For sinus grafting, different methods and materials are available. One possible shortcoming of particulate bone grafts is either overfilling or augmenting the planned implant area insufficiently. To overcome this risk and to determine the implant position prior augmentation, we present an approach using three-dimensional printed scaffolds. A patient with a remaining anterior dentition and bilateral severely atrophied posterior maxilla was seeking oral rehabilitation. The cone beam computed tomography (CBCT) showed residual bone heights between one and two millimeters. Following the three-dimensional reconstruction of the CBCT data, the positions of the implants were determined in areas 16 and 26. Three-dimensional scaffolds adapted to the topography of the sinus were virtually designed and printed using a calcium phosphate cement paste. Bilateral sinus floor augmentation applying the printed scaffolds with an interconnecting porosity followed. After nine months, a satisfying integration of the scaffolds was obvious. At the re-entry, vital bone with sufficient blood supply was found. One implant could be placed in positions 16 and 26, respectively. After five months, the implants could be uncovered and were provided with a temporary denture. The application of three-dimensionally printed scaffolds from calcium phosphate cement paste seems to be a promising technique to graft the severely atrophied posterior maxilla for the placement of dental implants.
AR/VR applications are a valuable tool in product design and lifecycle. But the integration of AR/VR is not seamless, as CAD models need to be prepared for the AR/VR applications. One necessary data transformation is the tessellation of the analytically described geometry. To ensure the usability, visual quality and evaluability of the AR/VR application, time consuming optimisation is needed depending on the product complexity and the performance of the target device.Widespread approaches to this problem are based on iterative mesh decimation. This approach ignores the varying importance of geometries and the required visual quality in engineering applications. Our predictive approach is an alternative that enables optimisation without iterative process steps on the tessellated geometry.The contribution presents an approach that uses surface-based prediction and enables predictions of the perceived visual quality of the geometries. This contains the investigation of different geometric complexity metrics gathered from literature as basis for prediction models. The approach is implemented in a geometry preparation tool and the results are compared with other approaches.
Companies are increasingly struggling to manage their complex product portfolios. Since they do not fully understand the complexity, intelligent solutions are required. Emerging technologies and tools offer new ways to deal with existing problems. With the help of clustering, similarities between product variants can be identified automatically, and complexity can be systematically reduced. This article aims to develop a methodological approach to identify correlations between product variants in complex product portfolios automatically by using clustering algorithms. The approach includes the systematic cleaning and transformation of product portfolio data. In addition, a guide for algorithm selection and evaluation of clustering results is presented. As the last step, the results are systematically analysed and visualised. To validate the methodical approach, it is applied to a real-world data set of a commercial vehicle manufacturer and the usefulness of the results is confirmed in an expert workshop.
Water scarcity and resource depletion can be expected during the climate crisis. Therefore, thermally loaded processes in particular, must be made more efficient in the future. Heat exchangers will play a key role in this optimization process. More efficient designs allow a greater heat flow to be removed from processes while mass flows remain constant. In this context, the heat-transferring wall of heat exchangers is a focus of current research on the design of heat exchangers. The aim is to increase the heat-transferring surface of the wall as much as possible and to keep the design space as compact as possible. Therefore, this study investigates the suitability of the differential-growth method for generating complex heat-transferring walls for heat exchangers using CFD-analysis. Firstly, a framework for generating the wall structures and a computational model for predicting the design influence of such structures for the thermal and fluid-dynamic behavior of the heat exchanger are presented. Thereby, the potential of such wall structures is analyzed in this study. Furthermore, the study identified weaknesses of such walls designed with the differential-growth method, which should be the focus of future investigations.
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