Research on Knowledge Network Modelling for Aero-craft

System Design

Xiang Zhai

, Feng Dai

, Huiyang Qu

, Lingling Zhong

and Chenyong Du

Beijing Complex Product Advanced Manufacturing Engineering Research Center, Beijing Simulation Center,

Beijing, China

School of Mechanical Engineering, Zhejiang University, Hangzhou, China

State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering,

Beijing, China

Aviation Engineering Institute, Civil Aviation Flight University of China, Sichuan, China

Beijing ZhiYuanChuangTong IT Co,Ltd, Beijing, China

Keywords: Knowledge Network Modelling, Aero-Craft Design, Ontology.

Abstract: A great amount of existing knowledge is required during the development of aero-craft system. At present,

the existing knowledge organization model construct different knowledge model for different stages is

difficult to adapt to the complicated product life cycle application. This study proposes a product

development oriented knowledge network model focusing on expressing the knowledge demands and

connecting the computer-aided system. Under the overall knowledge network model, this study describes

the ontology description method of spacecraft product model, development tasks and aerospace

terminology. Recommending missile aerodynamic knowledge within the design stage is presented as a case

study, and the framework and the method is proved to be effective.

1 INTRODUCTION

A great amount of existing knowledge is required

during the development of aero-craft system. The

current knowledge modelling methods are only

focus on single discipline, as they are highly

specified which are impossible to describe the Multi-

disciplinary knowledge related to aero-craft design.

This study analyses the concepts related to digital

prototyping of aero-craft system, and proposes a

knowledge organizing framework for aero-craft

design. Based on ontology language and unified

prototyping system, the quest of aero-craft

development and aerospace engineering knowledge

are constructed and described in an organized

knowledge framework. This study focuses on

expressing the knowledge demands in modelling and

connecting the computer-aided system. Pushing

aero-craft aerodynamic knowledge within the

framework is presented as a case study, and the

framework and the method is proved to be effective.

The demand of knowledge in aero-craft system

development can be categorized into the following

aspects (Feng, 2015):

(1) Aero-craft development involves many

practitioners and disciplines. Multi-disciplinary

knowledge support is highly required, and product

design phrase is required for consistent

communication and collaboration of experts from

design, manufacture and support.

(2) The application of knowledge content is

restricted, and the specialization rate is high.

Designers need to obtain specified knowledge in

individual requests. Thus, there is a need to match

the knowledge and the specified design activities.

(3) Knowledge such as existing design cases is

of high value. Based on previous experiences, the

design period can be shortened, and similar failures

can be avoided.

(4) The contents of knowledge are expressed in

different forms. A single knowledge note in product

design can have many forms, including technical

reports, models, algorithms and figures. The

description of knowledge is highly diversified which

requires for a knowledge system can express, store

and connect different forms of knowledge vectors

(5) The requirements of new aero-craft system

are changing, with an increasing flow of data and

240

Zhai, X., Dai, F., Qu, H., Zhong, L. and Du, C.

Research on Knowledge Network Modelling for Aero-craft System Design.

DOI: 10.5220/0006403202400247

In Proceedings of the 7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2017), pages 240-247

ISBN: 978-989-758-265-3

knowledge. The newly added knowledge should be

properly recorded and managed for avoiding

unnecessary loss and keeping

With development of information technology,

the development of aero-craft system is changing

towards a driving mode based on data, information,

knowledge and wisdom. The knowledge module and

product developing automation have becoming key

measures for improving development efficiency.

Thus, it requires unified depiction and organization

of knowledge storage, description, transmit, share

and reuse for covering corresponding aero-craft

development phrases. The method is supposed to

support the knowledge sharing, organizing and

automatic application during aero-craft development

procedure.

In this work, a novel knowledge network model

for aero-craft development is proposed for

integrating knowledge engineering and product

design. The main contributions include follows:

(1) Discussing the knowledge framework for

product development. Based on design of "product-

task-discipline", the internal structure and

connectivity of knowledge were discussed from

application and case study perspectives. The

framework covers all knowledge involving sectors

in product development.

(2) Constructing aerospace term base, and

using ontology language to express the standardized

terms and their interrelationships.

