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arXiv 2024年

作者： Amiri, Mahsa Foumani, Zahra Zanjani Cao, Penghui Valdevit, Lorenzo Bostanabad, Ramin Materials and Manufacturing Technology Program University of California IrvineCA92697 United States Department of Mechanical and Aerospace Engineering University of California IrvineCA92697 United States Department of Materials Science and Engineering University of California IrvineCA92697 United States Department of Civil and Environmental Engineering University of California IrvineCA92697 United States

Achieving desired mechanical properties in additive manufacturing requires many experiments and a well-defined design framework becomes crucial in reducing trials and conserving resources. Here, we propose a methodology embracing the synergy between high-throughput (HT) experimentation and hierarchical machine learning (ML) to unveil the complex relationships between a large set of process parameters in Laser Powder Bed Fusion (LPBF) and selected mechanical properties (tensile strength and ductility). The HT method envisions the fabrication of small samples for rapid automated hardness and porosity characterization, and a smaller set of tensile specimens for more labor-intensive direct measurement of yield strength and ductility. The ML approach is based on a sequential application of Gaussian processes (GPs) where the correlations between process parameters and hardness/porosity are first learnt and subsequently adopted by the GPs that relate strength and ductility to process parameters. Finally, an optimization scheme is devised that leverages these GPs to identify the processing parameters that maximize combinations of strength and ductility. By founding the learning on larger "easy-to-collect" and smaller "labor-intensive" data, we reduce the reliance on expensive characterization and enable exploration of a large processing space. Our approach is material-agnostic and herein we demonstrate its application on 17-4PH stainless steel. © 2024, CC BY.

关键词： Global positioning system

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Experimental Investigation and Validation of Strength-Based Topology and Fiber Path Optimization in Continuous Fiber Reinforced Composites

SSRN

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SSRN 2024年

作者： Yap, Timothy He, Zhelong Wang, Zhichao Tamijani, Ali Tehrani, Mehran Department of Structural Engineering University of California San Diego La Jolla CA92093 United States Program in Materials Science and Engineering University of California San Diego La Jolla CA92093 United States State-Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle Engineering Hunan University Changsha410082 China

Material Extrusion (ME) based Fused Filament Fabrication (FFF) excels with Continuous Carbon Fiber (CCF) reinforced filaments. This Additive manufacturing (AM) technology allows for intricate parts to be made with topologies where fibers are aligned in directions that optimize strength and stiffness, albeit within certain manufacturing limitations. This study investigates the performance of strength-based optimization methods applied to two benchmark structural domains and loading scenarios. Two methods were used to concurrently design the topology and fiber paths: shape optimization using the level-set method, and topology optimization using both density-based Solid Orthotropic Material with Penalization (SOMP) and level-set methods. CCF filaments were printed to follow the post-processed fiber paths, and a discontinuous fiber reinforced filament was used to fill in the remaining gaps. The parts were then compression molded for full consolidation, followed by testing for their stiffness and strengths (failure loads). Finite Element Analysis (FEA) was used to simulate the stiffness and failures of the tested parts. FEA predicted stiffnesses, locations of failure, and failure loads with reasonable accuracy (less than 10% difference with experiment). A micro-computed tomography (µCT) examination of failed coupons showed that fiber flow (deviation from printed paths) during compression molding was a major source of error. In one case, a progressive damage failure model performed more accurately than a linear static simulation. Finally, comparing designs optimized for stiffness versus strength showed premature failures due to stress concentrations in stiffness-optimized designs. This study underscores the critical need for integrating proper optimization strategy with realistic AM constraints to enhance the performance and reliability of CFF reinforced AM parts. © 2024, The Authors. All rights reserved.

关键词： Finite element method

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Correction: Materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

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MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National Laboratory, Lemont, USA." Argonne National Laboratory was left off the original publication. © The Author(s) 2025.

