Personne :
Lalonde, Jean-François

En cours de chargement...
Photo de profil
Adresse électronique
Date de naissance
Projets de recherche
Structures organisationnelles
Nom de famille
Université Laval. Département de génie électrique et de génie informatique
Identifiant Canadiana

Résultats de recherche

Voici les éléments 1 - 5 sur 5
  • Publication
    Accès libre
    A photobiological approach to biophilic design in extreme climates
    (Pergamon, 2019-03-20) Parsaee, Mojtaba; Demers, Claude; Potvin, André; Hébert, Marc; Lalonde, Jean-François
    This paper proposes the biophilic design approach as a plausible hypothesis for the challenging conditions related to living and working in extreme cold climates. Biophilic design has recently been developed to overcome the adverse effects of the built environment and to improve human well-being by redefining the human-nature relationship. Yet, biophilic design should be adapted to extreme cold climates in order to meet the biological needs of people in northern territories. This issue becomes more important when considering the availability of natural light due to the strong seasonal photoperiod and its effects on human well-being in such regions. The present paper critically reviews biophilic design patterns and identifies their main shortcomings. These shortcomings include the lack of (1) recommendations applicable to extreme cold climates (2) adaptation to the local photoperiods, and (3) a systemic framework integrated into the design process. The paper draws attention to the image-forming and non-image-forming effects of light as a basis of the human-nature design approach. In this regard, photobiological outcomes have been reviewed. Then, the paper discusses the existing lighting standards and guidelines in North America and how they have mainly been developed to fulfil the image-forming demands for light. Further efforts are needed to revise these standards with respect to the non-image-forming effects of light and the biophilic design requirements. Finally, adaptive building envelopes are presented as a hypothetical solution to optimize the biophilic qualities of buildings and address the biological needs of people living and working in extreme cold climates in northern territories.
  • Publication
    Accès libre
    Biophilic, photobiological and energy-efficient design framework of adaptive building façades for Northern Canada
    (Sage, 2020-02-12) Parsaee, Mojtaba; Demers, Claude; Potvin, André; Hébert, Marc; Lalonde, Jean-François
    This paper develops an integrated design framework of adaptive building façades (ABFs) to respond to photobiological and thermal needs of occupants, biophilic factors, energy requirements and climatic features in Northern Canada, i.e. near and above 50°N. The paper discusses the importance of biophilic and photobiological factors and ABFs to improve occupants’ health and human-nature relations and deal with the extreme climate in Northern Canada where non-adapted buildings that could negatively affect occupants’ wellbeing. The paper shows that existing ABFs must be further developed for northern applications in terms of (i) the physical structure and configuration of components (ii) the design of solar shading/louver panels to address photobiological and biophilic requirements (iii) the development of lighting adaptation scenarios to respond to biophilic and photobiological needs, local photoperiods and energy issues, and (iv) the overall biophilic quality for accessibility to natural patterns. The ABFs’ framework was developed in three phases including (1) process environmental data (2) produce adaptation scenarios, and (3) operate adaptation scenarios. The research discussed major issues of all phases that must be further studied, especially the development of hourly/daily/seasonally lighting adaptation scenarios. The paper develops a holistic parametric methodology to integrate and optimize major design variables of ABF’s components.
  • Publication
    Accès libre
    Human-centric lighting performance of shading panels in architecture: a benchmarking study with lab scale physical models under real skies
    (Association for Applied Solar Energy, 2020-05-07) Parsaee, Mojtaba; Demers, Claude; Potvin, André; Hébert, Marc; Lalonde, Jean-François; Inanici, Mehlika
    This study investigates shading panels’ (SPs) impacts on daylighting features in a lab scale model in terms of parameters representing potential human eyes’ biological responses identified as image forming (IF) and non-image forming (NIF). IF responses enable vision and NIF responses regulate internal body clocks known as circadian clocks. Human-centric lighting evaluates photopic units, representing IF responses, and melanopic units representing NIF responses, combined with correlated color temperature (CCT) of light for potential biological effects. SPs’ impacts on such parameters of daylighting have not yet been studied. Previous research mostly studied panels’ impacts on visual comfort and glare related to IF responses. This research explores the impact of SPs’ color, reflectance, orientation, and openness on photopic and melanopic units and CCT of daylighting inside a 1:50 physical scale model of a space. Approximately prototypes of SPs were evaluated. An experimental setup was designed under outdoor daylighting conditions to capture high dynamic range (HDR) images inside the model. HDR images were post processed to calculate and render the distribution of photopic and melanopic units, melanopic/photopic (M/P) ratios and CCTs in the captured viewpoint of the model. Results reveal the behavior of SPs’ color, reflectance, orientation, and openness in modifying daylighting parameters related to biological responses. Bluish panels, in particular, increase daylighting melanopic units and CCTs whereas reddish panels increase photopic units and reduce CCTs. The research results were discussed to provide an outline for future developments of panels to adapt daylighting to occupants' IF and NIF responses.
  • Publication
    Accès libre
    Inferring the solution space of microscope objective lenses using deep learning
    (Optical Society of America, 2022-02-14) Thibault, Simon; Zhang, Yueqian; Lalonde, Jean-François; Menke, Christoph; Côté, Geoffroi
    Lens design extrapolation (LDE) is a data-driven approach to optical design that aims to generate new optical systems inspired by reference designs. Here, we build on a deep learning-enabled LDE framework with the aim of generating a significant variety of microscope objective lenses (MOLs) that are similar in structure to the reference MOLs, but with varied sequences—defined as a particular arrangement of glass elements, air gaps, and aperture stop placement. We first formulate LDE as a one-to-many problem—specifically, generating varied lenses for any set of specifications and lens sequence. Next, by quantifying the structure of a MOL from the slopes of its marginal ray, we improve the training objective to capture the structures of the reference MOLs (e.g., Double-Gauss, Lister, retrofocus, etc.). From only 34 reference MOLs, we generate designs across 7432 lens sequences and show that the inferred designs accurately capture the structural diversity and performance of the dataset. Our contribution answers two current challenges of the LDE framework: incorporating a meaningful one-to-many mapping, and successfully extrapolating to lens sequences unseen in the dataset—a problem much harder than the one of extrapolating to new specifications.
  • Publication
    Accès libre
    Deep learning-enabled framework for automatic lens design starting point generation
    (Optical Society of America, 2021-01-25) Côté, Geoffroi; Thibault, Simon; Lalonde, Jean-François
    We present a simple, highly modular deep neural network (DNN) framework to address the problem of automatically inferring lens design starting points tailored to the desired specifications. In contrast to previous work, our model can handle various and complex lens structures suitable for real-world problems such as Cooke Triplets or Double Gauss lenses. Our successfully trained dynamic model can infer lens designs with realistic glass materials whose optical performance compares favorably to reference designs from the literature on 80 different lens structures. Using our trained model as a backbone, we make available to the community a web application that outputs a selection of varied, high-quality starting points directly from the desired specifications, which we believe will complement any lens designer's toolbox.