CN105956326A - Response surface model-based roll coolant system technological parameter optimization method - Google Patents
Response surface model-based roll coolant system technological parameter optimization method Download PDFInfo
- Publication number
- CN105956326A CN105956326A CN201610349243.5A CN201610349243A CN105956326A CN 105956326 A CN105956326 A CN 105956326A CN 201610349243 A CN201610349243 A CN 201610349243A CN 105956326 A CN105956326 A CN 105956326A
- Authority
- CN
- China
- Prior art keywords
- roll
- model
- fatigue
- technological parameter
- response surface
- 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
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000005457 optimization Methods 0.000 title claims abstract description 28
- 239000002826 coolant Substances 0.000 title claims abstract description 15
- 238000001816 cooling Methods 0.000 claims abstract description 33
- 238000013461 design Methods 0.000 claims abstract description 24
- 238000004458 analytical method Methods 0.000 claims abstract description 21
- 230000008878 coupling Effects 0.000 claims abstract description 15
- 238000010168 coupling process Methods 0.000 claims abstract description 15
- 238000005859 coupling reaction Methods 0.000 claims abstract description 15
- 238000005098 hot rolling Methods 0.000 claims abstract description 9
- 238000005096 rolling process Methods 0.000 claims description 24
- 238000012360 testing method Methods 0.000 claims description 17
- 229920001187 thermosetting polymer Polymers 0.000 claims description 13
- 230000026676 system process Effects 0.000 claims description 10
- 239000000463 material Substances 0.000 claims description 6
- 230000005855 radiation Effects 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000000977 initiatory effect Effects 0.000 claims description 3
- 238000004088 simulation Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 abstract description 3
- 239000007787 solid Substances 0.000 abstract 1
- 239000000498 cooling water Substances 0.000 description 20
- 238000004519 manufacturing process Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 230000035882 stress Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000003754 machining Methods 0.000 description 2
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000004224 protection Effects 0.000 description 1
- 230000008646 thermal stress Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/36—Circuit design at the analogue level
- G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Control Of Metal Rolling (AREA)
- Metal Rolling (AREA)
Abstract
The invention discloses a response surface model-based roll coolant system technological parameter optimization method. The method is characterized by comprising the following steps: (1) establishing a thermo-solid coupling model for optimizing an object hot rolling system and a fatigue life prediction model of an object roll; (2) selecting a plurality of roll coolant system technological parameters as optimization variables, determining a design space and an optimization objective thereof, extracting experimental sample points, and carrying out calculation to obtain a response value of a roll work period; (3) establishing a second-order response surface model, reflecting the relationship between input and output, of the roll work period according to the obtained response value; and (4) determining a roll cooling technological parameter value when the roll work period is the longest according to the response surface model, substituting the optimization result into the fatigue life prediction model to carry out fatigue analysis, and verifying the coolant system technological parameters until the optimum technological parameter is obtained. The method disclosed in the invention has relatively high reliability, applicability and operability, and can be used for effectively prolonging the fatigue life of roll parts in the hot rolling process.
Description
Technical field
The present invention relates to a kind of Machining Technology, especially a kind of Roller Machining technology, specifically one is based on response
The roll coolant system process parameter optimizing method of surface model.It is particularly suitable for roll coolant system various in the operation of rolling
Technological parameter is optimized design.
Background technology
It is known that roll is as the expendable part of the operation of rolling, expensive, it should by complicated severe periodicity alternation
Power, including thermal stress, rolling stress, reaction of bearing etc., surface is easily generated fatigue crack, has a strong impact on product quality.Mesh
Before, general cut deal volume each order of classes or grades at school of factory (8 hours) will carry out reconditioning to roll.Cut it is therefore desirable to propose one
Real feasible, the method for actually active raising roll campaign.
