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检索条件"丛书名=Lecture Notes in Mechanical Engineering"

共 6719 条记录，以下是281-290 订阅

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Crashworthiness of C-Shaped CFRP Composites: A Numerical and Experimental Study 5th

Crashworthiness of C-Shaped CFRP Composites: A Numerical and...

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5th International Symposium on Dynamic Response and Failure of Composite Materials

作者： Capretti, Monica Ricciardi, Maria Rosaria Papa, Ilaria Lopresto, Valentina Boria, Simonetta Antonucci, Vincenza Univ Camerino Sch Sci & Technol Div Math Via Madonna Carceri 9 I-62032 Camerino Italy CNR Inst Polymers Composites & Biomat Ple E Fermi I-80055 Portici Italy Univ Naples Federico II Dept Chem Mat & Prod Engn Ple Tecchio 80 I-80125 Naples Italy

ISBN: (纸本)9783031776991;9783031776977;9783031776960

Carbon fiber-reinforced polymers (CFRPs) are widely used in transportation applications for structural components due to their outstanding lightweight and crashworthiness properties. Unlike metals, these composites fail through a combination of different failure mechanisms that contribute to the energy absorption capability of the final structure. In this study, the crash absorption capability of flat and C-shaped CFRPs, specifically carbon/epoxy composites, under dynamic conditions was investigated both experimentally and numerically. Initially, Charpy impact tests were conducted at different impact velocities using a three-point bending procedure. Subsequently, a finite element model was developed and simulated using LS-DYNA software. The numerical results closely replicated the outcomes of the physical experiments and exhibited a strong correlation with the experimental data, thereby validating the effectiveness of the designed model. Furthermore, the model successfully reproduced the observed damage mechanisms occurring during the physical tests, demonstrating its capability to accurately capture the composite behavior under the prescribed impact loading conditions.

关键词： Composites Carbon fiber Charpy impact Energy absorption Finite element analysis

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OPC UA Discovery-Driven Dynamic Reconfiguration of Robotic Manufacturing Systems: Method and Deployment 1

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7th International Workshop on Autonomous Remanufacturing (IWAR)

作者： Yang, Zhijian Ye, Xun Li, Ruifang Xu, Wenjun Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Wuhan Univ Technol Hubei Key Lab Broadband Wireless Commun & Sensor Wuhan 430070 Peoples R China

ISBN: (数字)9783031526497

ISBN: (纸本)9783031526480;9783031526497

In recent years, the diversification and individuation of market demand are becoming more and more obvious, which puts forward higher requirements for the flexibility of the manufacturing system. For cyber-physical systems, flexibility refers to the ability to be scalable and reconfigurable. The traditional industrial reconfiguration method is inefficient and lacks practical deployment, it can no longer achieve the flexibility required in practical manufacturing processes. To address these problems, this paper proposes a reconfiguration solution based on an optimization algorithm and the OPC UA discovery mechanism. The optimization algorithm is used to fast generate the optimal combination of system resources for minimizing the makespan. OPC UA discovery enables the plug-and-produce functionality that can accelerate new device integration. The proposed solution can provide decision-making support for the rapid reconfiguration of the manufacturing system and also allow for the dynamic integration of newly inserted devices into the manufacturing system. Finally, the feasibility of the solution is verified by a demonstration of reconfiguration in robotic manufacturing systems.

关键词： OPC UA discovery Reconfiguration Information model Data communication Local discovery server

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Comparison of Iterative Solvers in Isogeometric Boundary Element Formulation for Heat Transfer Problems with Non-linear Boundary Conditions 14th

Comparison of Iterative Solvers in Isogeometric Boundary Ele...

