CN109063388A - The micro climate architecture design addressing design method of wind environment simulation - Google Patents
The micro climate architecture design addressing design method of wind environment simulation Download PDFInfo
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Abstract
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, which comprises the steps of: obtains climatic data, hydrographic data and the terrain data in target plot.The physical model in target plot is established according to climatic data, hydrographic data and terrain data.Physical model is subjected to grid dividing and is separated into calculating grid model.Building CA model is iterated calculating to grid model is calculated, to obtain the physical descriptor of target.It is multiple Land units by target Parcel division, to obtain the unit physical descriptor of each Land unit.Unit physical descriptor is matched with the environmental variance of micro climate architecture design addressing design by big data algorithm, to obtain the matching degree of unit physical descriptor and environmental variance, further according to the height of matching degree to obtain the plot scoring of each Land unit, further according to the height of plot scoring, selection is suitable for the building that each Land unit is arranged from building library.
Description
Technical field
The present invention relates to evaluation analog analysing methods, and in particular to the micro climate architecture design addressing design of wind environment simulation
Method belongs to siteselecting planning design field.
Background technique
It makes people be increased to a new level to the understanding of ecological environment and building ecological to arcology, it is
Based on the Technologies in Construction Planning Design theory and method on ecological principle.So-called ecotecture is exactly according to local natural environment
With ecology, the basic principle of Building Technology Science, modern science and technology means etc., reasonable arrangement and organizing construction and other
Relationship between correlative factor, build it becomes an organic combination between environment.Simultaneously and there is good interior
Weather conditions and stronger bioclimate regulating power.To meet people's life, the required a home from home that works, make one, build
A benign cycle system is formed between natural ecological environment.Dynamic process and the external environment factor about Architectural foundation
Relationship between Architectural foundation is the major issue in Architectural foundation ecology development process, causes ecologists'
Extensive concern.Regional ecology is more sparse, is in spot block distribution, and change in time and space amplitude is larger more, and the ecosystem is particularly important,
In addition the interference of mankind's activity, ecological characteristic are significant for stablizing for this area's ecological environment, can play and conserve water and soil
Effect.Life, work required a home from home, makes one, and forms a benign cycle between building and natural ecological environment and is
System
Influence building Distribution Pattern and dynamic because being known as very much, interaction relationship therebetween is sufficiently complex.About putting
It is relatively more to herd the research influenced on the Ecological Patterns of building, and about environmental factor each under long period sequence to building
The research of the influence of Ecological Patterns is less.
Common Architectural foundation design selects situation of building and type according to design experiences by designer, makes building
Not high with the matching degree in plot, construction pattern lacks ecological.The present invention will be assessed using CA modelling, and CA modelling mentions
Supply integrated Markov chain and CA function in the CA model of one.More characteristic, CA model can be evaluated with multi-standard
And multiobjective decision-making supports system to define the rule shifted between land use pattern.CA model is in application Markov chain to not
Come on the basis of land use quantitative structure Accurate Prediction, the analog capability of spatial framework is strengthened by Domain relation analysis.
Therefore effectively land use structure quantity and spatial distribution can be predicted.The present invention is further corresponded to using except trend
Analysis and two kinds of sort methods of Canonical correspondence analysis analyze Architectural foundation feature and the correlation of each factor, and selection is suitable for
The building that plot is built, it is intended to provide theoretical foundation for micro climate architecture design addressing design.
Summary of the invention
To solve the above problems, present invention employs following technical solutions:
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, for selecting appropriate target
The building that block is built, which comprises the steps of:
Step S1 obtains the climatic data in target plot；
Step S2 obtains the hydrographic data in target plot；
Step S3, obtains the terrain data in target plot, which contains at least two level of detail；
Step S4, terrain data and hydrographic data are imported into modeling software to establish the physical model in target plot and
According to the initial physical condition and boundary of climatic data and hydrographic data setting physical model；
Physical model is carried out grid dividing and is separated into calculating grid model by step S5；
Step S6 will calculate grid model and import fluid calculation numerical simulation software, by building CA model to calculating net
Lattice model is iterated calculating, to obtain the physical descriptor in target plot；
Target Parcel division is multiple Land units, to be obtained often according to the physical descriptor in target plot by step S7
The unit physical descriptor of a Land unit；
Step S8 is carried out by environmental variance of the computer to unit physical descriptor and micro climate architecture design addressing design
Matching, to obtain the matching degree of unit physical descriptor and environmental variance, the height further according to matching degree is to obtain eachly
The plot of module unit is scored, and further according to the height of plot scoring, selection is suitable for what each Land unit was built from building library
Building, to complete micro climate architecture design addressing design.