In the roll operation of rolling, the cooling effect of cooling water has important shadow to roller surface temperature field and Stress Field Distribution
Ring, there is large effect the fatigue life of roll.Thus can be by the cooling technological parameter of cooling system (is included cooling
Water pressure, jet angle, water temperature, jet density etc.) optimization, improve roll fatigue life.And for this parameter tradition
Optimization Design mainly determined the optimal solution scope of optimised parameter by single factor experiment, this method is difficult to search out
The concrete numerical value of optimised parameter, it is impossible to meet actual production demand.It is therefore proposed that a kind of roll based on response surface model
Cooling system process parameter optimizing method for designing, the problem solving to determine optimum cooling technological parameter exact value.
Summary of the invention
It is an object of the invention to mainly pass through single factor experiment for the Optimization Design of existing roll cooling technological parameter
Determine the optimal solution scope of optimised parameter, be difficult to search out the concrete numerical value of optimised parameter, it is impossible to meet actual production need
The problem asked, invents a kind of roll coolant system process parameter optimizing method based on response surface model, tired to improve roll
Life-span.
The technical scheme is that
A kind of roll coolant system process parameter optimizing method based on response surface model, it is characterised in that comprise the steps:
(1) thermosetting coupling model and the fatigue life prediction model of object roll of optimization object hot rolling system are set up；
(2) choose multiple roll coolant system technological parameter as optimized variable, and determine its design space and optimization aim,
Extract test sample point, and be calculated roll working cycle response value by model in step (1)；
(3) according to calculated response value in step (2), the roll working cycle of reflection input and output relation is set up
Second-order response surface model；
(4) according to response surface model, determine the roll cooling process parameter value when roll working cycle is the longest, and will optimize
Result is brought fatigue life prediction model into and is carried out analysis of fatigue, verifies cooling system technological parameter, until the technique obtaining optimum
Parameter.
Wherein:
The thermosetting coupling model setting up optimization object hot rolling system described in step (1), comprises the steps:
1) consider the symmetry of rolling system, the 1/4 of realistic model is analyzed, i.e. set up the 1/2 of upper roller axially,
Material properties axially and 1/2 thickness of rolled piece and the FEM (finite element) model of 1/2 width, and is added in the 1/2 of upper backup roll, setting
Constraint；
2) when calculating Coefficient of Roll Temperature Field, it is considered to transmission of heat by contact between high temperature rolled piece and roll, cooling system to wandering
Heat and the aerial heat radiation of roll, utilize the rotary simulation operation of rolling roll mechanical periodicity of roll model coordinate systems
Heat exchanging process, to ensure the precision of model；
3) respectively contact is set between roll model and rolled piece model, roll model and support roller former, according to rolling work
Skill parameter is that rolled piece arranges drafts, linear velocity, adds angular velocity for roll.
The fatigue life prediction model setting up roll described in step (1), to calculate the time of roll fatigue crack initiation；
In conjunction with rolling system thermosetting coupling model, and the stress-longevity of roll material need to be added when setting up roll fatigue life prediction model
Life curve.
Optimized variable described in step (2) refers to combine Rolling Production field condition and controlled cold in the operation of rolling
But system process parameters.
The design space of the optimized variable described in step (2) refers to contain the Parameters variation model of optimum cooling technological parameter
Enclose.
Optimization aim described in step (2) refers to that roll roll working cycle before germinating fatigue crack is the longest.
The test sample point of the analysis of Fatigue-life described in step (2) is to determine rationally according to non-linear test design method
Testing site.
The calculating of the response value described in step (2) includes:
1) use finite element analysis software that test sample point is carried out thermosetting coupling analysis, extract answering of key position node
Power state；
2) based on finite element analysis of fatigue software, roll is carried out analysis of Fatigue-life, obtain roll before germinating fatigue crack
Working cycle be response value.
In step (3), the second-order response surface model representation for n design variable is:
In formula: y is the output variable roll working cycle；XiTechnological parameter is cooled down for design variable；N is design variable
Number；β is undetermined coefficient, least square fitting obtain.
The response surface built by step (3) described in step (4), it is thus achieved that the roll when roll working cycle is the longest is cold
But process parameter value, carries out analysis of fatigue using optimum results as fatigue life prediction model boundary condition, contrasts cooling technique
Analysis of Fatigue-life result before and after parameter optimization, if the cooling technological parameter after You Huaing can significantly extend the working cycle of roll,
Then meet requirement, optimize and terminate and export optimum results, otherwise, rebuild the response surface, continue to optimize.
