ALBERT

Description: The EU is committed to achieve ambitious energy efficiency and CO2 reduction targets. Regarding improving the energy performance of the building stock, detailed building related energy data made accessible by means of GIS are crucial. For this purpose, geo-referenced data from Energy Performance Certificates (EPC) according to the Energy Performance of Buildings Directive is of central importance, in order to facilitate decision-making about large-scale renovation projects and developing targeted products and services. The ENERFUND project developed a method and subsequently an internet based tool making use of EPC data from 13 EU member states as well as other open-source data (such as renovation costs), thus clearly demonstrating the feasibility and usefulness of this approach. However, also technical challenges and legal barriers were encountered, such as a lack of data and varying data specifications depending on the national transposition of the European Directive, and different interpretation of specific clauses of the General Data Protection Regulation depending on EU member states’ societal norms. Recommendations include the development of guidance notes to be issued by the responsible EU bodies to specify and harmonize data for mandatory public access, to ensure the effective implementation of energy efficiency and CO2 reduction policies in the EU’s building sector.

Description: In this work, a large deformation, non-linear semi-analytical model for an all-elastomer, capacitive tactile unit-sensor is developed. The model is capable of predicting the response of such sensors over their entire sensing range under the application of normal forces. In doing so the finite flat punch indentation model developed earlier is integrated with a capacitance model to predict the change-in-capacitance as a function of applied normal forces. The empirical change-in-capacitance expression, based on the parallel plate capacitance model, is developed to account for the fringe field and saturation effects. The elastomeric layer used as a substrate in these sensors is modeled as an incompressible, non-linear, hyperelastic material. More specifically, the two term Mooney-Rivlin strain energy function is used as a constitutive response to relate the stresses and strains. The developed model assumes both geometrical as well as material non-linearity. Based on the related experimental work presented elsewhere, the inverse analysis, combining finite element (FE) modeling and non-linear optimization, is used to obtain the Mooney-Rivlin material parameters. Finally, to validate the model developed herein the model predictions are compared to the experimental results obtained elsewhere for four different tactile sensors. Great agreements are found to exist between the two which shows the model capabilities in capturing the response of these sensors. The model and methodologies developed in this work, may also help advancing bio-material studies in the determination of biological tissue properties.