(3) Analysing product data model system and

combining multi-view requests. The relationships

between physical structure model, data result model,

case studies were discussed. Through connecting

product structure and development tasks, the reuse

of knowledge is improved. On the other hand, the

multi-disciplinary knowledge is automatically

matched to the product structure and development

tasks via using standardized terms in knowledge

expression, as a semantic support for knowledge

automation.

(4) Pushing knowledge based on application

scenarios within the knowledge network framework.

Taking aero-craft knowledge as a case study,

modelling it using ontology and using SPARQL

ontology reasoning query technology for knowledge

pushing and searching.

The merits of the proposed method: (1)

Combining knowledge network model and product

development mode, the knowledge generated during

the whole aero-craft development is organized and

modified to fit the requirements of practitioners with

the purpose of improving knowledge utilization

efficiency while lowering the management cost. (2)

Organizing knowledge according to the work flow,

which facilitates the automatic application of

knowledge in aero-craft development. (3) Fully

expressing the logic reasoning based on ontology

terms of knowledge, and knowledge pushing based

on scenarios is realized.

2 THE RELATED WORK

For knowledge organization and modelling the

current methods are only focus on single discipline

or function, as they are highly specified which are

impossible to satisfy the need of digital prototype

based developing mode. No report on life cycle

knowledge management and application. Some

researchers established knowledge models based on

product structure and specified disciplinary domain.

Yongdang proposed the implementing framework of

knowledge organization model for aircraft engine

design based on ontology (Yongdang et al., 2007).

Changjie et al. put forward ontology based

knowledge expressing method for tooling design

knowledge, which included four sub-ontology

models: design object, designer, design flow and

design knowledge (Changjie et al., 2014). Bock

established a product-based descriptive model to

depict products from environmental, behavioural,

and performance perspectives (Bock et al., 2010).

The existing methods have some values in various

applications, but they have certain limitations in

current product design activities. Physical

prototyping is now gradually replaced by digital

prototyping. The knowledge generated in the process

requires for proper management. Knowledge

organization model should be robust and adaptive

during the mode transformation, due to co-existence

of knowledge within new and old prototype

development modes (Abdullah et al., 2002). For

development of complicated product such as aero-

craft system, multi-disciplinary knowledge is

desirable, hence knowledge organization should.

Instead of single knowledge note, knowledge cluster

is required. Current knowledge models are

developed for certain phrase, which cannot handle

the life cycle (Teswanich et al., 2002). During the

establishing ontology, the relationships between

tasks, products and knowledge have always been

neglected. In the proposed knowledge model, digital

prototyping and expression of technical terms during

product development are discussed, with a focus on

modelling knowledge demand and application of

CAD system.

Research on Knowledge Network Modelling for Aero-craft System Design

241

Devopement

Task

Product

Model

Standard

Terminology

Aerocraft System

Task

Aerocraft

Pneumatic Shape

Design

Assembly

Shape Design

Pneumatic

Parameter

Calculation

Aerocraft

System

Pneumatic

Sub-system

Guidance

Sub-system

Aerocraft

Pneumatic

Layout

Aerocraft Pneumatic

Shape Design For

Pac-3

Pac-3 Pneumatic

Sub-system

Pac-3

Guidance

Sub-system

Wingless

Rudder

Normal Type

Duck-style

Layout

Abstract

Layer

Business

Layer

Instance

Layer

Figure 1: Knowledge modelling architecture for aero-craft design.

3 KNOWLEDGE MODELING

ARCHITECTURE

Knowledge modeling architecture for aero-craft

design is divided into three layers as shown in

Figure 1. In abstraction layer defines the contents of

top-level knowledge, in business layer divides the

complex product manufacturing system into details,

and in instance layer realizes concrete expression

and organization of knowledge oriented to the

specific product models. In knowledge modeling

architecture the dotted lines represent the subclass

inheritance relationship in various knowledge

resources, while the solid lines describe the

relationship between related objects.