Beneficial effects of the present invention:
Roll for hot-rolling operation of rolling non linear finite element analysis is combined by the present invention with response surface optimization method, improves cooling
The optimization efficiency and precision of technological parameter, is designed by the optimization of cooling system technological parameter, it is possible to increase the working cycle of roll,
Effectively increase the service life.Solve and existing optimisation technique is difficult to ensure that the accurate and the most excellent problem of result, have higher
Reliability, the suitability and operability.
Accompanying drawing explanation
Fig. 1 is the rolling system schematic diagram of the present invention.
Fig. 2 is the cooling system process parameter optimizing designing technique flow chart of the present invention.
Detailed description of the invention
The present invention is further illustrated with embodiment below in conjunction with the accompanying drawings.
As shown in Figure 1-2.
A kind of roll coolant system process parameter optimizing method based on response surface model, comprises the steps:
1. set up the thermosetting coupling model of optimization object hot rolling system (as shown in Figure 1) and the tired longevity of object roll
Life forecast model.
The step of the thermosetting coupling model setting up optimization object hot rolling system is:
(1) consider the symmetry of rolling system, the 1/4 of realistic model is analyzed, i.e. set up the 1/2 of upper roller axially,
Material properties axially and 1/2 thickness of rolled piece and the FEM (finite element) model of 1/2 width, and is added in the 1/2 of upper backup roll, carries out
Reasonably constraint；
(2) when calculating Coefficient of Roll Temperature Field, it is considered to the transmission of heat by contact between high temperature rolled piece and roll, the convection current of cooling system
Heat radiation and the aerial heat radiation of roll, utilize the rotary simulation operation of rolling roll mechanical periodicity of roll model coordinate systems
Heat exchanging process, it is ensured that the precision of model；
(3) between roll model and rolled piece model, roll model and support roller former, contact is set, according to rolling respectively
Technological parameter is that rolled piece arranges drafts, linear velocity, adds angular velocity for roll.
Set up the fatigue life prediction model of roll, thermosetting coupling model meter need to be extracted in conjunction with rolling system thermosetting coupling model
The load information obtained, and add the S-N curve of roll material.
2. choose multiple roll coolant system technological parameter as optimized variable, and determine its design space and optimization aim,
Extract test sample point, and be calculated roll working cycle response value by model in step 1.
In the present invention, with certain cut deal volume factory rolling cooling system in be available for adjust cooling water pressure, cooling water temperature and
Cooling water jet density is as optimized variable.It is understood that except this three, it is also possible to select other cooling technique ginseng
Number, as optimized variable, is only to carry out example with cooling water pressure, cooling water temperature and cooling water jet density in the present invention
Property explanation, not limitation of the present invention.
Heretofore described optimization aim refers to that the roll working cycle before germinating fatigue crack is the longest.
Design space in invention refer to as optimized variable cooling technological parameter excursion, choose cooling water pressure,
Cooling water temperature and cooling water jet density are investigation factor, with the working cycle before roll germinating fatigue crack as evaluation index,
Carry out single factor experiment, determine the design space of each optimized variable, as shown in table 1.
The design space of table 1 optimized variable
The present invention has 3 to optimize design variable, chooses 17 test sample points by non-linear test design method, wherein
Comprise 5 central points.The test sample chosen point is substituted into the model set up in step 1 and is calculated response value, response value
Calculating include:
(1) use finite element analysis software that test sample point is carried out thermosetting coupling analysis, extract key position node
Stress state；
(2) based on finite element analysis of fatigue software, roll is carried out analysis of Fatigue-life, obtain roll at germinating fatigue crack
The front working cycle is response value.
The response value result of calculation of test sample point is as shown in table 2.
The response value of table 2 test sample point
3., according to response value calculated in step 2, set up the two of the reflection input roll working cycle with output relation
Rank response surface model.
