CN111208990A - Object analysis method and device - Google Patents
Object analysis method and device Download PDFInfo
- Publication number
- CN111208990A CN111208990A CN201911381033.4A CN201911381033A CN111208990A CN 111208990 A CN111208990 A CN 111208990A CN 201911381033 A CN201911381033 A CN 201911381033A CN 111208990 A CN111208990 A CN 111208990A
- Authority
- CN
- China
- Prior art keywords
- target
- analysis
- unit
- class
- working condition
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 254
- 238000000034 method Methods 0.000 claims abstract description 46
- 230000008859 change Effects 0.000 claims description 8
- 238000013515 script Methods 0.000 claims description 7
- 239000003086 colorant Substances 0.000 claims description 6
- 230000005291 magnetic effect Effects 0.000 description 49
- 238000010586 diagram Methods 0.000 description 19
- 238000004364 calculation method Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 7
- 238000012360 testing method Methods 0.000 description 7
- 230000006835 compression Effects 0.000 description 6
- 238000007906 compression Methods 0.000 description 6
- 238000004088 simulation Methods 0.000 description 5
- 238000013461 design Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000003068 static effect Effects 0.000 description 3
- 230000014509 gene expression Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012827 research and development Methods 0.000 description 2
- 239000013589 supplement Substances 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000005358 geomagnetic field Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 238000012805 post-processing Methods 0.000 description 1
- 230000000452 restraining effect Effects 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/30—Creation or generation of source code
- G06F8/31—Programming languages or programming paradigms
- G06F8/315—Object-oriented languages
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computing Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Stored Programmes (AREA)
Abstract
The embodiment of the invention provides an object analysis method and device, wherein the method comprises the following steps: determining a target unit contained in an object to be analyzed and attribute information of the target unit; acquiring characteristic information associated with a target unit from a preset analysis software bottom data structure library; acquiring load working conditions related to the target unit from an analysis software bottom data structure library; acquiring analysis items related to the target unit from an analysis software bottom data structure library; receiving setting operation of a user on characteristic information, load working conditions and analysis classes, and determining target characteristic information, target load working conditions and target analysis items; and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item. By the method, data related to analysis is searched and analyzed from a preset analysis software bottom data structure base based on the incidence relation between the elements, an engineer does not need to establish a model in a targeted mode, the object analysis efficiency can be improved, and human resources can be saved.
Description
Technical Field
The invention relates to the technical field of analysis software, in particular to an object analysis method and device.
Background
With the rapid development of industrial software, the speed of analysis software and embedded software is increased rapidly, and the degree of localization is gradually improved. The industrial software is mainly divided into embedded software, production control software, analysis software and information management software. The analysis software occupies a certain proportion in the industrial software and is significant in the industrial software. However, industrial software has specificity, and general software cannot meet more specific requirements of engineers. With the approval of engineers on simulation analysis, the need for specialized and customized platforms is more urgent.
At present, the model expression form of industrial software mainly comprises five core elements of units, characteristics, loads, analysis and results. Different analysis objects have different models, so that engineers are required to create models with different expressions in a targeted manner, which is time-consuming and labor-consuming.
In summary, how to analyze an object to be analyzed quickly and conveniently becomes an urgent problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above-mentioned prior art problems, the present invention has been made to provide an object analysis method and apparatus that overcomes or at least partially solves the above-mentioned problems.
According to an aspect of the present invention, there is provided an object analysis method, wherein the method includes: determining a target unit contained in an object to be analyzed and attribute information of the target unit; acquiring characteristic information associated with the target unit from a preset analysis software bottom data structure library; acquiring the load working condition associated with the target unit from the analysis software bottom data structure library; acquiring analysis items related to the target units from the analysis software bottom data structure library; receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class, and determining target characteristic information, target load working condition and target analysis item; and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item.
Preferably, the analysis software underlying data structure library comprises: characteristic class, unit class, load class, working condition class, analysis class and result class; the unit classes include: the base classes of a plurality of units, the base classes of a plurality of objects, and the nodes, the identifiers, the angles, the intervals and the unit types contained in each unit; the property classes include: base classes of a plurality of objects, base classes of a plurality of properties, and types of each property; the load classes include: base classes of the plurality of objects, base classes of the plurality of payloads, colors of the display, and payload types; the working condition types comprise: base classes of a plurality of objects, base classes of a plurality of working conditions and working condition types; the analysis classes include: base classes of a plurality of objects, base classes of a plurality of analyses, types of each analysis, solvers, scripts, associated unit information, condition load information, result information and result table information; the result category includes: base classes of a plurality of objects, base classes of a plurality of results, and types, generation times, result files, associated unit information, work load information, result information, and result table information of each result; wherein the characteristic class is associated with the unit class, and the analysis class is associated with the unit class, the load class, the condition class, and the result class.
Preferably, the step of receiving user setting operations on the characteristic information, the load condition and the analysis class, and determining target characteristic information, a target load condition and a target analysis class includes: receiving a first selection operation of a user on the characteristic information and/or a first input operation on newly added characteristic information; determining target characteristic information according to the first selection operation and/or the first input operation; receiving a second selection operation of the user on the load working condition and/or a second input operation on a new load working condition; determining a target load working condition according to the second selection operation and/or the second input operation; receiving a third selection operation of the user on the analysis item associated with the target unit and/or a third input operation on the newly added analysis item; and determining a target analysis item according to the third selection operation and/or the third input operation.
Preferably, the step of analyzing the object to be analyzed according to the target characteristic information, the target load condition and the target analysis item includes: judging whether the target characteristic information, the target load working condition and the target analysis item are changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit; and if the target characteristic information does not change, acquiring the target characteristic information, the target load working condition and an analysis result corresponding to the target analysis item from the analysis underlying data structure library.