The abstraction layer of knowledge modelling

architecture mainly includes: (1) Product-model

class, which mainly characterizes the general

product structure, including detailed product

structure and some parameters related to product life

cycle (Panetto et al.,2012), such as physical model,

data model, core function, performance parameters

and etc. These parameters can be specifically

expressed as researching products, mature models or

product structure and key indicators’ parameters for

other historical products. From the physical

structure, the class contains systems, subsystems,

equipment and their hierarchical relationships, key

parameters and functional description. (2) R&D

class: is the main scene for R&D and an important

carrier of knowledge demand. In this paper, the class

is playing a more important role in organizationally

expressing knowledge from time and scene

dimension. (3) Terminology class: is unified

knowledge of professional standard vocabulary and

the relationship between them, mainly used for

illustrating product model examples and description

constraints for developing task instances.

Additionally, the knowledge resources with the

terms or the keywords can also be organized into

knowledge modeling architecture of professional

domain dimensions.

The business layer defines subclasses of three

abstract classes, R&D tasks, aero-craft subsystems

and space terms, combining with specific business

process division, product structure division and

involved professional areas in R&D of aero-craft

system. Among them, aero-craft-subsystem class is

refined into detailed subsystem and related

architecture of the aero-craft. R&D class is refined

into a series of specific R&D tasks connected with

each specific sub-system. Space-term class includes

the professional area, environmental requirements,

technical approaches and other contents in the field

of aero-craft’s R&D.

The instance layer puts forward the specific task

examples, product model examples, standard

terminology examples and etc. for classes defined in

the business layer. In the layer, the product models,

composed of composition and parameters, are

divided into the product subsystems and

corresponding parameter file reports in accordance

with aero-craft overall category templates in aero-

craft system. The tasks are refined into specific

models in work nodes of collaborative design

system. The standard terminology examples are

specifically illustrated as terminology entries,

standard definitions and professional relationship.

After the completion of knowledge modeling

architecture, this paper will discuss about the

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product model, R&D task and storage and

expression of standard terminology. As the

mainstream knowledge representation method in the

field of knowledge engineering, ontology,

implementing the knowledge model, can guarantee

the uniqueness of knowledge comprehension,

express various types of semantic-complex

knowledge and establish the interrelations among

amount of knowledge.

4 ONTOLOGY DESCRIPTION

FOR PRODUCT-MODEL CLASS

In the R&D of aero-craft system, the product model

of product structure, data and function, has multi-

view application requirements (Lu et al., 2010). It is

necessary to organize, analyse and elaborate the

product model by comparing R&D goals and current

modes in different views. In the process of R&D, the

system can be divided into structure view, function

view and performance view according to different

uses. Figure 2 shows the interaction between various

modes of view application.

Function View

(For Lifecycle

Activities And

Process)

Structure View

（For Design And

Definition）

Performance

View

(For Analysis,

Simulation And

Test Validation)

· Flight Process

· Assembly

Process

· Maintenance

Process

· Flight Process

· Assembly

Process

· Maintenance

Process

· Mechanical

System

Structure And

Interface

· Electrical

Composition

And Interface

· Mechanical

System

Structure And

Interface

· Electrical

Composition

And Interface

· Mechanics

· Electromagneti

· Optics

· Mechanics

· Electromagneti

· Optics

Figure 2: Various modes of view application.

The background of multi-view application puts

forward new requirements for constructing,

describing and storing aerospace product models and

information by using ontology description method.

The requirements are mainly reflected in the

following aspects:

(1) Dynamicity. The storage and display of the

ontology model should be dynamic, especially when

describing the functional view, which is able to

satisfy the need for illustration and application of

space knowledge from time to time.

(2) Flexibility. Storage of the ontology model

can be instantly switched referring to different needs

for various views. It cannot be occurred that the

application needs are not be quickly satisfied due to

complexity of the structure.

(3) Comprehensiveness. The storage and display

of ontology model should be able to cover the

different needs of various view application.

(4) Intuitiveness. Visualization of the ontology

model should be intuitive for being presented

directly in front of the applicators through by

graphical structure.

(5) Extendibility. New product model and R&D

task may cause optimization and complement to the

ontology model due to uncertainty during R&D

procedure. As a consequent, storage and display of

ontology model should be of extendibility from

ontology class structure to the related instance.

System

Subsystem

Part Of Part Of

Device1

Device2

Part Of

Subsystem

Functional

Requirements

Key

Parameter1

Device Functional

Requirements

Key

Parameter1

System Functional

Requirements

Key

Parameter3

Figure 3: Aero-craft product model.

