English

This study presents a theoretical method that can quickly and accurately identify the locations and strengths of multiple constant contaminant sources indoors by using a single or a limited number of ideal sensors. The method was numerically demonstrated and validated by case studies of sixteen scenarios of contaminant releases in a three-dimensional office. The effects of the number and positions of sensors used, total sampling time, and sampling intervals on the performance of identification were thoroughly studied.

This paper presents a novel methodology that aims at optimising energy flows and HVAC control in Sport and Recreation Buildings. The proposed methodology integrates the use of building simulation and artificial neural networks to support better operation of Sport facilities, which are unique in terms of variable energy demand profiles and complex environmental conditions. The overall methodology is presented in conjunction with a demonstration case study. A procedure for swimming pool simulation is also tested within the case study work. 

The aim of this work is to model the energy consumption and the on-site production of an existing building, the Leaf House (LH), that was designed in order to be a Net Zero CO2 emission home. For a more effective use of energy some of the most advanced available technologies in the field of renewable sources were used. In particular, the technological building plant includes several subsystems as a Geothermal Heat Pump (GHP), solar PV and thermal panels, integrated in a fully automatic heat distribution system.

This paper shows a new DSF modeling approach so-called a co-simulation of the heterogeneous systems. In this approach, the calibrated DSF MATLAB model developed by [Park 2003] and the EnergyPlus building model are integrated in the BCVTB environment. As a result, more reliable simulation results can be obtained. Finally, the paper shows the difference between two approaches: (1) DSF simulation with EnergyPlus only and (2) the heterogeneous simulation approach using the in-house DSF model augmented with the whole building simulation model. 

CFD (Computational Fluid Dynamics) simulation is the main research method for assessing the wind environment around building complexes. Recent research showed the importance of turbulence models used in simulation and different turbulence models were developed to improve the precision of CFD simulation results. In this paper, a comparison of different turbulence models in simulating wind environment around building complexes is conducted to discuss their precision of simulation in three key elements of engineering application.

To maintain good indoor air quality, this investigation proposes a prototype of an active breathing wall system, which is composed of a solar radiation absorption board, air heating cavity, porous filtration unit and fan device. The thermo-flow performance of a physical model is measured and compared against the computational fluid dynamics (CFD) modeling. Then an office environment with a breathing wall is simulated by CFD. This study finds different ventilation modes are formed within the room in different seasons.

Because of the complexity and diversification of today’s HVAC systems, Fault Detection and Diagnosis (FDD) systems have become necessary to reduce maintenance cost and to provide building energy efficiency, but with a minimum of engineering cost. Based on a generic method of generating Fault Detection (FD) systems from Building Information Models (BIM), we now propose an  extension of the underlying Heat Flow Model (HFM) to implement a diagnosis engine and thus create the complete software system called HFM-FDD.

This paper presents a Simulation Domain Model (SimModel) - a new interoperable XML-based data model for the building simulation domain. SimModel provides a consistent data model across all aspects of the building simulation process, thus preventing information loss. The model accounts for new simulation tool architectures, existing and future systems, components and features. In addition, it is a multi-representation model that enables integrated geometric and MEP simulation configuration data.

The indoor moisture production is of great interest when simulating the indoor air humidity. Surface materials in an apartment will buffer some of the moisture produced depending on the features of the materials. Monte Carlo simulation of stochastically chosen moisture production rates in dwellings coupled to the moisture buffering capacity of surface materials, the ventilation rates and the outdoor climate define the moisture supply in a dwelling. The resulting distribution and variation of the indoor moisture supply are critical when designing moisture safe and durable buildings. 

Standard office building control systems operate the heating, ventilating, and air conditioning on a fixed schedule, based upon anticipated occupancy and use of the building. This study introduces and illustrates a method for integrated building heating, cooling and ventilation control to reduce energy consumption and maintain indoor temperature set points, based on the prediction of occupant behaviour patterns and local weather conditions. The experiment test-bed is setup in the Solar Decathlon House (2005), with over 100 sensor points.