Preferably, the step of determining the target unit contained in the object to be analyzed comprises: determining a target base class to which an object to be shared belongs; displaying each first unit contained in the target base class; receiving a fourth selection operation of the user on the first unit and/or a fourth input operation on the newly added unit; and determining a target unit contained in the object to be analyzed according to the fourth selection operation and/or the fourth input operation.
According to another aspect of the present invention, there is provided an object analysis apparatus, wherein the apparatus comprises: the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining a target unit contained in an object to be analyzed and attribute information of the target unit; the first acquisition module is used for acquiring the characteristic information associated with the target unit from a preset analysis software bottom data structure library; the second acquisition module is used for acquiring the load working condition associated with the target unit from the analysis software bottom data structure library; a third obtaining module, configured to obtain an analysis item associated with the target unit from the analysis software underlying data structure library; the receiving module is used for receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class and determining target characteristic information, target load working condition and target analysis item; and the analysis module is used for analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item.
Preferably, the analysis software underlying data structure library comprises: characteristic class, unit class, load class, working condition class, analysis class and result class;
the unit classes include: the base classes of a plurality of units, the base classes of a plurality of objects, and the nodes, the identifiers, the angles, the intervals and the unit types contained in each unit;
the property classes include: base classes of a plurality of objects, base classes of a plurality of properties, and types of each property;
the load classes include: base classes of the plurality of objects, base classes of the plurality of payloads, colors of the display, and payload types;
the working condition types comprise: base classes of a plurality of objects, base classes of a plurality of working conditions and working condition types;
the analysis classes include: base classes of a plurality of objects, base classes of a plurality of analyses, types of each analysis, solvers, scripts, associated unit information, condition load information, result information and result table information;
the result category includes: base classes of a plurality of objects, base classes of a plurality of results, and types, generation times, result files, associated unit information, work load information, result information, and result table information of each result;
wherein the characteristic class is associated with the unit class, and the analysis class is associated with the unit class, the load class, the condition class, and the result class.
Preferably, the receiving module includes:
the first submodule is used for receiving a first selection operation of a user on the characteristic information and/or a first input operation on newly added characteristic information;
the second submodule is used for determining target characteristic information according to the first selection operation and/or the first input operation;
the third submodule is used for receiving a second selection operation of the user on the load working condition and/or a second input operation on a newly-added load working condition;
the fourth submodule is used for determining a target load working condition according to the second selection operation and/or the second input operation;
the fifth submodule is used for receiving a third selection operation of the user on the analysis item associated with the target unit and/or a third input operation on the newly added analysis item;
and the sixth submodule is used for determining a target analysis item according to the third selection operation and/or the third input operation.
Preferably, the analysis module comprises:
the judgment submodule is used for judging whether the target characteristic information, the target load working condition and the target analysis item are changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit;
and the result obtaining submodule is used for obtaining the target characteristic information, the target load working condition and the analysis result corresponding to the target analysis item from the analysis bottom layer data structure library if the target characteristic information, the target load working condition and the analysis result are not changed.
Preferably, the determining module is specifically configured to:
determining a target base class to which an object to be shared belongs;
displaying each first unit contained in the target base class;
receiving a fourth selection operation of the user on the first unit and/or a fourth input operation on the newly added unit;
determining a target unit contained in the object to be analyzed according to the fourth selection operation and/or the fourth input operation;
determining attribute information of the target unit.
According to still another aspect of the present invention, there is provided a computer apparatus including: the object analysis system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize any one of the object analysis methods in the embodiment of the invention.
According to a further aspect of the present invention, there is provided a storage unit having stored thereon a computer program for execution by a processor of any one of the object analysis methods as described in embodiments of the present invention.
According to the object analysis scheme provided by the embodiment of the invention, the target unit contained in the object to be analyzed and the attribute information of the target unit are determined; acquiring characteristic information associated with the target unit from a preset analysis software bottom data structure library; acquiring the load working condition associated with the target unit from the analysis software bottom data structure library; acquiring analysis items related to the target units from the analysis software bottom data structure library; receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class, and determining target characteristic information, target load working condition and target analysis item; and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item. The method can search and analyze related data from a preset analysis software bottom data structure base based on the incidence relation between elements, an engineer does not need to establish a model in a targeted manner, the object analysis efficiency can be improved, and human resources can be saved.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a schematic diagram of relationships of classes;
FIG. 2 is a schematic diagram of the internal relationships between unit classes and nodes;
FIG. 3 is a diagram illustrating property classes and internal relationships;
FIG. 4 is a schematic diagram of load classes and internal relationships;
FIG. 5 is a schematic diagram of analysis classes and internal relationships;
FIG. 6 is a diagram illustrating result classes and internal relationships;
FIG. 7 is a diagram illustrating relationships between modules in a generalized model;
FIG. 8 is a flowchart illustrating steps of a method for analyzing objects according to a first embodiment of the present invention;
FIG. 9 is a schematic diagram of an object analysis principle according to a second embodiment of the present invention;
FIG. 10 is a diagram of a satellite magnetic simulation software architecture according to a third embodiment of the present invention;
fig. 11 is a block diagram showing the structure of an object analysis apparatus according to a fourth embodiment of the present invention;
FIG. 12 is a block diagram schematically illustrating a computing device for performing the object analysis method of the present invention; and
fig. 13 schematically shows a computer-readable storage unit for holding or carrying program code for implementing an object analysis method according to the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The object analysis method in the embodiment of the present invention is executed based on a preset analysis software underlying data structure library, and first, a structure of the preset analysis software underlying data structure library is described below.
