The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform

Long Enshen - One of the best experts on this subject based on the ideXlab platform.

  • are the relative variation rates rvrs approximate in different cities with the same increase of Shape Coefficient
    Building and Environment, 2005
    Co-Authors: Long Enshen
    Abstract:

    The influence of the building's Shape Coefficient on annual heating and cooling energy consumption is significant, therefore, when laying down design standard for building efficiency, each country makes specific limitations to building Shape Coefficient. This paper takes two types of buildings with great difference of Shape Coefficient as the study objects and studies the influence rule of the same increase of Shape Coefficient on the annual cooling and heating energy consumption and its relative variation rates (RVRs) of the two buildings with the same envelope under 14 cities' climatic conditions in China, America and Europe respectively by DOE-2, DeST-h and CTM. It can be found that though the absolute increments of annual cooling and heating needs are obviously different in various cities with the same increase of Shape Coefficient, the annual relative variation rates (RVRs) of cooling and heating need are approximate in different cities.

  • Identifications: the relative variation rates (RVRs) of cooling and heating are approximately the same in different cities with the same increase of Shape Coefficients
    Building and Environment, 2005
    Co-Authors: Long Enshen
    Abstract:

    Among 14 background cities, Boulder of America and Shanghai of China which differ in climatic conditions are selected for comparison. Taking the building with traditional envelope when the ventilation rate is 0 as an example, this paper studies the variation laws of hourly, daily and monthly relative variation rates (RVRs) with the same increase of Shape Coefficient in the two cities. By comparisons, we find that though there exists significant difference in annual heating and cooling hours, days and months between Boulder and Shanghai, the distribution laws of hourly, daily and monthly RVRs are very similar and their variation ranges are also approximately the same in the two cities. This similarity in hourly, daily and monthly distribution determines the inevitable approximate equality of the annual heating and cooling RVRs in different cities and thus the proposition is right in a wide range.

Feng Qi - One of the best experts on this subject based on the ideXlab platform.

  • regional similarity of Shape Coefficient of rural residences taking hangzhou rural region as a case
    Building Simulation, 2019
    Co-Authors: Feng Qi, Wenlong Lv, Tailong Zhang, Brian Mutale Musonda
    Abstract:

    Shape Coefficient (SC) is an important factor affecting energy consumption of residential buildings. Due to lack of suitable and efficient methods for building three-dimensional data acquisition, there are few studies on the regional characteristics of rural residential SC. In view of this, taking the rural residential buildings in Hangzhou as the case, a new analysis method for regional similarity of rural residential Shape Coefficient at the municipal level is presented in this paper. This method contains four steps of work. Firstly, the applicability tests need to be conducted for the selected remote sensing images in Google Earth. Secondly, Hangzhou is divided into several sub-regions and the sample villages are selected in each sub-region. Thirdly, SC of rural residences in each sample village can be obtained based on Google Earth. Lastly, regional similarity of residential SC can be analyzed at municipal level by cluster analysis method. The case study shows that there are obvious regional similarity characteristics for the SC of rural residences. When the clustering distance is 10, the sample villages can be divided into three types, namely type A villages, type B villages and type C villages which have different mean and standard deviation. The new method makes it feasible to assess the geographical distribution characteristics of SC of a certain type of buildings, which can provide basic reference data not only for policymakers to make the most suitable building retrofit policy but also for building designers to conduct energy efficiency designs at regional scale.

  • Regional similarity of Shape Coefficient of rural residences—Taking Hangzhou rural region as a case
    Building Simulation, 2019
    Co-Authors: Feng Qi, Wenlong Lv, Tailong Zhang, Brian Mutale Musonda
    Abstract:

    Shape Coefficient (SC) is an important factor affecting energy consumption of residential buildings. Due to lack of suitable and efficient methods for building three-dimensional data acquisition, there are few studies on the regional characteristics of rural residential SC. In view of this, taking the rural residential buildings in Hangzhou as the case, a new analysis method for regional similarity of rural residential Shape Coefficient at the municipal level is presented in this paper. This method contains four steps of work. Firstly, the applicability tests need to be conducted for the selected remote sensing images in Google Earth. Secondly, Hangzhou is divided into several sub-regions and the sample villages are selected in each sub-region. Thirdly, SC of rural residences in each sample village can be obtained based on Google Earth. Lastly, regional similarity of residential SC can be analyzed at municipal level by cluster analysis method. The case study shows that there are obvious regional similarity characteristics for the SC of rural residences. When the clustering distance is 10, the sample villages can be divided into three types, namely type A villages, type B villages and type C villages which have different mean and standard deviation. The new method makes it feasible to assess the geographical distribution characteristics of SC of a certain type of buildings, which can provide basic reference data not only for policymakers to make the most suitable building retrofit policy but also for building designers to conduct energy efficiency designs at regional scale.

