Intelligent evaluation and optimization method for coupling of block space intensification and climate adaptability

Abstract

The invention discloses an intelligent evaluation and optimization method for coupling of block space intensification and climate adaptability, and relates to the technical field of high-density city updating, and the method comprises the steps: constructing a space intensification and climate adaptability coupling evaluation framework of a city plot; and based on a space intensification and climate adaptability coupling evaluation framework of the urban plot, constructing an urban plot building form and climate adaptability index identification and evaluation method. Through quantitative evaluation of coupling of multi-dimensional indexes such as plot building form composition and climate adaptation, the method can deeply participate in the early-stage design stage of city updating, and timely and effectively feed back the influence of form design change on the block plot wind environment, thereby better assisting scheme design optimization.

Description

Technical Field

[0001] This invention relates to the field of urban renewal technology, and in particular to an intelligent evaluation and optimization method that couples the spatial intensification and climate adaptability of neighborhoods. Background Technology

[0002] High-density urban blocks typically exhibit complex spatial structures and hierarchical characteristics. This spatial heterogeneity leads to differentiated wind comfort requirements for outdoor spaces at different levels. Simultaneously, the morphological layout of buildings affects the wind environment on building surfaces, thus influencing building energy consumption. However, in past urban renewal designs, considerations for morphological layout and wind environment optimization have often relied on practical experience, lacking scientific quantitative methods. This makes it difficult to fully understand the impact mechanism of block morphological intensification on microclimate. Furthermore, previous climate adaptability analyses have mostly served as supplementary analyses to the final design, with limited in-depth involvement in the design phase and failing to provide timely feedback on morphological changes during the design process. Therefore, in the era of high-quality urban construction, sustainable renewal of high-density cities presents new requirements for constructing a methodology capable of real-time quantitative evaluation of block morphological intensification and climate adaptability, as well as the coupling mechanism of their impact.

[0003] Existing technologies have limitations in effectively quantifying and analyzing the optimization of morphology and wind environment during urban renewal, and in providing rapid feedback on the impact of morphological changes on climate adaptation during the renewal design process. Summary of the Invention

[0004] The technical problem to be solved by this invention is to overcome the shortcomings of the prior art and provide an intelligent evaluation and optimization method that couples the spatial intensification and climate adaptability of urban blocks. This invention participates in the early design stage of urban renewal and can provide timely feedback on the impact of morphological changes on the wind environment of urban blocks during the design process, providing scientific quantitative guidance for morphological design and wind environment optimization.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] A smart evaluation and optimization method for coupling street space intensification and climate adaptability, proposed according to the present invention, includes:

[0007] Construct a coupled evaluation framework for the spatial intensification and climate adaptability of urban land parcels;

[0008] Based on the coupled evaluation framework of spatial intensification and climate adaptability of urban plots, a method for identifying and evaluating the indicators of building form and climate adaptability of urban plots is constructed.

[0009] As a further optimization of the intelligent evaluation and optimization method for coupling the spatial intensification and climate adaptability of urban blocks described in this invention, a framework for evaluating the coupling of spatial intensification and climate adaptability of urban plots is constructed; specifically as follows:

[0010] For urban plots, a four-dimensional evaluation framework for spatial compactness and climate adaptability is constructed from the perspectives of morphology and climate adaptation. The four dimensions include building density, configuration level, outdoor wind environment, and building wind pressure.

[0011] As a further optimization of the intelligent evaluation and optimization method for coupling urban street space intensification and climate adaptability described in this invention, a method for identifying and evaluating urban plot building morphology and climate adaptability indicators is constructed based on the evaluation framework for the coupling of urban plot space intensification and climate adaptability; specifically as follows:

[0012] Step 2.1: Select the building density and plot ratio of the land parcel as key indicators of reaction density;

[0013] Step 2.2: Divide the land parcel into spatial units;

[0014] Step 2.3: Use depth, connectivity and accessibility to quantify the morphological configuration of spatial units to obtain the configuration quantification of spatial units;

[0015] The configuration quantification is based on spatial units, followed by overall configuration quantification of the land parcels.

[0016] Step 2.4: Identify and evaluate outdoor space wind environment indicators;

[0017] Step 2.5: Identify and evaluate wind environment indicators on building surfaces.

