Virginia's research focuses on the estimation of thermal parameters (such as U-values, thermal resistance and thermal capacity, time shift, etc.) of real building elements by using experimental data collected during in-situ monitoring campaigns. Data are analysed using a novel dynamic method developed at the UCL Energy Institute.
The method consists of a lumped thermal mass model for model identification and an inverse Bayesian-based optimisation technique for parameters identification (i.e. thermal resistance and thermal capacity – and therefore U-values and other thermal quantities). This research attempts to overcome some of the limitations (e.g., long survey length, surveys restricted to the winter season) of current methods to estimate U-values from in-situ measurements.
The use of thermal parameters directly derived from in-situ measurement is of fundamental importance during simulations to bridge the performance gap between predicted and measured energy demand in the built environment. A number of studies show discrepancies between the U-values calculated from the literature and those estimated from real measurements, with important implications on the cost-effectiveness of retrofitting interventions or the achievement of the energy expectations of new constructions.
The use of thermal properties of building elements derived from monitoring campaigns also enables the characterisation of the actual thermal performance of the building element under study, accounting for the usage and state of conservation of the building. Therefore, it allows designers to provide for example customised energy-saving strategies or case-specific design of heating and cooling plants.