Research on Optimization of Climate Responsive Indoor Space Design in Residential Buildings

Abstract

This paper first analyzes the climate characteristics of five typical cities in China, including Harbin, Beijing, Shanghai, Shenzhen and Kunming. Then, based on Grasshopper, Ladybug and Honeybee analysis software, according to the indoor layout of typical residential buildings, this research extracts design parameters such as the depth and width of different rooms and their window-to-wall ratios etc., to establish a climate responsive optimization design process with indoor lighting environment comfort, with heating and cooling demand as the objective functions. Meanwhile, based on Monte Carlo simulation data, ANN (Artificial Neural Network) is used to establish a prediction model to analyze the sensitivity of interior design parameters under different typical cities’ climatic conditions. The study results show that the recommended values for the total width and total depth of indoor units under the climatic conditions of each city are both approximately 14.97 m and 7.88 m. Among them, under the climatic conditions of Harbin and Shenzhen, the design parameters of residential interiors can take the recommended value of UDI optimal or nZEB optimal. While the recommended values of window-to-wall ratios for the north bedroom, master bedroom and living room in Shanghai residential interiors are 0.26, 0.32 and 0.33, respectively. The recommended value of the window-to-wall ratio of the master bedroom in Kunming residences is 0.36, and that of the remaining rooms is between 0.15 and 0.18. The recommended values of window-to-wall ratios for the master bedroom and living room in Beijing residences are 0.41 and 0.59, respectively, and that for the remaining rooms are 0.15. The multi-objective optimization process based on parametric performance simulation used in the study can effectively assist architects in making energy-saving design decisions in the preliminary stage, allowing architects to have a case to follow in the actual design operation process.

Layout Optimization of Urban Cultural Space Construction Based on Forward Three-Layer Neural Network Model

“…e results are subjective, and the number of solutions obtained is very small. In practice, there may be better solutions that have not been found, so it is necessary and urgent to seek an e ective systematic method [8].…”

Research-Integrated Pedagogy with Climate-Responsive Strategies: Vernacular Building Renovation Design

“…Li et al proposed an optimization process based on a parametric platform for building climate-responsive design. The optimal solution was provided from two different perspectives of the public sector (energy saving optimal) and private households (cost-optimal), respectively [47,48]. The multiobjective optimization process using Octopus ® based on the Grasshopper ® (GH) parametric platform [49] provided an available choice for students running on their modeling tool Rhino ® software (RN, Version 6.0, Robert McNeel & Associates, Seattle, WA, USA) [50].…”

“…Li et al proposed an optimization process based on a parametric platform for building climate-responsive design. The optimal solution was provided from two different perspectives of the public sector (energy saving optimal) and private households (cost-optimal), respectively[47,48]. The multiobjective optimization process using Octopus ® based on the Grasshopper ® (GH) parametric platform [49] provided an available choice for students running on their modeling tool Rhino ® software (RN, Version 6.0, Robert McNeel & Associates, Seattle, WA, USA)[50].As the program attempted to develop a sustainable renovation design for an urban house, the integration of studies on hot-humid climate, vernacular buildings, climateresponsive design strategies, and simulation tools was introduced and utilized[51,52].…”

The Effect of European Climate Change on Indoor Thermal Comfort and Overheating in a Public Building Designed with a Passive Approach

“…By getting a detailed overview of the energy consumption of each system and the building envelope's most important parameters, such as heat flow or surface temperatures, it becomes possible to assess user thermal comfort, indoor air quality, and total energy consumption. It is clear that the design of a space is not a single target exercise, thus multi-objective optimization is required for any meaningful and well-planned space, be it public [2] or residential [3]. The aim of providing good IAQ (indoor air quality) with low energy consumption is not only a problem for contemporary building owners and users [4] but for future cases too.…”

“…ASHRAE 90.1's Appendix G in Table G2. 3 states that "The simulation program shall perform the simulation using hourly values of climatic data, such as temperature and humidity from representative climatic data, for the site in which the proposed design is to be located. For cities or urban regions with several climatic data entries, and for locations where weather data are not available, the designer shall select available weather data that best represent the climate at the construction site.…”