Figure 3 shows a description example of an aero-

craft product model. According to the definition of

aero-craft’s digital prototype, the device components

are established as the ontology class referring to the

product hierarchical division method of “system,

subsystem, single-device”, and the hierarchical

relationship is constructed based on existing method

of modelling digital prototype.

For system, subsystem or device, each level of

the ontology class has many related instances,

covering different functional requirements, key

parameters and key models. The associated models

are mainly represented as the following categories:

(1) System functional requirements: consist of

task requirements, combat process, maintenance

process and other items. Functional requirements

must be marked with environmental constraints,

such as the influence of environment, like the

atmosphere and electromagnetic, and non-system

entities, for instance the target’s characteristics faced

by weapon system.

Research on Knowledge Network Modelling for Aero-craft System Design

243

(2) Key parameters: key information in R&D

process of the aero-craft product digital prototype in

accordance with requirements for parametric

development.

(3) Key models: are the structure, the electronic

CAD files and CAE three-dimensional models for a

cured device.This type of information can also be

treated as a structural content associated in the

ontology framework.

Figure 4 shows a model view of aero-craft

pneumatic subsystem. For the case of mature aero-

crafts, the view involves the relationship between

product-model class and parameters, the relationship

between product-model class and files, and the

relationship between product-model class and

models.

Aerocraft

(missile)

Pneumatic

Subsystem

Guidance

Subsystem

Part Of Part Of

Pneumatic

Surface

Head

Part Of

Diameter

Rudder Surface

Size

Combat

Altitude

Pneumatic

Layout

Combat

Distance

Attack

Targets

Airfoil

Size

Head

Curve

Figure 4: A model view of product structure.

The instance, describing the components and related

parameters of aero-craft subsystem by the ontology

language, is shown as follows:

<MACH NUMBER RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#FLOAT

"> 5 </ MACH NUMBER>

<MANEUVERABILITY RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#FLOAT

"> 2.0 </ MANEUVERABILITY>

<TARGET AND AIRSPACE> <OWL:

NAMEDINDIVIDUAL RDF: ID = "XX - CRUISE

MISSILE AIRSPACE">

<COMBAT HEIGHT RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#FLOAT

"> 12KM </ COMBAT HEIGHT>

<DEVELOPED COUNTRY RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#STRIN

G"> US </ DEVELOPED COUNTRY>

<RUDDER SIZE RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#FLOAT

"> 332.0 </ RUDDER SIZE>

<AIRFOIL SIZE RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#FLOAT

"> 1056.0 </ WING SIZE>

</MISSILE CLASS RDF: ID = "XX

MISSILE">

5 THE ONTOLOGY OF DESIGN

TASK

Design task mainly shows the scene and

environment of products’ development, as well as an

important concrete scene of knowledge reuse

(Xuwei et al., 2009). In the actual description, using

IDEF0 model expression method, combined with

ICOM (Input, Control, Output, Mechanism)

structure to achieve the model description for

products’ design task. One advantage of the IDEF

modeling approach is that graphical representations

can clearly describe model order, constraints, and

resources. Also in ICOM, supplementary task

activity description D and Mechanism M which is

decomposed into personnel organization H and

knowledge resource K, constitute a task node model

ICO-DHK model that describes knowledge

integration applications. The design task’s ontology

description model can be expressed as shown in the

figure.

Output

Task Work

Surface

Input

Context Description

Area

Historical

Case

Expert

Experience

Standard And

Specification

Time Period Environment Quality Target

Figure 5: Ontology description of design task.

The task ontology model can be described as a group

of six-tuple model ICO-DHK (I, C, O, D, H, K).

