Precision Engineering ​Research Group

Yılmaz Laboratory


Recent news on the research group

November '23: Efforts for SGDs x Sustainability @ Sophia Univ.

Our research theme on friction reduction phenomenon in machine elements was included in the FY22-23 SDGs Report of Sophia University. The report can be accessed through the following link. See report

October '23: United Nations Weeks Symposium  

Professor Yilmaz attended United Nations Weeks Symposium “Bringing science and engineering knowledge on to the world”, along with Science Entertainer Miki Igarashi

August '23: Professor Yilmaz was invited to the Turkish Embassy

Professor Yilmaz, along with other academics who are continuing their research in Japan, were invited for an idea exchange meeting with Professor Hisakazu Mihara (provost at Turkish-Japanese Science and Technology University (TJU)). 

July '23: A new journal is published in Scientific Reports

Dr. Yilmaz first authored a new journal about ammonia/gasoline co-combustion. Follow the link for the open access paper. Click here

July '23: Professor Tanaka and Professor Yilmaz will be visiting Sabanci University

Professor Tanaka and Professor Yilmaz will be heading to Istanbul, Turkey to have preliminary meetings about academic & student exchange between Sophia University and Sabanci University. The meeting will take place on August 15th.

July '23: Professor Yilmaz will chair the session "Surface Texturing 1" at ITC'23, in Fukuoka Japan.

Professor Yilmaz will be the chair for the session called "Surface Texturing 1" at Room E. The session will take place on Wednesday September 27th, 2023. Link for the schedule: Click here

About the Research Group

Precision Engineering Research Group consits two distinct laboratories (Tanaka & Yılmaz labs), which investigate mechanics and physics of material surface phenomena at different length scales ranging from the nano to macroscopic scales. Our research activities focus a wide range of topics including tribology (e.g. friction, wear, lubrication), manufacturing  of CFRP materials (e.g. machining and molding/forming - PI Prof. Tanaka*) ​incorporated with CAD・CAE・CAM tools. The group conducts experiments and numerical simulations to translate scientific understanding into novel manufacturing methods & mathematical models.


- Investiation of micro texturing effect on reduction of friction/wear phenomena in Ammonia fueled Internal Combustion Engines


- Evaluation of utilizing Electrical Discharge Machining to create micro-scale textures on sliding surfaces

Deep Learning

- Development of heat transfer models based on in-house built Deep Learning frameworks 

Molding/Forming of CFRP*

- Incremental forming of CFRTP on the basis of 3D-CAD data
- Development of press molding preform design and fabrication method with open-up diagram for CFRP

CFRP Machining*

- Optimization of CFRTP turning process
- Evaluation of machinability for CFRP milling process 

Surface finishing*

- Analytical study of diamond tip burnishing process
- Development of in-process temperature measurement methodof burnishing by CVD tools

Research Outline

Our modeling and experimental methodology aim to contribute to the advancement of general knowledge in engine tribology & engine/battery cooling systems. An in-house built tribological experimental apparatus along with Computational Fluid Dynamics simulation results are being used for the development of next-generation ICEs (NG-ICEs), which are fueled by ammonia. From the tribological perspective, engine Piston - cylinder Liner Interaction (PLI) accounts for roughly 10% of total mechanical losses in a conventional ICE. By decreasing these losses, created during the reciprocating motion of the piston, NG-ICEs can benefit greatly to further improving their efficiencies, enabling "greener" transportation.
We are also focusing on the effect of surface characteristics on heat transfer enhancement due to nucleate boiling phenomenon by altering bubble generation frequency from a heated surface. Electrical Discharge Machining (EDM) method is being adapted to create functional surfaces that can enhance heat transfer mechanism. The know-how will be used to minimize the size and the weight of the conventional cooling systems for next-generation engines/batteries. 
In addition, utilization of deep learning models is being to further improve our understanding on these topics and further improve the adaptability of these technologies.  

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