Empirical modeling between degree days and optimum insulation thickness for external wall

Autor: Cihad Fidan, Umut Ercan, Hakan Karakaya, Mehmet Ali Kallioğlu, Ali Serkan Avcı
Přispěvatelé: Batman Üniversitesi Mühendislik - Mimarlık Fakültesi Makine Mühendisliği Bölümü
Rok vydání: 2019
Předmět:
Zdroj: Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 42:1314-1334
ISSN: 1556-7230
1556-7036
DOI: 10.1080/15567036.2019.1651797
Popis: Insulating is the most effective method that is used to save energy in buildings. Samples from cities from different climatic zones from TS 825 (Turkey) first. Optimum insulation thickness () analysis is based on two types of insulating and four different fuels (natural gas, coal, fuel oil and electric) of related cities. Cost accounts, payback period and CO2-SO2 emission calculations were performed based on these analyses. Second of all, the relationship between a number of degree day (NDD) and optimum insulation thickness () was developed by linear, quadratic and cubic correlations. Thirty different mathematical correlations based on different fuel types by using XPS and EPS insulating materials. Twenty-four of these models that were developed were generated peculiar to the fuel type; six of them were generated based on average insulation thickness. R2 values of related correlations are between 0.9989 most and 0.9952 at least as well as it is pretty close to (R ≤ 1) one value. The model among these models is the cubic mathematical model that gives the best average value. a = 0.0036, b = 5E-05, c = – 7E-09 and d = 6E-13 are the values for XPS material. Following values are for EPS material; a = 0.0028, b = 5E-13, c = – 7E-09 and d = 4E-05. R2 determination coefficient of both two equations is pretty close to 0.9989 and 1; the models obtained are less-than-stellar. Optimum insulation thickness of the area can be known based on the type of material via the number of degree day without the need for long analyses. According to the R2 values, the use of all models is recommended for academic and industrial users.
Databáze: OpenAIRE