Samsonenko O. Energy and environmental efficiency increasing at domestic refrigerator manufacturing

Українська версія

Thesis for the degree of Candidate of Sciences (CSc)

State registration number

0408U002685

Thesis Registration Form

0408U002685.pdf

Applicant for

Specialization

  • 05.05.14 - Холодильна, вакуумна та компресорна техніка, системи кондиціювання

12-05-2008

Specialized Academic Board

Д. 41.087.01

Essay

The research results directed to minimize the greenhouse gases emission at domestic refrigerator manufacturing are given In is proven the main contribution into Life Cycle Climatic Performance (LCCP) provides the indirect effects of global warming as a result of row material extracting, manufacturing? Exploitation Artificial neural network (ANN) models are proposed to present with high accuracy the results of calorimetric tests at different external conditions. ANN as a selection criterion of quality production at domestic refrigeration temperature testing is used. The application of ANN allows to decrease time and number of acceptance testing at serial domestic refrigerator manufacturing.

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Files

aref.doc.doc

dis.doc.doc

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