SAMPE 2019 - Charlotte, NC最新文献_第9页

Investigation of Influence of Different Piercing Methods of Abrasive Waterjet on Delamination of Fiber Reinforced Composite Laminate 磨料水射流不同穿孔方式对纤维增强复合材料层合板分层影响的研究

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1458

Garam Kim, B. Denos, R. Sterkenburg, P. Wang, S. Ahsan

引用次数: 0

Process Modelling of Induction Welding for Thermoplastic Composite Materials By Neural Networks 热塑性复合材料感应焊接过程的神经网络建模

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1370

Hao Guo, J. Pandher, M. Tooren, Song Wang

{"title":"Process Modelling of Induction Welding for Thermoplastic Composite Materials By Neural Networks","authors":"Hao Guo, J. Pandher, M. Tooren, Song Wang","doi":"10.33599/NASAMPE/S.19.1370","DOIUrl":"https://doi.org/10.33599/NASAMPE/S.19.1370","url":null,"abstract":"Induction welding for thermoplastic composite materials uses an alternating current flowing through a coil to induce an electromagnetic field and generate eddy current inside laminate with various fiber orientations – the generated heat causes the laminate to heat up and melt the polymer. As a pressure is applied to the induction heating zones, cohesive bonding may occur during the melting of the polymer. The welding quality of the composite materials is highly influenced by the temperature varying inside the heating zones. Thus, it is beneficial for induction welding if temperature varying during heating can be acquired given a set of welding parameters, such as current, pressure, fiber orientations, etc. Conducting practical induction heating experiments for this purpose is laborious and time consuming given the large varying space of welding parameters. In this paper, we propose to address this problem by using machine learning techniques to model the relation between the welding parameters and the temperature varying inside the heating zones. We conduct two sets of induction heating experiments for laminate welding and the collected sample temperature varying data are used to train the neural networks with input of welding parameters and output of the predicted temperature varying. Testing of the models demonstrates that process modeling of induction welding with machine learning techniques is viable.","PeriodicalId":162077,"journal":{"name":"SAMPE 2019 - Charlotte, NC","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128944560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Virtual Comissioning of Manufacturing System Intelligent Control 制造系统智能控制的虚拟调试

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1403

K. Xia, C. Sacco, M. Kirkpatrick, R. Harik, A. Bayoumi

{"title":"Virtual Comissioning of Manufacturing System Intelligent Control","authors":"K. Xia, C. Sacco, M. Kirkpatrick, R. Harik, A. Bayoumi","doi":"10.33599/NASAMPE/S.19.1403","DOIUrl":"https://doi.org/10.33599/NASAMPE/S.19.1403","url":null,"abstract":"Smart manufacturing systems seek to provide adaptive intelligent strategies to manufacturing practitioners in response to environmental changes, system prognosis, and optimal solution identification. For large scale manufacturing processes, their control methodologies are expensive to train, test and develop. Virtual Commissioning, as a digital transformation method, offers a datadriven approach to automate manufacturing system knowledge so that a digital twin can be developed to visually represent manufacturing plants, numerically simulate robot behaviors, predict system faults and adaptively control manipulated variables. In this work, integrating a Machine Learning agent into the Virtual Commissioning platform Siemens Technomatix Process Simulate further expands the usage of the digital twin by training and verifying intelligent control algorithms before pushing them to the physical world for implementation. This is accomplished by transferring data between the Siemens Process Simulate Software Development Kit and Google’s TensorFlow framework to implement a Reinforcement Learning-based dynamic scheduling algorithm on a virtual manufacturing cell. For future development, control via an industrial controller will allow communication between the digital world and physical manufacturing plant so that synchronous control can be achieved. The developed control algorithms are expected to assign tasks, schedule work, generate optimal path solutions and demonstrate control robustness.","PeriodicalId":162077,"journal":{"name":"SAMPE 2019 - Charlotte, NC","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129001040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

High Throughput Carbon Fiber Surface Modification 高通量碳纤维表面改性

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1528

Z. Hinton, M. Kubota, Lavenia J Thursch, J. Deitzel, G. Palmese, N. Alvarez

引用次数: 0

Approximations By Reduced-Order Models for Nonlinear Flutter of Variable Stiffness Composite Plates 变刚度复合材料板非线性颤振的降阶模型逼近

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1499

H. Akhavan, P. Ribeiro

{"title":"Approximations By Reduced-Order Models for Nonlinear Flutter of Variable Stiffness Composite Plates","authors":"H. Akhavan, P. Ribeiro","doi":"10.33599/NASAMPE/S.19.1499","DOIUrl":"https://doi.org/10.33599/NASAMPE/S.19.1499","url":null,"abstract":"In this investigation, we analyze errors due to using reduced-order models instead of full-order models in the examination of nonlinear flutter of variable stiffness composite laminates (VSCLs). These plates can be made, e.g., by Automated Tow Placement Machines, using composite laminates with curvilinear fibers; in our particular case, the orientation angle of the reference curvilinear fiber path changes linearly from T 0 at the left edge to T 1 at the right edge of the plate. A Third-order Shear Deformation Theory (TSDT) is used to model the laminate and a p-version finite element is applied to discretize the displacements and rotations. The plates are subjected to a supersonic airflow of which the aerodynamic pressure is approximated using linear Piston theory. The equations of motion of the full-order model of the self-excited vibrational system are formed using the principle of virtual displacements. In order to reduce the number of degrees-of-freedom of the full-order model, static condensation and/or a modal summation method are used. The equations of motion of the reduced-order and full-order models are solved using Newmark method to study the dynamic responses, focusing on limit cycle oscillations (LCOs). Approximation errors are discussed for LCO amplitudes of VSCL plates with various curvilinear fiber paths.","PeriodicalId":162077,"journal":{"name":"SAMPE 2019 - Charlotte, NC","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117109625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Compression Experiment and Simulation Study of Shape Memory Alloy Lattice Structure 形状记忆合金晶格结构压缩实验与仿真研究

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1469

O. Ishida, Junichi Kitada, Katsuhiko Nunoani, K. Uzawa

引用次数: 0

Out-of-autoclave Process and Automation: A Successful Path to Highly Integrated and Cost Efficient Composite Wing Moveables 高压灭菌器外工艺和自动化:高度集成和成本效益的复合机翼可移动的成功途径

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1409

Thibault de Lumley, François Mathieu, D. Cornet, Dimitri Gueuning, Nicolas Van Hille

引用次数: 2

The Effect of Shape and Orientation on the Barrier Properties of Flake-filled Composites: A 3D Approach 形状和取向对片状填充复合材料阻挡性能的影响:一种三维方法

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1421

A. Tsiantis, T. Papathanasiou

引用次数: 0

Closed-form Solutions for Predicting Interlaminar Shear Stress and Hygrothermomechanical Normal Stress in Composite Beams with Rectangular and Tubular Cross-sections 矩形和管状截面组合梁层间剪应力和湿热力学法向应力预测的封闭解

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1364

S. Mahadev, W. Chan, Reiley A Schraeger

引用次数: 0

Hybridization of Carbon Nanotube-Glass Fiber Based Hierarchical Composites Using Electrophoretic Deposition 电泳沉积碳纳米管-玻璃纤维复合材料的杂交研究

SAMPE 2019 - Charlotte, NC Pub Date : 2019-04-11 DOI: 10.33599/NASAMPE/S.19.1487

D. Sung, S. Doshi, A. Rider, E. Thostenson

引用次数: 1