The analysis software bottom data structure base comprises: characteristic class, unit class, load class, working condition class, analysis class and result class; the unit classes include: the base classes of a plurality of units, the base classes of a plurality of objects, and the nodes, the identifiers, the angles, the intervals and the unit types contained in each unit; the property classes include: base classes of a plurality of objects, base classes of a plurality of properties, and types of each property; the load classes include: base classes of the plurality of objects, base classes of the plurality of payloads, colors of the display, and payload types; the working conditions include: base classes of a plurality of objects, base classes of a plurality of working conditions and working condition types; the analysis classes include: base classes of a plurality of objects, base classes of a plurality of analyses, types of each analysis, solvers, scripts, associated unit information, condition load information, result information and result table information; the results categories include: base classes of a plurality of objects, base classes of a plurality of results, and types, generation times, result files, associated unit information, work load information, result information, and result table information of each result;
wherein the characteristic class is associated with the unit class, and the analysis class is associated with the unit class, the load class, the working condition class and the result class.
In the invention, the generalized model underlying data structure is researched to form an analysis software underlying data structure library so as to solve the problem of universality of the analysis software underlying data structure. The definition and the extension of each element class and the incidence relation among the elements are used for realizing the validity and the openness of the data structure. And analyzing a software bottom layer data structure library, and adopting a layered design idea. Layer by layer definition and layer by layer association. And the expandability is strong. All objects have a common base class, and then according to the base class, object classes of five elements including units, characteristics, loads, analysis and results are defined. Then, according to the object class of each element, defining respective class. Because each element of the unit, the characteristic, the load, the analysis and the result has different types, and finally a specific object class required to be described is created according to the respective class, wherein a relation diagram of the class is specifically shown in fig. 1.
There is also a certain associative relationship between the five core elements of the unit, the characteristic, the load, the analysis and the result of the generalized model. The unit is the object of design analysis, and the characteristics, loads and analysis are related to the unit to finally generate a result.
A unit: is an abstract carrier of CAE analysis objects. The specific units represented by the generalized units vary from one CAE domain to another, but their basic constituent elements are the same. The unit is composed of nodes, there is an internal association relationship between the unit and the nodes, and a schematic diagram of the internal relationship between the unit class and the nodes is shown in fig. 2.
And (3) node: units are all composed of nodes, which are elements that make up the unit. Through the nodes, the relevant information such as the shape type of the unit can be obtained. Cotenobject is the base class of all objects and cotenonodeobject is the base class of all nodes. The node class cotenode item contains coordinate information of the node and belonging unit information in addition to the cotenode object and the cotenode object.
A unit: CoteElementObject is the base class for all elements. The unit class CoteElementItem, besides inheriting the CoteObject and the CoteElementObject, also contains relevant information such as nodes, representations, angles, distances, unit types and the like contained in the unit.
The node class (cotelementitem) and the unit class (cotelementitem) have a mutual association relationship, the node class associates the ObjectID of the unit class through belongtoeelements, and the unit class associates the ObjectID of the node through containment nodes.
The characteristics are as follows: the method is an abstraction of a type of general characteristic data in CAE analysis and is mainly used for explaining some properties of a generalized unit. The characteristics are also different for different CAE domains. FIG. 3 is a diagram illustrating feature classes and relationships.
Property class (cotepopertyitem): the CotePropertyObject is a base class of all properties, and the property class CotePropertyItem contains information of the type of the property, the associated unit, and the like in addition to the CotePropertyObject and the CotePropertyObject.
Loading: is some constraint and load (force, temperature, velocity, etc.) information loaded onto the unit in the CAE analysis. FIG. 4 is a schematic diagram of load classes and internal relationships.
payload-CoteLoadObject is the base class of all properties, and the payload class (CoteLoadItem) contains information such as color of display, payload type, etc. in addition to inheriting CoteObject and CoteLoadObject.
Working conditions are as follows: the CoteLoadcaseObject is a base class of all the conditions, and the condition class (CoteLoadcaseObject) includes information such as the type of the condition in addition to the CoteObject and the CoteLoadcaseObject.
And (3) analysis: the method is an abstraction of one operation process under unit and load in CAE analysis. The analysis can only be performed if the requirements of the analysis itself are met. The analysis class and internal relationship diagram is shown in fig. 5.
Analysis class (coteanalystisitem): the CoteAnalyssObject is a base class of all analyses, and the analysis class CoteAnalyssItem includes, in addition to inheriting the CoteObject and the CoteAnalyssObject, the type of analysis, a solver, a script of analysis, associated unit information, workload information, result information, and result table information.
As a result: and analyzing the set of output information obtained after the execution. The result is a generic class that contains mainly the following elements. The result class and the internal relationship are shown in FIG. 6.
Result class (cotereultitem): the coteResultObject is a base class of all results, and the result class coteResultItem also contains the type of the result, the result generation time, the result file, the associated unit information, the workload information, the result information and the result table information in addition to inheriting the coteObject and the coteResultObject.
The improved generalized model, i.e. the internal association relationship between elements in the analysis group structure base, is shown in fig. 7. As shown in fig. 7, each module is independent, and there is a certain association relationship between modules. A property is associated with a cell. The analysis correlates units, loads and results.
Example one
Referring to fig. 8, a flowchart illustrating steps of an object analysis method according to a first embodiment of the present invention is shown.
The object analysis method provided by the embodiment of the invention is realized based on a preset analysis software bottom data structure base, and comprises the following steps:
step 101: and determining a target unit contained in the object to be analyzed and attribute information of the target unit.
