LoginBeing increasingly insulated, new buildings are more and more sensitive to variations of solar and internal gains.
Bibliographic database Airbase
AIRBASE is the Bibliographic Database of the AIVC. It contains publications and abstracts of articles related to energy efficient ventilation. Where possible, sufficient detail is supplied in the bibliographic details for users to trace and order the material via their own libraries. Topics include: ventilation strategies, design and retrofit methods, calculation techniques, standards and regulations, measurement methods, indoor air quality and energy implications etc. Entries are based on articles and reports published in journals, internal publications and research reports, produced both by university departments and by building research institutions throughout the world. AIRBASE has grown and evolved over many years (1979 to present day, over 22000 references and 16000 documents available online). For most of the references, the full document is also available online.
Access to the publications is free of charge.
This paper presents the first step modelling process of a smart building in order to ensure better energy management and human comfort in buildings.
Computational building performance simulation can be employed to develop various future solutions.
Building energy model reduction exchanges accuracy for improved simulation speed by reducing the number of dynamical equations.
To study the impact variations in input on output vari-ation (Sobol index) of building model, a stochastic model (time series) of variables is introduced.
This paper depicts a formulation of the global home electricity management problem, which consists in ad-justing the electric energy consumption to the cost and availability variations of the power supply.
In this paper, the authors present the Georgia Tech Uncertainty and Risk Analysis Workbench (GURA-W), a software toolkit that explicitly captures uncertainty about the physical properties of the building and the energy models used to predict its p
This paper evaluates the influence of windows in thermal energy performance of a social interest bulding in Dunas District - Pelotas/RS, analizing the performance for heating and cooling over the year. The original design was modeled and analized
The optimal building management models require predicting the behaviour of building systems. To achieve this goal, we propose to make available on the web remote computing services for the composition, simulation and optimization of equipments.
Architecture practice is on the front line directly applying best-case evidence-based solutions to conserve energy.