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14th International Conference on Computational Heat and Mass Transfer (ICCHMT)

作者： Atak, Kaan Gumus, Ozgur Can Cetin, Barbaros ID Bilkent Univ Mech Engn Dept Microfluid & Lab On A Chip Res Grp TR-06800 Ankara Turkiye

ISBN: (纸本)9783031666087;9783031666094

Boundary element method is a widely used numerical technique to solve partial differential equations (PDEs). Although the solution of linear PDEs with linear boundary conditions is straightforward, the presence of non-linearities requires additional steps which is the case for many heat transfer problems. In this study, a basis for heat transfer problems with non-linear boundary conditions is constructed by employing the isogeometric boundary element method, which leverages parametric functions used for geometry modeling to represent the field variables. The heat transfer problem with radiative and convective boundary conditions is solved with a non-linear solver in which different linear solvers are utilized. The performances of direct and iterative solvers are assessed. Preconditioners are employed to increase the convergence rate of iterative solvers. The accuracy of the proposed method is assessed by comparing the results with the analytical solution and the performance of each solver is determined by the elapsed time required for the convergence.

关键词： IGABEM Non-linear boundary conditions Newton-Raphson Iterative solver Preconditioner

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Analysis of Strategies and Models for Industrial Symbiosis in Manufacturing Ecosystems 7th

Analysis of Strategies and Models for Industrial Symbiosis i...

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7th International Workshop on Autonomous Remanufacturing (IWAR)

作者： Di Pasquale, Valentina Caterino, Mario Riemma, Stefano Rinaldi, Marta Fruggiero, Fabio Iannone, Raffaele Univ Salerno Dept Ind Engn I-84084 Fisciano Italy Univ Campania I-81031 Aversa Italy Univ Basilicata Sch Engn Potenza Italy

ISBN: (纸本)9783031526480;9783031526497

In the coming decades, a primary challenge for the global economy lies in reconciling economic growth with environmental sustainability and the responsible consumption of natural resources. The transition from a linear economy to a circular one has gained recognition as a pivotal strategy for achieving net-zero greenhouse gas emissions. Industrial Symbiosis (IS) emerges as a crucial tool in this transition, fostering a circular economy at both national and global levels. IS represents an innovative approach to minimize raw material extraction and optimize resource utilization. Despite recognized environmental, economic, and social benefits, various barriers hinder IS implementation, particularly in manufacturing environments and few detailed case studies in scientific literature have been reported. This study aims to bridge this knowledge gap by systematically analyzing 16 selected articles on IS in manufacturing systems. The analysis categorizes case studies by various parameters, including publication year, manufacturing sector, country, entities involved, IS network characteristics, and exchange methods. It also highlights key trends, barriers, and drivers for IS implementation. The study reveals an increasing interest in IS since 2011, emphasizing its potential to address sustainability challenges while fostering economic growth. It underscores the importance of clear legislation, economic incentives, and knowledge dissemination to facilitate IS adoption. In conclusion, industrial symbiosis and the circular economy are vital strategies to achieve sustainable resource management and economic resilience. Overcoming barriers and promoting IS practices are essential steps towards a more sustainable future.

关键词： Circular economy Industrial systems Industrial symbiosis

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A Study of Gaussian Fuzzy Preprocessing for Image Classification 1

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Liu, Chieh-An Lin, Kuo-Ping Tunghai Univ Dept Ind Engn & Enterprise Informat Taichung Taiwan

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

The evolution of artificial intelligence has progressed through distinct waves since the 1960s, with a current focus on deep learning. It is worth noting that, due to the development of computer vision, machines are now able to process visual data in a similar way to humans. In healthcare, artificial intelligence integration, particularly in diagnostics, leverages machine learning and deep learning to enhance speed, accuracy, and early disease detection, significantly elevating healthcare quality. This study aims to develop a system integrating fuzzy preprocessing with GoogLeNet image classification. Initially, publicly available image datasets, the COVID-19 Lung CT Scans Dataset are utilized. These datasets are divided into training, validation, and test sets. Gaussian fuzzy preprocessing is applied to the images, followed by training and validation of the GoogLeNet model. Subsequently, the trained model is tested on the dataset, achieving an average accuracy of 89.87%. Furthermore, if this technology is applied to future manufacturing processes, it can lead to higher production efficiency and improved product quality.

