Syndrome du bâtiment malsain | EPFL Graph Search

Le syndrome du bâtiment malsain (SBM) ou (SBS) est, dans le domaine de la santé environnementale et de la santé au travail, un syndrome décrivant une combinaison de symptômes ou de maladies médicalement inexpliquées et associées à un lieu construit. Ce syndrome est parfois assimilé aux maladies émergentes et est devenu un problème fréquemment traité par la médecine du travail. La perception du problème d'hypersensibilité aux polluants chimiques par la médecine et les pratiques des médecins évoluent également. Il est différent du concept de Building-Related Illness (BRI) dans lequel les symptômes sont imputés à une cause identifiée et spécifique. Lieux concernés Il peut s'agir :

d'un lieu de travail ; immeuble de bureaux, ateliers, entrepôts ;
du domicile : maison, appartement ;
d'un lieu d'apprentissage : école maternelle ou primaire, collège, lycée, université, salle de sport ;
d'un lieu de soin : hôpital, maison de retraite… ;
d'un lieu d'accueil et de p

Gas Sampling Using Convection and Humidity Stabilization to Improve Point Gas Sensor Responses

Emily Ann Hammes

Many diseases including sick building syndrome, respiratory problems and cancers can be caused by exposure to high concentrations of toxins commonly used in modern building materials, paints, glues and furniture. To minimize exposure to these toxins, it is important to have air exchange with the outside environment. However, this is usually not energy efficient because the air must be heated or cooled. The purpose of the Intasense project was to resolve this problem by creating an air quality monitor which could determine the current quality of air within the building. This information would then be used to control the ventilation system within an energy efficient building. The purpose of this Ph.D. thesis was both to build a system which could be used to test and calibrate sensors used in the air quality monitor as well as to build its final fluidic platform. During this thesis, three fluidic platforms which include a humidity buffering system were designed, tested and constructed. The first platform was used to test an electrochemical sensor or metal oxide sensor in the laboratory. The second and third platforms held three electrochemical or metal oxide sensors, respectively. They are able to deliver equal quantities of gas to the sensors simultaneously. To date, the multisensor metal oxide platform has been used to create two versions of the Intasense Demonstrator and used to calibrate novel and commercial gas sensors. In both of these applications simultaneous delivery of equal quantities of the sample gas are required for optimal gas sensor signal processing: equal quantities are required so that the amount of analyte in contact with each sensor is the same and simultaneous delivery allows all three sensors to respond concurrently. This was achieved by creating a computational model of gas flow through the system, conducting a parameter sweep and then selecting the optimal set. To confirm that the model and machine error were not significant, a Latin square design was used to test the platform. This test showed that gas delivery to each channel was equal within statistical boundaries. Another major challenge was buffering humidity fluctuations without loss of analyte gas. This was necessary because metal oxide gas sensors are also sensitive to humidity fluctuations. To prevent a false positive caused by a rapid humidity increase, a reversible adsorbent was placed upstream of the gas sensors. However, there was concern that the adsorbent may remove analyte gasses. To optimize the tradeoff between humidity buffering and loss or delay of analyte signal, a computational model of adsorption and desorption of gasses within the filtration system was developed. It was experimentally tested using benzene, carbon monoxide, formaldehyde and nitrogen dioxide. To date ten platforms have been delivered to laboratories throughout Europe. Three are being used to test and calibrate gas sensors. The rest have been used to create demonstrators of the Intasense Air Quality Monitor.

EPFL2016

Occupant satisfaction with indoor environmental quality, sick building syndrome (SBS) symptoms and self-reported productivity before and after relocation into WELL-certified office buildings

Dusan Licina, Serra Yildirim

Recent green building certification programs have put a strong emphasis on occupant health and well-being. For recently emerged WELL certification, we lack evidence about its effectiveness in relation to occupant satisfaction, productivity and health. Here, we compared the results of occupant satisfaction with the indoor environmental quality (IEQ) obtained from the same cohort of employees who transitioned from three non-WELL (two BREEAM and one conventional) to three WELL-certified office buildings. For two out of three building pairs, we found a statistically significant increase in building and workspace satisfaction after relocation to WELL buildings. However, for 55 % of compared cases, there was insignificant difference as the result of relocation. The positive effect of WELL certification was evident for parameters such as building cleanliness and furniture, but there was no difference in satisfaction with noise and visual comfort. Relocation from BREEAM to WELL buildings had insignificant effect on satisfaction with IEQ, except for air quality in one case. Regardless of the certification label, buildings usually did not attain the 80 % standard satisfaction threshold. The satisfaction scores did not alter during the first year of working in WELL buildings. We also observed that the level of certification did not scale with the overall building satisfaction scores. Comparisons between the occurrence of Sick Building Syndrome (SBS) symptoms and self-reported productivity scores revealed insignificant differences between WELL and non-WELL buildings, except for symptom of tiredness that was lower in WELL buildings. The effect of Covid-19 measures interfered with the self-reported work abilities of 78 % of occupants.

2021

STEP-NC machine tool data model and its applications

Ian Anthony Stroud, Jumyung Um

The machine tool data model of STEP-NC (ISO 14649) was conceived as a necessary extension to the original STEP-NC set of standards to make efficient control possible. The intention of this paper is to describe the background to the data model as well as related research work building on a higher level of information than can currently be found in the control information. The development of STEP-NC controllers promises improved manufacturing and resource use. However, even with legacy controllers there are advantages in using STEP-NC as an intermediate representation. This paper describes how the data model for describing machine capability was developed and what can be delivered by using this standard data model for machine tool. A machine tool selection algorithm is developed in order to validate the data model. Technical issues were derived from developing a system for process planning based on STEP-NC. Machine tools are selected automatically by the comparison with machine capability, work space and tolerance with the proposed data model. This function can contribute reconfigurable manufacturing systems and distributed and multi-controller-based manufacturing environment.

Taylor & Francis Ltd2016

Gas Sampling Using Convection and Humidity Stabilization to Improve Point Gas Sensor Responses

Emily Ann Hammes

EPFL2016