Shear viscosities from the Chapman-Enskog and the relaxation time approaches A Wiranata, M Prakash Physical Review C 85 (5), 054908, 2012 | 76 | 2012 |
Shear viscosity of hadrons with K-matrix cross sections A Wiranata, V Koch, M Prakash, XN Wang Physical Review C 88 (4), 044917, 2013 | 38 | 2013 |
Comparison of viscosities from the Chapman-Enskog and relaxation time methods A Wiranata, M Prakash, P Chakraborty Open Physics 10 (6), 1349-1351, 2012 | 22 | 2012 |
Bulk viscosity of interacting hadrons A Wiranata, M Prakash Nuclear Physics A 830 (1-4), 219c-222c, 2009 | 20 | 2009 |
Hadronic Shear Viscosity: A Comparison between the Green-Kubo and Chapmann Enskog Methods NDA Wiranata J. Phys.: Conf. Ser. 535 012018 535, 012018, 2014 | 16 | 2014 |
Shear viscosity of a multi-component hadronic system A Wiranata, V Koch, M Prakash, XN Wang Journal of Physics: Conference Series 509 (1), 012049, 2014 | 12 | 2014 |
The η/s of hadrons out of chemical equilibrium A Wiranata, M Prakash, P Huovinen, V Koch, XN Wang Journal of Physics: Conference Series 535 (1), 012017, 2014 | 6 | 2014 |
Production of charged ρ meson in bottom hadron charmed decays and the effect of the finite width correction of the ρ meson ZH Zhang, YD Yang, XH Guo, G Lü, A Wiranata The European Physical Journal C 73 (9), 2555, 2013 | 1 | 2013 |
Improving part failure prediction performance through targeted prediction delays D Cherry, ND Venkata, A Wiranata, D Siddall, P Hegde https://www.tdcommons.org/cgi/viewcontent.cgi?article=4117&context=dpubs_series, 2020 | | 2020 |
A framework to monitor a failure predictive machine learning model performance with non-failure data M Bhuyar, S Bradburn, P Hegde, D Siddall, K Ferguson, A Wiranata https://www.tdcommons.org/cgi/viewcontent.cgi?article=4112&context …, 2020 | | 2020 |
A Failure Predictive Algorithm Using Sequence of Event Codes with a Deep Learning Model (LSTM) SV Pelt, F Arca, K Hirschey, M Bhuyar, A Wiranata tdcommons.org 2894 (https://www.tdcommons.org/dpubs_series/), https://www …, 2020 | | 2020 |
Critical Request for Proposals (RFPs) Requirement Insight Engine (CaRRIE) A Wiranata, J Bansal tdcommons.org 2688 (https://www.tdcommons.org/dpubs_series/), https://www …, 2019 | | 2019 |
Multi‐factor Adaptive Machine Learning Evaluation in Production Environments A Wiranata, D Siddal, DD Cherry tdcommons.org 1694 (1694), https://www.tdcommons.org/dpubs_series/1, 2018 | | 2018 |
Shear Viscosities of Hadrons with K-Matrix Cross Sections A Wiranata, V Koch, XN Wang, M Prakash Bulletin of the American Physical Society 58, 2013 | | 2013 |
Transport Coefficients of Interacting Hadrons A Wiranata Ohio University, 2011 | | 2011 |