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  • 1.
    Davoodi, Anahita
    et al.
    Jönköping University, School of Engineering, JTH, Civil Engineeering and Lighting Science.
    Johansson, Peter
    Jönköping University, School of Engineering, JTH, Civil Engineeering and Lighting Science.
    Henricson, Maria
    Jönköping University, School of Health and Welfare, HHJ, Dep. of Nursing Science. Jönköping University, School of Health and Welfare, HHJ. ADULT.
    Aries, Myriam
    Jönköping University, School of Engineering, JTH, Civil Engineeering and Lighting Science.
    A Conceptual Framework for Integration of Evidence-Based Design with Lighting Simulation Tools2017In: Buildings, ISSN 2075-5309, E-ISSN 2075-5309, Vol. 7, no 4, article id 82Article, review/survey (Refereed)
    Abstract [en]

    The use of lighting simulation tools has been growing over the past years which has improved lighting analysis. While computer simulations have proven to be a viable tool for analyzing lighting in physical environments, they have difficulty in assessing the effects of light on occupant’s perception. Evidence-based design (EBD) is a design method that is gaining traction in building design due to its strength in providing means to assess the effects of built environments on humans. The aim of this study was to develop a conceptual framework for integrating EBD with lighting simulation tools. Based on a literature review, it was investigated how EBD and lighting simulation can be combined to provide a holistic lighting performance evaluation method. The results show that they can mutually benefit from each other. EBD makes it possible to evaluate and/or improve performance metrics by utilizing user feedback. On the other hand, performance metrics can be used for a better description of evidence, and to analyze the effects of lighting with more details. The results also show that EBD can be used to evaluate light simulations to better understand when and how they should be performed. A framework is presented for integration of lighting simulation and EBD

  • 2.
    Jalilzadehazhari, Elaheh
    et al.
    Linnaeus University, Växjö, Sweden.
    Vadiee, Amir
    Mälardalens högskola, Vasteras, Sweden.
    Johansson, Peter
    Jönköping University, School of Engineering, JTH, Civil Engineeering and Lighting Science.
    Achieving a trade-off construction solution using BIM, an optimization algorithm, and a multi-criteria decision-making method2019In: Buildings, ISSN 2075-5309, E-ISSN 2075-5309, Vol. 9, no 4, p. 1-14, article id 81Article in journal (Refereed)
    Abstract [en]

    The Energy Performance of Building Directive obligated all European countries to reduce the energy requirements of buildings while simultaneously improving indoor environment quality. Any such improvements not only enhance the health of the occupants and their productivity, but also provide further economic benefits at the national level. Accomplishing this task requires a method that allows building professionals to resolve conflicts between visual and thermal comfort, energy demands, and life-cycle costs. To overcome these conflicts, this study exploits the incorporation of building information modelling (BIM), the design of experiments as an optimization algorithm, and the analytical hierarchy process (AHP) into a multi-criteria decision-making method. Any such incorporation can (i) create constructive communication between building professionals, such as architects, engineers, and energy experts; (ii) allow the analysis of the performance of multiple construction solutions with respect to visual and thermal comfort, energy demand, and life-cycle costs; and (iii) help to select a trade-off solution, thereby making a suitable decision. Three types of energy-efficient windows, and five types of ground floors, roofs, and external wall constructions were considered as optimization variables. The incorporation of several methods allowed the analysis of the performance of 375 construction solutions based on a combination of optimization variables, and helped to select a trade-off solution. The results showed the strength of incorporation for analyzing big-data through the intelligent use of BIM and a simulation in the field of the built environment, energy, and costs. However, when applying AHP, the results are strongly contingent on pairwise comparisons. 

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