structure optimization of the hub component in catia v5 _ mbi-wiki

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Structure Optimization of the Hub Component inCATIA V5Posted on 14. December 2010 by houdezhi

1. Introduction of Model and Structure Optimization inCATIA V5


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1.1 Introduction of the Hub Components Model

Hub is a force bearing component, which is used to connect the wheeland the axle shaft. According to different diameters, widths and

materials, the hub can be classified into many sorts. In this optimizationcase, the diameter of general family autos hub, 16 Inch, will bechoosed. Furthermore, the most common steel hub will be analyzed inthis structure optimization.

1.2 Purpose and Approach of the Hub Structure

Optimization in CATIA V5The structure optimization in CATIA V5 bases on model in Part Design

module and Generative Structural Analysis module. Generally

speaking, a target variable, which must be maximized or minimized in

optimization procedure, is necessarily defined before the optimization

procedure. First of all, 3D model of hub structure is constructed in

CATIA V5 with the respective determined parameters except diameter

of the hub, as shown in Fig1.1a and Fig1.1b. After attributing the

material property, next step is to make FEM static analysis of the

constructed model in Generative Structural Analysis module of CATIA

V5.


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Fig1.1a Model of Hub Component


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Fig1.1b Initial Dimension of Hub Component

In this structure optimization case, maximum stress is controlled in

order to ensure the safety condition during the using period of wheel,

and avoid unexpected damage on the surface of hub component, such

as crack. Boundary and loading condition is shown as Fig1.2a, in order

to reduce the time cost of calculation, the local mesh should be finely

generated (Fig1.2b). According to FEM analysis result in Fig1.2c, it is

certain from the Von Mises Distribution that Von Mises stress in

the area near the loading is maximum in the whole part, so it seems

that the crack will happen firstly probably at this region. However, in

real case the crack will begin most probably at the outside part of thewhole component, not at the center area. It is a interesting problem for

the engineers, the experience here plays a very important role in the

designing procedure. Then a local sensor is so essential to be applied

to illustrate the change of optimized target variable, maximum Von

Mises stress. It becomes clear, whether the optimized variable is

acceptable or not. In Fig1.2c, maximum Von Mises stress is 3,205MPa,

in next optimization steps this Von Mises stress will be minimized as

much as possible.


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Fig1.2a Boundary and Loading condition in Generative Structure

Analysis


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Fig1.2b Mesh and Local Mesh Generation


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Fig1.2c Result of FEM Analysis

In CATIA V5 there is a module Product Engineering Optimizer, it

supports the optimization of different parameters easily with different

included algorithms. In this case the maximum Von Mises stress is

defined as optimized parameter, and optimized type is setted as

minimum. Convergent speed and accuracy of the final result dependsheavily on how to choose free parameters. That means the select of

free parameters has an important influence on the final result. In the

following section, it will be discussed about how to choose free

parameters in this structure optimization case. After setting termination

criteria, the optimization process can be started finally.


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2. Preprocessing and Processing of OptimizationProcedure

As mentioned above, the choosing of free parameters is very important

for final result. So at the first time, six parameters are chose as the free

parameters, as shown in Fig2.1.

Fig2.1 Six free parameters in first time

At the first time, six parameters would be as free parameters with

inferior range and superior range. These parameters are modified

between the inferior and superior range during optimization, until

optimized parameter is acceptable, which in this case is minimum on

Von Mises stress. The other attribute of optimization, such asoptimization algorithm, maximum running time and so on, can also be


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set in the optimization window, as shown in Fig2.2. In this case

Simulated Annealing Algorithm is set as algorithm type, Convergence

Speed is fast.

Fig2.2 Optimization Window

The purpose to choose six dimensions as free parameters is to confirm

which parameter has large influence on optimized parameter

(maximum Von Mises stress). That means, if some free parameters arechanged slightly, optimized parameter will faster converge to

the acceptable result. Oppositely, the convergence effect of other

parameters is not so obvious. After the first optimization, the structure is


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changed as shown in Fig2.3a and Fig2.3b.

Fig2.3a Model of Hub Structure with Maximum Von Mises Stress

3.173MPa after the First Optimization with six Free Parameters


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Fig2.3b Sketch of Hub Structure after First Optimization with six Free

Parameters

It is obvious that maximum Von Mises stress is reduced to 3.173MPa.

Next step, one free parameter is abandoned, only five left (highlighted

in Fig2.4b). The other properties are same as previous. After 1 hour

running time, Von Mises stress is reduced to 2.947MPa (Fig2.4a and

Fig2.4b).

Fig2.4a Model of the Hub Structure with Maximum Von Mises Stress

2.947MPa after Five Free Parameters Optimization


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Fig2.4b Sketch of Hub Structure with Maximum Von Mises Stress

2.947MPa

According to the sight of model, it is clear that the holes on the hub

structure have crossed with the fillet on the surface. The position

dimension of the wholes should be modified as shown in Fig2.5.Due to

the modification the maximum Von Mises stress is decreased to

2.908MPa.


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Fig2.5 the Modified Hub Structure with Maximum Von Mises Stress

2.908MPa

By now, maximum Von Mises stress decreases from 3.205MPa to

2.908MPa, only 9.3% reduction. This result is far from acceptable.

Further optimization must be made. From now on, three free

parameters are set, highlighted in Fig 2.6a.


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Fig 2.6a Sketch of Hub Structure with maximum Von Mises Stress

2.667MPa

After half hours running, the maximum Von Mises stress on the surface

is reduced to 2.667MPa, as shown in Fig 2.6b.


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Fig2.6b Model of Hub Structure with Maximum Von Mises Stress

2.667MPa

From original maximum Von Mises stress 3.205MPa to 2.667MPa, it is

already 16.8% reduction. However, at least 20% of original maximum

stress should be reduced. The maximum Von Mises stress should

be further optimized. Because it takes long time to get little reduction of

optimized parameter, when optimization is going on with the same

three free parameters, the constraint in the sketch is changed. As


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shown in Fig2.7a, Radius.32 is token place by Length.31.

Fig2.7a Sketch with the Changed Constraint for Next Steps

Optimization

Fig2.7b Model of Hub Structure with Maximum Von Mises Stress

2.485MPa at the Last Optimization


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As shown in Fig 2.7b, at the last optimization the maximum Von Mises

stress is reduced to 2.485MPa, it is 22.5% reduction compared to the

original 3.205MPa. Finally, an acceptable result is achieved.

3. Data Processing of Optimization Procedure

At the first attempting of optimization, six free parameters are selected

(Fig3.1a) and the optimization data is reserved (Fig3.1b). The

maximum Von Mises stress is reduced from 3.205MPa to 3.172MPa

(Fig3.1c).

Fig3.1a Free parameters in optimization processing


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Fig3.1a Optimization data at the first optimization with six free

parameters

Fig3.1b the change processing of Maximum Von Mises stress in the

first optimization

Next step, one free parameter is less and the maximum Von Mises

stress is reduced from 3.172MPa to 2.947MPa, 7% reduction.


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Fig3.2a Optimization data at the second optimization processing with

five free parameters


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Fig3.2b the change processing of maximum Von Mises stress at the

second optimization

From now on, only there free parameters are set, but the maximum

stress is greatly reduced, from 2.947MPa to 2.667MPa, 8% reduction.

And after modification of constraint, 5.6% of original maximum is

decreased.


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Fig 3.3a Optimization data in the optimization with three free

parameters

Fig3.3b the change processing of maximum Von Mises stress


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Fig3.4a Optimization data after modification of constraints

Fig3.4b the change processing of maximum Von Mises stress


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