surfaces consisting of densely packed, sharp-edged individuals connected with cement-like bonds. To investigate the interactions between reef structure, shape and formation and wave as well as tidal currents, an understanding of the surface roughness is essential. This work reports on observations of oyster reefs for which seven new structural classes (Central Reef, Transitional Zone, Cluster I, Cluster II, Patch I, Patch II, and Garland) are proposed. For each class, high resolution Digital Elevation Models (DEMs) have been elaborated based on Structure-from-Motion (SfM) photogrammetry and analyzed using spatial statistics. By determining probability density functions (PDFs), vertical porosity distributions, abundances, orientations and second-order structure functions (SSFs), topographical parameters that influence the hydraulic bed roughness have been determined. The results suggest, that by applying the structural classification and their distinct topographical roughness parameters, the oyster reef surfaces can be described appropriately accounting for their complexity. The roughness accounts to a total roughness height kt = 103 ± 15 mm and root-mean-square roughness height krms = 23 ± 5 mm. These values were found similar across all structural classes, yet the shape of the PDFs reveal differences. With decreasing abundance, the distributions become more positively skewed and are characterized by more extreme outliers. This is reflected in the higher statistical moments, as the skewness ranges between Sk = 0.4–2.1 and the kurtosis between Ku = 2.2–11.5. The analysis of the orientations and the SSFs confirms anisotropic behavior across all structural classes. Further, the SSFs reveal the oyster shells as significant roughness elements with exception of Cluster I and II, where the clusters are identified as significant roughness elements. The provided set of topographical roughness parameters enhances the knowledge of oyster reef surfaces and gives insights into the interactions between biogenic structure and surrounding hydrodynamics. The new intra-reef classification allows for more accurate determination of the overall roughness as well as the population dynamics of the habitat forming oyster. Combined with hydraulic measurements, the results can be used to estimate the hydraulic bed roughness induced by the oyster reef surfaces.

Additive manufacturing with concrete opens up new possibilities in the mass production of individualized and highly material-efficient building components. However, the absence of the commonly used formwork places high demands on the material during production, often leading to inaccuracies in the printed object. In order to guarantee dimensional accuracy and component quality, this paper presents an integrated and fully automatic quality inspection method as well as a subsequent fully automatic local postprocessing process.

A Lean-based Production Approach for Shotcrete 3D Printed Concrete Components Gerrit Placzek, Leon Brohmann, Karam Mawas, Patrick Schwerdtner, Norman Hack, Mehdi Maboudi and Markus Gerke Pages 811-818 (2021 Proceedings of the 38th ISARC, Dubai, UAE, ISBN 978-952-69524-1-3, ISSN 2413-5844) Abstract: Additive Manufacturing allows for high geometric freedom and the fabrication of non-standard building components. This new-found flexibility results from the fact that no formwork is required with additive manufacturing and thus each part can be different at no additional cost. One drawback however is that the geometric freedom comes at the price of non-verified geometric precision, requiring methods to determine and possibly counteract deviations and ensure building component's quality. Within this paper we present an "Lean-based Production Approach" for an off-site production of concrete components. Therefore, firstly lean construction is introduced and its synergies with additive manufacturing are shown. Shotcrete 3D Printing is used as a case study and illustrates the approach and unveils current potentials and challenges. Our approach is mainly based on an on demand production, bi-directional digital workflows and quality checks. Current methods for geometric and surface quality as well as for predicting production (and process) times for varying components still need to be developed further. We conclude with forecasting a new and more intelligent production system in construction. Keywords: Additive Manufacturing; Construction; Prefabrication; Lean Construction; SC3DP; Quality Control DOI: https://doi.org/10.22260/ISARC2021/0110 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley

The Large Particle 3D Concrete Printing (LP3DCP) process presented in this paper is based on the particle bed 3D printing method; here, the integration of significantly larger particles (up to 36 mm) for selective binding using the shotcrete technique is presented. In the LP3DCP process, the integration of large particles, i.e., naturally coarse, crushed or recycled aggregates, reduces the cement volume fraction by more than 50% compared to structures conventionally printed with mortar. Hence, with LP3DCP, the global warming potential, the acidification potential and the total non-renewable primary energy of 3D printed structures can be reduced by approximately 30%. Additionally, the increased proportion of aggregates enables higher compressive strengths than without the coarse aggregates, ranging up to 65 MPa. This article presents fundamental material investigations on particle packing and matrix penetration as well as compressive strength tests and geometry studies. The results of this systematic investigation are presented, and the best set is applied to produce a large-scale demonstrator of one cubic meter of size and complex geometry. Moreover, the demonstrator features reinforcement and subtractive surface processing strategies. Further improvements of the LP3DCP technology as well as construction applications and architectural design potentials are discussed thereafter.

