25
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A New Hybrid MCDM Model for Insulation Material Evaluation for Healthier Environment

      , , ,
      Buildings
      MDPI AG

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          One of the easiest and most common methods for effectively reducing building energy demand is the selection of adequate thermal insulation materials. Thermal insulation is a substantial contribution and an evident, logical and practical first stage toward improving energy performance, particularly in envelope-load-dominant structures located in difficult climate zones. Today’s insulating materials come in a broad variety of sizes and shapes, each with its a own qualities. It is well acknowledged that material selection is one of the most difficult and time-consuming aspects of a construction project. Therefore, choosing the right insulation material is also a very important topic to increase energy efficiency. However, it is a complex problem with many criteria and alternatives. This study integrates three different multi criteria decision making methods, which are Fuzzy Best-Worst Method, CRiteria Importance Through Inter-criteria Correlation and Mixed Aggregation by COmprehensive Normalization Technique. In this study, the following eight criteria were taken into account in the evaluation: thermal conductivity, periodic thermal transmittance, specific heat, density, decrement factor, surface mass, thermal transmittance, and thermal wave shift. The first method will be used to find the subjective weights, while the second method will be used to find the objective weights. The third method will be used to rank the insulation materials. According to the results of the Fuzzy Best-Worst Method, the most important criterion was determined as thermal conductivity. According to the results of the CRiteria Importance Through Inter-criteria Correlation, the most important criterion was determined as thermal wave shift. According to the results of the Mixed Aggregation by COmprehensive Normalization Technique, the top 10 insulation materials are as follows: polyisocyanurate, polyurethane (1), polyurethane (2), wood fiber (1), kenaf, jute, cellulose (2), wood fiber (1), XPS (1) and XPS (2). According to the results of the proposed method, polyisocyanurate was determined as the best insulation material for healthier environment. This study makes two contributions to the literature: first, a new hybrid method was developed in this study. Secondly, in this study, the newly introduced Mixed Aggregation by COmprehensive Normalization Technique method was used.

          Related collections

          Most cited references56

          • Record: found
          • Abstract: not found
          • Article: not found

          Determining objective weights in multiple criteria problems: The critic method

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Optimization of Weighted Aggregated Sum Product Assessment

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Fuzzy best-worst multi-criteria decision-making method and its applications

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Buildings
                Buildings
                MDPI AG
                2075-5309
                May 2022
                May 13 2022
                : 12
                : 5
                : 655
                Article
                10.3390/buildings12050655
                4949cf01-3699-4f59-9b61-89bb30f64488
                © 2022

                https://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article