Pour savoir comment effectuer et gérer un dépôt de document, consultez le « Guide abrégé – Dépôt de documents » sur le site Web de la Bibliothèque. Pour toute question, écrivez à corpus@ulaval.ca.
 

Personne :
Gosselin, Louis

En cours de chargement...
Photo de profil

Adresse électronique

Date de naissance

Projets de recherche

Structures organisationnelles

Fonction

Nom de famille

Gosselin

Prénom

Louis

Affiliation

Université Laval. Département de génie mécanique

ISNI

ORCID

Identifiant Canadiana

ncf13674232

person.page.name

Résultats de recherche

Voici les éléments 1 - 9 sur 9
  • PublicationRestreint
    Lessons learned with respect to the CAE roadmap from the monitoring of a high-performance social housing building in Quebec City
    (Université Concordia, 2020-10-16) Gosselin, Louis; Rouleau, Jean; Blanchet, Pierre; Athienitis, Andreas
    A prototype was built in Quebec City to demonstrate the feasability of low-energy social housing buildings. The case study building was heavily monitored to follow its energy performance. This paper presents observations that emerged from this project regarding the design and operation of this social housing building. It shows the energy consumption of each individual dwelling, the indoor temperature in summer and heat fluxes flowing through the envelope. Lessons learned regarding lowenergy residential buildings that are resilient and powered by renewable energy are discussed.
  • PublicationAccès libre
    Probabilistic window opening model considering occupant behavior diversity : a data-driven case study of Canadian residential buildings
    (Pergamon, 2020-01-20) Gosselin, Louis; Rouleau, Jean
    It was found from monitored data from eight dwellings in a case study building in Quebec City (Canada) that there are clear differences in the window opening behavior between different households. This paper aims to develop from data a probabilistic window opening model that accounts for occupant behavior. Logit regression is employed to predict the state (opened/closed) of windows according to indoor and outdoor temperatures environmental and temporal parameters. To replicate the diversity of behavior, normal distribution functions applied to the logit regression coefficients are used so that simulated occupants respond differently to environmental stimuli. It was found that the model offers good prediction for the monitoring by only using the outdoor and indoor temperatures as predictors. The proposed methodology was tested by simulating 10,000 times a full validation year of the case study building and comparing the results with measured data. The agreement was good. The model overestimated slightly the total frequency of window opening in the dwellings and the number of window changes-of-state. A vast range of window opening behavior was generated by the model, showing its ability to reproduce both the aggregated window opening behavior and the diversity of behaviors of the case study building.
  • PublicationAccès libre
    New concept of combined hydro-thermal response tests (H/ TRTs) for ground heat exchangers
    (ScienceDirect, 2016-03-31) Gosselin, Louis; Raymond, Jasmin; Rouleau, Jean
    Current thermal response tests, used to estimate the subsurface thermal conductivity in the geothermal domain, are not designed to take into account groundwater flows. To measure the flow parameters, a new concept has been developed. Heating cables are installed within a borehole in contact to the formation, with three temperature probes strategically located at the edge of the borehole. Study of the evolution of temperature for each probe during both a heat injection phase and a recovery period allows determining ground thermal conductivity, groundwater flow velocity and orientation. Numerical simulations have been used to validate the proposed concept and establish its limits.
  • PublicationAccès libre
    Analysis of strategies to reduce thermal discomfort and natural gas consumption during heating season in Algerian residential dwellings
    (SUSB, 2020-03-31) Gosselin, Louis; El Hassar, Sidi Mohamed Karim; Khelifa Kerfah, Ilyas; Rouleau, Jean; Larabi, Abdelkader
    In the Algerian building sector, the heating needs are essentially satisfied with fossil fuels (in particular natural gas). The more common heating system in multifamily buildings is a gas heater in the central corridor of each dwelling. This system can cause important overheating in the corridor and significant gas consumption. The present study evaluates the energy savings and thermal comfort improvement, for three different cities of Algeria, achieved with a different heating system based on hot water radiators. In situ measurements were performed in a typical dwelling (which served as a reference case) and the results were used to calibrate and validate the TRNSYS model that was used for this study. A parametric analysis was performed by varying the location, heating system, envelope and windows. It was found that among the scenarios tested, it was possible to substantially reduce the heating needs compared to the reference dwelling and that the number of hours of thermal discomfort could be virtually eliminated. The most influential parameters affecting these model outputs appeared to be the wall thermal insulation.
  • PublicationAccès libre
    Impact of window-to-wall ratio on heating demand and thermal comfort when considering a variety of occupant behavior profiles
    (Frontiers Media, 2021-12-09) Gosselin, Louis; Veillette, Debby; Rouleau, Jean
    Energy consumption and thermal comfort in residential buildings are highly influenced by occupant behavior, which exhibits a high level of day-to-day and dwelling-to-dwelling variance. Although occupant behavior stochastic models have been developed in the past, the analysis or selection of a building design parameter is typically based on simulations that use a single “average” occupant behavior schedule which does not account for all possible profiles. The objective of this study is to enhance the understanding of how window-to-wall ratio (WWR) of a residential unit affects heating demand and thermal comfort when considering occupant behavior diversity through a parametric analysis. To do so, a stochastic occupant behavior model generates a high number of possible profiles, which are then used as input in an energy simulation of the dwelling. As a result, one obtains probability distributions of energy consumption and comfort for different WWR values. The paper shows that the shape of the probability distributions is affected by WWR and dwelling orientation, and that the influence of different occupant behavior aspects on performance also varies with WWR. This work could help designers to better assess the impact of WWR for a large spectrum of possible occupant behavior profiles.