Based on the different dimensions of the units constituting the analysis object, the units can be divided into a plurality of large classes, each large class comprises one or more unit classes, and the method specifically comprises the following steps: 0-dimensional lattice cells (mass cells, hinge cells, etc.), 1-dimensional lattice cells (rods, beams, etc.), 2-dimensional lattice cells (triangles, quadrilaterals, membranes, shells, etc.), 3-dimensional lattice cells (tetrahedrons, pentahedrons, hexahedrons, etc.).
When the target unit contained in the object to be analyzed is determined, the unit class to which the target unit belongs can be searched from a preset analysis software bottom data structure library, and then each target unit is inherited from the corresponding unit class. Of course, the method is not limited to this, and the target units can be manually input by the user or can be supplemented or deleted from the analysis software underlying data structure library.
The attribute information of the target unit may include, but is not limited to: material basis properties, compression properties, etc.
One way to preferably determine the target units comprised by the object to be analyzed is to: determining a target base class to which an object to be shared belongs; displaying each first unit contained in the target base class; receiving a fourth selection operation of the user on the first unit and/or a fourth input operation on the newly added unit; and determining a target unit contained in the object to be analyzed according to the fourth selection operation and/or the fourth input operation.
Step 102: and acquiring the characteristic information associated with the target unit from a preset analysis software bottom data structure library.
The associated characteristic information is different for different target units. If the target unit is a unit inherited from the analysis software bottom data structure library, the characteristic information associated with the target unit can be directly inherited from the analysis software bottom data structure library; if the target unit is a user newly-added unit, the user is required to input the characteristic information associated with the target unit.
Step 103: and acquiring the load working condition associated with the target unit from an analysis software bottom data structure library.
Load conditions may include, but are not limited to: unit force loads, unit restraining force loads, and the like.
If the target unit is a unit inherited from the analysis software bottom data structure library, the load working condition associated with the target unit can be directly inherited from the analysis software bottom data structure library; if the target unit is a user newly-added unit, the user is required to input the load working condition associated with the target unit. Moreover, the user can modify the load condition associated with the target unit inherited from the analysis software underlying data structure library.
Step 104: and acquiring the analysis item associated with the target unit from the analysis software underlying data structure library.
In a specific implementation process, the user may also delete or add an analysis item associated with the target unit acquired from the analysis software underlying data structure library.
Step 105: and receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class, and determining target characteristic information, the target load working condition and a target analysis item.
Preferably, the setting operation of the user on the characteristic information, the load condition and the analysis class is received, and the mode for determining the target characteristic information, the target load condition and the target analysis class is as follows:
receiving a first selection operation of a user on the characteristic information and/or a first input operation on the newly added characteristic information; determining target characteristic information according to the first selection operation and/or the first input operation;
receiving a second selection operation of a user on the load working condition and/or a second input operation on a new load working condition; determining a target load working condition according to the second selection operation and/or the second input operation;
receiving a third selection operation of the user on the analysis item associated with the target unit and/or a third input operation on the newly added analysis item; and determining a target analysis item according to the third selection operation and/or the third input operation.
Step 106: and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item.
One way to analyze the object to be analyzed, preferably according to the target characteristic information, the target load condition, and the target analysis item, is:
judging whether the target characteristic information, the target load working condition and the target analysis item are changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit; and if the target characteristic information does not change, obtaining target characteristic information, target load working conditions and analysis results corresponding to the target analysis items from the analysis underlying data structure library. If any one of the target characteristic information, the target load working condition and the target analysis item is changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit, determining a target analysis item related to the change and a target analysis item not related to the change, and analyzing the related target analysis item according to the change and pertinently aiming at each target analysis item related to the change to obtain a first analysis result; and aiming at each target analysis item which is not involved in the change, acquiring a second analysis result corresponding to the target analysis item from the analysis bottom layer data structure library, and determining the first analysis result and the second analysis result as final analysis results of the object to be analyzed.
According to the object analysis scheme provided by the embodiment of the invention, the target unit contained in the object to be analyzed and the attribute information of the target unit are determined; acquiring characteristic information associated with the target unit from a preset analysis software bottom data structure library; acquiring the load working condition associated with the target unit from the analysis software bottom data structure library; acquiring analysis items related to the target units from the analysis software bottom data structure library; receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class, and determining target characteristic information, target load working condition and target analysis item; and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item. The method can search and analyze related data from a preset analysis software bottom data structure base based on the incidence relation between elements, an engineer does not need to establish a model in a targeted manner, the object analysis efficiency can be improved, and human resources can be saved.
Example two
Referring to fig. 9, a schematic diagram of an object analysis principle according to a second embodiment of the present invention is shown.
In the embodiment of the invention, the analysis software underlying data structure library is applied to the static strength analysis scene of the aircraft structure as an example.
Aircraft structural designs must meet strength requirements. Meeting the strength requirements means that the aircraft structure is capable of meeting safety regulations under the action of external loads in various use situations of the aircraft. In the embodiment of the present invention, a flat plate compression instability analysis specifically included in the static strength analysis of the aircraft structure is taken as an example for explanation.
As shown in fig. 9: the method comprises the following steps of (1) performing flat plate compression instability analysis on static strength of an airplane structure, wherein a unit is firstly performed, and an analysis object is a plate unit, so that a target unit is determined to be the plate unit; characteristics, the materials required for analysis are metallic materials and plate thickness; load, analysis of required plate restraint and operating stress; the analysis is the flat plate compression instability analysis; the result is the analyzed result.