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, can also have such spy
Sign, wherein the physical descriptor in step S8 includes multiple individual event unit physical descriptors, each individual event unit physical descriptor and environment
Corresponding item environment variable is matched in variable, so that the individual event unit physical descriptor for obtaining each Land unit is commented
Point, it is added each individual event unit physical descriptor scoring of Land unit to obtain plot scoring.
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, can also have such spy
Sign, wherein individual event unit physical descriptor is temperature, wind speed, humidity and the air pressure of each Land unit.
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, can also have such spy
Sign, wherein climatic data include by the firsthand information of the weather system in meteorologic instrument target plot obtained and according to
The data that firsthand information is reorganized.
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, can also have such spy
Sign, wherein terrain data is the remote sensing image that target plot is obtained by satellite remote sensing technology.
The present invention provides a kind of micro climate architecture design addressing design methods of wind environment simulation, can also have such spy
Sign, wherein hydrographic data includes the individual event hydrographic data and root in multiple target plot obtained by observation and copmputing laboratory
According to maximum value, minimum value, average value, total amount, graph and the isopleth of the obtained individual event hydrographic data of individual event hydrographic data,
Individual event hydrographic data is precipitation, evaporation capacity, water level, flow and the silt content in target plot.
Invention action and effect
The micro climate architecture design addressing design method of wind environment simulation according to the present invention, due to obtaining the gas in target plot
Data, hydrographic data and terrain data are waited, therefore terrain data and hydrographic data can be imported modeling software to establish
The physical model in target plot and initial physical condition and the boundary that physical model is set according to climatic data and hydrographic data.
Since terrain data contains at least two level, various virtual scene demands needed for can satisfy evaluation simulation.
Since physical model is carried out grid dividing and is separated into calculating grid model, it can will calculate grid model and import calculating
Numerical simulation software, and calculating is iterated to grid model is calculated by building CA model, to obtain the object in target plot
Manage variable.Due to being iterated calculating by computer, what is calculated is more efficient, as a result more acurrate.Due to by target
Block is divided into multiple Land units, therefore the unit physics of each Land unit can be obtained according to the physical descriptor in target plot
Variable.Since the environmental variance to unit physical descriptor and micro climate architecture design addressing design carries out matching scoring, energy
The selection from building library of enough height to be scored according to plot is suitable for the building that each Land unit is built, and is built to complete micro climate
Build addressing design.Due to carrying out matching scoring by computer, matching is scored more efficient, as a result more acurrate.
Detailed description of the invention
Fig. 1 is the physical model schematic diagram of the embodiment of the present invention；
Fig. 2 is the calculating grid model schematic diagram of the embodiment of the present invention；
Fig. 3 is the mean temperature cloud atlas in the target plot of the embodiment of the present invention；
Fig. 4 is the wind speed cloud atlas in the target plot of the embodiment of the present invention；
Fig. 5 is the wind vector figure in the target plot of the embodiment of the present invention；
Fig. 6 is the ground block analysis schematic diagram in the target plot of the embodiment of the present invention；
In figure, 10- building；The waters 20-；The land 30-.
Specific embodiment
In order to be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, tie below
Attached drawing is closed to be specifically addressed the micro climate architecture design addressing design method of wind environment simulation of the invention.
As shown in Figure 1, the target plot in the present embodiment includes building 10, waters 20 and land 30.