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Improve industrial performance based on systematic analyses of manufacturing data

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IFAC-PapersOnLine 2021年第1期54卷 709-716页

作者： M. Lisboa E. Jesus R. Seixas P. Valle F. Deschamps C. Strobel Institute of Applied Technology Solutions (InSTA) Manufacturing Engineering Graduate Program (PPGEM) Department of Mechanical Engineering (DEMEC) Federal University of Paraná (UFPR) Curitiba Brazil

This Article was written based on a systematic review of the literature considering three reference axes, Industry 4.0, Data Analytics and Predictive Maintenance, including specific combination of search terms to ensure a reasonable quantity of articles keeping adherence to the topic that is decision making based on collection and analysis of relevant data on B2B (Business to Business). The study focuses on the area of predictive maintenance, which has been strongly highlighted by the fourth industrial revolution, due to the mechanical and mainly the electronic embedded systems complexity increases in the last decades, as well as network connectivity possibilities for equipment’s data acquisition, enabling technologies for predictive maintenance as a key factor for competitiveness, reducing costs, increasing equipment’s availability, or as a servitization strategy. The article is divided into five parts, starting with the research model and selection of articles, including the proposal for a data analysis framework and the application of systematic analysis of these data, concluding with the opening of a discussion and the indication of future directions.

关键词： Industry 4.0 Industrial Internet of things (IIOT) Data Analytics Predictive Maintenance

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Implementation of position control, anti-sway and anti-collision systems on a rubber tyred gantry crane for human and environmental safety

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AIP Conference Proceedings 2024年第1期3140卷

作者： Andi Muh. Farid Parenrengi Abdul Kadir Muhammad Pria Gautama Manufacturing Engineering Master Program Department of Mechanical Engineering Politeknik Negeri Ujung Pandang Makassar 90245 Indonesia

The purposes of this study are to propose an effective control scheme to meet safety requirements for human and environment, and to perform experiments on a laboratory scale gantry crane. The RTG (rubber tyred gantry) prototype used in this paper consist of a hoist mechanism, trolley mechanism and a spreader. The hoist and trolley mechanism used an asynchronous motor as actuator. The variable frequency drive width modulation (PWM) signal was used to drive the asynchronous motor for a hoist and trolley mechanism. A proportional (P) controller was designed in such a way to drive the hoist and the trolley to reduce the sway and to avoid collisions of the spreader. The system and the proposed control scheme were confirmed through experiments. The experimental results revealed that the position, the sway and collision of the system can be controlled effectively.

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Mathematical modelling and optimization of parameters for Al-Si-Fe aluminum alloy reinforced by Al 2 O 3 and graphite particles using Taguchi method

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Materials Today: Proceedings 2021年 44卷 979-986页

作者： Robale Dinsa Daba Devendra Kumar Sinha Habtamu Beri Satyam Shivam Gautam Gulam Mohammed Sayeed Ahmed Ram Sewak Singh Program of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering ASTU ADAMA Ethiopia Department of Mechanical Engineering North Eastern Regional Institute of Science and Technology Itanagar India Department of Electronics and Communication School of Electrical Engineering and Computing ASTU ADAMA Ethiopia

In the present scenario the aluminum and its alloys are preferred due to requirement of lightweight high strength material. The present research article interrogates experimentally the study of actual density and porosity using powder metallurgy method. The experimental design is done using Taguchi L 16 orthogonal array. Actual density and porosity has been analyzed based on ‘smaller is best’ basis. Actual density and porosity are calculated using Archimedes principle. The leverage of four levels and five process parameters such as weight percentage of Al 2 O 3 , weight percentage of graphite, compaction pressure, compaction time and milling time are considered. Results reveal that Al 2 O 3 weight percentage has the highest leverage on density followed by compaction time and graphite weight percentage.

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Optimal Vision-Based Orientation Steering Control for a 3D Printed Dexterous Snake-Like Manipulator to Assist Teleoperation

TechRxiv

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TechRxiv 2023年

作者： Razjigaev, Andrew Pandey, Ajay K. Howard, David Roberts, Jonathan Jaiprakash, Anjali Crawford, Ross Wu, Liao The School of Electrical Engineering and Robotics The QUT Centre for Robotics Brisbane Australia The Cyber Physical Systems Program Data61 CSIRO Australia The Department of Orthopaedic Surgery Prince Charles Hospital ChermsideQLD Australia The School of Mechanical and Manufacturing Engineering University of New South Wales Sydney Australia

Endoscopic cameras attached to miniaturised snakelike continuum robotic arms can improve dexterity, accessibility, and visibility in minimally invasive surgical tasks. This steerable camera can expand the field of view and enhance the surgical experience with additional degrees of freedom. However, it also creates more control options that complicate human-machine interaction. This challenge presents an opportunity to develop novel human-machine control strategies using visual sensing to complement the dexterous actuation of a steerable surgical manipulator. This study presents a semi-autonomous controller to assist teleoperation by steering a camera such that it keeps an arbitrary target in the centre of the field of view, thus assisting in surveying different orientations about the target with image-based information. Two controllers are proposed using classical image-based visual servoing techniques and optimal visual predictive control techniques. These techniques are simulated and validated on our robot SnakeRaven: a 3D-printed patient-specific end-effector attached to the RAVEN II surgical platform. Both systems, most notably the visual predictive approach, operated successfully with robustness to a lack of information about the target. A video demonstrating the main results of this paper can be found via https://***/fiUM9qYdl1U © 2023, CC BY.

关键词： Remote control

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FIB-DIC ring-core measurement of the residual stress on HiPIMS W/Cu and Cr/Cu multilayer thin films

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Surface and Coatings Technology 2024年 483卷

作者： Zeng, Zhen-Yi Nguyen, Tra Anh Khoa Dang, Nhat Minh Wu, Xiu-Wei Chen, Terry Yuan-Feng Lin, Ming-Tzer Graduate Institute of Precision Engineering National Chung Hsing University Taichung402 Taiwan REMElab Faculty of Mechanical Engineering Ho Chi Minh City University of Technology and Education Ho Chi Minh70000 Viet Nam Taiwan Semiconductor Manufacturing Co. Ltd. HsinChu300 Taiwan Department of Mechanical Engineering National Cheng Kung University Tainan70101 Taiwan Industrial and Smart Technology Program Academy of Circular Economy National Chung Hsing University Nantou 540 Taiwan

Residual stress in multilayer coatings is a complex phenomenon influenced by layer number and thickness, layer and substrate materials, deposition technique, process parameters, and working pressure. It is crucial to realize these stresses because they have a significant impact on the performance and reliability of multilayer structures in their applications. The measurement of the residual stress on multilayer thin films locally and globally is crucial. This study employed ring-core milling residual stress measurement on the High-Power Impulse Magnetron Sputtering (HiPIMS) fabricated Tungsten/Copper (W/Cu) Chromium/Copper (Cr/Cu) multilayer thin films. The displacement transformation strain was analyzed using Focused Ion Beam (FIB) ring-core milling combined with Digital Image Correlation (DIC), and the strain stress transformation calibration coefficients were analyzed through Finite Element Method (FEM) to investigate the residual stress of the thin films layer by layer. The study results indicated that the hard thin films (W, Cr) were the main source of residual stress in the multilayer thin film structure, while the soft thin film (Cu) had a lower residual stress. Having Cu as the intermediate layer was found to be effective for controlling the residual stress of thin films. The hard thin films encapsulated by the soft thin films had smaller stress values than those with hard films on the surface. In addition, the study observes the stress gradient and distribution at different depths and locations on the sample to reveal process parameters to balance between the soft and hard thin films and could help to predict the location of the damage on the multilayer thin films caused by higher stress. © 2024 Elsevier B.V.

关键词： Multilayers

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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

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Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

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Influence of Crystallographic Orientation on the Deformation of Ag Nanoparticles During High-Speed Impact

SSRN

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SSRN 2022年

作者： Becker, Michael F. Kovar, Desiderio Chitrakar, T.V. The University of Texas at Austin AustinTX78712 United States Materials Science and Engineering Program Texas Materials Institute United States Department of Electrical and Computer Engineering United States Department of Mechanical Engineering Center for Additive Manufacturing and Design Innovation

Several related aerosol processes utilize high velocity impact of solid nanoparticles to produce nanograined films including the aerosol deposition method, jet molding, vacuum kinetic spraying, and micro cold spray. Although the influence of important variables such as particle size and particle impact velocity, on particle deformation and film formation have been previously explored, other variables have not been systematically explored. Because particles impact with a full range of orientations, an understanding of the effect of particle orientation is required to predict film microstructures. Molecular dynamics simulations were conducted to determine the influence of particle crystallographic orientation on the particle deformation upon impact and the resulting microstructure of the deposit. We show that the orientations that produce the largest overall particle deformation are not correlated to orientations where initiation of plastic deformation is easiest. Rather, the deformation is heterogenous and depends on the mechanisms responsible for deformation. Two deformation mechanisms are identified: 1) dislocation plasticity and 2) disordering followed by viscous flow. The fraction of the atoms in the impacting particle that experience permanent deformation by each mechanism is quantified as a function of particle orientation. The implications of the effects of particle crystallographic orientation on film microstructures are also discussed. © 2022, The Authors. All rights reserved.

关键词： Molecular dynamics

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