I represents the data input of the task node,

describes the source, format, unit and quantity of the

data entry;

C represents the task node control, which is

actually composed of various constraints of the task

process, including time period, environment, quality,

target, cost, task flow, cycle judgment condition;

O represents the data output of the task node,

describing the destination, format, unit and quantity

of the data output;

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244

D describes the professional and working content

of the task node;

—H describes the personnel organization of the

task node;

K describes the task tool resource and task

knowledge resource of the task node

The data input of the task node I, the task node

control C, the data output of the task node D, the

personnel organization H constitute the task

ontology description. In addition, inheriting from the

IDEF0 structure description, it still has the task of

decomposition of the lower level, as shown in Figure

An example of using the ontology language to

describe the design task is as follows:

<TASK NODE RDF: ID = "BALLISTIC

VERIFICATION">

<TASK NAME RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#STRIN

G"> BALLISTIC VALIDATION </ TASK NAME>

<DOWNSTREAM TASK RDF: RESOURCE = "#

TASK END" /><CONSTRAINT>

<CONSTRAINT CLASS RDF: ID = "FULL

WEIGHT VERIFICATION">

<CONSTRAINT NAME RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#STRIN

G"> FULL WEIGHT VERIFICATION QUALIFIED

</ CONSTRAINT NAME>

<CONSTRAINT VALUE RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#STRIN

G"> 235KG </ CONSTRAINT VALUE>

<CONSTRAINT TYPE RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#STRIN

G"> FULL WEIGHT </ CONSTRAINT TYPE>

</ CONSTRAINT>

<TASK DESCRIPTION RDF: DATATYPE =

"HTTP://WWW.W3.ORG/2001/XMLSCHEMA#STRIN

G"> BALLISTIC VALIDATION </ TASK

DESCRIPTION>

</TASK NODE>

6 THE ONTOLOGY

DESCRIPTION OF SPACE

TERMINOLOGY

The use of standard terminology in the field of

expertise can clearly regulate the relationship

between terminology and jargon, and ensure the

normalization and consistency of semantic

representations in the knowledge network model

(Feng, 2015). At the same time, the use of the

association relationship between terminologies can

achieve the knowledge networking of product and

development task example.

This article draws on the "space science and

technology descriptors" as the lexicon of descriptors.

It is an industry vocabulary in the field of aerospace

industry with System integrity, which sets the

terminology of the various disciplines and expertise

as a whole. It contains 21 first-class categories and

221 secondary categories (Ying, 1995). Each of the

terminology includes Chinese name, pinyin, English

name, and category. The association relationships

between terminologies include the use, substitution,

belonging, dividing and so on. An example of using

the ontology language to describe the terminology is

as follows:

<Terminology rdf: about =

"http://www.owl-

ontologies.com/unnamed.owl# satellite

spray logo">

<Pinyin rdf: datatype =

"http://www.w3.org/2001/XMLSchema#strin

g"> Wei xing pen tu biao zhi </ Pinyin>

<English word rdf: datatype =

"http://www.w3.org/2001/XMLSchema#strin

g"> Satellite marking </ english words>

<Category rdf: about = "http://www.owl-

ontologies.com/unnamed.owl# general

concept of aerospace technology">

<Category number rdf: datatype =

"http://www.w3.org/2001/XMLSchema#strin

g"> 0201 </ category>

<Category name rdf: datatype =

"http://www.w3.org/2001/XMLSchema#strin

g"> general concept of aerospace

technology </ category name>

</ Category>

<Chinese word rdf: datatype =

"http://www.w3.org/2001/XMLSchema#strin

g"> satellite spray logo </ Chinese

words>

</ Terminology>

It is important to emphasize that the above

professional standard terminology will be construed

as a described constraint for product design task or

product structure. In other words, such as attack

target, combat height, combat distance and other key

parameters of aero-craft overall system development

task, and pneumatic layout, track diameter, head

curve, rudder dimensions , air foil dimensions and

other key parameters of pneumatic related product

structure need to be expressed in professional

standard terminology.

