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Development of Joining Methods of Thermoplastic Composites for Aerospace Applications
No full textFiber-reinforced thermoplastic matrix composite laminates pose great potential for current and future aircraft components. Thermoplastic composites' recyclability, long shelf life, resistance to environmental conditions, and high toughness properties are rapidly increasing their application areas. In addition, its environmental hazardous is much lower compared to thermosets. Thermoplastic composites have gained an important position in aviation due to these properties. In this study, some joining methods that can be used for a thermoplastic matrix composite aircraft structure have been experimentally examined. The methods were compared by performing a single lap shear test (ASTM D5868) at the coupon level. In addition, details about a novel ultrasonic welding machine that performs the welded joining method are also given. Results show that the joint strength of thermoplastic composites can be tailored by the chosen method and corresponding parameters.https://doi.org/10.56193/matim.1540358https://dergipark.org.tr/tr/pub/matim/issue/92048/154035
Evaluation of Damage to Existing Buildings Induced by Tunnel Excavation
No full textThis study emphasizes the significance of employing systematic approaches and precise modeling techniques to evaluate potential building damage from metro tunnel excavations. Mair et al. (1996) proposed a three-stage assessment framework comprising preliminary assessment, second-stage assessment, and detailed assessment to analyze the damage to buildings inflicted by tunnel excavation. For preliminary and second-stage assessments, parametric calculation methods have been examined; however, detailed assessment requires using a 3D numerical analysis model. This study selected a school building, to examine this three-stage assessment method. For the preliminary and second stage assessments, a “greenfield” analysis approach was utilized using the PLAXIS 2D to determine the ground settlement curve caused by tunnel excavation. Based on the obtained settlement values, the evaluation was conducted using the boundary conditions proposed by Mair et al. (1996). Since the obtained settlement values did not meet the proposed boundary conditions, a three-dimensional finite element model was generated using the SAP2000 analysis program. This paper offers practical guidance on the nonlinear modeling principles of structural elements during the detailed assessment of a building subjected to vertical settlement. It provides a framework for assessing buildings near tunnel construction sites.https://doi.org/10.3390/infrastructures10010013https://doaj.org/article/844ab219ad0c4d9686470d5c2485214
Accuracy Enhancement in Refractive Index Sensing via Full-Spectrum Machine Learning Modeling
No full textWe present a full-spectrum machine learning framework for refractive index sensing using simulated absorption spectra from meta-grating structures composed of titanium or silicon nanorods under TE and TM polarizations. Linear regression was applied to 80 principal components extracted from each spectrum, and model performance was assessed using five-fold cross-validation, simulating real-world biosensing scenarios where unknown patient samples are predicted based on standard calibration data. Titanium-based structures, dominated by broadband intensity changes, yielded the lowest mean squared errors and the highest accuracy improvements—up to an 8128-fold reduction compared to the best single-feature model. In contrast, silicon-based structures, governed by narrow resonances, showed more modest gains due to spectral nonlinearity that limits the effectiveness of global linear models. We also show that even the best single-wavelength predictor is identified through data-driven analysis, not visual selection, highlighting the value of automated feature preselection. These findings demonstrate that spectral shape plays a key role in modeling performance and that full-spectrum linear approaches are especially effective for intensity-modulated index sensors.https://doi.org/10.3390/bios15090582https://dx.doi.org/10.48550/arxiv.2504.06195https://pubmed.ncbi.nlm.nih.gov/41002322/https://pmc.ncbi.nlm.nih.gov/articles/PMC12467005/http://arxiv.org/abs/2504.0619
Forced Response of a Nonlinear Translating Brake Band in the Presence of Friction Guides