  • a new calculation method for Shape Coefficient of residential building using google earth
    Energy and Buildings, 2014
    Co-Authors: Feng Qi, Yixiang Wang
    Abstract:

    Abstract Shape Coefficient is a key factor to evaluate building energy efficiency. But few investigations have been done on calculating Shape Coefficient for existing building using Google Earth. Based on Google Earth, GIS slope analysis, astronomy principle and geometry, a new calculation method for Shape Coefficient of residential building is presented in this paper. Conditions such as date of shooting RS image, slope angle, solar elevation angle and solar azimuth are discussed for its practical application. From a case study of residential buildings in Lin’an city, the new method is found to be more efficient than field measurement at the same precision level. Due to its great convenience in calculating building Shape Coefficient this new method is especially applicable to evaluate energy-saving potential of existing buildings in a certain area.

Li Zheng - One of the best experts on this subject based on the ideXlab platform.

Yixiang Wang - One of the best experts on this subject based on the ideXlab platform.

  • a new calculation method for Shape Coefficient of residential building using google earth
    Energy and Buildings, 2014
    Co-Authors: Feng Qi, Yixiang Wang
    Abstract:

    Abstract Shape Coefficient is a key factor to evaluate building energy efficiency. But few investigations have been done on calculating Shape Coefficient for existing building using Google Earth. Based on Google Earth, GIS slope analysis, astronomy principle and geometry, a new calculation method for Shape Coefficient of residential building is presented in this paper. Conditions such as date of shooting RS image, slope angle, solar elevation angle and solar azimuth are discussed for its practical application. From a case study of residential buildings in Lin’an city, the new method is found to be more efficient than field measurement at the same precision level. Due to its great convenience in calculating building Shape Coefficient this new method is especially applicable to evaluate energy-saving potential of existing buildings in a certain area.

Ji Zhou - One of the best experts on this subject based on the ideXlab platform.

  • the test study of Shape Coefficient of low rise buildings roof with different positions of openings
    Advanced Materials Research, 2012
    Co-Authors: Ji Zhou
    Abstract:

    The majority of low-rise buildings are generally susceptible to wind damage in previous wind disaster, thus it is necessary to gain understanding of the characteristics of wind pressure for these types of building. Based on Wind Tunnel Test, the Shape Coefficients were studied with pressure measurement on gable roofs laying aside purlin of low-rise building roof in this paper. Three aspects were arerespectively discussed: the lows of Shape Coefficients and the Shape Coefficient value with specific wind angle on roofs of the houses completely closed, the house opened doors and windows and the house opened the hole on roof with different wind angle. The laws of Shape Coefficients were propounded for low-rise buildings with different positions of openings in contrast to load code. A detailed analysis of the experimental results shows that the Shape Coefficients will increase notably when there are the openings on metope and on roof, and the one is outward of roof, another is inward of roof. It is expected that the results should be valuable for the wind-resistance design of low-rise buildings.

  • The Analysis on Shape Coefficient of Low-Rise Buildings Wall
    Applied Mechanics and Materials, 2011
    Co-Authors: Ji Zhou
    Abstract:

    In order to improve the wind resistance of single-storey house in the rural areas, this paper has carried countryside house's rigid model on the wind tunnel test in view of the south area. This paper has studied Coefficient distributed rules of the single-layer house building and calculates the Shape Coefficient under various wind angles, and draws the build Coefficient distribution figure finally. The result indicated that when the wind angles are 0 or 90 degrees, the front wall is most unsafe. When the wind angles are 60, 90, 150, 180 degrees the back wall is unsafe. When the wind angles are 0, 180 degrees wind angles, the flank wall are unsafe. But speaking of the entire house, 0 degrees wind angles is the unsafe wind angles.