IBPSA1997

A new integrated simulation system for the building services design and facilities management purposes is being developed by Insinööritoimisto Olof Granlund Oy. The system covers the thermal simulation needs of the whole building life cycle from the preliminary design to renovations. The main components of the simulation system are a simulation database, user interfaces, a result module, a building geometry modeller and a calculation engine. The building geometry modeller generates a 3-D surface model of the building. The calculation engine of the first version is DOE 2.1E.

In  this  paper,  the  parameters  in  a  building  thermal simulation model are tracked, which are subject to modeling uncertainty, i.e. uncertainty arising from commonly applied physical assumptions and simplifications. As an example, the simulation of the thermal comfort performance of a naturally ventilated office building without cooling plant is analyzed.

If a map of a city is encoded as a Digital Elevation Model, it becomes amenable to image-processing software, such as the public-domain NIH Image application. Standard techniques can be used to measure plan areas and volumes and simple macros can be devised to measure perimeter length and wall areas. A macro for calculating shadow volumes is elaborated for the simulation of solar gains and daylight, including indirect lighting, leading to the possibility of an image-based urban-scale environmental model.

Combined conduction-convection-radiation heat transfer in concrete block walls with one or two cavities is simulated using the CFD code “FIDAP”. It is shown that the resistance of the block itself depends on the temperature difference between the external and internal parts. The heat flux is shown to vary appreciably, approximately 30 %, between the upper and the lower parts of the block.

A new method aimed at the selection of the best reduction technique for each given invariant linear system, such as those obtained when modelling the thermal behaviour of building envelopes, is presented here. The method can be divided into three main steps. In the first step, we evaluate a priori whether or not the selection of the reduction technique is critical knowing either the desired reduction order or either the level of accuracy required for the reduced model.

Training new users of simulation programs typically focuses on a single tool–specific techniques for interacting with, creating models, and assessing performance. Unfortunately, this tends to produce users limited by a particular tool’s capabilities—not users that can easily decide how best to tackle a simulation problem, regardless of tool.

Models of faulty components or processes may either be used on-line as part of a fault detection and diagnosis (FDD) system or may be used in simulations to train or test FDD procedures. Some faults may be modelled by choosing suitable values of the parameters of fault free models, whereas other faults require specific extensions to fault freemodels. An example of themodelling of various faults in a cooling coil subsystem is presented and different methods of using simulation in testing and training are discussed.

This paper investigates the feasibility of using short segments of weather data to simulate annual energy use in buildings. Use of a “typical week” of weather data is investigated as an alternative to the normal 8760-hour annual simulation process. Statistically correct weekly weather data were first generated; then trial runs were made on a skin-load-dominated building in four U.S.

Application of the finite control volume method on simulating thermal fire resistance of building materials and elements was evaluated. Example was taken on studying the thermal responses of a concrete column under fire. By neglecting moisture transfer, the thermal conduction equation in concrete was solved numerically to get the temperature distribution. Results were compared with those calculated from other finite difference schemes including the forward difference, backward difference and central difference schemes.

A major barrier to using energy simulation tools during the design process of a building has been the difficulty of using the available programs. The ENERGY-10 program overcomes this hurdle by automating many of the time-consuming tasks, shortening the time required from hours or days to minutes. Building descriptions are created automatically based on defaults. The APPLY and RANK features speed the process of comparing the performance of energy-efficient strategies by automatically modifying the building description and sequencing the operations.