CN108717481A - Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting - Google Patents
Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting Download PDFInfo
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- CN108717481A CN108717481A CN201810432422.4A CN201810432422A CN108717481A CN 108717481 A CN108717481 A CN 108717481A CN 201810432422 A CN201810432422 A CN 201810432422A CN 108717481 A CN108717481 A CN 108717481A
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- 238000004458 analytical method Methods 0.000 claims abstract description 22
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- 239000002184 metal Substances 0.000 claims description 39
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- 238000002076 thermal analysis method Methods 0.000 claims description 3
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- 230000007704 transition Effects 0.000 claims 1
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- 230000008646 thermal stress Effects 0.000 description 2
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Abstract
The invention discloses Temperature Distributions during a kind of selective laser melting and buckling deformation prediction technique, this method to be mainly made of heat analysis and mechanical analysis.Heat analysis includes the following steps：Step1 determines machined parameters and carries out process planning；Step2 obtains the hot association attributes of metal material and establishes model according to SLM scantlings；Step3 loads temperature boundary condition；Step4, transient analysis obtain the temperature field of SLM components.Mechanical analysis includes the following steps：Step5 changes model according to properties of material mechanics；Step6, adds boundary condition and using the temperature field that Step4 is analyzed as load, analysis obtains stress field and the deformation of component.The present invention is coupled by thermosetting, and heat analysis is combined with mechanical analysis, establishes temperature and Deformation Prediction system, and reducing SLM component buckling deformations for Optimizing Process Parameters provides technical support.
Description
Technical field
The present invention relates to advanced manufacturing technology fields, more specifically to a kind of selective laser melting process medium temperature
Degree distribution and buckling deformation prediction technique.
Background technology
SLM technologies (Selective laser melting) are complete under the heat effect of laser beam using metal powder
Fusing, molding a kind of increases material manufacturing technology through cooled and solidified.Its operation principle is horizontal control laser according to certain movement
Track acts on coating metal powder, and after one layer of end of scan, matrix declines a thickness, and powdering system is uniform by metal powder
Ground is layered on machined solidification layer, so repeats above-mentioned process, until the metal component needed.This uniqueness
Characteristic so that it is processed complicated part, without the process of expensive shaping jig and complexity, make laser gain material
Manufacturing technology becomes engineering and manufacturing discipline research hotspot, and the technology is natural by National Science Foundation, China national
The science fund committee is considered a great innovation of 21 century manufacturing technology.
But since SLM techniques include moving heat source and metal molten and solidification, lead to each region heating and cooling speed
Degree is different, cracks to produce residual stress in component and component is caused to deform even, makes component failure.In order to subtract
Few component failure generally requires printing test block and carries out trial and error experiment, obtains relatively reasonable technological parameter.However this process is provided
The limitation of gold and time cost, cannot predict the buckling deformation of entire component.Simultaneously because the limitation of laboratory facilities, it cannot be accurate
The variation for measuring component temperature during heating, for studying molten bath forming process and temperature gradient.Based on fluid structurecoupling
The SLM components analogue system of exploitation can disclose temperature change in process well, predict component buckling deformation, for optimization
Technological parameter reduces component defect and provides technical support.
Invention content
It is an object of the invention to overcome the deficiencies of the prior art and provide temperature during a kind of selective laser melting point
Cloth and buckling deformation prediction technique, for metal material phase-state change, molten bath forming process, temperature point in component manufacturing process
Cloth, thermal stress and buckling deformation are analyzed, and finally predict the Temperature Distribution in component process and final buckling deformation
Distribution.
The purpose of the present invention is achieved through the following technical solutions：Design a kind of selective laser melting process medium temperature
Degree distribution and buckling deformation prediction technique, this approach includes the following steps；
Step1 chooses SLM working process parameters, using the method for custom function to technique in fluid analysis software
Parameter is compiled；
Step2, by carrying out laser penetration irradiation experiment to metal powder, analysis obtains metal powder layer laser absorption rate
And laser penetration coefficient, while metal powder and solid-liquid state material properties are distinguished, and can be successively according to the foundation of SLM scantlings
Activate the simulation model of unit；
Step3 loads fixed environment temperature in component base bottom, and each surface setting insulation is being contacted with metal powder,
Surface tension is set in heating surface, while according to the phase of heating surface, decision loads it body heat source or plane heat source；
Step4 obtains the temperature field of SLM components on the basis of determining time step and step number by Transient Thermal Analysis；
Step5 changes SLM element mechanics model according to properties of material mechanics and controls SLM unit using method of killing activating elements
Mechanical attribute；
Step6 adds displacement constraint, and the load step on mechanics analysis model to SLM element mechanics model bottoms
Temperature field obtained by Step4, stress field and the deformation of component are obtained using finite element method.