As shown in Fig. 1~Fig. 6, the micro climate architecture design addressing design method of the present embodiment, includes the following steps:
Step S1 obtains the climatic data in target plot；
Step S2 obtains the hydrographic data in target plot；
Step S3, obtains the terrain data in target plot, which contains at least two level of detail；
Step S4, terrain data and hydrographic data are imported into modeling software to establish the physical model in target plot and
According to the initial physical condition and boundary of climatic data and hydrographic data setting physical model；
Physical model is carried out grid dividing and is separated into calculating grid model by step S5；
Step S6 will calculate grid model and import fluid calculation numerical simulation software, by building CA model to calculating net
Lattice model is iterated calculating, to obtain the physical descriptor in target plot；
Target Parcel division is multiple Land units, to be obtained often according to the physical descriptor in target plot by step S7
The unit physical descriptor of a Land unit；
Step S8, by computer using big data algorithm to unit physical descriptor and micro climate architecture design addressing design
Environmental variance matched, so that the matching degree of unit physical descriptor and environmental variance is obtained, further according to the height of matching degree
To obtain the plot scoring of each Land unit, further according to the height of plot scoring, selection is suitable for each from building library
The situation of building that Land unit is built, to complete micro climate architecture design addressing design.
Wherein, a CA mould is can be obtained into terrain data substitution original state and state transition probability in step S2
Type, acquires the transition probability of later any year each plot use pattern between the starting year, and then calculates the face of each plot use pattern
Accumulate percentage when quantity changes in demand.
The quality of calculating grid model in step S5 can satisfy the required precision that more limit members calculate, and calculate grid model
Quality it is higher, the precision of calculated result is higher.
The basic principle of CA model in step S6 is the addressing type matrix of transition probabilities using CA model, in conjunction with more
The addressing pattern that criterion evaluation model generates changes suitability figure, determines the CA transformation rules of imitative position pattern variation.
Using the land use for predicting the base period as original state, stated with base period and before land use transfer area and suitability atlas
The suitable land use pattern of pixel is foundation, is redistributed to land type, until reaching Markov Chain Forecast
Land use area.It was verified that CA model is in terms of simulation of land use changes with bigger than based on GIS technology method
Many successful applications have been carried out in accuracy benefits.
It is specific to calculate step are as follows:
Step 1: establishing null hypothesis H0 and alternative hypothesis Hl；
Step 2: carrying out statistical calculation；
Step 3: one significance (α=0.05 or α=0.01) of regulation looks into related statistics according to significance
The distribution table of amount, obtains critical value；
Step 4: must be worth real compared with critical value, it was therefore concluded that.
For example, now to examine the average (μ 1 and μ z) of experimental group and control group either with or without difference, step and method are as follows:
1. establishing null hypothesis, i.e., first think that the two without difference, is indicated with H0: μ 1=μ 2；
2. determining the probability P for assuming that H0 is set up by statistical calculation；
3. judging to assume all no establishments according to the size of P.
Iterative calculation in step S6 is to calculate completion automatically by evaluation simulation software, is carried out according to physical model more
First iteration is limited, until the numerical convergence of iteration is to stationary value, specific finishing control is by the residual of each physical descriptor
Difference control, when each residual error is both less than preset threshold value, computer is automatically stopped calculating.It can also pass through in calculating process
The iterative steps of user's setting terminate to iterate to calculate, and iterative steps are mainly the calculating experience and observation object for relying on user
The change curve of variable is managed to determine.
Matching methods of marking in step S8 is as shown in table 1, will carry out vector using space summation in evaluation process and ask
With and take Vector Mode to obtain load situation index.Development variable and dominated variable are chosen, using vector modulus method to Architectural foundation knot
Fruit has carried out analysis and assessment.It crosses in title specifically matching and can assign different environmental variances to different specific weight, so that
Matched result is more in line with actual conditions, specifically:
1 plot grade form of table
A is weight coefficient when each unit physical descriptor calculates, and b is each unit physical descriptor and environmental physics variable
Matching degree, n is the quantity of unit physical descriptor.
In the present embodiment, unit physical descriptor is temperature, wind speed, humidity and the air pressure of Land unit, i.e. n=4.
Each Land unit is numbered, and the environment of the design of unit physical descriptor and micro climate architecture design is become
Amount carries out matching scoring, and during matching scoring, the weight coefficient of each unit physical descriptor is different.
By taking No. 1 plot is with the matching methods of marking of No. 1 building as an example, the weight coefficient a of temperature1=0.7, the matching of temperature
Spend b1=0.8, the weight coefficient a of wind speed2=0.5, the matching degree b of wind speed2=0.9, the weight coefficient a of humidity3=0.9, humidity
Matching degree b3=0.7, the weight coefficient a of air pressure4=0.6, the matching degree b of air pressure4=0.8, then plot 1 is built relative to No. 1
The plot scoring built is i.e. are as follows:
Each Land unit is matched one by one with every kind of building in building library using big data algorithm by computer
Scoring, to obtain plot scoring of each Land unit relative to every kind of building in building library, the result to score according to plot
It chooses scoring highest one and is used as optimal solution, to select building for each Land unit construction of optimum from building library
It builds.