[0018] As a further optimization scheme of the intelligent evaluation and optimization method for coupling the spatial intensification and climate adaptability of the block as described in this invention, according to steps 2.1-2.5, an automatic calculation battery pack is constructed based on the Grasshopper platform to calculate the indicators of plot density, spatial unit division, spatial unit configuration quantification, outdoor wind environment, and building surface wind environment. Based on the automatic calculation battery pack, the indicators of four dimensions, namely building density, configuration level, outdoor wind environment, and building wind pressure, are calculated to evaluate the design scheme of the block renewal and to compare and optimize the different block renewal design schemes.

[0019] As a further optimization scheme of the intelligent evaluation and optimization method for coupling the spatial intensification and climate adaptability of urban blocks described in this invention, step 2.2 includes:

[0020] First, based on the spatial relationships, lines are drawn from the building endpoints to the nearest points of each outline, and then filtered to obtain preliminary control lines.

[0021] Secondly, constrained denaulay triangulation is performed using control lines, building outlines, and site outlines to form a triangular mesh unit grid.

[0022] Finally, based on the principles of merging the longest sides and avoiding concave corners, the triangular mesh units in the triangular mesh are merged to form the final spatial unit partitioning result.

[0023] As a further optimization scheme of the intelligent evaluation and optimization method for coupling the spatial intensification and climate adaptability of urban blocks described in this invention, step 2.3 includes:

[0024] The morphological configuration of spatial units is quantitatively described using depth, connectivity, and accessibility.

[0025] Depth is the topological distance between a spatial cell and a reference street: the depth of the reference street is 0, the depth of a spatial cell directly connected to it is 1, and the depth of a spatial cell connected to it through another z spatial cells is z+1.

[0026] Connectivity is the number of spatial units that are directly connected to a given spatial unit;

[0027] Accessibility is the product of the difference between the depth of a spatial unit and the maximum depth within a block and the connectivity of that spatial unit.

[0028]

[0029] in, For spatial unit accessibility, C i and D i These represent the connectivity and depth of spatial units, respectively, D max The maximum depth of a spatial unit within the block;

[0030] The overall configuration of the land parcel is defined by both the accessibility per unit area and the diversity of land parcel configurations;

[0031] Accessibility per unit area refers to the accessibility of the weighted spatial unit area;

[0032]

[0033] Among them, AC i and A i AC represents the reachability and area of ​​the i-th spatial unit, respectively. plot For land parcel accessibility, n is the total number of spatial units.

[0034] As a further optimization scheme of the intelligent evaluation and optimization method for coupling the spatial intensification and climate adaptability of the block as described in this invention, the diversity of plot configuration reflects the ratio of the number of combinations of different depths and connectivity of each plot to the number of spatial units.

[0035] As a further optimization scheme for the intelligent evaluation and optimization method of street space intensification and climate adaptability coupled as described in this invention,

[0036] Ansys-Fluent software was used to conduct urban wind environment simulation experiments to quantitatively analyze the wind environment at pedestrian height in the outdoor space within the plot; and the area ratio of comfortable wind speed was selected as an indicator to measure the comfort of the outdoor wind environment.

[0037]

[0038] Where V represents the area ratio of comfortable wind speed, V i N represents the number of simulated wind speed measurement points within the comfortable wind speed range.

[0039] As a further optimization scheme of the intelligent evaluation and optimization method for coupling the spatial intensification and climate adaptability of urban blocks described in this invention, step 2.5 includes:

[0040] The standard deviation of the overall wind pressure of the site is used as an indicator to evaluate the wind environment on the building surface;

[0041] First, calculate the standard deviation of wind pressure for each building within the plot:

[0042]

[0043] in, Let P be the standard deviation of wind pressure for the I-th building unit. i Let i be the wind pressure value at the i-th point in the i-th floor of the i-th building. denoted as the average wind pressure of all sampling points on the I-th building floor, and 'a' is the total number of wind pressure sampling points on the surface of the building floor.

[0044] Secondly, at the plot scale, the overall wind pressure standard deviation of the plot is obtained by weighted averaging of the standard deviations of the wind pressure of each single floor of all buildings within the plot.