Today, the majority of research in 3D concrete printing focuses on one of the three methods: firstly, material extrusion; secondly, particle-bed binding; and thirdly, material jetting. Common to all these technologies is that the material is applied in horizontal layers. In this paper, a novel 3D concrete printing technology is presented which challenges this principle: the so-called Injection 3D Concrete Printing (I3DCP) technology is based on the concept that a fluid material (M1) is robotically injected into a material (M2) with specific rheological properties, causing material M1 to maintain a stable position within material M2. Different to the layered deposition of horizontal strands, intricate concrete structures can be created through printing spatially free trajectories, that are unconstrained by gravitational forces during printing. In this paper, three versions of this method were investigated, described, and evaluated for their potential in construction: A) injecting a fine grain concrete into a non-hardening suspension; B) injecting a non-hardening suspension into a fine grain concrete; and C) injecting a fine grain concrete with specific properties into a fine grain concrete with different properties. In an interdisciplinary research approach, various material combinations were developed and validated through physical experiments. For each of the three versions, first architectural applications were developed and functional prototypes were fabricated. These initial results confirmed both the technological and economic feasibility of the I3DCP process, and demonstrate the potential to further expand the scope of this novel technology.

The Technical University of Braunschweig (Brunswick) and Technical University of Munich were successful to establish a Collaborative Research Centre called “Additive Manufacturing in Construction (AMC) – The Challenge of Large Scale” starting from 2020 and funded by the German Research Foundation (DFG). The aim of this project is “to create the basic conditions for the introduction of additive manufacturing in construction, and thus to pave the way for the use of resource-efficient constructions with a high level of design freedom”. Surveying engineering (geodetic surveying, photogrammetry, laser scanning and GNSS) plays a major role in one of the sub-projects called “Integration of Additive Manufacturing in the Construction Process”. This paper aims at introducing the large scale AMC with the main focus on investigating the role of surveying engineering in this topic which will be a topic of high interest in the coming years in the digital fabrication within construction field. After a short introduction on additive manufacturing in construction, this paper will present the general aims and structure of the Collaborative Research Centre. Thereupon, the importance of geometric quality inspection and establishing and transferring different coordinate systems during the Additive Manufacturing (AM) construction steps (elements fabrication, installation and whole structure/building control) and the role of geodetic surveying, photogrammetry, laser scanning and GNSS will be outlined. This will be presented within a subproject called “C06: Integration of Additive Manufacturing in the Construction Process” and potentials and challenges for integrating surveying engineering in component and building level additive manufacturing in construction are mentioned.

Additive manufacturing in construction: first 3-D-printed reinforced concrete components using Shotcrete 3-D Printing (SC3DP) technology 3-D printing (additive manufacturing) is a digitally controlled manufacturing technology, that has the potential to be specifically developed for the construction industry and to become a key technology for the digitalization in building industry. In additive manufacturing (AM), the component construction is done solely by a digitally controlled layer-by-layer material application, without mold construction or forming processes. This represents a paradigm shift to the still predominantly manual shaping construction processes. In order to fully exploit the potential of AM structural design, material behavior and manufacturing processes must be integratively aligned. This enables buildings with a high degree of design freedom and resource-efficient use of materials. At the Institute of Structural Design (ITE) and at the Institute of Building Materials, Concrete Construction and Fire Safety (iBMB) at the Technische Universitat Braunschweig, research has been carried out for several years into processes for the 3-D printing of large-format concrete components. The so-called Shotcrete 3-D Printing (SC3DP) technology was developed in an interdisciplinary research project. The SC3DP technology is an automated robotic, additive manufacturing process that builds up concrete components layer by layer with the controlled addition of compressed air. This report presents the first 3-D-printed and reinforced concrete components that demonstrate the potential of SC3DP.