The present invention chooses second-order response surface model and carries out the optimization design of roll coolant system technological parameter.By cooling system technique
Parameter as output variable, carries out multiple regression matching to calculation result data as input variable, roll working cycle,
Working cycle before roll germinating fatigue crack is many to the secondary of cooling water pressure, cooling water temperature and cooling water jet density
Item formula regression model is:
In formula: y is the roll working cycle；X1For cooling water pressure；X2For jet density；X3For cooling water pressure.
4., according to response surface model, determine the roll cooling process parameter value when roll working cycle is the longest, and optimization is tied
Fruit is brought fatigue life prediction model into and carries out analysis of fatigue, the reliability of checking cooling system process parameter optimizing design.
On the basis of the second-order response surface model that step 3 is set up, use canonical tanalysis method that model is optimized, permissible
Obtain 1 group or several groups solution meeting canonical algorithm, all solutions contain optimal solution, that group that Response to selection variable is maximum
Solution be rolling the working cycle the longest time cooling process parameter value.
Optimize, in order to verify, the result obtained, re-establish roll thermosetting coupling model and fatigue life prediction model, contrast cold
But analysis of Fatigue-life result before and after process parameter optimizing, if the cooling technological parameter after You Huaing can significantly extend roll
Working cycle, then meet requirement, optimize and terminate and export optimum results, otherwise, rebuild the response surface, continue to optimize.
Before optimization, in actual production process in cooling system cooling water pressure be 1.1MPa, jet density 0.04L/min/mm2、
Cooling water temperature is 30 DEG C, and the working cycle before roll crack initiation is 13.33 hours.And after optimizing, cooling water pressure
1.21MPa, jet density 0.08L/min/mm2, cooling water temperature be 8.38 DEG C, the roll working cycle is 14.82 hours,
Improve 11.2%.
Whole optimization process is as shown in Figure 2.
Below only the present invention preferably example is described, but is not to be construed as limitations on claims.The present invention is not
Being limited only to above example, its concrete optimized variable allows to change.In a word, all protections in independent claims of the present invention
In the range of the various changes made the most within the scope of the present invention.
Part that the present invention does not relate to is the most same as the prior art maybe can use prior art to be realized.
Claims (10)
1. a roll coolant system process parameter optimizing method based on response surface model, it is characterised in that comprise the steps:
(1) thermosetting coupling model and the fatigue life prediction model of object roll of optimization object hot rolling system are set up；
(2) choose multiple roll coolant system technological parameter as optimized variable, and determine its design space and optimization aim,
Extract test sample point, and be calculated roll working cycle response value by model in step (1)；
(3) according to calculated response value in step (2), the roll working cycle of reflection input and output relation is set up
Second-order response surface model；
(4) according to response surface model, determine the roll cooling process parameter value when roll working cycle is the longest, and will optimize
Result is brought fatigue life prediction model into and is carried out analysis of fatigue, verifies cooling system technological parameter, until the technique obtaining optimum
Parameter.
Method the most according to claim 1, it is characterised in that: set up optimization object hot rolling system described in step (1)
The thermosetting coupling model of system, comprises the steps:
(1) consider the symmetry of rolling system, the 1/4 of realistic model is analyzed, i.e. set up the 1/2 of upper roller axially,
Material properties axially and 1/2 thickness of rolled piece and the FEM (finite element) model of 1/2 width, and is added in the 1/2 of upper backup roll, setting
Constraint；
(2) when calculating Coefficient of Roll Temperature Field, it is considered to the transmission of heat by contact between high temperature rolled piece and roll, the convection current of cooling system
Heat radiation and the aerial heat radiation of roll, utilize the rotary simulation operation of rolling roll mechanical periodicity of roll model coordinate systems
Heat exchanging process, to ensure the precision of model；
(3) between roll model and rolled piece model, roll model and support roller former, contact is set, according to rolling respectively
Technological parameter is that rolled piece arranges drafts, linear velocity, adds angular velocity for roll.
Method the most according to claim 1, it is characterised in that: the fatigue life prediction setting up roll described in step (1)
Model, to calculate the time of roll fatigue crack initiation；Need to be in conjunction with rolling system heat when setting up roll fatigue life prediction model
Gu coupling model, and add the S-N curve of roll material.
