Performance prediction methods for screw compressors

Author(s):  
M.A. Heiyanthuduwage ◽  
S. Mounoury ◽  
A. Kovacevic
Energy ◽  
2020 ◽  
Vol 213 ◽  
pp. 119071
Author(s):  
Yongju Jeong ◽  
Seongmin Son ◽  
Seong Kuk Cho ◽  
Seungjoon Baik ◽  
Jeong Ik Lee

1968 ◽  
Vol 13 (2) ◽  
pp. 1-26 ◽  
Author(s):  
David S. Jenney ◽  
John H. Olson ◽  
Anton John Landgrebe

1974 ◽  
Author(s):  
Karl L. Kirkman

A program of Experiments with a series of four geometrically similar yacht hull models was conducted in the HYDRONAUTICS’ Ship Model Basin with the aim of improving engineering methods for model/full-scale correlation. The paper presents a brief review of the background of existing hydrodynamic performance prediction methods, outlines a number of scaling problems, and presents results from the family of models tested.


2001 ◽  
Author(s):  
Thomas Poorman ◽  
Joseph Bielecki ◽  
Mojun Chang ◽  
Sharad Belsare ◽  
Fadi El-Khatib

1989 ◽  
Vol 4 (03) ◽  
pp. 311-318 ◽  
Author(s):  
A.S. Emanuel ◽  
G.K. Alameda ◽  
R.A. Behrens ◽  
T.A. Hewett

Author(s):  
M. Karthika ◽  
T. Meyyappan

In the today's industrial world, every company’s growth is depends on their employees. The company achievements are completely based on the employees in the organization. The employees’ performances are measured by the targets and achievements. But some external and internal factors affect the employees’ goals and achievements. Hence, the company has to find the performance of every employee and make proper solutions to improve the performance. This research work proposes a fully automated framework which can perform deep analysis of employees’ performance and job fitness using data mining and prediction methods.


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