  • PublicationAccès libre
    Inverse heat transfer applied to a hydrogeological and thermal response test for geothermal applications
    (ScienceDirect, 2016-06-06) Gosselin, Louis; Rouleau, Jean
    Actual thermal response tests, used to estimate the subsurface thermal conductivity in the geothermal domain, do not provide any estimate on the velocity of the groundwater flow and its orientation. These parameters are important for sizing geothermal borefield, since they influence the heat transfer around a geothermal borehole and the surrounding ground. To correct this shortcoming, a conceptual test has been developed in which heating cable sections inject heat in a borehole. Three temperature probes are strategically located at the borehole edge. This paper applies inverse heat transfer strategies to this thermal response test concept in order to identify the ground thermal conductivity, as well as the groundwater flow velocity and its direction. The suggested thermal response test and parameters estimation methodology are detailed. The influence of initial guessed values for the three unknown parameters was also studied. The work presented in this paper was carried out by numerical simulations.
  • PublicationRestreint
    Robustness of energy consumption and comfort in high-performance residential building with respect to occupant behavior
    (Pergamon, 2019-08-22) Gosselin, Louis; Rouleau, Jean; Blanchet, Pierre
    Building energy simulations rely on assumptions that can affect their reliability. Occupant behavior in particular is highly uncertain, especially for residential buildings. The great variability of occupants’ actions has a great impact on the energy performance of a building and can explain the failures of building simulations to accurately forecast the energy demand of a building. This study quantifies the impacts of humans on the performance of a residential building by simulating dwellings using multiple realistic occupant behavior profiles. The dwelling models were validated with monitored data. Aspects of occupant behavior covered in this study are occupancy, hot water and electricity consumption, heating set point temperature and openings of windows. The individual impact of all these aspects on energy demand and thermal comfort are analysed. Results show great variability of energy consumption and thermal comfort for a given dwelling when different occupants are living in it, with coefficient of variation of approximately 50%. Large housing stocks are less sensitive to occupant behavior than individual dwellings, but their consumption levels remain difficult to predict when using a deterministic approach to represent occupant behavior.
  • PublicationAccès libre
    A unified probabilistic model for predicting occupancy, domestic hot water use and electricity use in residential buildings
    (ScienceDirect, 2019-08-13) Gosselin, Louis; Ramallo-Gonzalez, Alfonso; Rouleau, Jean; Blanchet, Pierre; Natarajan, Sukumar
    A strategy to combine separate probabilistic models into a unified model for predicting schedules of active occupancy, domestic hot water (DHW) use, and non-HVAC electricity use in multiple residences at 10-minute resolution for every day of the year is described. In addition to combining the models, a variety of new model functions are introduced in order to to generate stochastic predictions for each of numerous residences at once, to enforce appropriate variability of behaviors from a dwelling to another and to ensure that domestic hot water and electricity use predictions are coincident with occupancy. The original separate models were developed for the US and the UK; several scaling factors were added in the model to adjust the predictions so as to better agree with national aggregated data for Canada since the model developed from the described strategy was validated with measured data from a social housing building in Quebec City, Canada. This validation was made by comparing predictions from the unified model to measurements of domestic hot water use and electricity consumption from the 40 residential units of the monitored building. The validation showed that the tool can produce realistic profiles since it is mostly in agreement with consumption patterns found in the monitored building. However, there remain discrepancies which suggest potential research ideas for future work in occupant behavior modelling.
  • PublicationRestriction temporaire
    Understanding energy consumption in high-performance social housing buildings : a case study from Canada
    (Elsevier, 2017-12-23) Rouleau, Jean; Gosselin, Louis; Blanchet, Pierre
    This paper presents a case study of a recently built high-performance Canadian social housing building with the aim of comparing the expected and measured energy consumptions and to identify the parameters affecting the most the energy need. A monitoring system compiles at a 10-min frequency information related to the energy use and the thermal conditions observed in the building and its HVAC system. The building has the particularity of comprising two symmetric sections made of different timber structure systems. No significant differences of energy consumption were detected between the two parts of the buildings. However, a large variance was observed when comparing each dwelling individually regardless of their structures. The orientation of the dwelling also exhibited a minimal influence compared to these variations, suggesting that occupant behavior is the dominant factor explaining dwelling-to-dwelling variability and is thus critical for understanding energy use in residential buildings. Regression analysis showed that specific occupant actions, such as opening windows in winter or using electrical appliances, have a great impact on the energy balance of the apartments. In 2016, the performance gap between measured and expected total energy demand of the building was 74%. With the use of the large dataset coming from the building, it was possible to determine the causes behind this large gap for the reference building.