Process parameters in Additive Manufacturing (AM) are key factors in the mechanical performance of 3D-printed parts. In order to study their effect, a three-zone model based on the printing pattern was developed. This modelization distinguished three different zones of the 3D-printed part, namely cover, contour, and inner; each zone was treated as a different material. The cover and contour zones were characterized via uniaxial tensile tests and the inner zones via computational homogenization. The model was then validated by means of bending tests and their corresponding computational simulations. To reduce the number of required characterization experiments, a relationship between the raw and 3D-printed material was established by dimensional analysis. This allowed describing the mechanical properties of the printed part with a reduced set of the most influential non-dimensional relationships. The influence on the performance of the parts of inter-layer adhesion was also addressed in this work via the characterization of samples made of Polycarbonate Acrylonitrile Butadiene Styrene (ABS/PC), a polymeric material well known for its poor adhesion strength. It was concluded that by using this approach, the number of required testing configurations could be reduced by two thirds, which implies considerable cost savings.
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http://dx.doi.org/10.3390/polym13111766 | DOI Listing |
Sci Rep
January 2025
Department of Ophthalmology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
To assess the choroidal vessels in healthy eyes using a novel three-dimensional (3D) deep learning approach. In this cross-sectional retrospective study, swept-source OCT 6 × 6 mm scans on Plex Elite 9000 device were obtained. Automated segmentation of the choroidal layer was achieved using a deep-learning ResUNet model along with a volumetric smoothing approach.
View Article and Find Full Text PDFPhys Med Biol
January 2025
Beijing institute of control and electronic technology, 51 Beilijia, Muxidi, Xicheng District, Beijing 100038, Beijing, 100038, CHINA.
Objective Ultrasound is the predominant modality in medical practice for evaluating thyroid nodules. Currently, diagnosis is typically based on textural information. This study aims to develop an automated texture classification approach to aid physicians in interpreting ultrasound images of thyroid nodules.
View Article and Find Full Text PDFHeart Lung
January 2025
Department of Radiology, Rehabilitation and Physiotherapy, Faculty of Nursing, Physiotherapy and Podiatry, Complutense University of Madrid, Madrid, Spain; Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain. Electronic address:
Background: Fatigue is one of the most limiting symptoms in individuals with heart disease (HD). However, valid and reliable instruments for assessing fatigue in clinical practice still need to be improved.
Objective: To assess the dimensional structure of the self-reported Spanish Multidimensional Fatigue Inventory (MFI) and analyze its psychometric properties in individuals with HD.
Environ Monit Assess
January 2025
Technische Hochschule Nürnberg Georg Simon Ohm, Institute of Hydraulic Engineering and Water Resources Management, Nuremberg, Germany.
Through the mobilization of movable objects due to the extreme hydraulic conditions during a flood event, blockages, damage to infrastructure, and endangerment of human lives can occur. To identify potential hazards from aerial imagery and take appropriate precautions, a change detection tool (CDT) was developed and tested using a study area along the Aisch River in Germany. The focus of the CDT development was on near real-time analysis of point cloud data generated by structure from motion from aerial images of temporally separated surveys, enabling rapid and targeted implementation of measures.
View Article and Find Full Text PDFBehav Res Methods
January 2025
Department of Psychology, University of Quebec at Trois-Rivières, Trois-Rivières, Canada.
Frequently, we perceive emotional information through multiple channels (e.g., face, voice, posture).
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