[0045]

[0046] in, The standard deviation of wind pressure for the entire plot. For the first Standard deviation of wind pressure for a single building floor For the first The building area of ​​a single floor of a building. This represents the total number of floors in all buildings within the block.

[0047] Compared with the prior art, the present invention, employing the above technical solution, has the following technical effects:

[0048] By conducting quantitative evaluations that couple multiple indicators such as the building form composition and climate adaptability of the plot, we can deeply participate in the early design stage of urban renewal, provide timely and effective feedback on the impact of changes in form design on the wind environment of the block, and thus better assist in optimizing the design scheme. Attached Figure Description

[0049] Figure 1 A schematic diagram of a coupled evaluation framework for urban land use spatial intensification and climate adaptability;

[0050] Figure 2 Grasshopper program battery pack for automatically calculating urban land density-related indicators;

[0051] Figure 3 The Grasshopper program automatically identifies and divides battery packs into spatial units;

[0052] Figure 4 The Grasshopper program automatically calculates battery packs for spatial configuration hierarchy indicators.

[0053] Figure 5 Grasshopper program battery pack for automatic calculation of outdoor space wind environment indicators;

[0054] Figure 6 Grasshopper program battery pack for automatic calculation of wind environmental indicators for building surfaces;

[0055] Figure 7 This is a schematic diagram of the demonstration project building;

[0056] Figure 8 Schematic diagram of spatial unit division for the demonstration project;

[0057] Figure 9 The results of spatial unit connectivity calculations for the demonstration project are shown (the darker the color of the spatial unit, the weaker the connectivity).

[0058] Figure 10 The results of spatial unit depth calculation for the demonstration project (the darker the color of the spatial unit, the deeper the depth).

[0059] Figure 11 The results of accessibility calculations for spatial units in the demonstration project are shown (the darker the color of the spatial unit, the weaker its accessibility).

[0060] Figure 12 The results of the calculation of the proportion of comfortable wind speed in the spatial units of the demonstration project;

[0061] Figure 13 The results of wind pressure calculations for the building layers in the demonstration project. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0063] 1. Construct a coupled evaluation framework for urban land use spatial intensification and climate adaptability.

[0064] For urban plots, a coupled evaluation framework for spatial compactness and climate adaptability is constructed from two perspectives: morphology and climate adaptation. This framework considers four dimensions: building density, structural hierarchy, outdoor wind environment, and building wind pressure. Figure 1 As shown, in the process of urban renewal, the rapid feedback on the impact of changes in the design scheme on the four-dimensional evaluation indicators of this assessment framework helps to scientifically optimize the renewal design scheme.

[0065] The identification and evaluation methods for the four dimensions of morphological and climate adaptation are as follows:

[0066] 2. Methods for Identifying and Evaluating Urban Plot Building Morphology and Climate Adaptability Indicators

[0067] 2.1 Identification and Calculation of Density-Related Urban Morphology Indicators:

[0068] There are various mature indicators for measuring urban density, such as population density, building density, and floor area ratio. Since the density of block plots, which is related to the wind environment, needs to be reflected in the physical space, this study selects building density and floor area ratio at the plot level as key indicators of density. Table 1 shows the urban morphology indicators related to plot-level density.

[0069] Table 1

[0070]

[0071] Building computing battery packs in the Grasshopper platform, such as Figure 2 As shown.

[0072] 2.2 Identification and division of spatial units:

[0073] In the urban built environment, accurately identifying and representing the morphological layout of buildings on a site is crucial. At the block and site scale, urban morphology has mature geometric and structural representation methods. However, in the built environment, the layout of buildings and public spaces within a site is more complex, and existing morphological representation systems are insufficient to clearly analyze the complex spatial relationships within the site. Therefore, based on existing morphological representations, this paper optimizes the method of dividing outdoor space units and further subdivides the spatial units within the site, laying the foundation for accurately representing the morphology of buildings on the site and for subsequent quantitative analysis of the wind environment.

[0074] The specific steps are as follows:

[0075] First, based on spatial relationships, lines are drawn from the building endpoints to the nearest points on each contour, and these are then filtered to obtain preliminary control lines. Second, constrained Denaulay triangulation is performed using the control lines, building contours, and site contours. Finally, based on the principles of merging the longest sides and avoiding concave angles, the triangulation units are merged to form the final spatial division result.

