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

作者： Guo, Y. Kwon, J. Sumption, M.D. Collings, E.W. Cao, D. Meng, H. Marzang, V. Liu, X. Robert, R. Layhew, G. Schafer, D. The Ohio State University College of Engineering Department of Material Science and Engineering ColumbusOH43210 United States University of Dayton School of Engineering Department of Electrical and Computer Engineering DaytonOH45469 United States Tennessee Tech University School of Engineering Department of Electrical and Computer Engineering CookevilleTN38505 United States Tennessee Tech University College of Engineering Department of Mechanical Engineering CookevilleTN38505 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The rapid development of electric aircraft technology drives the need for highly effective cooling systems to manage the significant heat generated by high-power electronic components. In this work, liquid ammonia, with its excellent thermophysical properties including a high specific heat, and volumetric energy density, is evaluated as a good coolant (especially relevant when it will also serve aviation fuel at the same time). This work focuses on designing fuel storage and cooling strategies to address thermal management challenges both globally and locally for the electric aircraft. Aluminum was chosen as the material for the heat exchanger/heat sink due to its excellent resistance to liquid ammonia corrosion, high thermal conductivity, and low density. Using computational fluid dynamics (CFD) simulations, we analyzed the heat transfer performance and liquid ammonia flow characteristics within the aluminum heat sink. Temperature distribution of aluminum heat sink and flowing liquid are simulated to determine the viability and effectiveness of this cooling strategy. In addition, various design configurations, including fluid storage methods (cold-temperature or high-pressure) and flow channel topology, are explored to optimize the cooling efficiency. The results shows that liquid ammonia cooling is feasible to maintain the power electronics within safe operating temperatures under the given flow rates and operating conditions, especially for the cold-temperature storage strategy. This research provides valuable insights into the design and implementation of advanced cooling systems for next generation electric aircraft, indicating the potential of liquid ammonia as an effective and innovative cooling media good cooling media, despite challenges related to environmental, safety, and corrosion concerns. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Aluminum corrosion

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Skeleton-Based Volumetric Parameterizations for Lattice Structures

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computer Modeling in engineering & sciences 2023年第4期135卷 687-709页

作者： Long Chen Shuxun Liang Nan Yan Xiangqian Yang Baotong Li School of Mechanical Engineering University of Shanghai for Science and TechnologyShanghai200093China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai200093China Key Laboratory of EducationMinistry for Modern Design&Rotor-Bearing System Xi’an Jiaotong UniversityXi’an710049China

Lattice structures with excellent physical properties have attracted great research *** this paper,a novel volume parametric modeling method based on the skeleton model is proposed for the construction of threedimensional lattice *** skeleton model is divided into three types of *** the corresponding algorithms are utilized to construct diverse types of volume parametric *** unit-cell is assembled with distinct nodes according to the geometric *** final lattice structure is created by the periodic arrangement of *** different types of volume parametric lattice structures are constructed to prove the stability and applicability of the proposed *** quality is assessed in terms of the value of the Jacobian ***,the volume parametric lattice structures are tested with the isogeometric analysis to verify the feasibility of integration of modeling and simulation.

关键词： Lattice structure volumetric parameterization skeleton model node modeling

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DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios 14

DRL-Based Satellite Network Slice Planning and Handover in t...

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14th International Conference on Information and Communication Technology Convergence, ICTC 2023

作者： Kim, Seonghoon Kim, Taeyeoun Kwak, Jeongho Choi, Jihwan P. Korea Advanced Institute of Science and Technology Dept. of Aerospace Engineering Korea Republic of Daegu Gyeongbuk Institute of Science and Technology Dept. of Electrical Engineering and Computer Science Korea Republic of

ISBN: (纸本)9798350313277

This paper introduces a novel approach using deep reinforcement learning (DRL) to enhance network slicing planning and handovers in satellite networks. We propose a proactive handover trigger based on remaining service time and employ the deep deterministic policy gradient (DDPG) algorithm to maximize the utility of virtual networks (VNs). Focusing on the Korean Peninsula, we simulate a low earth orbit (LEO) satellite network based on Starlink satellite specifications and demonstrate the superiority of our intelligent network management technique compared to baseline methods, particularly in terms of latency performance and the number of handovers. © 2023 IEEE.

关键词： deep reinforcement learning handover Satellite network satellite network slicing planning

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Comparison of Several Machine-Learning-Enhanced Sub-grid Scale Stress Models for Meso-scale Hurricane Boundary Layer Flow Simulation

Comparison of Several Machine-Learning-Enhanced Sub-grid Sca...

