Basil M. Darras, Ph.D.
Affiliations: | 2008 | University of Kentucky, Lexington, KY |
Area:
Mechanical EngineeringGoogle:
"Basil Darras"Parents
Sign in to add mentorMarwan K. Khraisheh | grad student | 2008 | University of Kentucky | |
(Integrated thermo-mechanical investigations of friction stir processing of light weight alloys.) |
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Publications
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Saad MH, Jarrah OM, Nazzal MA, et al. (2020) Sustainability-based evaluation of Friction Stir Back Extrusion of seamless tubular shapes Journal of Cleaner Production. 267: 121972 |
Saad MH, Darras BM, Nazzal MA. (2020) Evaluation of Welding Processes Based on Multi-dimensional Sustainability Assessment Model International Journal of Precision Engineering and Manufacturing-Green Technology. 1-19 |
Hegab H, Kishawy HA, Darras B. (2019) Sustainable Cooling and Lubrication Strategies in Machining Processes: A Comparative Study Procedia Manufacturing. 33: 786-793 |
Saad MH, Nazzal MA, Darras BM. (2019) A general framework for sustainability assessment of manufacturing processes Ecological Indicators. 97: 211-224 |
Hegab H, Darras B, Kishawy HA. (2018) Sustainability Assessment of Machining with Nano-Cutting Fluids Procedia Manufacturing. 26: 245-254 |
Hegab HA, Darras B, Kishawy HA. (2018) Towards sustainability assessment of machining processes Journal of Cleaner Production. 170: 694-703 |
Naser A, Darras B. (2017) Micro-hardness prediction of friction stir processed magnesium alloy via response surface methodology Multidiscipline Modeling in Materials and Structures. 13: 377-390 |
Naser AZ, Darras BM. (2017) Experimental investigation of Mg/SiC composite fabrication via friction stir processing The International Journal of Advanced Manufacturing Technology. 91: 781-790 |
Darras BM, Abed FH, Abdul-Latif A, et al. (2015) Experimental Investigation of Deformation in 5083 Marine-Grade Aluminum Alloy at Elevated Temperatures Journal of Materials Engineering and Performance. 24: 1663-1668 |
Darras BM, Deiab IM, Naser A. (2014) Prediction of Friction Stir Processed AZ31 Magnesium Alloy Micro-Hardness Using Artificial Neural Networks Advanced Materials Research. 1043: 91-95 |