The flat plate compression instability analysis is executed in the process that ① firstly obtains the attribute information of the object plate unit and the unit to be analyzed, ② obtains the characteristic information of the related unit according to the unit, ③ obtains the load working condition related to the analysis according to the analysis, ④ transmits all the information obtained in the step ①②③ to the analysis and executes the analysis, and ⑤ obtains the analysis result.
In the embodiment of the invention, each unit, characteristic, load, analysis and result related to the flat plate compression instability analysis are corresponding to corresponding elements in a software bottom layer data structure library, the corresponding class is inherited according to each element, and the association relationship between the elements is inherited, so that a user only needs to supplement the specific attribute of the analysis, and the research and development efficiency is greatly improved.
EXAMPLE III
Referring to fig. 10, a schematic diagram of a satellite magnetic simulation software architecture according to a third embodiment of the present invention is shown.
In the embodiment of the invention, the analysis software underlying data structure library is applied to a satellite magnetic simulation scene as an example for explanation.
The satellite magnetic simulation software is mainly used for researching satellite environment engineering magnetics and application, the system is mainly used for spacecraft magnetic simulation and analysis, and the oriented users are mainly related test analysts and general designers.
The satellite magnetic simulation software mainly provides a simulation analysis function taking magnetic moment and magnetic field analysis of components and whole satellites as a core, and provides pretreatment such as spacecraft structure, dipole and test data management and various post-processing functions of analyzed data.
The system provides a method for analyzing the magnetic moments and magnetic fields of the components and the whole star, wherein the magnetic moment analysis method mainly comprises an equatorial method, a multi-dipole method and a component magnetic moment superposition method; the magnetic field analysis method mainly comprises a spherical harmonic analysis method, a multi-dipole method, a whole star and a component magnetic field superposition method. As shown in fig. 10, the unit: the units of the satellite magnetic simulation software mainly comprise a spacecraft whole satellite, a satellite common component, a magnetic torquer, a magnetic block, a dipole component, a cable, a cabin section and the like. The listed units inherit the general class of the unit, and are expanded on the basis of the characteristics of each unit. Take the spacecraft whole star and dipole components as examples.
The whole star of the spacecraft: besides the attributes of the general unit classes, the central coordinates, the included sub-components, the test data, the local magnetic moments, the self magnetic moments, the test magnetic moments, the bound dipoles, the included compensation points, the included magnetic blocks, the convergence curve data and the like are also expanded.
Dipole member: in addition to the generic element class properties, the list of dipole elements involved, the part to which the dipole belongs, etc. is also expanded.
The characteristics are as follows: since the star magnetic simulation software does not need to relate to characteristics, the star magnetic simulation software does not need to inherit from an analysis software underlying data structure library.
Load working condition: the load working condition of the satellite magnetic simulation software mainly comprises a satellite magnetic moment working condition and test data. The enumerated load conditions inherit the general class of the load conditions, and are expanded on the basis according to the characteristics of each load condition.
Satellite magnetic moment working condition: besides the properties of the general load condition class, the start time, the end time, the time step and the satellite magnetic moment are extended.
Test data: besides the attributes of the general load working condition class, the method also needs to expand the associated components, the testing steps, the probe number and coordinates, the self coordinate system, the real experiment data information, the associated components, the scaling factor and the steps.
And (3) analysis: the analysis of the satellite magnetic simulation software mainly comprises a whole-satellite magnetic field multi-dipole method, a whole-satellite magnetic field spherical harmonic analysis method, a whole-satellite magnetic field component superposition method, a component magnetic field spherical harmonic analysis method, a component magnetic field multi-dipole method, a cable magnetic field calculation analysis method, a magnetic torquer magnetic field analysis method, a spacecraft orbit calculation method, a geomagnetic field calculation method, a magnetic interference moment calculation method, a specific point magnetic field analysis and a magnetic compensation analysis. The above listed analysis items inherit the general class of analysis and are extended based on the characteristics of each analysis. Take earth magnetic field calculation and cable line magnetic field calculation as examples.
Calculating the earth magnetic field: besides the attributes of the general analysis class, the coordinates of the orbit point, the working condition magnetic moment and the satellite orbit inclination angle are also expanded, the required magnetic moment is calculated, and the position of the point to be calculated is calculated.
Calculating the magnetic field of the cable: besides the attributes of the general analysis class, the current of the cable during calculation, the origin of the cable during calculation, the coordinate of the maximum value, the coordinate of the minimum value, the step length in the X direction, the step length in the Y direction and the step length in the Z direction are extended, and included sub-components are included.
As a result: the results in the satellite magnetic simulation software mainly comprise table results, picture results, report results, cloud picture results and the like. The result class of the underlying data structure completely meets the condition without any expansion.
The satellite magnetic simulation software performs the process of ① determining the information of the object unit to be analyzed, ② obtaining the information of the load associated with the analysis based on the analysis, ③ transferring the information obtained ①② to the analysis and performing the analysis, ④ the production results.
In the embodiment of the invention, each unit, characteristic, load, analysis and result related to satellite magnetic simulation are corresponding to corresponding elements in a software bottom layer data structure library, corresponding classes are inherited according to each element, and the association relationship between the elements is inherited, so that a user only needs to supplement the specific attribute of the analysis, and the research and development efficiency is greatly improved.
Example four
Referring to fig. 11, a block diagram of an object analysis apparatus according to a fourth embodiment of the present invention is shown.