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

作者： Hasan, Md Badrul Yu, Meilin Oates, Tim Department of Mechanical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States

ISBN: (纸本)9781624107238

The complicated energy cascade and backscatter dynamics present a challenge when studying turbulent flows in storms at the meso-scale. When performing standard large-eddy simulations (LES), sub-grid scale (SGS) stress models usually fail to consider energy backscatter. These models assume that kinetic energy only moves continuously from larger to smaller scales. However, coherent energy backscatter structures exist when analyzing hurricane boundary layer flows at the meso-scale. Our recent research has shown that machine-learning SGS models trained with high-resolution data can effectively forecast forward and backward energy transfers in meso-scale hurricane-like vortex flows. Therein, physical and geometrical invariances were introduced to better represent flow physics. This further improved the predictability and generalizability of machine-learning-enhanced SGS models. In this study, we compare the performance of several machine-learning-enhanced SGS models, especially those based on neural networks (NNs), with varying physical and geometrical invariance embedding levels for SGS stress modeling in an a priori sense, which sets the cornerstone for ongoing a posteriori tests of NN models. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Vortex flow

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Classification of PC Baseband Signals from Wireless Egress 26

Classification of PC Baseband Signals from Wireless Egress

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26th International ITG Workshop on Smart Antennas, WSA 2023 and 13th Conference on Systems, Communications, and Coding, SCC 2023

作者： Leghari, Mohammad Ahmed Pralle, Sina Mei Peik, Sören F. Lütje, Sebastian Henkel, Werner Computer Science and Engineering Jacobs University Bremen Bremen Germany Electrical Engineering and Computer Science Bremen University of Applied Sciences Bremen Germany Development and TEMPEST Aerospace Data Security GmbH Bremen Germany

ISBN: (纸本)9783800760510

Being related to so-called TEMPEST activities, we show some possibilities to classify standard signal emissions from a PC environment, such as Ethernet, USB, or HDMI. Hereto, we make use of time-frequency analysis followed by deep learning or alternatively, by looking into individual signal properties, such as symbol rates, special fixed patterns, common-mode presence, or amplitude histograms. We will see that the distinction of such standard signals can be very efficient, even in the case of 100Base-T and 1000Base-T Ethernet that are designed to use the same frequency range and hence have a very similarly looking time-frequency representation. Under noise-free conditions, 100 % correct classification is achieved. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Ethernet

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Glass Wet Deep Etching for Fabricating Biomimetic Devices in Biosensing 15

Glass Wet Deep Etching for Fabricating Biomimetic Devices in...

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15th IEEE International Conference on ASIC, ASICON 2023

作者： Li, Yuxin Duan, Zhenxia Wang, Jie Zhou, Zijian Yang, Ming Wu, Enqi Du, Lin University of Shanghai for Science and Technology School of Mechanical Engineering Shanghai China University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai200433 China

ISBN: (纸本)9798350312980

The advancement of semiconductor fabrication methods has sped up the development of bionic structures and biosensing technologies. The device structure of an imitation lotus leaf and the digital biomolecular diagnostic technology are developed in this work using the wet etching procedure. The mold formed of high borosilicate glass BF33 has the benefit of low roughness and superior etching controllability over a calcium sodium glass, and the roundness parameter is raised by an average of more than 4% up to an etching depth of more than 100 μm. The produced droplet volume by device preparation can have a relative standard deviation as low as 4.5%, and the one-time filling rate is greater than 90%. The novel tool is used in biological Loop-Mediated Isothermal Amplification (LAMP) assessment to confirm that digital detection and biocompatibility are feasible. © 2023 IEEE.

关键词： BF33 glass droplet array LAMP wet deep etching

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Aerial refueling scheduling of multi-receiver and multi-tanker under spatial-temporal constraints for forest firefighting

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Chinese Journal of Aeronautics 2024年第5期37卷 71-91,I0001页

作者： Jing HUANG Jiaqi XING Jinrui REN Quan QUAN Youmin ZHANG Department of Information and Control Engineering Xi’an University of TechnologyXi’an 710048China Jiujiang Measuring Test Technology Research Institute Jiujiang 332000China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Automation Xi’an University of Posts&TelecommunicationsShaanxiXi’an 710121China Department of Mechanical Industrial and Aerospace EngineeringConcordia UniversityMontreal H3G 1M8Canada

Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest *** the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and *** order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver ***,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for *** methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling *** optimization problem is established as nonlinear optimization models along with *** integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified *** has a complete solution space and excels in optimizing total fuel *** decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational ***,this comes at the cost of sacrificing optimality by excluding specific feasible ***,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed *** simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world *** comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.

关键词： Aerial refueling Scheduling Planning Spatial-temporal constraint Firefighting

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Current research status of tumor cell biomarker detection

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Microsystems & Nanoengineering 2023年第5期9卷 17-34页

作者： Liying Jiang Xinyi Lin Fenghua Chen Xiaoyun Qin Yanxia Yan Linjiao Ren Hongyu Yu Lingqian Chang ang Wang School of Electrical and Information Engineering Zhengzhou University of Light IndustryZhengzhou 450002China Academy for Quantum Science and Technology Zhengzhou University of Light IndustryZhengzhou 450002China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong Kong SARChina key Laboratory of Biomechanics and Mechanobiology(Beihang University) Ministry of EducationBeijing Advanced Innovation Center for Biomedical EngineeringSchool of Biological Science and Medical EngineeringBeihang UniversityBeijing 100083China School of Engineering Medicine Beihang UniversityBeijing 100083China

With the annual increases in the morbidity and mortality rates of tumors,the use of biomarkers for early diagnosis and real-time monitoring of tumor cells is of great *** used for tumor cell detection in body fluids include circulating tumor cells,nucleic acids,protein markers,and extracellular *** them,circulating tumor cells,circulating tumor DNA,and exosomes have high potential for the prediction,diagnosis,and prognosis of tumor diseases due to the large amount of valuable information on tumor characteristics and evolution;in addition,in situ monitoring of telomerase and miRNA in living cells has been the topic of extensive research to understand tumor development in real *** techniques,such as enzyme-linked immunosorbent assays,immunoblotting,and mass spectrometry,have been widely used for the detection of these *** them,the detection of tumor cell markers in body fluids based on electrochemical biosensors and fluorescence signal analysis is highly preferred because of its high sensitivity,rapid detection and portable ***,we summarize recent research progress in the detection of tumor cell biomarkers in body fluids using electrochemical and fluorescence biosensors,outline the current research status of in situ fluorescence monitoring and the analysis of tumor markers in living cells,and discuss the technical challenges for their practical clinical application to provide a reference for the development of new tumor marker detection methods.

关键词： diagnosis mortality diseases

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Enhancing Multimodal Rumor Detection with Statistical Image Features and Modal Alignment via Contrastive Learning 21st

Enhancing Multimodal Rumor Detection with Statistical Image...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Zhou, Chenyu Li, Xiuhong Li, Zhe Chen, Fan Sheng, Jiabao Chen, Bin Wang, Haoyu School of Computer Science and Technology Xinjiang University Xinjiang China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong Department of Electrical Engineering Stanford University CA United States Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9789819601219

The swift proliferation of multimodal rumors on social media, particularly those with manipulated images and complex intermodal interactions, significantly challenges current detection methods. In response, we utilize statistical image features, including mean and variance, to capture spatial attributes effectively and improve the detection of image-tampered tweets. To tackle complex intermodal correlations, we introduce a contrastive learning approach that aligns features across modalities efficiently. Additionally, we introduce a cross-attention fusion module (CAFM) that enhances the integration of image and text modalities, thereby improving multimodal rumor detection performance. In conclusion, we propose the cross-attention fusion network (ConCAFN), leveraging contrastive learning for robust multimodal rumor detection. Extensive experiments on two real-world datasets confirm the model’s enhanced capability to detect multimodal rumors accurately, demonstrating our methods’ effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Prognostics for Lithium-ion batteries for electric Vertical Take-off andLanding aircraft using data-driven machine learning

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Energy and AI 2023年第2期12卷 145-162页

作者： Mihaela Mitici Birgitte Hennink Marilena Pavel Jianning Dong Faculty of Science Utrecht UniversityHeidelberglaan 83584 CSUtrechtThe Netherlands Faculty of Aerospace Engineering Delft University of TechnologyKluyverweg 1HS 2926DelftThe Netherlands Electrical Engineering Mathematics and Computer Science FacultyTU Delft2628 CDDelftThe Netherlands

The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landingvehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinctcharacteristic of batteries for eVTOLs is that the discharge rates are significantly larger during take-off andlanding, compared with the battery discharge rates needed for automotives. Such discharge protocols areexpected to impact the long-run health of batteries. This paper proposes a data-driven machine learningframework to estimate the state-of-health and remaining-useful-lifetime of eVTOL batteries under varying flightconditions and taking into account the entire flight profile of the eVTOLs. Three main features are consideredfor the assessment of the health of the batteries: charge, discharge and temperature. The importance of thesefeatures is also quantified. Considering battery charging before flight, a selection of missions for state-ofhealth and remaining-useful-lifetime prediction is performed. The results show that indeed, discharge-relatedfeatures have the highest importance when predicting battery state-of-health and *** several machine learning algorithms, it is shown that the battery state-of-health and remaining-useful-lifeare well estimated using Random Forest regression and Extreme Gradient Boosting, respectively.

关键词： Electric Vertical Take-off and Landing vehicles Lithium-ion battery State-of-health Machine learning Remaining-useful-life

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