Illustrate the Conversion Relations of plot use pattern in the same area in different time sections using transfer matrix, generally
It is expressed with bivariate table, from can quickly check the concrete condition mutually converted between each ground class in bivariate table.
Embodiment action and effect
According to the micro climate architecture design addressing design method that the wind environment of the present embodiment is simulated, due to obtaining target plot
Climatic data, hydrographic data and terrain data, therefore terrain data and hydrographic data can be imported modeling software to build
The physical model in vertical target plot and initial physical condition and the side that physical model is set according to climatic data and hydrographic data
Boundary.Since terrain data contains at least two level, various virtual scenes needed for can satisfy evaluation simulation are needed
It asks.Since physical model is carried out grid dividing and is separated into calculating grid model, it can will calculate grid model and import
Evaluation simulation software, and calculating is iterated to grid model is calculated by building CA model, to obtain target plot
Physical descriptor.Due to being iterated calculating by computer, what is calculated is more efficient, as a result more acurrate.Due to by mesh
Mark Parcel division is multiple Land units, therefore can obtain the unit of each Land unit according to the physical descriptor in target plot
Physical descriptor.Due to by big data algorithm to the environmental variance of unit physical descriptor and micro climate architecture design addressing design into
Row matches scoring, therefore can be suitable for building for each Land unit construction from selection in library is built according to the height that plot is scored
It builds, to complete micro climate architecture design addressing design.Due to carrying out matching scoring using big data algorithm by computer,
It is as a result more acurrate with the more efficient of scoring.
Since unit physical descriptor includes multiple individual event unit physical descriptors, each individual event unit physical descriptor can
Item environment variable corresponding with environmental variance is matched, so that the individual event unit physics for obtaining each Land unit becomes
Amount scoring is added each individual event unit physical descriptor scoring of Land unit to obtain plot scoring.
Since physical model is the diminution model for meeting computational accuracy and requiring established in proportion, the essence of physical model
Degree can be corresponding with computational accuracy, to save the consumption for calculating power.
The preferred embodiment of the present invention has been described in detail above.It should be appreciated that the ordinary skill of this field is without wound
The property made labour, which according to the present invention can conceive, makes many modifications and variations.Therefore, all technician in the art
Pass through the available technology of logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Scheme, all should be within the scope of protection determined by the claims.
For example, the individual event physical descriptor in the present embodiment includes temperature, wind speed, humidity and the air pressure of Land unit,
In micro climate architecture design addressing design method provided by the invention, individual event physical descriptor can also include sunshine duration, geological characteristics
And radiation etc., the Architectural foundation for designing the different plot of various conditions design.
Claims (6)
1. the micro climate architecture design addressing design method of wind environment simulation, the building for selecting appropriate target plot to arrange is special
Sign is, includes the following steps:
Step S1 obtains the climatic data in the target plot；
Step S2 obtains the hydrographic data in the target plot；
Step S3, obtains the terrain data in the target plot, and the terrain data contains at least two level of detail；
The terrain data and the hydrographic data are imported modeling software to establish each target plot by step S4
Physical model and initial physical condition and the side that the physical model is set according to the climatic data and the hydrographic data
Boundary；
The physical model is carried out grid dividing and is separated into calculating grid model by step S5；
The calculating grid model is imported fluid calculation numerical simulation software by step S6, by building CA model to the meter
It calculates grid model and is iterated calculating, to obtain the physical descriptor in the target plot；
The target Parcel division is multiple Land units by step S7, to be obtained according to the physical descriptor each described
The unit physical descriptor of Land unit；
Step S8 is carried out by environmental variance of the computer to the unit physical descriptor and micro climate architecture design addressing design
Matching, to obtain the matching degree of the unit physical descriptor and the environmental variance, further according to the matching degree height from
And the plot scoring of each Land unit is obtained, further according to the height of plot scoring, selection is suitable from building library
The building of preferably each Land unit arrangement, to complete the micro climate architecture design addressing design.
2. the micro climate architecture design addressing design method of wind environment simulation according to claim 1, it is characterised in that:
Wherein, the unit physical descriptor include multiple individual event unit physical descriptors, each individual event unit physical descriptor with
Corresponding item environment variable is matched in the environmental variance, to obtain the individual event unit of each Land unit
Physical descriptor scoring is added the individual event unit physical descriptor scoring of each of the Land unit to obtain the plot
Scoring.
3. the micro climate architecture design addressing design method of wind environment simulation according to claim 2, it is characterised in that:
Wherein, the individual event unit physical descriptor is temperature, wind speed, humidity and the air pressure of each Land unit.
4. the micro climate architecture design addressing design method of wind environment simulation according to claim 1, it is characterised in that:
Wherein, the climatic data includes the firsthand information by the weather system in the meteorologic instrument target plot obtained
And the data reorganized according to the firsthand information.
5. the micro climate architecture design addressing design method of wind environment simulation according to claim 1, it is characterised in that:
Wherein, the terrain data is the remote sensing image that the target plot is obtained by satellite remote sensing technology.
6. the micro climate architecture design addressing design method of wind environment simulation according to claim 1, it is characterised in that:
Wherein, the hydrographic data includes the individual event hydrology number in multiple target plot obtained by observation and copmputing laboratory
Accordingly and according to the maximum value of the obtained individual event hydrographic data of the individual event hydrographic data, minimum value, average value, total
Amount, graph and isopleth, the individual event hydrographic data be the precipitation in the target plot, evaporation capacity, water level, flow and
Silt content.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110006640A (en) * | 2019-04-09 | 2019-07-12 | 洛阳理工学院 | A kind of detection method of forest Simulating warming phjytotron Building Structure Strength |
| CN110135103A (en) * | 2019-05-24 | 2019-08-16 | 南京大学 | A kind of method and system using water flow simulation Urban Natural ventilation potentiality |
| CN110188941A (en) * | 2019-05-27 | 2019-08-30 | 华南理工大学 | Design partition method in Urban Waterfront based on water body climatic effect |
| CN111191312A (en) * | 2019-12-27 | 2020-05-22 | 深圳集智数字科技有限公司 | Method for obtaining block floor-arranging angle and related device |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184328A (en) * | 2011-05-10 | 2011-09-14 | 南京大学 | Method for optimizing land use evolution CA model transformation rules |
| WO2017161643A1 (en) * | 2016-03-22 | 2017-09-28 | 东南大学 | Block three-dimensional pattern optimization method based on wind environment effect field mode |
-
2018
- 2018-09-28 CN CN201811136238.1A patent/CN109063388A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102184328A (en) * | 2011-05-10 | 2011-09-14 | 南京大学 | Method for optimizing land use evolution CA model transformation rules |
| WO2017161643A1 (en) * | 2016-03-22 | 2017-09-28 | 东南大学 | Block three-dimensional pattern optimization method based on wind environment effect field mode |
Non-Patent Citations (2)
| Title |
|---|
| 姚博: "风环境影响下的陕南山区小城镇空间布局方法研究 ——以丹凤县城龙驹寨镇为例", 《中国优秀硕士学位论文全文数据库信息科技辑 工程科技Ⅱ辑》 * |
| 孙贺: "滨海湿地实验区生态化规划设计策略研究", 《中国优秀硕士学位论文全文数据库信息科技辑 工程科技Ⅰ辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110006640A (en) * | 2019-04-09 | 2019-07-12 | 洛阳理工学院 | A kind of detection method of forest Simulating warming phjytotron Building Structure Strength |
| CN110006640B (en) * | 2019-04-09 | 2020-10-20 | 洛阳理工学院 | Method for detecting building structure strength of forest simulation heating artificial climate chamber |
| CN110135103A (en) * | 2019-05-24 | 2019-08-16 | 南京大学 | A kind of method and system using water flow simulation Urban Natural ventilation potentiality |
| CN110188941A (en) * | 2019-05-27 | 2019-08-30 | 华南理工大学 | Design partition method in Urban Waterfront based on water body climatic effect |
| CN111191312A (en) * | 2019-12-27 | 2020-05-22 | 深圳集智数字科技有限公司 | Method for obtaining block floor-arranging angle and related device |
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Application publication date: 20181221 |