CN108763823B - Simulation method for pre-service thermodynamic training process of SMA wave spring driver - Google Patents

Simulation method for pre-service thermodynamic training process of SMA wave spring driver Download PDF

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CN108763823B
CN108763823B CN201810625820.8A CN201810625820A CN108763823B CN 108763823 B CN108763823 B CN 108763823B CN 201810625820 A CN201810625820 A CN 201810625820A CN 108763823 B CN108763823 B CN 108763823B
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王骏
朱继宏
许英杰
张卫红
谷小军
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Northwestern Polytechnical University
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Abstract

The invention provides a simulation method of a pre-service thermodynamic training process of a shape memory alloy wave spring driver, which is characterized in that an SMA constitutive model considering residual deformation accumulation and material thermodynamic performance degradation under the condition of large deformation period cyclic load is established on a theoretical level, and the model is integrated into commercial finite element software through secondary development on a numerical aspect to form a set of simulation method of the pre-service training process of the SMA wave spring driver. The simulation prediction result can accurately describe the phenomena of phase-change domain expansion, residual deformation accumulation, internal stress concentration and the like in the pre-service training process of the SMA wave spring driver, and can provide important reference for the SMA component in the aspects of improving the size design accuracy and enhancing the two-way memory effect.

Description

Simulation method for pre-service thermodynamic training process of SMA wave spring driver
Technical Field
The invention relates to a simulation method for a shape memory alloy driver pre-service training process, in particular to a simulation method for a shape memory alloy wave spring driver pre-service thermodynamic training process.
Background
Shape Memory Alloy (SMA) is a typical intelligent material, has excellent thermodynamic properties such as Shape Memory effect, superelasticity, high damping, and has been widely used in aerospace, biomedicine, transportation, unmanned systems, and micro-electromechanical systems.
In engineering application environments, SMA functional components are often subjected to cyclic loading. During the initial tens to hundreds of cyclic loading and unloading processes, the thermodynamic properties of the SMA material show extremely strong instability, which is mainly represented by residual deformation accumulation and superelasticity degradation. Therefore, to achieve functional stability, SMA components are typically subjected to a training process prior to service. The training before the SMA service is mainly to apply periodic cycle thermodynamic load to the SMA component, so that the residual deformation of the SMA component before service reaches a saturation value, and the thermodynamic performance enters a stable state. The residual deformation and the material performance degradation in the training process bring negative effects on the assembly requirement and the service performance of the SMA member, and how to reasonably predict the residual deformation and how to effectively improve the material performance has important scientific significance on the design and optimization of the SMA actuator.
The document "Gaitzsch U,
Figure GDA0003459700570000011
m, Roth S, et al, mechanical training of polycrystalline 7M Ni50Mn30Ga20 magnetic shape memory alloy, 2007,57(6): 493-. However, the training method is mainly based on experimental experience, and a theoretical model and a numerical simulation method are lacked. Therefore, the training method is low in efficiency, is only suitable for SMA test samples with simple structures, and cannot realize accurate pre-service training of the complex SMA engineering component.
Disclosure of Invention
The invention provides a simulation method for a pre-service thermodynamic training process of an SMA wave spring driver, which relates to the key problems of multi-field coupling, limited deformation, periodic cyclic load and the like, aims at the defects of low training efficiency and incapability of realizing pre-service training of a complex SMA member in background documents, establishes an SMA constitutive model considering residual deformation accumulation and material thermodynamic performance degradation under the condition of large-deformation periodic cyclic load on a theoretical level, integrates the model into commercial finite element software through secondary development on a numerical aspect, and forms a set of simulation method for the pre-service training process of the SMA wave spring driver. The simulation prediction result can accurately describe the phenomena of phase-change domain expansion, residual deformation accumulation, internal stress concentration and the like in the pre-service training process of the SMA wave spring driver, and can provide important reference for the SMA component in the aspects of improving the size design accuracy and enhancing the two-way memory effect.
The technical scheme of the invention is as follows:
the method for simulating the pre-service thermodynamic training process of the shape memory alloy wave spring driver is characterized by comprising the following steps of: the method comprises the following steps:
step 1: and (3) measuring the mechanical property of the material:
selecting an SMA wire made of the same material as the wave spring driver to perform a uniaxial periodic cyclic loading and unloading experiment, and measuring the influence rule of the strain rate, the environmental temperature and the maximum stress on the mechanical response of the SMA material to obtain the thermodynamic characteristics of the SMA material under different load conditions, including a stress-strain relation, the maximum residual deformation, the maximum restorable deformation and the stable cycle times;
step 2: establishing a material model:
under the finite deformation and consistency thermodynamic framework, establishing a thermodynamic constitutive model of the SMA material under the condition of periodic cyclic loading and unloading, wherein the thermodynamic characteristics of the SMA which can be characterized by the constitutive model comprise: residual deformation accumulation, material property degradation, temperature and strain rate sensitivity, smooth transition, and thermal coupling;
realizing the numerical development and finite element integration of the constitutive model through a custom material subprogram in finite element software, and creating a corresponding SMA material model in the finite element software;
