Zobrazeno 1 - 10
of 94
pro vyhledávání: '"Pokharel, Reeju"'
Autor:
Scheinker, Alexander, Pokharel, Reeju
We present a physics-constrained neural network (PCNN) approach to solving Maxwell's equations for the electromagnetic fields of intense relativistic charged particle beams. We create a 3D convolutional PCNN to map time-varying current and charge den
Externí odkaz:
http://arxiv.org/abs/2301.13715
Autor:
Wang, Zhehui, Dujardin, Christophe, Freeman, Matthew S., Gehring, Amanda E., Hunter, James F., Lecoq, Paul, Liu, Wei, Melcher, Charles L., Morris, C. L., Nikl, Martin, Pilania, Ghanshyam, Pokharel, Reeju, Robertson, Daniel G., Rutstrom, Daniel J., Sjue, Sky K., Tremsin, Anton S., Watson, S. A., Wiggins, Brenden W., Winch, Nicola M., Zhuravleva, Mariya
Publikováno v:
IEEE Transactions on Nuclear Science ( Volume: 70, Issue: 7, July 2023), pp. 1244 - 1280
Scintillators are important materials for radiographic imaging and tomography (RadIT), when ionizing radiations are used to reveal internal structures of materials. Since its invention by R\"ontgen, RadIT now come in many modalities such as absorptio
Externí odkaz:
http://arxiv.org/abs/2212.10322
We have developed a machine learning-based interatomic potential (MLIP) for the quaternary MoNbTaW (R4) and quinary MoNbTaTiW (R5) high entropy alloys (HEAs). MLIPs enabled accurate high throughput calculations of elastic and mechanical properties of
Externí odkaz:
http://arxiv.org/abs/2201.08906
Autor:
Lee, Seunghyeon, Cho, Hansohl, Bronkhorst, Curt A., Pokharel, Reeju, Brown, Donald W., Clausen, Bjørn, Vogel, Sven C., Anghel, Veronica, Gray III, George T., Mayeur, Jason R.
Publikováno v:
Int. J. Plast., 163 (2023), Article 103529
A physically-informed continuum crystal plasticity model is presented to elucidate the deformation mechanisms and dislocation evolution in body-centered-cubic (bcc) tantalum widely used as a key structural material for mechanical and thermal extremes
Externí odkaz:
http://arxiv.org/abs/2109.15214
Autor:
Scheinker, Alexander, Pokharel, Reeju
We present a novel adaptive machine-learning based approach for reconstructing three-dimensional (3D) crystals from coherent diffraction imaging (CDI). We represent the crystals using spherical harmonics (SH) and generate corresponding synthetic diff
Externí odkaz:
http://arxiv.org/abs/2008.10094
Autor:
Pandey, Anup, Pokharel, Reeju
We present a novel machine learning based surrogate modeling method for predicting spatially resolved 3D microstructure evolution of polycrystalline materials under uniaxial tensile loading. Our approach is orders of magnitude faster than the existin
Externí odkaz:
http://arxiv.org/abs/2005.00951
Autor:
Pateras, Anastasios, Harder, Ross, Cha, Wonsuk, Gigax, Jonathan G., Baldwin, J. Kevin, Tischler, Jon, Xu, Ruqing, Liu, Wenjun, Erdmann, Mark J., Kalt, Robert, Sandberg, Richard L., Fensin, Saryu, Pokharel, Reeju
Measurement modalities in Bragg coherent diffraction imaging (BCDI) rely on finding signal from a single nanoscale crystal object, which satisfies the Bragg condition among a large number of arbitrarily oriented nanocrystals. However, even when the s
Externí odkaz:
http://arxiv.org/abs/2002.11859
Autor:
Pokharel, Reeju, Clausen, Bjørn, Savage, Daniel J., Zhang, Jianzhong, Vogel, Sven C., Beal, Roberta, Valdez, James, Anghel, Veronica, Brown, Donald W., Gray, George T., III
Publikováno v:
In International Journal of Plasticity September 2023 168
Akademický článek
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Autor:
Lee, Seunghyeon, Cho, Hansohl, Bronkhorst, Curt A., Pokharel, Reeju, Brown, Donald W., Clausen, Bjørn, Vogel, Sven C., Anghel, Veronica, Gray, George T., III, Mayeur, Jason R.
Publikováno v:
In International Journal of Plasticity April 2023 163