An object analysis device according to an embodiment of the present invention includes: a determining module 201, configured to determine a target unit included in an object to be analyzed and attribute information of the target unit; a first obtaining module 202, configured to obtain characteristic information associated with the target unit from a preset analysis software underlying data structure library; a second obtaining module 203, configured to obtain a load condition associated with the target unit from the analysis software underlying data structure library; a third obtaining module 204, configured to obtain an analysis item associated with the target unit from the analysis software underlying data structure library; a receiving module 205, configured to receive setting operations of the user on the characteristic information, the load condition, and the analysis class, and determine target characteristic information, a target load condition, and a target analysis item; and the analysis module 206 is configured to analyze the object to be analyzed according to the target characteristic information, the target load condition, and the target analysis item.
Preferably, the analysis software underlying data structure library comprises: characteristic class, unit class, load class, working condition class, analysis class and result class; the unit classes include: the base classes of a plurality of units, the base classes of a plurality of objects, and the nodes, the identifiers, the angles, the intervals and the unit types contained in each unit; the property classes include: base classes of a plurality of objects, base classes of a plurality of properties, and types of each property; the load classes include: base classes of the plurality of objects, base classes of the plurality of payloads, colors of the display, and payload types; the working condition types comprise: base classes of a plurality of objects, base classes of a plurality of working conditions and working condition types; the analysis classes include: base classes of a plurality of objects, base classes of a plurality of analyses, types of each analysis, solvers, scripts, associated unit information, condition load information, result information and result table information; the result category includes: base classes of a plurality of objects, base classes of a plurality of results, and types, generation times, result files, associated unit information, work load information, result information, and result table information of each result; wherein the characteristic class is associated with the unit class, and the analysis class is associated with the unit class, the load class, the condition class, and the result class.
Preferably, the receiving module includes: the first submodule is used for receiving a first selection operation of a user on the characteristic information and/or a first input operation on newly added characteristic information; the second submodule is used for determining target characteristic information according to the first selection operation and/or the first input operation; the third submodule is used for receiving a second selection operation of the user on the load working condition and/or a second input operation on a newly-added load working condition; the fourth submodule is used for determining a target load working condition according to the second selection operation and/or the second input operation; the fifth submodule is used for receiving a third selection operation of the user on the analysis item associated with the target unit and/or a third input operation on the newly added analysis item; and the sixth submodule is used for determining a target analysis item according to the third selection operation and/or the third input operation.
Preferably, the analysis module comprises: the judgment submodule is used for judging whether the target characteristic information, the target load working condition and the target analysis item are changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit; and the result obtaining submodule is used for obtaining the target characteristic information, the target load working condition and the analysis result corresponding to the target analysis item from the analysis bottom layer data structure library if the target characteristic information, the target load working condition and the analysis result are not changed.
Preferably, the determining module is specifically configured to: determining a target base class to which an object to be shared belongs; displaying each first unit contained in the target base class; receiving a fourth selection operation of the user on the first unit and/or a fourth input operation on the newly added unit; determining a target unit contained in the object to be analyzed according to the fourth selection operation and/or the fourth input operation; determining attribute information of the target unit.
The object analysis apparatus provided in the embodiment of the present invention can implement each process in the object analysis method shown in the method embodiments of fig. 8 to 10, and is not described here again to avoid repetition.
The object analysis device provided by the embodiment of the invention determines the target unit contained in the object to be analyzed and the attribute information of the target unit; acquiring characteristic information associated with the target unit from a preset analysis software bottom data structure library; acquiring the load working condition associated with the target unit from the analysis software bottom data structure library; acquiring analysis items related to the target units from the analysis software bottom data structure library; receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class, and determining target characteristic information, target load working condition and target analysis item; and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item. The method can search and analyze related data from a preset analysis software bottom data structure base based on the incidence relation between elements, an engineer does not need to establish a model in a targeted manner, the object analysis efficiency can be improved, and human resources can be saved.
Each software module in the embodiment of the present invention has the same function as each corresponding software module in the foregoing system embodiment, and for the specific operation description that each software module can execute, the related description in the first embodiment, the second embodiment, and the third embodiment may be referred to, and details are not described here.
An object analysis method and apparatus provided herein is not inherently related to any particular computer, virtual system, or other apparatus. Various general purpose systems may also be used with the teachings herein. The structure required to construct a system incorporating aspects of the present invention will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in an object analysis scheme according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
For example, FIG. 12 illustrates a computing device in which the object analysis method of the present invention may be implemented. The computing device conventionally includes a processor 1010 and a computer program product or computer-readable medium in the form of a memory 1020. The memory 1020 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read only memory), an EPROM, a hard disk, or a ROM. The memory 1020 has a storage space 1030 in which program code 1031 for performing any of the method steps of the above-described method is stored. For example, the storage space 1030 storing the program codes may store the respective program codes 1031 respectively for implementing the various steps in the above method. The program code can be read from or written to one or more computer program products. These computer program products comprise a program code carrier such as a hard disk, a Compact Disc (CD), a memory card or a floppy disk. Such a computer program product is typically a portable or fixed storage unit as shown for example in fig. 13. The memory unit may have memory segments, memory spaces, etc. arranged similarly to memory 1020 in the computing device of fig. 12. The program code may be compressed in a suitable form. Typically, the storage unit comprises computer readable code 1031', i.e. code that is readable by a processor such as 1010, which when executed by a computing device causes the computing device to perform the steps of the method described above.
Reference herein to "one embodiment," "an embodiment," or "one or more embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Moreover, it is noted that instances of the word "in one embodiment" are not necessarily all referring to the same embodiment. In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Claims (10)
1. An object analysis method, characterized in that the method comprises:
determining a target unit contained in an object to be analyzed and attribute information of the target unit;
acquiring characteristic information associated with the target unit from a preset analysis software bottom data structure library;
acquiring the load working condition associated with the target unit from the analysis software bottom data structure library;
acquiring analysis items related to the target units from the analysis software bottom data structure library;
receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class, and determining target characteristic information, target load working condition and target analysis item;
and analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item.