Further, in the step Step1, the technological parameter specifically includes：Laser species, laser heat source distribution side
Formula, laser power, sweep speed, laser useful effect radius, environment temperature, layering thickness, scan path, sweep span and each
Layer scanning direction angle.Wherein, it is in Gaussian Profile that laser heat source distribution mode, which is mainly manifested in horizontal direction, in effective radius
Intensity is up to 95% or more.
Further, in the step Step2, the material properties specifically include：Solidification/condensing temperature, is glued latent heat
Property, emissivity, convection coefficient, porosity, density, thermal coefficient and specific heat capacity, wherein density, thermal coefficient and specific heat capacity with
Material real time temperature is related.
Further, in the step Step2, the difference metal powder is with solid-liquid state material properties mechanism：Pass through
Microstructure temperature data in SLM components is extracted, by it compared with condensing temperature and combination temperature change rate, judges SLM components
Whether melt, to assign metal powder material attribute or solid-liquid state material properties, wherein metal powder and solid-liquid state
The ratio of material properties is related to porosity.
It is further, described that the model that can successively activate unit is established according to SLM scantlings in the step Step2,
Specifically include following steps：According to SLM member exterior sizes, physical model is established, and combine layering thick based on finite volume method
Degree and computational accuracy requirement, choose unit size appropriate, and mesh generation, and the spy successively processed in conjunction with SLM are carried out to it
Point successively activates unit.
Further, in the step Step3, the phase according to heating surface, decision loads it in body heat source or face
Heat source specifically includes following steps：Temperature change is knitted by analyzing heating surface particle, by it with condensing temperature relatively and in conjunction with temperature
Change rate is spent, judges whether it has melted, since there is metal powder hole, laser to be scattered during being aimed downwardly
And secondary radiation, heat flow density exponentially decay in vertical direction, therefore metal powder is needed to load body heat source, and consolidate/
Liquid metal has formed dense organization, and laser can not permeate, and relies primarily on heat transfer by heat conduction between microstructure, thus for it is solid/
Liquid metal needs to load plane heat source.
Further, the step Step4, specifically includes following steps：By the ratio of size of mesh opening and laser scanning speed
Value determines time step, according to step number is determined the time required to actual condition, the unit in model is successively activated, by CFD
(Computational Fluid Dynamics) tool, emphasis consider the construction material phase that conventional method does not consider and become
Influence of the effect of change, the metal liquid convection effect under molten condition and liquid metal surface tension to Temperature Distribution, utilizes
Finite volume method calculates equation of heat balance and obtains the temperature and heat flow density on transient state SLM component nodes, to obtain material phase
State variation, molten bath forming process and each moment profiling temperatures of SLM components, can be used for probing into different technical parameters to most
The influence of high-temperature, temperature gradient, cooling velocity can be reduced material maximum temperature by Optimizing Process Parameters, obtain rationally life
At rate and temperature gradient.
Further, in the step Step5, the mechanical attribute includes：Density, elasticity modulus, Poisson's ratio, thermal expansion
Coefficient and yield stress, the parameter are related to material real time temperature.
Further, described to utilize method of killing activating elements control unit attribute in the step Step5, it specifically includes following
Step：Judge whether SLM unit temperature reaches condensing temperature, gradually activates unit using method of killing activating elements, and power is assigned to it
Learn attribute.
Further, described using the temperature field that step Step4 is analyzed as load in the step Step6, analysis
Stress field and the deformation of component are obtained, following steps are specifically included：The temperature results obtained using in step Step4 are defeated as load
Enter, calculating thermoelasticity equation of equilibrium using finite element method obtains each moment stress of SLM models and Strain Distribution feelings
Condition can be used for probing into different technical parameters to obtain residual stress, strain and the buckling deformation of SLM component all directions
Influence for residual stress and buckling deformation, and buckling deformation is reduced by Optimizing Process Parameters, simultaneously because forecasting system
There is no the constraint in scanning constant path, new scan path can be developed, to reduce the buckling deformation of SLM components.