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245

7 KNOWLEDGE

RECOMMODATION

The ultimate goal of establishing a knowledge

network model for business scenarios is to realize

the knowledge networking and efficient reuse of the

product development process, and to open up the

knowledge flow in the business scene .In order to

verify the validity of the discussion model, the text

uses the OWL language to compile a set of

knowledge network model for the pneumatic

selection design task with the model development

background. The model example uses the model

pneumatic subsystem as the product, and the

Pneumatic shape design tasks for the examples of

development tasks, associated with pneumatic

design-related standard terminology. Examples of

knowledge in the model include the Aero-craft

pneumatic design scheme the empirical and

knowledge related to the pneumatic design selection

in the World Aero-craft Cluster. Through the

description of the knowledge network model to

realize the close relation in product models,

development tasks and professional terms, and

design system to support specific model tasks for

knowledge push associated with the enterprise

system. The specific process is as follows:

(1) First of all, the existing aero-craft case

should be localized. Its structured description can be

achieved through expressed in Standard

Terminology. The main products covered the key

aero-craft models in the United States, Russia and

other countries of the "Aero-craft Daquan (third

edition)", as well as some parameters, reports and

models related with products pneumatic designs in a

research institute. The application software obtains

the product description files and automatically.

(2) The application software cooperates with

the enterprise collaborative design platform and the

product development task example to obtain the

basic attribute and the key core index requirement of

the task, and obtains the situation information of the

task by using the interface provided by the

collaborative design system. It mainly includes: (1)

Basic attributes of the task, including the task name,

the project name, the task template of the source,

etc. (2)Task subscription and published data,

including Input parameter name, parameter value,

parameter type, and output description name,

parameter requirements, and parameter type. The

specific task requires designing a model of ground-

to-air aero-craft pneumatic layout design. The

development of the task type package in knowledge

network is the specific development task example.

Table 1 shows the main pneumatic parameters.

Table 1: Main parameter for task.

Project Name

Missile Design

Xxx Missile Design

Task Name

Pneumatic Layout Design

Product System

Pneumatic Subsystem

Input Parameter

Target

High Speed Fixed Wing

Aircraft, Cruise Missiles

Mach

Combat Distance

1.5KM-10KM

Combat Height

0km-12km

Output Parameter

Pneumatic Layout

Diameter

Rudder Size

Wing Size

(3) The software system utilizes the SPARQL

query method to obtain the existing design

experience or scheme which meets the task

requirements by using the ontology description

reasoning of the specific product development in the

knowledge network model .In this case, we carry out

knowledge search for "aero-craft case" knowledge,

and then use the input parameters of the task to

match the reasoning .For example, the attack target

in this paper is a aero-craft case in the associated

knowledge base similar to a counterpart with a high-

speed fixed-wing aircraft, and the input parameter

constraint of the Mach 5. The SPARQL query is as

follows:

PREFIX rdf:

<Http://www.w3.org/1999/02/22-rdf-

syntax-ns#>

PREFIX rdfs:

<http://www.w3.org/2000/01/rdf-schema#>

PREFIX owl:

<http://www.w3.org/2002/07/owl#>

PREFIX base: <http://www.owl-

ontologies.com/unnamed.owl#>

SELECT distinct? Missile? Layout?

ControlSurfaceSize? WingSurfaceSize

WHERE {

Missile rdf: type base: missile class.

Missile base: aeronautical subsystems.

? Missile base: Pneumatic layout.

? Missile base: rudder size?

ControlSurfaceSize

? Missile base: wing size?

WingSurfaceSize

Missile base: aeronautical subsystems.

? Missile base: target and airspace? T.

? T base: target. Targets .Filter

(targets = 'high speed fixed wing

aircraft'

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246

|| targets = cruise missiles').

? Missile base: Mach number? MachNumber

.Filter (? MachNumber> = 5).

Missile base: operational distance.

OperationalRange .Filter

(operationalRange> = 1.5 ||

operationalRange> = 10).

? Missile base: combat altitude?

CombatAltitude .Filter

(? CombatAltitude <= 12).

};

After the ontology description push, product

development staff can get the product examples

which meet the requirements of the product

development and their associated product design,

model and other knowledge resources in the

pneumatic design task work surface. Figure 6 is the

interface of knowledge display pushed by

application software.

Figure 6: Case knowledge display.

8 CONCLUSION

This paper focuses on the framework of knowledge

network model for aero-craft design. And based on

the framework, this paper conducts knowledge

networking and push application validation for

pneumatic layout design tasks of aero-craft product

pneumatic subsystem. This framework realizes the

fusion of the simulation of knowledge network and

task scene, which can quickly build a knowledge

networking and application sharing platform.

Subsequent work will improve the overall

framework to make it suitable for applications such

as automatic knowledge discovery.

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