[0076] Building computing battery packs in the Grasshopper platform, such as Figure 3 As shown.

[0077] 2.3 Spatial Configuration Hierarchy Evaluation Method:

[0078] After dividing the space into units, the morphological configuration of the units is quantitatively described by depth, connectivity, and accessibility.

[0079] Depth describes the topological distance between a spatial unit and a benchmark street (usually a main or secondary urban road): the depth of the benchmark street is 0, the depth of a spatial unit directly connected to it is 1, the depth of a spatial unit connected to it through another spatial unit is 2, and so on. The greater the depth, the higher the topological distance cost required to reach the spatial unit from the benchmark street.

[0080] Connectivity describes the number of other spatial units that are directly connected to a given spatial unit. The higher the connectivity, the more path options there are to reach that unit, and the more important it is in the pedestrian system.

[0081] Accessibility describes the product of the difference between the depth of a spatial unit and the maximum depth within a block, and the connectivity of that spatial unit. Higher accessibility indicates more path options to that spatial unit, and thus greater importance in the pedestrian system. Where C... i and D i These represent the connectivity and depth of spatial units, respectively, D max AC represents the maximum depth of a spatial unit within a block. Unit For spatial unit accessibility.

[0082] The overall spatial configuration at the plot level is jointly defined by accessibility per unit area and plot configuration diversity. Accessibility per unit area is the accessibility of a weighted spatial unit area. Higher accessibility indicates more path options to the plot, making it easier and faster to reach. The formulas are shown in Table 2, which presents the spatial configuration indices for the spatial unit level and the plot level, where AC... i and A i These represent the accessibility and area of ​​a spatial unit, respectively. Plot Accessibility per unit area of ​​a site. Site configuration diversity reflects the ratio of the number of different depth-connectivity combinations to the number of spatial units. The greater the configuration diversity, the richer the spatial types of the site.

[0083] Table 2

[0084]

[0085] Building computing battery packs in the Grasshopper platform, such as Figure 4 As shown.

[0086] 2.4 Identification and Assessment of Outdoor Space Wind Environment Indicators:

[0087] In high-density urban environments, the wind environment at pedestrian height is difficult to predict simply based on experience due to the complex spatial morphology. Among commonly used wind environment research methods, Computational Fluid Dynamics (CFD) simulation offers advantages such as low cost, high speed, and the ability to simulate unbuilt design schemes. Therefore, this invention uses Ansys-Fluent software to conduct wind environment simulation experiments in high-density cities, quantitatively analyzing the wind environment at pedestrian height in outdoor spaces within a site. The area ratio of comfortable wind speed is selected as an indicator of wind environment comfort. The formulas are shown in Table 3, which represents the outdoor wind environment indicators at the site level, where V... i The simulated wind speed measurement points are those within the comfortable wind speed range, and N is the total number of simulated wind speed measurement points. Existing research shows that the required comfortable wind speed at pedestrian height varies in different seasons. Based on existing research, this invention defines comfortable wind speed as: 1 m / s-5 m / s in summer and 1 m / s-2 m / s in winter. The specific steps for evaluating the wind environment comfort of the site are as follows:

[0088] 1. Construct a three-dimensional model of the urban space to be studied.

[0089] 2. Import the city model into Ansys-Fluent for wind environment simulation.

[0090] 3. Output the wind speed simulation results for the research area.

[0091] 4. Import the obtained wind speed results from the measurement points into the Grasshopper platform.

[0092] 5. Using the constructed Figure 5 The battery pack automatically calculates the percentage of outdoor comfortable wind speed at the plot scale.

