T. Kıvak

Mechanical Engineering · 2012–2021

A researcher in the Science corpus: 7 papers; trusts 20 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Mechanical Engineering — 100 citations into it; #2,137 of 8,300 by trust here, #3,348 by citations
• Electrical and Electronic Engineering — 57 citations into it; #4,540 of 16,539 by trust here, #6,558 by citations
• Biomedical Engineering — 46 citations into it; #3,589 of 10,734 by trust here, #6,166 by citations
• Mechanics of Materials — 17 citations into it

Whom T. Kıvak trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. K. Palanikumar
2. M. Nalbant
3. Jenn-Tsong Horng
4. H. Gökkaya
5. Mustafa Kurt
6. A. Jawaid
7. B. Ozcelik
8. Tugrul Özel
9. Ilhan Asiltürk
10. G. Sur

Who trusts T. Kıvak overall

1. Ș. Karabulut
2. M. Sarıkaya
3. Ç. Yıldırım

Papers from T. Kıvak's perspective

Ordered by how strongly the researchers T. Kıvak trusts endorse each paper. Same corpus, a different order for every researcher.

1. Development of Empirical Models for Surface Roughness Prediction in Finish Turning
2. New cooling approach and tool life improvement in cryogenic machining of titanium alloy Ti-6Al-4V
3. Determining the influence of cutting fluids on tool wear and surface roughness during turning of AISI 304 austenitic stainless steel
4. Cutting temperature, tool wear, surface roughness and dimensional deviation in turning AISI-4037 steel under cryogenic condition
5. Dry machining: Machining of the future
6. Experimental evaluation of the lubrication properties of the wheel/workpiece interface in minimum quantity lubrication (MQL) grinding using different types of vegetable oils
7. Influence of Ranque-Hilsch vortex tube and nitrogen gas assisted MQL in precision turning of Al 6061-T6 (Precision engineering)
8. Sustainability assessment associated with surface roughness and power consumption characteristics in nanofluid MQL-assisted turning of AISI 1045 steel (The International Journal of Advanced Manufacturing Technology)
9. Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks
10. Analysis of tool wear patterns in finishing turning of Inconel 718

Their papers

• Performances of different eco-friendly nanofluid lubricants in the milling of Inconel X-750 superalloy (2019) — 155 citations
• Optimization of surface roughness and flank wear using the Taguchi method in milling of Hadfield steel with PVD and CVD coated inserts (2014) — 411 citations
• Machinability performance of nickel alloy X-750 with SiAlON ceramic cutting tool under dry, MQL and hBN mixed nanofluid-MQL (2021) — 181 citations
• Evaluation of tool wear, surface roughness/topography and chip morphology when machining of Ni-based alloy 625 under MQL, cryogenic cooling and CryoMQL (2020) — 275 citations
• Investigation of the influence of MWCNTs mixed nanofluid on the machinability characteristics of PH 13-8 Mo stainless steel (2020) — 138 citations
• The effect of addition of hBN nanoparticles to nanofluid-MQL on tool wear patterns, tool life, roughness and temperature in turning of Ni-based Inconel 625 (2019) — 333 citations
• Taguchi method based optimisation of drilling parameters in drilling of AISI 316 steel with PVD monolayer and multilayer coated HSS drills (2012) — 162 citations