关键词： Fuzzy Preprocessing GoogLeNet Medical Image Classification

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Toward ML-Based Application for Vehicles Operation Cost Management 1

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8th International Scientific-Technical Conference (MANUFACTURING)

作者： Rojek, Izabela Mikolajewski, Dariusz Przybylinski, Slawomir Dostatni, Ewa Sapietova, Alzbeta Kazimierz Wielki Univ Bydgoszcz Poland Poznan Univ Tech Poznan Poland Univ Zilina Zilina Slovakia

ISBN: (数字)9783031564673

ISBN: (纸本)9783031564697;9783031564673

This paper presents the design and implementation of a web-based application for managing vehicle operating costs. The application is intended to help vehicle users control and optimize the money spent on the maintenance of both a single vehicle and a group of vehicles (fleet) for the company. Moreover this application aims to collect data that will then serve as sample files that will then be used in a machine learning application. At the beginning of the work, the methodology and requirements to be met by the web application were discussed. In the following parts of the work, the implementation of the web application and tests of the application are presented. At the end of the work, proposals for further development of the application and conclusions of the work are presented. In the era of electric vehicles, such applications will play an increasingly important role, including as journey calculators (charging plans, etc., taking into account journey times, distance covered, stopping times, minimizing energy consumption, etc.), hence the role of machine learning (ML) will grow, as, for example, as a route is covered, the software will recalculate data and alternative options in real time, which can be reflected in ERP logistics and enterprise fleet management systems for sustainability.

关键词： Artificial Intelligence Machine Learning Industry 4.0 Fleet Management Cost Optimization Sustainable Exploitation

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The Early-Warning System to Predict Sediment Flux in the Mountain Basin During Typhoon Events 23rd

The Early-Warning System to Predict Sediment Flux in the Mou...

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2022 International Association for Hydraulic Environmental engineering and Research Asia Pacific Division

作者： Ho, Hao-Che Natl Taiwan Univ Dept Civil Engn Taipei 10617 Taiwan

ISBN: (纸本)9789819760084;9789819760091

The watershed sedimentation could be determined as the severe natural disaster source. The differences between the sediment yield estimation and the real situation are large due to the inadequacy of on-site measurement data. A robust early-warning approach that encloses both the physical mechanism and statistical analysis was proposed to predict the sedimentation and improve the deficit on the current methods. This three-phase early-warning system includes, Phase I (data collection), Phase II (data generation), and Phase III (AI prediction). In Phase I, HEC-HMS was applied to transform the measured precipitation data to the flow discharge from different sub-catchments. The empirical formulas of landslide volume and soil erosion were then adopted to provide reasonable boundary conditions to Phase II. A 2D model, SRH-2D, was verified with on-site data and conducted to obtain simulated data for the temporal variation of the sediment flux with different storm events. The simulated data can be the input for Phase III to train and test the artificial neural networks. Three prediction models presented a good performance from 1-h to 6-h lead time comparing to the observation. Even though the relatively poor performance was shown in the higher sediment discharge and the difference was gradually increasing with the longer forecast lead time, the prediction models still provide the proper prediction trend, especially the forecast lead time from 1-h to 3-h. This approach shows a significant improvement on the sediment prediction due to the sufficient simulated data, and can be well-applied to better manage sediment problems in advance.

关键词： Multi-phase approach Early-warning system ANNs Typhoon events Sediment flux

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Investigation of the Mechanism of Cutting by the Ball End Mill Tip and Its Influences on the Surface Topography and the Cutting Force 10th

Investigation of the Mechanism of Cutting by the Ball End Mi...

