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akaturk Akademik ölçüm

Makale detayı · 2019 · article

Prediction of Round Jet Flow with Artificial Neural Networks

ISSN0587-4246
YÖKSİS OpenAlex Açık erişim · diamond
Yıl2019
Atıf1OpenAlex
Yüzdelik%7,4
FWCI0,01,00 = dünya ortalaması
Scopus (SJR)Q3
WoS (JCR)Q4

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıACTA PHYSICA POLONICA A
  • Katalog eşleşmesi (ISSN)Acta Physica Polonica A
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

In this study, an artificial neural networks model was established by using experimental measurement values at low speed subsonic wind tunnel of which length was 75 cm and experiment test section was 32 cm × 32 cm, and model results were compared with experimental values and then, the prediction was made for the unmeasured tunnel stream values.In the wind tunnel, when the jet velocity was 25 m/s, four tunnel velocities, 0, 5, 10, and 20 m/s were used.At the four measurement stations; x/D = 0.3, x/D = 12.5, x/D = 31.2,and x/D = 50, experimental measurements were made by using hot wire anemometer.Plain circular jet flows at x/D = 0.3 and x/D = 50 stations with average tunnel flow velocities of 7.5 m/s and 15 m/s were studied by using artificial neural networks.The data was obtained and evaluated by graphics.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

1atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yazarlar

3
  1. UĞUR KESEN MARMARA ÜNİVERSİTESİ 1
  2. TUGAY ŞİŞMAN MARMARA ÜNİVERSİTESİ 2
  3. İLKNUR ÇAVUŞOĞLU MARMARA ÜNİVERSİTESİ 3