[0093] Table 3

[0094]

[0095] 2.5 Identification and Assessment of Wind Environmental Indicators for Building Surfaces:

[0096] Building-scale sustainability can be assessed through building energy consumption, and the uniformity of wind pressure distribution on building surfaces directly affects ventilation driving force, i.e., natural ventilation potential. Specifically, wind pressure distribution characteristics can be quantified by the wind pressure standard deviation to influence ventilation volume and air exchange rate: the higher the ventilation potential, the more significant the reduction in building energy consumption. Based on this, this invention proposes using stratified wind pressure standard deviation as the core indicator for evaluating building sustainability. The formula is shown in Table 4, where P... i Let be the wind pressure value (Pa) at the i-th point. Let N be the average wind pressure (Pa) at all sampling points, and N be the total number of wind pressure sampling points on a single floor of the building. This is the standard deviation (Pa) of wind pressure on a single building surface (the four exterior facades of the building, excluding the roof). This indicator measures the degree of wind pressure fluctuation on a single building surface. The larger the standard deviation, the more uneven the wind pressure distribution on the building surface. This reflects the significant difference between positive and negative wind pressure zones on the building surface, which in turn creates a stronger ventilation driving force, meaning that the building has better natural ventilation potential.

[0097] At the plot scale, the overall wind pressure standard deviation of the plot can be obtained by weighted averaging of the stratified wind pressure standard deviations of all buildings within the plot. The formula is shown in Table 4, which contains the building surface wind environment indicators at the overall plot level. The standard deviation of wind pressure for the entire plot (Pa) is given. For the first Standard deviation of wind pressure (Pa) for a single floor of a building. For the first The building area (m²) of a single floor of a building. This represents the total number of floors in all buildings within the block. This indicator reflects the weighted average of the overall block's wind pressure standard deviation, taking into account the impact of the floor area of ​​each floor in each building. Weighted by floor area, the larger the floor area, the greater the scale of usable space affected by wind pressure, and the better it reflects the overall ventilation effect of the block. It allows for a more comprehensive assessment of the site's overall natural ventilation potential and its impact on energy consumption.

[0098] Table 4

[0099]

[0100] Building computing battery packs in the Grasshopper platform, such as Figure 6 As shown.

[0101] 3. Sample Cases

[0102] This method constructs a site evaluation framework that couples spatial intensification and climate adaptability. Through the steps outlined above, a selected site is comprehensively evaluated across four dimensions: development density, morphological configuration, outdoor comfort, and building energy consumption. This approach helps in the sustainability assessment of different design schemes in urban renewal processes, considering the coupling of morphological layout and wind environment, providing more scientific design guidance for renewal strategies, and facilitating comparison among different renewal options. A demonstration is provided using the renovation and expansion project of the ward building at the Nanjing First Hospital Hexi Campus as an example. Figure 7 This is a schematic diagram of the demonstration project building; Figure 8 Schematic diagram of spatial unit division for the demonstration project; Figure 9 The results of spatial unit connectivity calculations for the demonstration project are shown (the darker the color of the spatial unit, the weaker the connectivity). Figure 10 The results of spatial unit depth calculation for the demonstration project (the darker the color of the spatial unit, the deeper the depth). Figure 11 The results of accessibility calculations for spatial units in the demonstration project are shown (the darker the color of the spatial unit, the weaker its accessibility). Figure 12 The results of the calculation of the proportion of comfortable wind speed in the spatial units of the demonstration project; Figure 13 The results of wind pressure calculations for the building layers in the demonstration project.

[0103] This method uses the constructed grasshopper to automatically calculate the morphological changes of the battery pack during the design process of the demonstration project and their impact on the outdoor and building wind environment in a timely manner, forming a real-time evaluation framework that couples spatial compactness and climate adaptability, helping to optimize the design of the project and contributing to the urban renewal of high-density blocks.

[0104] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for intelligent evaluation and optimization of block space intensity and climate adaptability coupling, characterized in that, include: Construct a coupled evaluation framework for the spatial intensification and climate adaptability of urban land parcels; Based on the coupled evaluation framework of spatial intensification and climate adaptability of urban plots, a method for identifying and evaluating the indicators of building form and climate adaptability of urban plots is constructed.

2. The method of claim 1, wherein, A coupled evaluation framework for the spatial intensification and climate adaptability of urban land parcels is constructed; the details are as follows: For urban plots, a four-dimensional evaluation framework for spatial compactness and climate adaptability is constructed from the perspectives of morphology and climate adaptation. The four dimensions include building density, configuration level, outdoor wind environment, and building wind pressure.