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10th International Conference on Design and Modeling of mechanical Systems (CMSM)

作者： Regaieg, Amine Belguith, Rami Sai, Lotfi Univ Sfax Unite Genie Prod Mecan & Mat ENIS Sfax Tunisia Univ Carthage EPT Ecole Polytech Tunisie Carthage Tunisia Univ ARTOIS FSA Bethune LGCgE Arras France Univ Carthage Inst Preparatoire Etud Ingenieurs Nabeul IPEIN Carthage Tunisia

ISBN: (纸本)9783031650062;9783031650079

The modeling of the cutting process is one of the important roads to optimize cutting parameters through computer-aided manufacturing simulations. However, many models, whether analytical, numerical, or geometrical, are plagued by inaccuracies, consistently exhibiting a percentage of errors when compared to experimental tests. This paper investigates and analyzes certain interpretations and observations to illustrate inaccuracies in the existing models for roughness, topography, and cutting forces, specifically in the context of 3-axis ball end milling. An approach is proposed to enhance the accuracy of predicting these models.

关键词： 3-axis ball end milling tool tip topography cutting forces rubbing

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Optimization of Process Variables in Warm Extrusion of a Mg-Al-Zn Alloy by Numerical Simulation 14th

Optimization of Process Variables in Warm Extrusion of a Mg-...

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14th International Conference on Numerical Methods in Industrial Forming Processes (NUMIFORM)

作者： Tamuly, Reeturaj Kumar, D. Ravi Aravindan, S. Indian Inst Technol Delhi Dept Mech Engn New Delhi 110016 India

ISBN: (纸本)9783031580086;9783031580062;9783031580055

Magnesium alloys are extensively used in various fields such as automobile, defense, and aerospace due to their high specific strength and good damping properties. Extrusion is one of the important metal forming processes that is used to process the cast alloy into various useful shapes at high production rates. It is also known to improve the workability and strength of the material. Due to these advantages, interest on the extrusion of magnesium alloys has significantly increased in the recent past. But due to poor formability at room temperature, extrusion of Mg alloys in the warm forming temperature range is an important process in the fabrication of these alloys. Optimization of process variables is critical for the minimization of extrusion load and prevention of defects. In this work, numerical simulations of the extrusion process of a Mg-Al-Zn (AZ31) alloy are carried out to predict the optimum combination of process parameters, namely, extrusion ratio, extrusion speed, and extrusion temperature. Hansel Spittle model was used to define the flow stress curve in the simulation. The effect of the process parameters on extrusion load was studied, and the optimum die angle required to minimize the load required for extrusion was predicted.

关键词： Mg alloy Extrusion Warm forming Finite element simulation

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Assessment of the Usefulness of Additively Manufactured AnatomicalModels in the Process of Preoperative Support and Education 8th

Assessment of the Usefulness of Additively Manufactured Anat...

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8th International Scientific-Technical Conference (MANUFACTURING)

作者： Zukowska, Magdalena Gorski, Filip Wichniarek, Radoslaw Kuczko, Wieslaw Buczkowska-Andruszko, Agata Banaszewski, Jacek Poznan Univ Tech Div Prod Engn Poznan Poland Poznan Univ Med Sci Dept Otolaryngol Head & Neck Surg Poznan Poland

ISBN: (纸本)9783031564581;9783031564567

Additive manufacturing reports on technology development indicate medicine as one of the four main areas of application of 3D printing. Anatomical models are understood as products presenting the individual anatomy of an organ and pathology occurring in a patient. These objects manufactured using additive manufacturing methods are used in several important areas of medicine, including: in preoperative preparation, training, education and communication between doctor and patient. The aim of the presented study was to evaluate two types of anatomical models of the same patient. Both products had high transparency of the structures of healthy organs, with one model imitating soft tissue and the other being a hard, only visual model. Additive manufacturing technologies such as polyjet, fused deposition modeling and vacuum casting were used to produce the models. The evaluation took the form of a survey during which a group of specialists in the field of laryngology checked the usefulness of both models and the possibility of implementing such solutions in preoperative preparation and education.

关键词： Preoperative support Anatomical models Additive manufacturing Vacuum Casting Soft Tissues Otolaryngology

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