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Journals / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi / 2006 / Cilt: 21 - Sayı: 2

MODELING OF THERMODYNAMIC PROPERTIES OF REFRIGERANT R410A WITH ARTIFICIAL NEURAL NETWORKS

R410A SOĞUTUCU AKIŞKANININ TERMODİNAMİK ÖZELLİKLERİNİN YAPAY SİNİR AĞLARI METODUYLA MODELLENMESİ

Önder KIZILKAN
Arzu ŞENCAN
Ali YAKUT
Pages
395–400
Publication Date
2013-03-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With these formulations, faster and simple solutions can be obtained.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, thermodynamic properties as saturation pressure, saturated liquid enthalpy and entropy,superheated vapor enthalpy and temperature of R410a refrigerant, which are harmful to the ozone layer, used inthe vapor compression refrigeration systems were determined with Artificial Neural Network (ANN) model.Data of thermodynamic properties used in the study were obtained from empirical and experimental data that isavailable in the literature.
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Key Findings & Data:In order to determine thermodynamic properties of refrigerant for all spans, newformulations were derived by ANN model which was very well trained.
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Conclusion & Impact:With these formulations, faster and simple solutions can be obtained.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay sinir ağları · buhar sıkıştırmalı sistemler · R410a

Abstract

In this study, thermodynamic properties as saturation pressure, saturated liquid enthalpy and entropy,superheated vapor enthalpy and temperature of R410a refrigerant, which are harmful to the ozone layer, used inthe vapor compression refrigeration systems were determined with Artificial Neural Network (ANN) model.Data of thermodynamic properties used in the study were obtained from empirical and experimental data that isavailable in the literature. In order to determine thermodynamic properties of refrigerant for all spans, newformulations were derived by ANN model which was very well trained. These formulations were derived withusing weights and bias values of network. With these formulations, faster and simple solutions can be obtained.

Özet

Bu çalışmada, buhar sıkıştırmalı soğutma çevriminde kullanılan ve ozon tabakasına zararı olmayan çevre dostuR410a soğutucu akışkanının doyma basıncı, sıvı ve buhar entalpileri, entropileri, kızgın buhar entalpisi ve sıcaklığı gibi termodinamik özellikleri Yapay Sinir Ağları (YSA) modeliyle belirlenmiştir. Bu modelde kullanılan veriler, literatürde mevcut olan ampirik ve deneysel veriler yardımıyla elde edilmiştir. Çalışmada; çok iyi eğitilmiş bir YSA modeliyle, istenilen her aralıkta soğutucu akışkanın termodinamik özelliklerinin tespiti için yeni formülasyonlar türetilmiştir. Bu formülasyonlar, ağ modeline ait ağırlık ve bias değerleri kullanılarak elde edilmiştir. Modelden elde edilen denklemlerle çok daha hızlı ve basit çözümlere ulaşılmıştır.

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Cite This Article

KIZILKAN, Ö., ŞENCAN, A., YAKUT, A. (2013). MODELING OF THERMODYNAMIC PROPERTIES OF REFRIGERANT R410A WITH ARTIFICIAL NEURAL NETWORKS. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 21 - Sayı: 2, 395–400. https://ajindex.com/articles/21142

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