2. The method of claim 1, wherein analyzing the software underlying database of data structures comprises: characteristic class, unit class, load class, working condition class, analysis class and result class;
the unit classes include: the base classes of a plurality of units, the base classes of a plurality of objects, and the nodes, the identifiers, the angles, the intervals and the unit types contained in each unit;
the property classes include: base classes of a plurality of objects, base classes of a plurality of properties, and types of each property;
the load classes include: base classes of the plurality of objects, base classes of the plurality of payloads, colors of the display, and payload types;
the working condition types comprise: base classes of a plurality of objects, base classes of a plurality of working conditions and working condition types;
the analysis classes include: base classes of a plurality of objects, base classes of a plurality of analyses, types of each analysis, solvers, scripts, associated unit information, condition load information, result information and result table information;
the result category includes: base classes of a plurality of objects, base classes of a plurality of results, and types, generation times, result files, associated unit information, work load information, result information, and result table information of each result;
wherein the characteristic class is associated with the unit class, and the analysis class is associated with the unit class, the load class, the condition class, and the result class.
3. The method of claim 1, wherein the step of receiving user setting operations for the characteristic information, the load condition, and the analysis class, and determining target characteristic information, a target load condition, and a target analysis class comprises:
receiving a first selection operation of a user on the characteristic information and/or a first input operation on newly added characteristic information;
determining target characteristic information according to the first selection operation and/or the first input operation;
receiving a second selection operation of the user on the load working condition and/or a second input operation on a new load working condition;
determining a target load working condition according to the second selection operation and/or the second input operation;
receiving a third selection operation of the user on the analysis item associated with the target unit and/or a third input operation on the newly added analysis item;
and determining a target analysis item according to the third selection operation and/or the third input operation.
4. The method of claim 3, wherein the step of analyzing the object to be analyzed according to the target characteristic information, the target load condition and the target analysis item comprises:
judging whether the target characteristic information, the target load working condition and the target analysis item are changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit;
and if the target characteristic information does not change, acquiring the target characteristic information, the target load working condition and an analysis result corresponding to the target analysis item from the analysis underlying data structure library.
5. The method according to claim 1, wherein the step of determining the target unit contained by the object to be analyzed comprises:
determining a target base class to which an object to be shared belongs;
displaying each first unit contained in the target base class;
receiving a fourth selection operation of the user on the first unit and/or a fourth input operation on the newly added unit;
and determining a target unit contained in the object to be analyzed according to the fourth selection operation and/or the fourth input operation.
6. An object analysis apparatus, characterized in that the apparatus comprises:
the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining a target unit contained in an object to be analyzed and attribute information of the target unit;
the first acquisition module is used for acquiring the characteristic information associated with the target unit from a preset analysis software bottom data structure library;
the second acquisition module is used for acquiring the load working condition associated with the target unit from the analysis software bottom data structure library;
a third obtaining module, configured to obtain an analysis item associated with the target unit from the analysis software underlying data structure library;
the receiving module is used for receiving the setting operation of the user on the characteristic information, the load working condition and the analysis class and determining target characteristic information, target load working condition and target analysis item;
and the analysis module is used for analyzing the object to be analyzed according to the target characteristic information, the target load working condition and the target analysis item.
7. The apparatus of claim 6, wherein the analysis software underlying database of data structures comprises: characteristic class, unit class, load class, working condition class, analysis class and result class;
the unit classes include: the base classes of a plurality of units, the base classes of a plurality of objects, and the nodes, the identifiers, the angles, the intervals and the unit types contained in each unit;
the property classes include: base classes of a plurality of objects, base classes of a plurality of properties, and types of each property;
the load classes include: base classes of the plurality of objects, base classes of the plurality of payloads, colors of the display, and payload types;
the working condition types comprise: base classes of a plurality of objects, base classes of a plurality of working conditions and working condition types;
the analysis classes include: base classes of a plurality of objects, base classes of a plurality of analyses, types of each analysis, solvers, scripts, associated unit information, condition load information, result information and result table information;
the result category includes: base classes of a plurality of objects, base classes of a plurality of results, and types, generation times, result files, associated unit information, work load information, result information, and result table information of each result;
wherein the characteristic class is associated with the unit class, and the analysis class is associated with the unit class, the load class, the condition class, and the result class.
8. The apparatus of claim 6, wherein the receiving module comprises:
the first submodule is used for receiving a first selection operation of a user on the characteristic information and/or a first input operation on newly added characteristic information;
the second submodule is used for determining target characteristic information according to the first selection operation and/or the first input operation;
the third submodule is used for receiving a second selection operation of the user on the load working condition and/or a second input operation on a newly-added load working condition;
the fourth submodule is used for determining a target load working condition according to the second selection operation and/or the second input operation;
the fifth submodule is used for receiving a third selection operation of the user on the analysis item associated with the target unit and/or a third input operation on the newly added analysis item;
and the sixth submodule is used for determining a target analysis item according to the third selection operation and/or the third input operation.
9. The apparatus of claim 8, wherein the analysis module comprises:
the judgment submodule is used for judging whether the target characteristic information, the target load working condition and the target analysis item are changed compared with the characteristic information, the load working condition and the analysis item associated with the target unit;
and the result obtaining submodule is used for obtaining the target characteristic information, the target load working condition and the analysis result corresponding to the target analysis item from the analysis bottom layer data structure library if the target characteristic information, the target load working condition and the analysis result are not changed.
