Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Sean P. Donegan"'
Autor:
Nicholas Tacca, Collin Dunlap, Sean P. Donegan, James O. Hardin, Eric Meyers, Michael J. Darrow, Samuel Colachis IV, Andrew Gillman, David A. Friedenberg
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract High-density electromyography (HD-EMG) can provide a natural interface to enhance human–computer interaction (HCI). This study aims to demonstrate the capability of a novel HD-EMG forearm sleeve equipped with up to 150 electrodes to captur
Externí odkaz:
https://doaj.org/article/ae72f5b053ad4b9091276bc63b9677da
Autor:
Nicolò Maria della Ventura, Connie Q. Dong, Sara A. Messina, Rachel R. Collino, Glenn H. Balbus, Sean P. Donegan, Jonathan D. Miller, Daniel S. Gianola, Matthew R. Begley
Publikováno v:
Materials & Design, Vol 238, Iss , Pp 112695- (2024)
The effective design of metallic metamaterials, characterized by interconnected struts or 'lattices,' hinges on the ability to predict strut and strut intersection ('node') responses. This is critical for predicting the macroscopic properties of stru
Externí odkaz:
https://doaj.org/article/55abccd9f25e414e9b20871a6b970d04
Autor:
Samuel M. Miller, Sean W. Donegan, Niesha Voigt, Adam E.M. Eltorai, Alan H. Daniels, Teena Shetty, Joseph Nguyen, Jason T. Machan
Publikováno v:
Orthopedic Reviews, Vol 11, Iss 1 (2019)
Transcranial motor-evoked potentials (TcMEPs) are used to monitor the descending motor pathway during scoliosis surgery. By comparing potentials before and after correction, surgeons may prevent postoperative functional loss in distal muscles. There
Externí odkaz:
https://doaj.org/article/1b8187590fae44728ffee3215b65342e
Publikováno v:
JOM. 73:3250-3262
While metal additive manufacturing (AM) offers significant benefits, such as design flexibility and lead time improvements, over traditional manufacturing approaches, the complexity of metal AM processing presents a challenge for understanding and ex
Autor:
Megna N. Shah, David B. Menasche, Peter Kenesei, Jun-Sang Park, Sean P. Donegan, Paul A. Shade, Mark Obstalecki, William D. Musinski, Joel V. Bernier
Publikováno v:
Integrating Materials and Manufacturing Innovation. 10:338-347
We describe 3D characterization of an additively manufactured Inconel 625 nickel-base superalloy specimen conducted during a uniaxial tension test using a suite of nondestructive x-ray techniques. High-energy diffraction microscopy in both near- and
Autor:
Megna N. Shah, Sean P. Donegan, Michael G. Chapman, J. Michael Scott, David B. Menasche, Paul A. Shade, Michael D. Uchic
Publikováno v:
Integrating Materials and Manufacturing Innovation. 10:129-141
High-energy diffraction microscopy (HEDM) in-situ mechanical testing experiments offer unique insight into the evolving deformation state within polycrystalline materials. These experiments rely on a sophisticated analysis of the diffraction data to
Autor:
Matt McCormick, Dennis M. Dimiduk, Dženan Zukić, Michael A. Jackson, Sean P. Donegan, Michael A. Groeber
Publikováno v:
Integrating Materials and Manufacturing Innovation. 10:115-124
Stitching partially overlapping image tiles into a montage is a common requirement for materials microscopy. We developed ITKMontage, a new module for the open-source Insight Toolkit (ITK), capable of robustly and quickly generating extremely large,
Publikováno v:
Additive Manufacturing. 25:485-498
Significant attention has been focused on modeling of metallic additive manufacturing (AM) processes, with the initial aim of predicting local thermal history, and ultimately structure and properties. Existing models range greatly in physical complex
Publikováno v:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIX.
Recent advances in the development of artificial intelligence and machine learning (AI/ML) techniques have shown great potential for enhancing the modeling and characterization of materials science issues. AI/ML techniques revolutionize big data anal
Autor:
Michael A. Groeber, Sean P. Donegan
Publikováno v:
Integrated Computational Materials Engineering (ICME) ISBN: 9783030405618
Integrated computational materials engineering (ICME) represents a grand challenge within materials research and development. Effective ICME involves coupling materials characterization and experimentation with simulation tools to produce a holistic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d63843ebd615fa117b8ef62297b3a106
https://doi.org/10.1007/978-3-030-40562-5_2
https://doi.org/10.1007/978-3-030-40562-5_2