Airbase publication

The aim of this paper is to present an automatic generator of zonal models that makes it possible to free the user from the choice of the specific flows models that have to be implemented in the zonal model and from the partitioning stage. The dynamic simulation tool called “O-Zone” is based on an advanced formulation of zonal models. It uses on a new way of sub-dividing the room that allows us to obtain a dynamic partitioning based on airflow patterns. The partitioning method chosen is the Octree method.

In the last years many building designers have turned their attention to natural ventilation, due to the potential benefits in terms of energy consumption related to ventilation and air-conditioning, especially in mild and moderate climates. Consequently, several calculation techniques have been developed to design and predict the performance of natural ventilation.  This article presents a review of the existing approaches to predict natural ventilation performance, including simple empirical models, nodal models (mono-zone and multi-zones), zonal models and CFD models.

The paper is concerned with the integration of building performance simulation within a collaborative/ multidisciplinary higher-education environment. The paper presents a semester-long setup in which a course attended by both architecture and engineering students and jointly taught by an architect and an engineer ultimately collaborate with an undergraduate architecture design studio on proposing upgrades to an existing building.

A wide range of scientifically validated Building Performance Simulation tools BPS is available internationally. The users of those tools are mainly researchers, physicists and experts who value empirical validation, analytical verification and calibration of uncertainty as defined by e.g. BESTEST. However, literature and comparative surveys indicate that most architects who use BPS tools in design practice are much more concerned with the (1) Usability and Information Management (UIM) of interface and (2) the Integration of Intelligent design Knowledge-Base (IIKB).

The daylight factor is usually one of the first daylight performance measures that simulation newcomers calculate. Apart from the intrinsic limitations of the daylight factor as a meaningful daylighting performance metric, little work has been done in the past as to how accurate one can actually expect simulation novices to simulate the daylight factor compared to an expert modeler. This paper presents the comparison of daylight factor predictions from a ‘best practice’ model of an L-shaped perimeter classroom to a total of 69 novice/student models.

In the current context of energy crisis and with the debate on climate change, low-energy buildings are required.

A genetic optimization approach has been used for the design of an external shading device in an office with a window and different glass characteristics. The primary energy consumption for heating cooling and lighting have been minimized. Simulations have been performed using the energy code ESP-r and lighting simulation package Radiance, the optimization loop has been driven by the software tool modeFRONTIER. Different optimal geometries for a panel shading device have been found.

Recently, a combination between simulation and optimisation has been important for many of HVAC design problems.

Distributed energy system based on cogeneration system has high potential of energy saving due to utilizing waste heat from power generator effectively. However, unless the appropriate combination of machinery and operation are conducted, the expected performance is not achieved, it is quite difficult to determine the optimal combination of machinery and operation. Authors had already developed and proposed new optimal design method for building energy systems or distributed energy systems using Genetic Algorithm (GA) in some previous studies (e.g. Ooka R et al, 2008).

The aim of this paper is to describe the features of a Genetic Algorithm (GA) developed to solve simulation-based optimization problems for the optimal design of building parameters. This GA has been developed using guidelines from top researchs in the field of evolutionary computation. It is mostly based on NSGA-II and Omni-optimizer.