No full textThe goal of this article is to investigate the response of a nonlinear translating brake band system under different external loading and constraint conditions. A friction bench experiment is designed, built, and instrumented accordingly. In this experiment, an actuation body (supported by the friction guides) is pushed against a translating brake band over a prescribed actuation cycle. Therefore, two friction regimes are generated; one between the actuation body and brake band, and another one between the actuation body and friction guide(s). Locations of the friction guides and external load application points are varied and all possible cases are experimentally and computationally studied. First, the effect of the center of contact force shift on the forced response is investigated, and conditions that lead to this shift are examined. Second, a nonlinear mathematical model is utilized to explain the relationship between the center of contact force location and the forced system response, as well as to observe certain trends. Finally, such trends are confirmed by measurements, and a better understanding of the effect of external load and constraint locations on a variation in the friction force is obtained. Some of the findings are briefly linked to the vehicle brake judder problem.https://doi.org/10.1007/978-1-4614-6570-6_12https://dx.doi.org/10.1007/978-1-4614-6570-6_1
Impact of UAV-Derived RTK/PPK Products on Geometric Correction of VHR Satellite Imagery
No full textSatellite imagery is a widely used source of spatial information in many applications, such as land use/land cover, object detection, agricultural monitoring, and urban area monitoring. Numerous factors, including projection, tilt angle, scanner, atmospheric conditions, terrain curvature, and fluctuations, can cause satellite images to become distorted. Eliminating systematic errors caused by the sensor and platform is a crucial step to obtaining reliable information from satellite images. To utilize satellite images directly in applications requiring high accuracy, the errors in the images should be removed by geometric correction. In this study, geometric correction was applied to the Pléiades 1A (PHR) image using non-parametric methods, and the effects of different transformation models and digital elevation models (DEMs) were investigated. Ground control points (GCPs) were obtained from orthophotos created by the photogrammetric method using precise positioning. The effect of photogrammetric DEMs with various spatial resolutions on geometric correction was investigated. Additionally, the effect of DEMs obtained using the photogrammetric method was compared with those from open-source DEMs, including SRTM, ASTER GDEM, COP30, AW3D30, and NASADEM. Two-dimensional polynomial transformation, the thin plate spline (TPS), and the rational function model (RFM) were applied as transformation methods. Our results showed that a higher-accuracy geometric correction process could be achieved with orthophotos and DEMs created using precise positioning techniques such as RTK and PPK. According to the results obtained, an RMSE of 0.633 m was achieved with RFM using RTK-DEM, while an RMSE of 0.615 m was achieved with RFM using PPK-DEM.https://doi.org/10.3390/drones9040291https://doaj.org/article/cb8dbb7cbf934ccf8646025827a7b97
A method for correcting the substructure of multiprong jets using the Lund jet plane
No full textA bstract Many analyses at the CERN LHC exploit the substructure of jets to identify heavy resonances produced with high momenta that decay into multiple quarks and/or gluons. This paper presents a new technique for correcting the substructure of simulated large-radius jets from multiprong decays. The technique is based on reclustering the jet constituents into several subjets such that each subjet represents a single prong, and separately correcting the radiation pattern in the Lund jet plane of each subjet using a correction derived from data. The data presented here correspond to an integrated luminosity of 138 fb − 1 collected by the CMS experiment between 2016–2018 at a center-of-mass energy of 13 TeV. The correction procedure improves the agreement between data and simulation for several different substructure observables of multiprong jets. This technique establishes, for the first time, a robust calibration for the substructure of jets with four or more prongs, enabling future measurements and searches for new phenomena containing these signatures.https://doi.org/10.1007/jhep11(2025)038https://dx.doi.org/10.5445/ir/1000188339https://dx.doi.org/10.3204/pubdb-2025-05297https://dx.doi.org/10.48550/arxiv.2507.07775https://dx.doi.org/10.3929/ethz-c-000790864https://dx.doi.org/10.3204/pubdb-2025-03567http://arxiv.org/abs/2507.07775https://hdl.handle.net/11368/3120658https://doi.org/10.1007/JHEP11(2025)038https://bib-pubdb1.desy.de/record/635883https://publikationen.bibliothek.kit.edu/1000188339/170719001https://publikationen.bibliothek.kit.edu/1000188339https://doi.org/10.5445/IR/1000188339https://hdl.handle.net/11384/159525http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-11559
A Computationally Efficient Method to Generate Plausible Conformers for Ensemble Docking and Binding Free Energy Calculations
No full texthttps://doi.org/10.1021/acs.jcim.5c00431https://pmc.ncbi.nlm.nih.gov/articles/PMC12344705/https://pubmed.ncbi.nlm.nih.gov/40696994
An Alternative Route to Extract Indium from Chalcopyrite Concentrate
No full textAbstract Indium is a significant by-product of zinc metal processing, since it is commonly found with zinc sulfides in the form of solid solution. Recovery of indium in metallurgical processing of zinc is a well-known technique. In addition to the conventional application for zinc concentrates, a wide range of research has been carried out to recover indium from different type of materials such as zinc plant tailings and e-wastes. However, zinc compounds and secondary resources are not the only indium- bearing materials. In this study, an indium carrier chalcopyrite concentrate was subjected to a detailed investigation, and an original process flowsheet was designed. The suggested process included sulfation roasting, cementation, and solvent extraction stages. Impressive results were achieved in terms of overall recoveries and the quality of the end products, with 82.0% In and 98.9% Cu overall recoveries with grades of > 90% for both metals being determined. Also, other products of the process were obtained, as the final leach cake containing 44.49 ppm Au and 3330 ppm Ag.https://doi.org/10.1007/s11837-025-07303-
Reconnaissance and Discussion on Ground Motion Induced by the 2023 Türkiye-Syria Earthquake
No full textThis paper discusses the output from the damage reconnaissance conducted after the 2023 Türkiye-Syria earthquake. First, a large landslide occurred in a limestone gentle slope without much ground water. Second, the ground subsidence in the coastal area does not comply the the local soil conditions and other observed post-seismic situations. Third, the acceleration records exhibit stronger motion with longer period and shorter duration towards the western end of the causative fault and suggest supershear rupture. To understand these features of the ground motion, this paper proposes a hypothetical model that can reproduce these observations to a good extent. © 2025 Taylor & Francis Group, LLC.Chuo Kaihatsu Corporation in Tokyohttps://doi.org/10.1080/13632469.2025.245860
Annotation-efficient, patch-based, explainable deep learning using curriculum method for breast cancer detection in screening mammography
No full textAbstract Objectives To develop an efficient deep learning (DL) model for breast cancer detection in mammograms, utilizing both weak (image-level) and strong (bounding boxes) annotations and providing explainable artificial intelligence (XAI) with gradient-weighted class activation mapping (Grad-CAM), assessed by the ground truth overlap ratio. Methods Three radiologists annotated a balanced dataset of 1976 mammograms (cancer-positive and -negative) from three centers. We developed a patch-based DL model using curriculum learning, progressively increasing patch sizes during training. The model was trained under varying levels of strong supervision (0%, 20%, 40%, and 100% of the dataset), resulting in baseline, curriculum 20, curriculum 40, and curriculum 100 models. Training for each model was repeated ten times, with results presented as mean ± standard deviation. Model performance was also tested on an external dataset of 4276 mammograms to assess generalizability. Results F1 scores for the baseline, curriculum 20, curriculum 40, and curriculum 100 models were 80.55 ± 0.88, 82.41 ± 0.47, 83.03 ± 0.31, and 83.95 ± 0.55, respectively, with ground truth overlap ratios of 60.26 ± 1.91, 62.13 ± 1.2, 62.26 ± 1.52, and 64.18 ± 1.37. In the external dataset, F1 scores were 74.65 ± 1.35, 77.77 ± 0.73, 78.23 ± 1.78, and 78.73 ± 1.25, respectively, maintaining a similar performance trend. Conclusion Training DL models with a curriculum method and a patch-based approach yields satisfactory performance and XAI, even with a limited set of densely annotated data, offering a promising avenue for deploying DL in large-scale mammography datasets. Critical relevance This study introduces a DL model for mammography-based breast cancer detection, utilizing curriculum learning with limited, strongly labeled data. It showcases performance gains and better explainability, addressing challenges of extensive dataset needs and DL’s “black-box” nature. Key Points Increasing numbers of mammograms for radiologists to interpret pose a logistical challenge. We trained a DL model leveraging curriculum learning with mixed annotations for mammography. The DL model outperformed the baseline model with image-level annotations using only 20% of the strong labels. The study addresses the challenge of requiring extensive datasets and strong supervision for DL efficacy. The model demonstrated improved explainability through Grad-CAM, verified by a higher ground truth overlap ratio. He proposed approach also yielded robust performance on external testing data. Graphical Abstracthttps://doi.org/10.1186/s13244-025-01922-whttps://pubmed.ncbi.nlm.nih.gov/40106066http://dx.doi.org/10.1186/s13244-025-01922-whttps://doaj.org/article/51d2d181de7c4b168e7aaf2feebf3d3