Method the most according to claim 1, it is characterised in that: it is raw that the optimized variable described in step (2) refers to combine rolling
Produce field condition and cooling system technological parameter controlled in the operation of rolling.
Method the most according to claim 1, it is characterised in that: the design space of the optimized variable described in step (2) refers to
Contain the parameter variation range of optimum cooling technological parameter.
Method the most according to claim 1, it is characterised in that: the optimization aim described in step (2) refers to that roll is in germinating
Before fatigue crack, the roll working cycle is the longest.
Method the most according to claim 1, it is characterised in that: the test sample of the analysis of Fatigue-life described in step (2)
Point is to determine rational testing site according to non-linear test design method.
Method the most according to claim 1, it is characterised in that the calculating of the response value described in step (2) includes:
(1) use finite element analysis software that test sample point is carried out thermosetting coupling analysis, extract key position node
Stress state；
(2) based on finite element analysis of fatigue software, roll is carried out analysis of Fatigue-life, obtain roll at germinating fatigue crack
The front working cycle is response value.
Method the most according to claim 1, it is characterised in that: for the second order of n design variable in step (3)
Response surface model is expressed as:
In formula: y is the output variable roll working cycle；XiTechnological parameter is cooled down for design variable；N is design variable
Number；β is undetermined coefficient, least square fitting obtain.
Method the most according to claim 1, it is characterised in that: the response surface that step (4) is built by step (3),
Roll cooling process parameter value when the acquisition roll working cycle is the longest, using optimum results as fatigue life prediction model border
Condition carries out analysis of fatigue, and contrast cools down analysis of Fatigue-life result before and after process parameter optimizing, if the cooling technique after You Huaing
Parameter can significantly extend the working cycle of roll, then meet requirement, optimizes and terminates and export optimum results, otherwise, again
Build the response surface, continue to optimize.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610349243.5A CN105956326B (en) | 2016-05-24 | 2016-05-24 | Roll coolant system process parameter optimizing method based on response surface model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610349243.5A CN105956326B (en) | 2016-05-24 | 2016-05-24 | Roll coolant system process parameter optimizing method based on response surface model |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105956326A true CN105956326A (en) | 2016-09-21 |
| CN105956326B CN105956326B (en) | 2018-10-19 |
Family
ID=56910655
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610349243.5A Active CN105956326B (en) | 2016-05-24 | 2016-05-24 | Roll coolant system process parameter optimizing method based on response surface model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105956326B (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112926146A (en) * | 2021-01-22 | 2021-06-08 | 北京科技大学 | Online fatigue prediction method and system for cold-rolled roller |
| CN112950071A (en) * | 2021-03-30 | 2021-06-11 | 北京瑞莱智慧科技有限公司 | Training method of process parameter adjustment model, and process parameter adjustment method and device |
| CN113704869A (en) * | 2021-07-20 | 2021-11-26 | 深圳市万泽航空科技有限责任公司 | Optimal design method for casting process of flame stabilizer |
| CN114155623A (en) * | 2021-11-26 | 2022-03-08 | 湖南华菱湘潭钢铁有限公司 | On-line calculation method for fatigue life of rolling mill coupling |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103366043A (en) * | 2013-05-31 | 2013-10-23 | 天津大学 | Three-point support optimization design method of machine tool bed based on response surface model |
| CN104573247A (en) * | 2015-01-11 | 2015-04-29 | 吉林大学 | Optimizing method of simplified model cooling structure of transition section |
-
2016
- 2016-05-24 CN CN201610349243.5A patent/CN105956326B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103366043A (en) * | 2013-05-31 | 2013-10-23 | 天津大学 | Three-point support optimization design method of machine tool bed based on response surface model |