10. The apparatus of claim 6, wherein the determining module is specifically configured to:
determining a target base class to which an object to be shared belongs;
displaying each first unit contained in the target base class;
receiving a fourth selection operation of the user on the first unit and/or a fourth input operation on the newly added unit;
determining a target unit contained in the object to be analyzed according to the fourth selection operation and/or the fourth input operation;
determining attribute information of the target unit.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911381033.4A CN111208990B (en) | 2019-12-27 | 2019-12-27 | Object analysis method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911381033.4A CN111208990B (en) | 2019-12-27 | 2019-12-27 | Object analysis method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111208990A true CN111208990A (en) | 2020-05-29 |
| CN111208990B CN111208990B (en) | 2024-05-24 |
Family
ID=70785581
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911381033.4A Active CN111208990B (en) | 2019-12-27 | 2019-12-27 | Object analysis method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111208990B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112130857A (en) * | 2020-08-18 | 2020-12-25 | 合科软件（北京）有限责任公司 | Data conversion method and device between models |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5566333A (en) * | 1992-11-05 | 1996-10-15 | Trace Technologies, Inc. | Relational database information management system for facilitating normalization of a relational database |
| CN102930164A (en) * | 2012-10-31 | 2013-02-13 | 北京航天自动控制研究所 | Conversion method of control data of aircraft |
| CN103793435A (en) * | 2012-11-02 | 2014-05-14 | 镇江华扬信息科技有限公司 | Method for converting object model to database structure |
| CN104636257A (en) * | 2015-03-13 | 2015-05-20 | 胡兢玉 | SQL coverage-based automatic testing method for application software in database based on |
| CN106796520A (en) * | 2014-10-08 | 2017-05-31 | 信号公司 | The real-time report of the instrumentation based on software |
| CN109165272A (en) * | 2018-08-21 | 2019-01-08 | 东北大学 | Geographical information visualization analysis system towards high score remote sensing image |
| CN109190007A (en) * | 2018-07-20 | 2019-01-11 | 阿里巴巴集团控股有限公司 | Data analysing method and device |
-
2019
- 2019-12-27 CN CN201911381033.4A patent/CN111208990B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5566333A (en) * | 1992-11-05 | 1996-10-15 | Trace Technologies, Inc. | Relational database information management system for facilitating normalization of a relational database |
| CN102930164A (en) * | 2012-10-31 | 2013-02-13 | 北京航天自动控制研究所 | Conversion method of control data of aircraft |
| CN103793435A (en) * | 2012-11-02 | 2014-05-14 | 镇江华扬信息科技有限公司 | Method for converting object model to database structure |
| CN106796520A (en) * | 2014-10-08 | 2017-05-31 | 信号公司 | The real-time report of the instrumentation based on software |
| CN104636257A (en) * | 2015-03-13 | 2015-05-20 | 胡兢玉 | SQL coverage-based automatic testing method for application software in database based on |
| CN109190007A (en) * | 2018-07-20 | 2019-01-11 | 阿里巴巴集团控股有限公司 | Data analysing method and device |
| CN109165272A (en) * | 2018-08-21 | 2019-01-08 | 东北大学 | Geographical information visualization analysis system towards high score remote sensing image |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112130857A (en) * | 2020-08-18 | 2020-12-25 | 合科软件（北京）有限责任公司 | Data conversion method and device between models |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111208990B (en) | 2024-05-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Paiva et al. | Robust and reliability-based design optimization framework for wing design | |
| US8126688B2 (en) | Method and apparatus for identifying gaps between parts | |
| US20070295700A1 (en) | Method and system for modeling spot welds in a finite element analysis | |
| Chiu et al. | On automating domain connectivity for overset grids | |
| US8862437B1 (en) | Multi-scale modeling of composite structures | |
| Morton et al. | HPCMP CREATETM-AV kestrel architecture, capabilities, and long term plan for fixed-wing aircraft simulations | |
| US20230028912A1 (en) | Automatic Design Assessment and Smart Analysis | |
| Morton et al. | A fixed-wing aircraft simulation tool for improving DoD acquisition efficiency | |
| Dey et al. | Capstone: a geometry-centric platform to enable physics-based simulation and system design | |
| US8244507B2 (en) | Method and apparatus for deriving associations between parts and fasteners | |
| Davies | Lockheed Martin overview of the AFRL EXPEDITE program | |
| CN111208990A (en) | Object analysis method and device | |
| CN109858189B (en) | Carrier rocket load analysis method | |
| CN108038335B (en) | Method and device for determining stress load of aircraft skin unit | |
| Petsch et al. | PANDORA-A python based framework for modelling and structural sizing of transport aircraft | |
| US8983817B2 (en) | Dynamic load balancing for adaptive meshes | |
| Morton et al. | Hpcmp createTM-av kestrel architecture capability and future direction | |
| Benaouali et al. | A surrogate-based integrated framework for the aerodynamic design optimization of a subsonic wing planform shape | |
| US8571838B1 (en) | Analysis of fluid flow over a surface | |
| CN111221921B (en) | Method and device for data transmission between models | |
| Zhang et al. | Modeling method and application in digital mockup system towards mechanical product | |
| Brooks | CREATE-AV DaVinci 3.0 and Capstone Integration | |
| Ahmed et al. | Real-time simulation as a new tool in future advanced aerospace project design and manufacturing processes | |
| US10831937B2 (en) | Formation of a simplified model | |
| CN115587805B (en) | Laboratory environment test project determining method and device and environment comprehensive test evaluation method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |