Influence of ICHTC correlations on the thermal characterization of façades using the quantitative internal infrared thermography method

Estimation of Dairy Cow Survival in the First Three Lactations for Different Culling Reasons Using the Kaplan–Meier Method

“…It aims to obtain clusters with cases (culling categories) that are as similar as possible to each other and as different as possible from cases (culling categories) belonging to other clusters [ 54 , 55 ]. This can be obtained by merging all possible cluster pairs and selecting, each time, the cluster with the minimum sum of squared deviations [ 56 , 57 , 58 , 59 ] using an approach based on the analysis of variance to determine the distance between clusters [ 55 , 60 , 61 , 62 , 63 ]. The measure of the distance between cases (culling categories) and the mean value of a given cluster was the error sum of squares ( EES ), given by the following formula [ 64 , 65 , 66 ]: where x i is the value of the variable that is a clustering criterion for the i th case, k is the number of cases (culling categories) within the cluster, is the mean value of this variable within the cluster.…”

Quality Control of the Thermal Properties of Superstructures in Accommodation Spaces in Naval Constructions

“…Given the influence of the equation used for the internal convective heat transfer coefficient, new studies should be conducted to determine the expression which is best adapted to this approach. In this regard, the approach through dimensionless numbers should be analyzed similarly to what has been done in the quantitative infrared thermography method in buildings [62]; (3) The progressive increase in the data filtering in the post-processing led to a decrease in the thermal transmittance value obtained, thus achieving more adjusted results in the heat flow meter method. It was also found that the criterion of data filtering could vary according to the layers of the superstructure, so that superstructures with a high thermal transmittance require a lower thermal gradient (greater than 2 • C), and those with a low thermal transmittance require a higher thermal gradient (greater than 5 • C); (4) The effect of placing the probes in zones affected by the thermal bridge could lead to obtaining non-representative results.…”

Estimation of the thermal resistance of a building wall with inverse techniques based on rapid active in situ measurements and white-box or ARX black-box models

“…Albatici et al [32] [33], Nardi et al [34] and Dall'O et al [35] used an empirical correlation based on the wind speed to estimate the heat transfer coefficient. Bienvenido et al thoroughly studied the influence of the correlation chosen for the internal [36] and external [37] coefficients on results of quantitative IRT methods. Finally, Ibos et al [38] implemented and compared three IRT methods to ISO 9869-1 [9] and pointed out the high dispersion results obtained.…”