Regressive model filling proekt desing to energy efficiency of building.
DOI:
https://doi.org/10.32347/2707-501x.2020.44.108-115Keywords:
energy efficiency classes, building energy efficiency standards, regression analysis, regression equation, determination coefficient.Abstract
Currently, the regulatory (compulsory) method of normalization in construction is used in Ukraine. Its essence lies in the elemental description of the construction object, according to which alternative design solutions are offered. In other words, building codes are transformed into rigid instructions. The parametric method of rationing involves the establishment of functional requirements, parameters, in particular, the energy efficiency parameters of individual structural solutions of a building. From many possible alternatives, the designer chooses the most effective solution, for example, on the criterion of energy efficiency. The parametric rationing method is based on a hierarchy of goals and objectives and is more progressive.
The purpose of the article is to substantiate the influence of engineering and design decisions on the energy efficiency of residential buildings by the method of correlation-regression analysis.
Using the methods of correlation (stochastic) analysis and the corresponding software product of the MS Excel environment, a regression model (equation) of dependence of the energy efficiency level of a residential building (B) on a set of engineering and technical design solutions was created. Specific energy consumption (ER) indicators for 27 projects of 4 - 9 storey residential buildings were considered as baseline data. The design solutions for each project were considered in the following areas: exterior wall and door structures, attic ceilings, translucent enclosure structures. of the given equation is only 11.6%, the coefficients of elasticity for each factor are calculated.
The regression equation obtained and the coefficients of regression and elasticity derived therefrom can be used in parametric normalization and in parametric pricing. Knowing the quantitative impact of each individual factor X and their totality on the resultant exponentials - the level of energy consumption B, one can purposefully focus on one or another factor. That is, to have a hierarchical, parametric series of influence of different design decisions on the energy efficiency index of a building.
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