3. The method of claim 1, wherein, Based on a coupled evaluation framework of spatial intensification and climate adaptability of urban plots, a method for identifying and evaluating urban plot building morphology and climate adaptability indicators is constructed; the details are as follows: Step 2.1: Select the building density and plot ratio of the land parcel as key indicators of reaction density; Step 2.2: Divide the land parcel into spatial units; Step 2.3: Use depth, connectivity and accessibility to quantify the morphological configuration of spatial units to obtain the configuration quantification of spatial units; The configuration quantification is based on spatial units, followed by overall configuration quantification of the land parcels. Step 2.4: Identify and evaluate outdoor space wind environment indicators; Step 2.5: Identify and evaluate wind environment indicators on building surfaces.

4. The method of claim 3, wherein, According to steps 2.1-2.5, an automatic calculation battery pack is constructed based on the Grasshopper platform to calculate the indicators of plot density, spatial unit division, spatial unit configuration quantification, outdoor wind environment, and building surface wind environment. Based on the automatic calculation battery pack, the indicators of four dimensions, namely building density, configuration level, outdoor wind environment, and building wind pressure, are calculated to evaluate the design scheme of the block renewal and to compare and optimize the different block renewal design schemes.

5. The method of claim 3, wherein, Step 2.2 includes: First, based on the spatial relationships, lines are drawn from the building endpoints to the nearest points of each outline, and then filtered to obtain preliminary control lines. Secondly, constrained denaulay triangulation is performed using control lines, building outlines, and site outlines to form a triangular mesh unit grid. Finally, based on the principles of merging the longest sides and avoiding concave corners, the triangular mesh units in the triangular mesh are merged to form the final spatial unit partitioning result.

6. The method of claim 3, wherein, Step 2.3 includes: The morphological configuration of spatial units is quantitatively described using depth, connectivity, and accessibility. Depth is the topological distance between a spatial cell and a reference street: the depth of the reference street is 0, the depth of a spatial cell directly connected to it is 1, and the depth of a spatial cell connected to it through another z spatial cells is z+1. Connectivity is the number of spatial units that are directly connected to a given spatial unit; Accessibility is the product of the difference between the depth of a spatial unit and the maximum depth within a block and the connectivity of that spatial unit. ； where, C for spatial unit reachability, i and D for spatial unit connectivity and depth, respectively, i D for spatial unit connectivity and depth, respectively, max Dmax for the maximum depth of spatial units within a block; The overall configuration of the land parcel is defined by both the accessibility per unit area and the diversity of land parcel configurations; Accessibility per unit area refers to the accessibility of the weighted spatial unit area; ； where AC i and A i are the accessibility and area of the ith spatial unit, respectively, AC plot is the plot accessibility, and n is the total number of spatial units.

7. The method of claim 5, wherein, The diversity of land parcel configurations reflects the ratio of the number of combinations of different depths and connectivity of land parcels to the number of spatial units.

8. The intelligent evaluation and optimization method for coupling street space intensification and climate adaptability according to claim 3, characterized in that, The Ansys-Fluent software is selected to simulate the wind environment of the city, and the outdoor space of the land is quantitatively analyzed in terms of the height of the wind environment of the people; and the area ratio of the comfortable wind speed is selected as an index to measure the comfort of the outdoor space of the wind environment; ； Wherein, V is the comfortable wind speed area ratio, V i is the simulated wind speed measurement point in the comfortable wind speed interval, and N is the total number of simulated wind speed measurement points.

9. The method of claim 3, wherein, Step 2.5 includes: The standard deviation of the overall wind pressure of the land is used as an index to evaluate the wind environment of the building surface; First, the layered wind pressure standard deviation of each building in the land is calculated: ； wherein, P is the standard deviation of wind pressure of the Ith building floor, i Pi is the wind pressure value at the ith point of the Ith building floor, P is the average value of wind pressure of all sampling points of the Ith building floor, and a is the total number of wind pressure sampling points on the surface of the building floor. Secondly, at the land scale, the layered wind pressure standard deviation of all single-layer buildings in the land is weighted and averaged to obtain the overall wind pressure standard deviation of the land. ； wherein, is the standard deviation of the wind pressure for the entire plot, is the standard deviation of the wind pressure for the th building single story, is the building area of the th building single story, is the total number of stories for all buildings in the block.

Images