Compared with prior art, the present invention having the advantages that：
The present invention is coupled by thermosetting, and heat analysis is combined with mechanical analysis, establishes temperature and Deformation Prediction system, is excellent
Change technological parameter and SLM component buckling deformations offer technical support is provided.
Description of the drawings
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing：
Fig. 1 is the schematic diagram of Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting；
Fig. 2 is the implementing procedure figure of Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting；
Fig. 3 is imparting SLM components in Temperature Distribution during a kind of selective laser melting and buckling deformation prediction technique
The schematic diagram of material properties；
Fig. 4 is Temperature Distribution during a kind of selective laser melting and the signal of the model in buckling deformation prediction technique
Figure；
The SLM that Fig. 5 predicts for Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting
Member temperature is distributed and deformation distribution map.
Specific implementation mode
The invention will be further described below in conjunction with the accompanying drawings.
As depicted in figs. 1 and 2, Temperature Distribution and buckling deformation are pre- during a kind of selective laser melting of present invention design
Survey method, for metal material phase-state change, molten bath forming process, Temperature Distribution, thermal stress in component manufacturing process and sticking up
Song deformation is analyzed, and finally predicts the Temperature Distribution in component process and final buckling deformation distribution, this method master
Include the following steps：
Step1 chooses SLM working process parameters, using the method for custom function to technique in fluid analysis software
Parameter is compiled.In step Step1, technological parameter specifically includes：Laser species, laser heat source distribution mode, laser power,
Sweep speed, laser useful effect radius, environment temperature, layering thickness, scan path, sweep span and each layer scanning direction folder
Angle.Wherein, it is in Gaussian Profile that laser heat source distribution mode, which is mainly manifested in horizontal direction, and intensity is up to 95% in effective radius
More than.It needs to be compiled laser beam scan path, by coordinate (x of the laser center in world coordinate system0,y0,z0) be defined as
Function using sweep speed, sweep span, layering thickness as parameter about the time.Defmacro letter is needed when being planned
Position horizontal coordinate (the x of number, each node of extraction SLM components or unit centere,ye,ze), so as to obtain each unit or
Node is (x relative to the coordinate of laser centere-x0,ye-y0,ze-z0), so as to obtain each unit relative to laser center
Horizontal distance reAnd longitudinal depth he, for reApply corresponding body heat source or face heat less than the unit of laser effective radius
Source.
Step2, by carrying out laser penetration irradiation experiment to metal powder, analysis obtains metal powder layer laser absorption rate
And laser penetration coefficient, while metal powder and solid-liquid state material properties are distinguished, and can be successively according to the foundation of SLM scantlings
Activate the simulation model of unit.In step Step2, material properties specifically include：Solidification/condensing temperature, latent heat, viscosity, radiation
Rate, convection coefficient, porosity, density, thermal coefficient and specific heat capacity, wherein density, thermal coefficient and specific heat capacity and material are real-time
Temperature is related.As shown in figure 3, difference metal powder is with solid-liquid state material properties mechanism：It is microcosmic in SLM components by extracting
Tissue temperature data judge whether SLM components have melted by it compared with condensing temperature and combination temperature change rate, to
Assign metal powder material attribute or solid-liquid state material properties；Known porosity is K, then metal powder and solid-liquid state specific heat capacity
It is (1-K) with the ratio of density, the ratio of metal powder and solid-liquid state thermal conductivity is (1-K)/(1+11K2), it is seen then that metal powder
End is related with porosity to the ratio of solid-liquid state material properties.The mould of unit can successively be activated by being established according to SLM scantlings
Type specifically includes following steps：As shown in figure 4, according to SLM member exterior sizes, physical model is established, and be based on limited bulk
Method combination lift height and computational accuracy requirement, choose unit size appropriate, mesh generation are carried out to it, calculated to reduce
Amount assigns lower part larger unit, and combine SLM to being affected by temperature larger matrix top using fining mesh generation
The characteristics of successively processing successively activates unit.
Step3 loads fixed environment temperature in component base bottom, and each surface setting insulation is being contacted with metal powder,
Surface tension is set in heating surface, while according to the phase of heating surface, decision loads it body heat source or plane heat source.Step
In Step3, according to the phase of heating surface, decision loads it body heat source or plane heat source, specifically includes following steps：Pass through analysis
Heating surface particle knits temperature change, by it compared with condensing temperature and combination temperature change rate, judges whether it has melted, by
In metal powder there is hole, laser scattering and secondary radiation to occur during being aimed downwardly, heat flow density is in vertical side
To exponentially decaying, therefore metal powder is needed to load and horizontal distance r of the unit relative to laser centereAnd it is longitudinal deep
Spend heRelevant body heat source, and solid-liquid state metal has formed dense organization, laser can not permeate, between microstructure mainly according to
By heat transfer by heat conduction, therefore for the load of solid-liquid state metal surface and horizontal distance r of the unit relative to laser centereIt is relevant
Plane heat source.
Step4 obtains the temperature field of SLM components on the basis of determining time step and step number by Transient Thermal Analysis.Step
Rapid Step4 specifically includes following steps：Time step is determined by the ratio of size of mesh opening and laser scanning speed, according to practical work
Step number is determined the time required to condition, the unit in model is successively activated, by CFD (Computational Fluid Dynamics)
Tool, emphasis consider the metal liquid convection current effect under the construction material phase-state change that conventional method do not consider, molten condition
It should calculate equation of heat balance with the influence of liquid metal surface tension effect to Temperature Distribution using finite volume method and obtain wink
Temperature (as shown in Figure 5) on state SLM component nodes and heat flow density, to obtain material phase-state change, molten bath forming process
And each moment profiling temperatures of SLM components, it can be used for probing into different technical parameters to maximum temperature, temperature gradient, cold
But the influence of speed can be reduced material maximum temperature by Optimizing Process Parameters, obtain reasonable production rate and temperature gradient.
Step5 changes SLM element mechanics model according to properties of material mechanics and controls SLM unit using method of killing activating elements
Mechanical attribute.In step Step5, mechanical attribute includes：Density, elasticity modulus, Poisson's ratio, coefficient of thermal expansion and yield stress,
Parameter is related to material real time temperature.Using method of killing activating elements control unit attribute, following steps are specifically included：Read temperature
Field file obtains each node for calculating temperature in step and being higher than condensing temperature, by self defining programm structure group, and in mechanics point
In analysis model unit is gradually activated using method of killing activating elements；Since material properties and material properties cannot be changed in calculating process
0 is had to be larger than, so can only COEFFICIENT K be multiplied by material properties, by changing COEFFICIENT K come control unit attribute, for activation
Unit, K=1, and unactivated unit, K=10-6。
Step6 adds displacement constraint, and the load step on mechanics analysis model to SLM element mechanics model bottoms
Temperature field obtained by Step4, stress field and the deformation of component are obtained using finite element method.In step Step6, with step
The temperature field that Step4 is analyzed obtains stress field and the deformation of component, specifically includes following steps as load, analysis：With
The temperature results obtained in step Step4 are inputted as load, and calculating thermoelasticity using finite element method balances public affairs
Formula obtains each moment stress of SLM models and Strain Distribution situation (as shown in Figure 5), to obtain the residual of SLM component all directions
Residue stress, strain and buckling deformation can be used for probing into influence of the different technical parameters for residual stress and buckling deformation, and
Reducing buckling deformation by Optimizing Process Parameters can develop simultaneously because forecasting system does not have the constraint in scanning constant path
New scan path, to reduce the buckling deformation of SLM components.
The embodiment of the present invention is described in attached drawing, but the invention is not limited in above-mentioned specific embodiment parties
Formula, the above mentioned embodiment is only schematical, rather than restrictive, and those skilled in the art are in this hair
Under bright enlightenment, without breaking away from the scope protected by the purposes and claims of the present invention, many forms can be also made, this
It is a little to belong within the protection of the present invention.
Claims (10)
1. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting, which is characterized in that including following
Step：
Step1 chooses SLM working process parameters, using the method for custom function to technological parameter in fluid analysis software
It is compiled；
Step2, by carrying out laser penetration irradiation experiment to metal powder, analysis obtains metal powder layer laser absorption rate and swashs
Light infiltration coefficient, while metal powder and solid-liquid state material properties are distinguished, and can successively be activated according to the foundation of SLM scantlings
The simulation model of unit；
Step3 loads fixed environment temperature in component base bottom, and each surface setting insulation is being contacted with metal powder, is being added
Surface tension is arranged in hot face, while according to the phase of heating surface, and decision loads it body heat source or plane heat source；
Step4 obtains the temperature field of SLM components on the basis of determining time step and step number by Transient Thermal Analysis；
Step5 changes SLM element mechanics model according to properties of material mechanics and controls SLM unit mechanics using method of killing activating elements
Attribute；
Step6 adds displacement constraint, and the load step Step4 institutes on mechanics analysis model to SLM element mechanics model bottoms
Temperature field is obtained, stress field and the deformation of component are obtained using finite element method.
2. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as described in claim 1,
It is characterized in that：In the step Step1, the technological parameter specifically includes：Laser species, laser heat source distribution mode, laser
Power, sweep speed, laser useful effect radius, environment temperature, layering thickness, scanning direction, sweep length, sweep span and
Each layer scanning direction angle.
3. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as described in claim 1,
It is characterized in that：In the step Step2, material properties specifically include：Solidification/condensing temperature, latent heat, viscosity, emissivity, convection current
Coefficient, porosity, density, thermal coefficient and specific heat capacity, wherein density, thermal coefficient and specific heat capacity and material real time temperature phase
It closes.
4. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as claimed in claim 3,
It is characterized in that：In the step Step2, difference metal powder is with solid-liquid state material properties mechanism：By analyzing SLM components
Microstructure temperature history judges its residing phase at this time, to assign metal powder material attribute or solid-liquid state material category
Property, wherein metal powder and the ratio of solid-liquid state material properties are related with porosity.
5. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as claimed in claim 4,
It is characterized in that：It is described that the simulation model that can successively activate unit is established according to SLM scantlings in the step Step2, specifically
Include the following steps：According to SLM scantlings, physical model is established, and be based on finite volume method combination lift height and calculating
The characteristics of required precision carries out it mesh generation, and combination SLM is successively processed, successively activates unit.
6. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as described in claim 1,
It is characterized in that：In the step Step3, the phase according to heating surface, decision loads it body heat source or plane heat source, specifically
Include the following steps：Each particle temperature change of heating surface is analyzed, judges whether its surface undergoes phase transition, metal powder part is added
Carrier heat source loads plane heat source to solid-liquid state metal surface.
7. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as described in claim 1,
It is characterized in that：In the step Step4, following steps are specifically included：It is determined by the ratio of size of mesh opening and laser scanning speed
Time step successively activates the unit in model according to step number is determined the time required to actual condition, by CFD tools, considers structure
The effect of metal liquid convection effect and liquid metal surface tension under part material phase-state change, molten condition is to Temperature Distribution
Influence, using finite volume method calculate equation of heat balance obtain the temperature and heat flow density on transient state SLM component nodes, to
Analysis of material phase-state change, molten bath forming process and each moment profiling temperatures of SLM components.
8. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as described in claim 1,
It is characterized in that：In the step Step5, the mechanical attribute includes：Density, elasticity modulus, Poisson's ratio, coefficient of thermal expansion and bend
Stress is taken, these parameters are related to material real time temperature.
9. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as claimed in claim 8,
It is characterized in that：It is described to utilize method of killing activating elements control unit attribute in the step Step5, specifically include following steps：Judge
Whether SLM unit temperature reaches condensing temperature, gradually activates unit using method of killing activating elements, and assign mechanical attribute to it.
10. Temperature Distribution and buckling deformation prediction technique during a kind of selective laser melting as described in claim 1,
It is characterized in that：In the step Step6, temperature field, the utilization obtained by load step Step4 on mechanics analysis model are limited
Element method obtains stress field and the deformation of component, specifically includes following steps：With the temperature results obtained in step Step4
As load input, using finite element method calculate thermoelasticity equation of equilibrium obtain each moment stress of SLM models and
Strain Distribution situation, to obtain residual stress, strain and the buckling deformation of SLM component all directions.
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| CN109871602A (en) * | 2019-01-30 | 2019-06-11 | 西安工程大学 | A kind of critical heat flux density prediction technique returned based on Gaussian process |
| CN110334469A (en) * | 2019-07-17 | 2019-10-15 | 佛山科学技术学院 | A kind of gear tooth breakage laser melting coating welding technology optimization and welding method based on ansys |
| CN111523269A (en) * | 2020-04-24 | 2020-08-11 | 合肥工业大学 | Method for predicting temperature and warping deformation of printed matter in fused deposition manufacturing process |
| CN111666663A (en) * | 2020-05-22 | 2020-09-15 | 西北工业大学 | SLM thermal stress rapid calculation method |
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| CN112989626A (en) * | 2021-04-13 | 2021-06-18 | 清华大学 | Additive manufacturing organization simulation method, device, computer equipment and storage medium |
| CN113343521A (en) * | 2021-05-27 | 2021-09-03 | 重庆大学 | Method for predicting interlayer thermal stress distribution in selective laser melting process based on COMSOL |
| CN114386303A (en) * | 2022-01-04 | 2022-04-22 | 大连理工大学 | Method for establishing numerical prediction model of laser melting deposition residual stress |
| CN114912322A (en) * | 2022-05-18 | 2022-08-16 | 华南理工大学 | Thermal behavior prediction method for selective laser melting forming process of 316L stainless steel |
| CN114919181A (en) * | 2022-05-30 | 2022-08-19 | 北京航空航天大学 | Continuous fiber 3D printing process dynamic simulation and printed part buckling deformation prediction method |
| CN116883400A (en) * | 2023-09-07 | 2023-10-13 | 山东大学 | Powder spreading porosity prediction method and system in laser selective melting process |
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| CN109871602A (en) * | 2019-01-30 | 2019-06-11 | 西安工程大学 | A kind of critical heat flux density prediction technique returned based on Gaussian process |
| CN110334469A (en) * | 2019-07-17 | 2019-10-15 | 佛山科学技术学院 | A kind of gear tooth breakage laser melting coating welding technology optimization and welding method based on ansys |
| CN110334469B (en) * | 2019-07-17 | 2023-04-18 | 佛山科学技术学院 | Gear broken tooth laser cladding welding process optimization method based on ansys |
| CN111523269A (en) * | 2020-04-24 | 2020-08-11 | 合肥工业大学 | Method for predicting temperature and warping deformation of printed matter in fused deposition manufacturing process |
| CN111666663B (en) * | 2020-05-22 | 2022-04-05 | 西北工业大学 | SLM thermal stress rapid calculation method |
| CN111666663A (en) * | 2020-05-22 | 2020-09-15 | 西北工业大学 | SLM thermal stress rapid calculation method |
| CN111859734B (en) * | 2020-06-22 | 2023-04-14 | 清华大学 | Optimization method for SLM additive manufacturing workpiece forming orientation |
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| CN112989626A (en) * | 2021-04-13 | 2021-06-18 | 清华大学 | Additive manufacturing organization simulation method, device, computer equipment and storage medium |
| CN113343521A (en) * | 2021-05-27 | 2021-09-03 | 重庆大学 | Method for predicting interlayer thermal stress distribution in selective laser melting process based on COMSOL |
| CN114386303A (en) * | 2022-01-04 | 2022-04-22 | 大连理工大学 | Method for establishing numerical prediction model of laser melting deposition residual stress |
| CN114386303B (en) * | 2022-01-04 | 2024-10-01 | 大连理工大学 | Method for establishing numerical prediction model of residual stress of laser melting deposition |
| CN114912322A (en) * | 2022-05-18 | 2022-08-16 | 华南理工大学 | Thermal behavior prediction method for selective laser melting forming process of 316L stainless steel |
| CN114919181A (en) * | 2022-05-30 | 2022-08-19 | 北京航空航天大学 | Continuous fiber 3D printing process dynamic simulation and printed part buckling deformation prediction method |
| CN116883400A (en) * | 2023-09-07 | 2023-10-13 | 山东大学 | Powder spreading porosity prediction method and system in laser selective melting process |
| CN116883400B (en) * | 2023-09-07 | 2023-11-21 | 山东大学 | Powder spreading porosity prediction method and system in laser selective melting process |
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