Ranga Komanduri
Affiliations: | Mechanical Engineering | Oklahoma State University, Stillwater, OK, United States |
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Mechanical EngineeringGoogle:
"Ranga Komanduri"Bio:
DOI: 10.1115/1.3677255 He then pursued his doctoral studies at Monash University in Australia under the guidance of R. H. Brown where the subject of his dissertation was the mechanics of chip segmentation in machining. After receiving his doctorate in 1972, ...
Children
Sign in to add traineeNagasubramaniyan Chandrasekaran | grad student | 2001 | Oklahoma State University |
Wen-Chen Lih | grad student | 2006 | Oklahoma State University |
Sony Varghese | grad student | 2006 | Oklahoma State University |
Milind Malshe | grad student | 2009 | Oklahoma State University |
Rutuparna Narulkar | grad student | 2009 | Oklahoma State University |
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Publications
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Cheng C, Bukkapatnam ST, Raff L, et al. (2016) Fast Monte Carlo Simulation-based Process Design and Planning for Carbon Nanotube Synthesis Procedia Manufacturing. 5: 1357-1368 |
Cheng C, Wang Z, Hung W, et al. (2015) Ultra-precision Machining Process Dynamics and Surface Quality Monitoring Procedia Manufacturing. 1: 607-618 |
Rao P, Bukkapatnam S, Beyca O, et al. (2014) Real-Time Identification of Incipient Surface Morphology Variations in Ultraprecision Machining Process Journal of Manufacturing Science and Engineering. 136 |
Rao PK, Bhushan MB, Bukkapatnam STS, et al. (2014) Process-machine interaction (PMI) modeling and monitoring of chemical mechanical planarization (CMP) process using wireless vibration sensors Ieee Transactions On Semiconductor Manufacturing. 27: 1-15 |
Ma J, Hanan JC, Komanduri R, et al. (2012) Simulation of the deformation mechanisms of bulk metallic glass (BMG) foam using the material point method Cmes - Computer Modeling in Engineering and Sciences. 86: 349-384 |
Cheng C, Bukkapatnam STS, Raff LM, et al. (2012) Towards control of carbon nanotube synthesis process using prediction-based fast monte carlo simulations Transactions of the North American Manufacturing Research Institution of Sme. 40: 371-378 |
Cheng C, Bukkapatnam STS, Raff LM, et al. (2012) Monte Carlo simulation of carbon nanotube nucleation and growth using nonlinear dynamic predictions Chemical Physics Letters. 530: 81-85 |
Pukrittayakamee A, Hagan M, Raff L, et al. (2011) Practical training framework for fitting a function and its derivatives. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 22: 936-47 |
Daphalapurkar NP, Wang F, Fu B, et al. (2011) Determination of Mechanical Properties of Sand Grains by Nanoindentation Experimental Mechanics. 51: 719-728 |
Malshe M, Raff LM, Hagan M, et al. (2010) Input vector optimization of feed-forward neural networks for fitting ab initio potential-energy databases. The Journal of Chemical Physics. 132: 204103 |