The effect of construction material, contents and room geometry on the sound field in dwellings at low frequencies

An experimentally validated finite element method is used to model the sound level in rooms at low frequencies. It is demonstrated that the dimensions of rectangular rooms strongly influence the sound pressure level difference. Additional factors were investigated which are not normally considered in the frequency range where diffuse sound field conditions can be assumed. Three effects were investigated: room damping due to wall vibrations, furniture, the effect of small deviations from simple rectangular shapes. It is confirmed by field measurements that the vibrations of masonry walls and floors introduce less damping than surfaces of lightweight construction. Assigning to the FE model a damping equivalent to a surface absorption of 0.02 reproduces the effect of walls of heavyweight construction. Damping equivalent to a surface absorption of 0.15 reproduces the effects of plastered timber-frame walls, floors and ceilings. The work was briefly extended to a room pair built with heavyweight and lightweight material of construction. The modification of the shape of the room frequency response highlights well the effect of material of construction. In-situ and laboratory measurements show that furniture has little effect on steady-state room response below 100 Hz. Modelling a wall recess smaller than 0.5 m improved the agreement between prediction and measurements but the assumption of a simple rectangular room remains appropriate.     

Detection of emissions from surfaces using ion mobility spectrometry

Emissions from surfaces (from furniture, wall paintings or floor coverings for instance) significantly influence indoor air quality and therefore the wellbeing or even the health of the occupants. Together with metabolites from mold they are responsible for the well-known “sick building syndrome”. Therefore, it is in the interest of the manufacturer as well as of the occupants to have a fast and accurate method for the detection of substances relevant to this syndrome in order to be able to monitor and control product quality and indoor air quality. The use of small and easy-to-transport ion mobility spectrometers that use UV light as the ionization source enables rapid in situ detection of such substances with high selectivity and sensitivity (detection limits in the lower ppb range). If a multicapillary column is used for preseparation as well, the selectivity is increased and the unwanted influence of humidity on the spectra can be eliminated, thus enabling the use of the instruments under normal ambient conditions. Furthermore, the use of air as carrier gas avoids the need for other sources of high-purity gas. An emission cell with a homogeneous and constant air flow over the surface to be investigated was developed in order to ensure reproducible results. Investigations of emissions from wooden surfaces with and without additional contamination as well as from complex mixtures are presented. The results demonstrate that relevant emissions can be identified and quantified with high sensitivity and selectivity in under five minutes. Therefore, the method is useful for indoor air quality monitoring, especially when miniaturized instruments are applied. Figure     

Furniture supply chain tactical planning optimization using a time decomposition approach

We study the supply chain tactical planning problem of an integrated furniture company located in the Province of Québec, Canada. The paper presents a mathematical model for tactical planning of a subset of the supply chain. The decisions concern procurement, inventory, outsourcing and demand allocation policies. The goal is to define manufacturing and logistics policies that will allow the furniture company to have a competitive level of service at minimum cost. We consider planning horizon of 1 year and the time periods are based on weeks. We assume that customer’s demand is known and dynamic over the planning horizon. Supply chain planning is formulated as a large mixed integer programming model. We developed a heuristic using a time decomposition approach in order to obtain good solutions within reasonable time limit for large size problems. Computational results of the heuristic are reported. We also present the quantitative and qualitative results of the application of the mathematical model to a real industrial case.