An optimal design method for the surface shape of exterior materials based on near-infrared rays retroreflection is presented as a countermeasure to the heat island phenomenon. A genetic algorithm was used to determine the optimal shapes, and a ray tracing method was used to estimate the reflection distribution characteristics for each shape. This method allows design goals to be set as objective functions enabling quantitative evaluation of performance. Objective functions for assessing the achievement of design goals were also considered. The surface shape design goals were achieved and we proposed a prototype of the optimal design method for exterior materials.

Expectations of advanced operation of building services, such as demand response and fault detection and diagnosis, have been difficult to meet as the construction of system simulations and the required data analysis are largely manual tasks. A framework using Brick Schema, a metadata schema, to build a Brick model of a cooling plant for air conditioning is presented herein along with proposed examples utilizing the Brick model. Brick Schema as a metadata schema for building services is a developing concept with few examples of utilization. This research focuses on the extraction of metadata by SPARQL queries and the characteristics of Brick Schema as a graph structure with directed labels and shows examples of automatic support for system simulation construction and data analysis. System simulations are generally constructed manually by either using information, such as system diagrams, or by creating prediction models from BEMS data. However, we present an example of automatic generation from metadata as an alternative method to manual simulation construction. The model automatically reads equipment information from the Brick model and calculates inlet and outlet temperatures of equipment based on the equipment’s connections. In addition, we show that the Brick model can be used to compare simulation results with BEMS data in a symple and scalable manner. These examples are applicable to the target system and can be applied to various systems if the Brick model is properly constructed, highlighting one of the advantages of using Brick Schema. The examples of Brick model applications presented in this paper are preliminary, and the ontology used is limited to typical relations such as “feeds”. Development of advanced applications including visualization of system operating conditions and detection of operating faults, is expected.

This study applies the concept of dynamic steady-state concentration to air recirculating system in order to develop a tracer gas method to experimentally determine ventilation efficiency. The air recirculating system treats exhaust and return air from a room before resupplying it. To build on the previous paper (part 1), this paper (part 2) presents a method for calculating the age of air distribution using the dynamic steady-state concentration in the air recirculating system. Additionally, we confirmed the principle of age of air measurement and performed CFD analysis to investigate the appropriate timing for sampling. Results indicate that the age of air distribution determined by the dynamic steady-state concentration in an air recirculating system coincides with the age of air distribution in an open-air system. As time passes from the start of measurement, the age of air in open-air systems, which are influenced by the spatial uniform generation of the passive scalar, tend to deviate from the distribution of air recirculating systems. This is especially true if there is an air infiltration port in the vicinity. Results show it is possible to measure the age of air with high accuracy if concentration data sampling is performed at the correct time. Sampling should occur at 1.0-1.5 times the nominal time constant, which considers recirculating airflow rate and room volume without immediate vicinity of an air infiltration port. To determine age of air in interior spaces, concentration data sampling is permitted at several times the nominal time constant from the start of measurement.