The influence of machining parameters using cryogenic cooling system

2021 ◽  
Author(s):  
Arie Yudha Budiman ◽  
Amrifan Saladin Mohruni ◽  
Safian Sharif ◽  
Aneka Firdaus ◽  
Bima Satria Nugraha
Keyword(s):  
Cooling System ◽  
Cryogenic Cooling ◽  
Machining Parameters

Design and Test Results of a Cryogenic Cooling System for a 25-T Cryogen-Free Superconducting Magnet

2017 ◽  
Vol 27 (4) ◽  
pp. 1-5 ◽  
Author(s):  
Masahiko Takahashi ◽  
Satoshi Awaji ◽  
Hidetoshi Oguro ◽  
Yuji Tsuchiya ◽  
Sadanori Iwai ◽  
...  
Keyword(s):  
Cooling System ◽  
Superconducting Magnet ◽  
Cryogenic Cooling ◽  
Test Results

scholarly journals Surface Roughness Prediction using Machine Learning Algorithms while Turning under Different Lubrication Conditions

2021 ◽  
Vol 2070 (1) ◽  
pp. 012243
Author(s):  
A Varun ◽  
Mechiri Sandeep Kumar ◽  
Karthik Murumulla ◽  
Tatiparthi Sathvik
Keyword(s):  
Machine Learning ◽  
Surface Roughness ◽  
Small Businesses ◽  
Cooling System ◽  
Gaussian Process Regression ◽  
Learning Model ◽  
Machine Learning Algorithms ◽  
Nano Particles ◽  
Machining Parameters ◽  
Machine Learning Model

Abstract Lathe turning is one of the manufacturing sector’s most basic and important operations. From small businesses to large corporations, optimising machining operations is a key priority. Cooling systems in machining have an important role in determining surface roughness. The machine learning model under discussion assesses the surface roughness of lathe turned surfaces for a variety of materials. To forecast surface roughness, the machine learning model is trained using machining parameters, material characteristics, tool properties, and cooling conditions such as dry, MQL, and hybrid nano particle mixed MQL. Mixing with appropriate nano particles such as copper, aluminium, etc. may significantly improve cooling system heat absorption. To create a data collection for training and testing the model, many standard journals and publications are used. Surface roughness varies with work parameter combinations. In MATLAB, a Gaussian Process Regression (GPR) method will be utilised to construct a model and predict surface roughness. To improve prediction outcomes and make the model more flexible, data from a variety of publications was included. Some characteristics were omitted in order to minimise data noise. Different statistical factors will be explored to predict surface roughness.

scholarly journals Numerical Study of the Effects of Injection Fluctuations on Liquid Nitrogen Spray Cooling

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 564 ◽  
Author(s):  
Rong Xue ◽  
Yixiao Ruan ◽  
Xiufang Liu ◽  
Liang Chen ◽  
Liqiang Liu ◽  
...  
Keyword(s):  
Liquid Nitrogen ◽  
Cooling System ◽  
Numerical Study ◽  
Spray Cooling ◽  
Volume Averaging ◽  
Cryogenic Cooling ◽  
Droplet Distribution ◽  
Cooling Effects ◽  
Spray Field ◽  
Lower Temperature

Spray cooling with liquid nitrogen is increasingly utilized as an efficient approach to achieve cryogenic cooling. Effects of injection mass flow rate fluctuations on the evaporation, temperature distribution, and droplet distribution of a spray field were examined by employing a validated Computational Fluid Dynamics (CFD) numerical model. The numerical results indicated that injection fluctuations enhanced the volume-averaging turbulent kinetic energy and promoted the evaporation of the whole spray field. The strengthened mass and heat transfer between the liquid nitrogen droplets and the surrounding vapor created by the fluctuating injection led to a lower temperature of the whole volume. A relatively smaller droplet size and a more inhomogeneous droplet distribution were obtained under the unsteady inlet. The changes of the frequency and the amplitude of the fluctuations had little effects on the overall spray development. The results could enrich the knowledge of the relation between the inevitable fluctuations and the overall spray development and the cooling performance in a practical spray cooling system with cryogenic fluids.

Thermal Effects on the Structure and Characteristics of Plasma Sprayed Self-Fluxing Alloys

2000 ◽  
Author(s):  
G. Bertrand ◽  
C. Malavolta ◽  
F. Tourenne ◽  
B. Hansz ◽  
C. Coddet ◽  
...  
Keyword(s):  
Plasma Spray ◽  
Mechanical Characteristics ◽  
Cooling System ◽  
Thermal Spraying ◽  
Heating System ◽  
Cryogenic Cooling ◽  
Precise Control ◽  
Heating And Cooling ◽  
Mechanical Deformations ◽  
Plasma Sprayed

Abstract In general, thermal spraying involves high temperatures that can be deleterious for the microstructure and deformation of the substrate. As a consequence, the use of a cooling system during spraying is often necessary. Meanwhile, in some cases, a too low surface temperature can induce a loss of properties, in particular concerning adherence and coating density. Therefore, it would be sometimes interesting to combine pre-heating and cooling stages with the plasma spray. A specific process, named HeatCool, was developed and patented to ensure a precise control of the temperature at the spraying location. The present work was focused on the study of the influence of pre-heating and cryogenic cooling conditions on the microstructure and mechanical characteristics of NiCrFeBSi self-fluxing alloy deposited by d.c. plasma spray technique. Firstly, a comparison between air and CO2 cooling was conducted to assess the efficiency corresponding to the specific use of cryogenic CO2. The main characteristics studied were the microhardness, roughness, porosity, mechanical deformations, morphology and crystallographic structures. Optimising the cooling methods and conditions combined with the process parameters improved microhardness of the plasma sprayed metal alloy and induced lower strain deformation of the substrate. Secondly, the pre-heating system was added to the device and the HeatCool process was evaluated. The process was demonstrated to be an efficient mean to enhance the structural and mechanical characteristics of coatings made of self-fluxing alloy.

Cryogenic cooling system of HTS transformers by natural convection of subcooled liquid nitrogen

Cryogenics ◽  
2003 ◽  
Vol 43 (10-11) ◽  
pp. 589-596 ◽  
Author(s):  
Ho-Myung Chang ◽  
Yeon Suk Choi ◽  
Steven W. Van Sciver ◽  
Kyeong Dal Choi
Keyword(s):  
Natural Convection ◽  
Liquid Nitrogen ◽  
Cooling System ◽  
Cryogenic Cooling ◽  
Subcooled Liquid

scholarly journals Development of Universal Exergy Analysis to the Selection of Cryogenic Cooling System

2017 ◽  
Vol 108 ◽  
pp. 11004
Author(s):  
S. V. Zaika ◽  
D. A. Uglanov ◽  
S. S. Dostovalova
Keyword(s):  
Exergy Analysis ◽  
Cooling System ◽  
Cryogenic Cooling ◽  
Selection Of
Sign in / Sign up

Export Citation Format

Share Document