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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Young, Calvin J. Cook, Andrew W. Bauer, Joseph D. Goodrich, Austin C. Perfect, Bradley H. McFarland, Jacob A. Texas A and M Dept. of Mechanical Engineering United States Lawrence Livermore National Laboratory Strategic Deterrence-Design Physics Division United States Lawrence Livermore National Laboratory Computational Engineering Division United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Water droplets interacting with shock waves are known to undergo a process of deformation and breakup into smaller droplets. These processes have been well studied for strong shocks up to Mach 5, however data is sparse for higher Mach number regimes. Such high Mach number regimes are of interest to fields such as high speed flight, where droplets in the form of atmospheric hydrometeors are likely to be encountered, potentially damaging any surface they impact. We have performed a series of numerical simulations to gather data on droplet breakup for normal shocks at Mach numbers ranging from 5 to 30. Early results suggest that the Ranger &Nichols model, developed in the 1960s, provides a reasonable estimate of the breakup time for a given Mach number and droplet size. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Mach number

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Variable stiffness design optimization of fiber-reinforced composite laminates with regular and irregular holes considering fiber continuity for additive manufacturing

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Chinese Journal of Aeronautics 2025年第3期38卷 334-354页

作者： Yi LIU Zunyi DUAN Chunping ZHOU Yuan SI Chenxi GUAN Yi XIONG Bin XU Jun YAN Jihong ZHU School of Mechanics Civil Engineering&ArchitectureNorthwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518063China Key Lab for Airborne Hi-performance Electro-magnetic Window RISACJinan 130012China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518055China State Key Laboratory of Structural Analysis for Industrial Equipment Department of Engineering MechanicsInternational Research Center for Computational MechanicsDalian University of TechnologyDalian 116024China State IJR Center of Aerospace Design and Additive Manufacturing MIIT Lab of Metal Additive Manufacturing and Innovative DesignNorthwestern Polytechnical UniversityXi’an 710072China

Fiber-reinforced composites are an ideal material for the lightweight design of aerospace structures. Especially in recent years, with the rapid development of composite additive manufacturing technology, the design optimization of variable stiffness of fiber-reinforced composite laminates has attracted widespread attention from scholars and industry. In these aerospace composite structures, numerous cutout panels and shells serve as access points for maintaining electrical, fuel, and hydraulic systems. The traditional fiber-reinforced composite laminate subtractive drilling manufacturing inevitably faces the problems of interlayer delamination, fiber fracture, and burr of the laminate. Continuous fiber additive manufacturing technology offers the potential for integrated design optimization and manufacturing with high structural performance. Considering the integration of design and manufacturability in continuous fiber additive manufacturing, the paper proposes linear and nonlinear filtering strategies based on the Normal Distribution Fiber Optimization (NDFO) material interpolation scheme to overcome the challenge of discrete fiber optimization results, which are difficult to apply directly to continuous fiber additive manufacturing. With minimizing structural compliance as the objective function, the proposed approach provides a strategy to achieve continuity of discrete fiber paths in the variable stiffness design optimization of composite laminates with regular and irregular holes. In the variable stiffness design optimization model, the number of candidate fiber laying angles in the NDFO material interpolation scheme is considered as design variable. The sensitivity information of structural compliance with respect to the number of candidate fiber laying angles is obtained using the analytical sensitivity analysis method. Based on the proposed variable stiffness design optimization method for complex perforated composite laminates, the numerical examples cons

关键词： Variable stiffness composite laminates Discrete material interpolation scheme Normal distribution fiber optimization Discrete fiber continuous filtering strategy Additive manufacturing of composite laminates

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A non-equilibrium wall model: application to the QinetiQ high-lift aircraft

A non-equilibrium wall model: application to the QinetiQ hig...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Agrawal, Rahul Bose, Sanjeeb T. Moin, Parviz Department of Mechanical Engineering Center for Turbulence Research Stanford University United States Cadence Design Systems Inc Institute for Computational and Mathematical Engineering Center for Turbulence Research Stanford University United States Dept. of Mechanical Engineering Center for Turbulence Research Stanford University United States

ISBN: (纸本)9781624107238

This work applies the non-equilibrium wall model of Agrawal et al., 2024 (arXiv preprint arXiv:2407.11390) to the flow over the QinetiQ High-Lift Common Research Model aircraft at low angles of attack. This choice is motivated by the previously reported misprediction of flow separation on the trailing edges of the flap in wall-modeled large-eddy simulations of this aircraft. It is shown that the proposed non-equilibrium model identifies conditions where the boundary layer significantly departs from equilibrium conditions around the trailing edges of the flap and the wing-body fairing. Further, the model provides improved predictions of the integrated loads, such as the lift, pitching moment, and drag in this regime for two grids containing 103 and 384 million control volumes, respectively, relative to the equilibrium wall model. The surface pressure data suggests the overprediction of lift from the equilibrium wall model is correlated with an overproduction of the suction peak and the reduced Cp flattening around the flaps. Finally, it is also shown that the refinement of the fuselage boundary layer and the uniformity of the grid distribution on the wing elements can further improve the predictions of flap separation. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Flow separation

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Pneumonia detection from X-ray images using federated learning–An unsupervised learning approach

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Measurement: Sensors 2025年 37卷

作者： Rana, Neeta Marwaha, Hitesh School of Engineering Design and Automation GNA University Punjab Phagwara India School of Computational Science GNA University Punjab Phagwara India

The emergence of advanced data analysis techniques has revolutionized patient healthcare by enabling the early and efficient detection of diseases. Traditionally, disease identification relied solely on the expertise of medical professionals. However, limitations in physician availability, particularly in resource-constrained regions, can hinder timely diagnosis. Fortunately, data analysis techniques are now widely employed to address a multitude of medical disease detection. This paper presents a novel Pneumonia disease detection model by analyzing the chest X-ray data. The development of robust diagnostic tools faces a critical challenge: the lack of access to large, labeled training datasets. This challenge arises because of privacy concerns about medical data. This research proposes a solution that tackles both data scarcity and privacy concerns. It leverages an unsupervised learning model trained on decentralized datasets. The unsupervised learning approach used is an Autoencoder neural network, and the decentralized learning technique used for model training is Federated Learning. The proposed approach trains the model on data residing at multiple locations, such as healthcare institutions, without compromising patient privacy. The datasets used to train the proposed model consist of chest X-ray images of pneumonia patients and healthy individuals. It offers satisfactory performance when compared to other existing Pneumonia detection models. In similar studies, medical institutions can collaborate and develop efficient medical tools without breaching patients’ data privacy. © 2024 The Authors

关键词： Unsupervised learning

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Evolutionary mapping across vast genetic space drives the discovery of causal gene blocks for designing high-potential aromatic cathodes

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Energy Storage Materials 2025年 78卷

作者： Ko, Yeongnam Yu, Seungho Song, Songi Kim, Ki Chul Computational Materials Design Laboratory Department of Chemical Engineering Konkuk University Seoul05029 Korea Republic of Division of Chemical Engineering Konkuk University Seoul05029 Korea Republic of

Optimizing redox-active organic compounds is crucial for next-generation battery technologies, particularly because these compounds show promise as sustainable, high-performance cathode materials. Despite the potential of aromatic architectures to enhance electronic conductivity, the perception that aromatic backbones hinder redox properties has discouraged their use in cathode design. In this study, we introduce a genetic algorithm-assisted protocol for optimizing the redox potential of aromatic benzene-framed organic compounds. Leveraging a genetic algorithm and density functional theory calculations, we navigate a vast chemical space of 30 genetic components to identify promising compounds. The top-performing candidate has a redox potential of 3.11 V vs. Li/Li+, surpassing traditional non-aromatic 1,4-benzoquinone. The key to success is the identification of critical gene combinations, particularly involving boron and phosphorus as well as bent polar carbonyl groups, which significantly enhances electron affinity. This study provides a scalable framework for efficiently optimizing organic cathode materials through the iterative genetic reorganizations of building blocks. These findings pave the way for the accelerated development of advanced energy storage systems through computational material design. © 2025 Elsevier B.V.

关键词： Redox reactions

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Fe single atom trigger asymmetric In-In polarized site pairs boosting near-infrared N2 photoreduction

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Materials Today 2025年 86卷 96-103页

作者： Liang, Huimin Ye, Caichao Wu, Yao Li, Yezi Long, Ran Xiong, Jun Jiang, Wei Di, Jun School of Chemistry and Chemical Engineering National Special Superfine Powder Engineering Research Center Nanjing University of Science and Technology Nanjing210094 China Academy for Advanced Interdisciplinary Studies & Department of Materials Science and Engineering Guangdong Provincial Key Laboratory of Computational Science and Material Design Southern University of Science and Technology Shenzhen518055 China School of Materials Science & Engineering Nanyang Technological University Singapore639798 Singapore National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience School of Chemistry and Materials Science University of Science and Technology of China Hefei230026 China Institute for Energy Research Jiangsu University Zhenjiang212013 China