| CN104573247A (en) * | 2015-01-11 | 2015-04-29 | 吉林大学 | Optimizing method of simplified model cooling structure of transition section |
Non-Patent Citations (3)
| Title |
|---|
| 夏玉峰 等: "基于响应面法的钩尾框渐进弯热曲工艺多目标优化", 《中南大学学报（自然科学版）》 * |
| 李智 等: "轧辊热力耦合分析及疲劳寿命研究", 《热加工工艺》 * |
| 杨阳 等: "热轧辊表面疲劳寿命研究", 《热加工工艺》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112926146A (en) * | 2021-01-22 | 2021-06-08 | 北京科技大学 | Online fatigue prediction method and system for cold-rolled roller |
| CN112926146B (en) * | 2021-01-22 | 2022-08-09 | 北京科技大学 | Online fatigue prediction method and system for cold-rolled roller |
| CN112950071A (en) * | 2021-03-30 | 2021-06-11 | 北京瑞莱智慧科技有限公司 | Training method of process parameter adjustment model, and process parameter adjustment method and device |
| CN113704869A (en) * | 2021-07-20 | 2021-11-26 | 深圳市万泽航空科技有限责任公司 | Optimal design method for casting process of flame stabilizer |
| CN114155623A (en) * | 2021-11-26 | 2022-03-08 | 湖南华菱湘潭钢铁有限公司 | On-line calculation method for fatigue life of rolling mill coupling |
| CN114155623B (en) * | 2021-11-26 | 2023-07-28 | 湖南华菱湘潭钢铁有限公司 | Online calculation method for fatigue life of rolling mill coupler |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105956326B (en) | 2018-10-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhang et al. | Equipment energy consumption management in digital twin shop-floor: A framework and potential applications | |
| CN105956326A (en) | Response surface model-based roll coolant system technological parameter optimization method | |
| CN109858085B (en) | Austenitization determination method in heat treatment process of metal material | |
| Alkebsi et al. | Design of graded lattice structures in turbine blades using topology optimization | |
| CN103823991B (en) | Heavy-duty tool thermal error prediction method taking environmental temperature into account | |
| Li et al. | Numerical simulation of temperature field and thermal stress field of work roll during hot strip rolling | |
| CN106484968B (en) | A kind of method for quick predicting of the heat exchange Correlations based on response surface | |
| CN108038266A (en) | A kind of method for numerical simulation of selective laser repair process | |
| Hou et al. | Prediction of fatigue crack propagation lives of turbine discs with forging-induced initial cracks | |
| Elhami et al. | Experimental study of surface roughness and tool flank wear during hybrid milling | |
| CN105046030A (en) | Method for obtaining quenching process heat transfer coefficient of aluminum alloy component under three-dimensional heat transfer condition based on finite element method | |
| CN202073605U (en) | Online thermal stress monitoring system for steam turbine rotor of ultrasupercritical unit | |
| CN112528535A (en) | Mortise broaching process simulation analysis method based on heat-force-flow multi-field coupling | |
| Venkata et al. | Numerical simulation of a three-pass TIG welding using finite element method with validation from measurements | |
| Zhou et al. | An effective selective assembly model for spinning shells based on the improved genetic simulated annealing algorithm (IGSAA) | |
| CN1641356B (en) | Rigid line product microscopic structure and mechanical property forecasting system | |
| CN102750453B (en) | Construction method of material deformation resistance unified model for rolling mill design | |
| CN108536968A (en) | A kind of regulation and control method of stress and deformation in welding process | |
| CN110059445A (en) | A kind of casting crack forms prognostic criteria and Simulation Methods | |
| CN103337000B (en) | A kind of safe monitoring and pre-alarming method of oil-gas gathering and transportation system | |
| JP5375506B2 (en) | Quality prediction apparatus, quality prediction method, program, and computer-readable recording medium | |
| Liu et al. | Thermal–elastic–plastic simulation of internal stress fields of quenched steel 40Cr cylindrical specimens by FEM | |
| CN105550463A (en) | Prediction method for temperature field in electromagnetic induction heating process of steel plate | |
| Hao et al. | Research on surface roughness prediction in turning Inconel 718 based on Gaussian process regression | |
| WO2022038840A1 (en) | Crack progress evaluation device and crack progress evaluation program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |