Improving rational thermal comfort prediction by using subpopulation characteristics: A case study at Hermitage Amsterdam.

This study aims to improve the prediction accuracy of the rational standard thermal comfort model, known as the Predicted Mean Vote (PMV) model, by (1) calibrating one of its input variables "metabolic rate," and (2) extending it by explicitly incorporating the variable running mean outdoor temperature (RMOT) that relates to adaptive thermal comfort. The analysis was performed with survey data ( = 1121) and climate measurements of the indoor and outdoor environment from a one year-long case study undertaken at Hermitage Amsterdam museum in the Netherlands. The PMVs were calculated for 35 survey days using (1) an assumed metabolic rate, (2) a calibrated metabolic rate found by fitting the PMVs to the thermal sensation votes (TSVs) of each respondent using an optimization routine, and (3) extending the PMV model by including the RMOT.

Pigment Degradation in Oil Paint Induced by Indoor Climate: Comparison of Visual and Computational Backscattered Electron Images.

For the first time the degradation of lead white pigment in mature oil paint has been used as an internal marker for the degree of saponification and hence chemical degradation of oil paint. Computational image analysis of the backscattered electron images quantified the degree of the intact lead white pigment versus the nonpigmented and lead-rich areas (degraded lead white) in the paint layers. This new methodology was applied to a series of paint samples taken from four painted wall hangings (dated 1778), which makes it possible to study the influence of indoor climate on chemical degradation of aged oil paintings.