Building differentiated charge distributed polarized atomic pairs may be an alternative for N2 activation. In this work, CuInS2 atomic layers with asymmetric In-In polarized site pairs are prepared by doping Fe single atoms, as proved by X-ray absorption fine structure spectroscopy, quasi in situ X-ray photoelectron spectra and calculated atomic charge distribution. The engineered Fe single atoms tuned the surface atomic charge distribution, building local polarization center to boost directional surface charge separation. The formed In-In polarized site pairs with asymmetric charge distribution creates distinct interaction with two N atoms in N2 molecule, contributing to the enhanced activation of N2. The alternating pathway is regarded as hydrogenation pathway over Fe-CuInS2 with *NNH formation as rate-determining step. The charge-redistributed surface atomic structure after engineered Fe single atoms strengthens intermediate interaction and lower the rate-determining step energy barrier. Benefiting from these features, Fe-CuInS2 exhibits excellent photocatalytic activity under near-infrared (NIR) irradiation with an ammonia synthesis rate of 94.1 μmol g−1 h−1. In comparison, the N2-NH3 conversion rate of Fe-CuInS2 under ultraviolet–visible (UV–Vis) irradiation could reach 137.4 μmol g−1 h−1, which is about 6.8 times higher than that of CuInS2. The apparent quantum efficiencies of Fe-CuInS2-2 at 380, 400, 450, 500, 550, 650, 700, 800, 850 and 1064 nm were 3.0 %, 3.3 %, 2.7 %, 2.1 %, 2.0 %, 1.5 %, 1.3 %, 0.4 %, 0.7 % and 0.6 %, respectively. © 2025 Elsevier Ltd

关键词： X ray absorption fine structure spectroscopy

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3D-Printed Stainless Steel Electrodes for Advancing Mems Microbial Fuel Cells Toward Sustainable on-chip Energy 38

3D-Printed Stainless Steel Electrodes for Advancing Mems Mic...

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38th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2025

作者： Elhadad, Anwar Li, Guangfa Yang, Jiaqi Liu, Dehao Choi, Seokheun State University of New York at Binghamton Integrated Computational Materials Design Lab Department of Mechanical Engineering BinghamtonNY United States State University of New York at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering BinghamtonNY United States State University of New York at Binghamton Center for Research in Advanced Sensing Technologies and Environmental Sustainability BinghamtonNY United States

ISBN: (纸本)9798331508890

This study introduces a stainless steel microbial anode fabricated via advanced laser powder bed fusion, marking a transformative step in microbial fuel cell (MFC) technology. By leveraging this cutting-edge metal 3D printing approach, we achieve a 3D microporous structure with superior electrical conductivity, outstanding corrosion resistance in aquatic environments, robust mechanical strength, and adaptability for surface modification - essential attributes for sustainable, high-performance MFCs. The assembled MFC demonstrates unparalleled power output, along with exceptional durability and stability over multiple cycles, outperforming existing MFCs based on alternative 3D-printed substrates. This advancement not only solidifies the role of MFCs as a sustainable energy solution for powering on-chip electronics but also opens new avenues for scalable, cost-effective bioelectronic systems that align with the demands of next-generation technology. © 2025 IEEE.

关键词： Corrosion resistance

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Spline-Based Stochastic Collocation Methods for Uncertainty Quantification in Nonlinear Hyperbolic PDEs

Spline-Based Stochastic Collocation Methods for Uncertainty...

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European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2023

作者： Chertock, Alina Iskhakov, Arsen S. Janajra, Safa Kurganov, Alexander Department of Mathematics North Carolina State University RaleighNC United States Department of Mechanical and Nuclear Engineering Kansas State University ManhattanKS United States Department of Mathematics Shenzhen International Center for Mathematics and Guangdong Provincial Key Laboratory of Computational Science and Material Design Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9783031861727

In this paper, we study the stochastic collocation (SC) methods for uncertainty quantification (UQ) in hyperbolic systems of nonlinear partial differential equations (PDEs). In these methods, the underlying PDEs are numerically solved at a set of collocation points in random space. A standard SC approach is based on a generalized polynomial chaos (gPC) expansion, which relies on choosing the collocation points based on the prescribed probability distribution and approximating the computed solution by a linear combination of orthogonal polynomials in the random variable. We demonstrate that this approach struggles to accurately capture discontinuous solutions, often leading to oscillations (Gibbs phenomenon) that deviate significantly from the physical solutions. We explore alternative SC methods, in which one can choose an arbitrary set of collocation points and employ shape-preserving splines to interpolate the solution in a random space. Our study demonstrates the effectiveness of spline-based collocation in accurately capturing and assessing uncertainties while suppressing oscillations. We illustrate the superiority of the spline-based collocation on two numerical examples, including the inviscid Burgers and shallow water equations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Normal distribution

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Fine- Tuning Pre-trained Models for Aspect-Based Sentiment Analysis of Amazon Food Reviews

Fine- Tuning Pre-trained Models for Aspect-Based Sentiment A...

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2025 International Conference on Computer, Electrical and Communication engineering, ICCECE 2025

作者： Sridhar, D. Manikandan, K.B. Padma Priya, R.S. Pradeepa, D. Vasumathi, B. Shankar, R. Alliane University Alliance College of Engineering and Design Central Campus Karnataka Bangalore India Hyderabad India Vignan's Foundation for Science Technology and Research Department of Information Technology and Computer Applications Guntur India Reva University School of Computer Science and Applications Bangalore India Brainware University Department of Computational Sciences West Bengal India Bharathiar University Research in Commerce Coimbatore India

ISBN: (纸本)9798331513894

The process of classifying consumer responses to a particular product review as neutral, negative, or positive is known as sentiment analysis. Product owners can utilize sentiment analysis for assistance in them decide whether to continue producing their product, increase production, or eliminate production altogether. As a result, they will gain a deeper comprehension of how customers feel about their products. The method used to determine the opinions expressed in the review regarding a specific feature or aspect of the product is called Aspect Based Sentiment Analysis, or ABSA. Numerous machine learning and natural language processing models are currently available for ABSA. The inability to precisely identify and categories the views expressed towards particular features is a major drawback of the aspect-based sentiment analysis (ABSA) techniques presently in usage for Amazon food assessment tasks. The Hybrid Contextual Aspect-Based Sentiment Analyzer (HCABSA), a hybridized framework for aspect-based sentiment analysis, is developed in this research to accurately assess the sentiment of Amazon food reviews through a number of processes. This research starts by collecting dataset for Amazon food reviews from Kaggle, preprocessing the data to eliminate noise and irrelevant information, and then using POS tagging to identify the specific aspects and sentiment words related to those aspects, which are nouns and adjectives in the review using the Lexicon based approach. In the following stage, the frequency-based candidate extraction method is utilized to pick the characteristics that are used to determine the product's internal and exterior features. The raw data is then transformed into features that the machine learning models can access using the Bag of Words feature extraction process. The Gradient Boosting Decision Tree technique is then used to categories the sentiment as either positive or negative. Using performance metrics like accuracy, precision, recall,

关键词： Decision trees

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Investigation of the mesmeric effect of substituents in DSSC based on thiophene and oxadiazole. Structural and optoelectronic study using the DFT approach

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Interactions 2025年第1期246卷 1-15页

作者： Agda, Fatima Nebbach, Diae Louazri, Latifa Ninis, Ouafae Merimi, Imane Ajana, Mohammed Aziz Bouachrine, Mohammed Laboratory Molecular and Computational Chemistry: Design Synthesis and Reactivity. Department of Chemistry Faculty of Science Moulay Ismail University Meknes Morocco Regional Center for Education and Training Professions Meknes Morocco Energy Materials and Computing Physics Research Group ENS Abdelmalek Essaadi University Tetouan Morocco Advanced Materials and Process Engineering Laboratory Faculty of Science Ibn Tofail University Kenitra Morocco National School of Architecture National Road N2 Compus de Savoir Technolopole Oujda Oujda60000 Morocco Faculty of Sciences Mohammed First University Oujda Morocco

In this work, we have developed a range of organic Donor- π -Acceptor;we are changing the π-spacers by adding novel substitutions (F, CH3, and CN) to the base molecule D-TTOxTT-A for dye-sensitized solar cells (DSSCs). Our aim is to improve the photovoltaic performance of these engineered organic dyes. We use the B3LYP (d,p) and TD/CAM-B3LYP (d,p) to study the impact of different types of the introduction of the substitution in the spacer, on the sensitizer characteristics, with the aim of highlighting the links between structure and property. Based on these results, it is possible to use these dyes as promising sensitizers for DSSCs. In addition, M4 could be an ideal compound for high throughput DSSC due to its planar geometry, low energy gap (1.73eV), higher absorption wavelength (449.3nm), longer lifetime (2.366 ns), lower ΔGreg (-0.64 eV), large hardness (-0.869 eV) and reasonable energy reorganization (0.488eV). © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Thiophene

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