# Theoretical study of the synergic relationships between the design parameters in energy-saving building design

## TL;DR

This paper presents a new model to find how building design parameters work together to save energy.

## Contribution

A novel model combining an improved genetic algorithm and numerical calculation to identify synergic relationships in energy-saving building design.

## Key findings

- The insulation thickness is exponentially related to the shading coefficient when Isum=0.
- The thermal conductivity of insulation material strongly affects the synergic relationship.
- At ESR=65%, insulation thickness becomes a segmented function of the shading coefficient.

## Abstract

With the rapid development of the economy, people have increasingly higher requirements for the comfort of living spaces, and the result is the sharp increase in building energy consumption. Several design parameters influence living space comfort and building energy efficiency. Since the same design standard can include different design parameter combinations, synergic relationships may exist between these criteria for one case. Identifying these synergic relationships requires an inverse problem approach. This paper established a model by combining an improved genetic algorithm (IGA) and numerical calculation to determine the synergic design parameter relationships (e.g. the thermophysical building material properties and energy-saving factors). For \documentclass[12pt]{minimal}
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\begin{document}$${{\text{I}}}_{{\text{sum}}}= {0} $$\end{document}Isum=0, the shading coefficient significantly influenced the linear function between the thermal conductivity and insulation thickness. In this case, the insulation thickness was exponentially related to the shading coefficient, while the thermal conductivity of the insulation material significantly impacted the synergic relationship. For \documentclass[12pt]{minimal}
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\begin{document}$${\text{ESR}}{=65}\%$$\end{document}ESR=65%, the insulation thickness was a segmented function of the shading coefficient. The results verified that the proposed model was efficient and reliable for identifying the synergic relationships between energy-saving parameters. In engineering applications, designers can select the optimal design parameter combination based on the relationship curve between the parameters in this paper according to the local market conditions and specific design requirements.