and step 3: determining model parameters:
determining model parameters of the SMA material model created in the step 2 according to the experimental data in the step 1; the model parameters comprise an elastic constant, a thermal constant, a phase transition temperature, an initial state parameter, a stable state parameter and an evolution rate parameter;
and 4, step 4: establishing a finite element model:
establishing a geometric model of the SMA wave spring driver according to the geometric parameters, and dividing a finite element grid by using 8-node solid units; defining material parameters according to the established material model and the model parameters, and defining analysis steps, displacement boundaries, thermal boundaries and an initial temperature field; applying a cyclic force load;
and 5: and (3) simulation result analysis:
outputting a finite element analysis result, drawing martensite volume fraction, temperature, stress and strain data on a finite element software post-processing module, and analyzing a thermodynamic phenomenon caused by pre-service training on the SMA wave spring driver: the method comprises the steps of expanding a phase change domain, changing temperature, concentrating internal stress and accumulating residual deformation, and obtaining a martensite volume fraction evolution rule, a maximum temperature rise value and temperature influence rule, an internal stress concentration point and maximum internal stress value, a residual deformation distribution cloud picture and a maximum residual deformation value;
step 6: establishing a geometric correction model
Selecting the geometric dimension of the SMA wave spring driver as a parameter, and carrying out parametric finite element simulation on the pre-service training process of the SMA wave spring driver under different dimension conditions according to the step 4 and the step 5; establishing a quantitative relation between the geometric parameters and the residual deformation according to the simulation result; and establishing a geometric correction model of the SMA wave spring actuator based on the quantitative relation, and introducing the residual deformation in the pre-service training process into the design optimization process of the SMA wave spring actuator as a design factor.
Further preferably, the method for simulating the pre-service thermodynamic training process of the shape memory alloy wave spring driver is characterized by comprising the following steps of: the geometric dimension of the SMA wave spring driver in the step 6 refers to the inner diameter and amplitude of the SMA wave spring driver.
Advantageous effects
The invention has the beneficial effects that: the mechanical property of the SMA wave spring actuator is measured by an experimental means, an SMA material constitutive model is established under a finite deformation and consistency thermodynamic framework, the phenomena of phase change domain expansion, temperature change, internal stress concentration and residual deformation accumulation on the SMA wave spring actuator in the pre-service training process are represented by finite element simulation, and the SMA wave spring actuator geometric correction model considering the pre-service training process is provided. The provided analysis method effectively overcomes the defects that the existing SMA training method is low in efficiency and only suitable for simple components, and the simulation result provides important reference for the design optimization of the SMA wave spring driver aiming at geometric parameter correction and bidirectional memory effect enhancement.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a stress-strain response under cyclic loading conditions of uniaxial tension cycling of SMA wires.
Fig. 2 is a geometric model and meshing schematic of an SMA wave spring actuator.
FIG. 3 is an evolution diagram of martensite volume fraction of a crest unit on the SMA wave spring driver.
Fig. 4 is a peak cell circumferential stress-strain response on an SMA wave spring actuator.
Fig. 5 is a force-displacement response for the load point position on an SMA wave spring actuator.
Detailed Description
The following detailed description of embodiments of the invention is intended to be illustrative, and not to be construed as limiting the invention.
The method for simulating the pre-service thermodynamic training process of the shape memory alloy wave spring driver in the embodiment comprises the following steps of:
step 1: and (3) measuring the mechanical property of the material:
and (3) selecting an SMA wire made of the same material as the wave spring driver to perform a uniaxial periodic cyclic loading and unloading experiment, and measuring the influence rule of the strain rate, the environmental temperature and the maximum stress on the mechanical response of the SMA material to obtain the thermodynamic characteristics of the SMA material under different load conditions, including the stress-strain relationship, the maximum residual deformation, the maximum restorable deformation and the stable cycle times.
In the embodiment, the experimental material object is a nickel-titanium alloy wire with the diameter of 1mm, the uniaxial tension periodic cyclic loading and unloading experiment is carried out on a BOSE fatigue testing machine, and the strain rate is set to be 1 multiplied by 10 in the experiment process-5、5×10-5、1×10-4、5×10-4And 1X 10-3Three sets of experiments were performed at 20 deg.C, 30 deg.C, 40 deg.C, 50 deg.C and 60 deg.C, and maximum stress levels of 400MPa, 500MPa, 600MPa, 700MPa and 800MPa, respectively. Recording stress, strain and temperature data under each experimental condition, and FIG. 1 shows the strain rate of 1 × 10 for the nitinol wire-3Stress-strain curve under the condition of maximum stress level 800MPa at the temperature of 50 ℃.
Step 2: establishing a material model:
under the framework of finite deformation and consistent thermodynamics, a thermodynamic constitutive model of the SMA material under the condition of periodic cycle loading and unloading is established, the model comprises a superelasticity stress-strain relation, a martensite phase change evolution equation, a residual strain evolution equation, a yield function and a temperature evolution equation, and the thermodynamic characteristics of the SMA which can be characterized by the model comprise: residual strain accumulation, material property degradation, temperature and strain rate sensitivity, smooth transition, and thermal coupling.
The numerical development and finite element integration of the constitutive model are realized through a custom material subprogram module VUMAT in the Explicit finite element software ABAQUS/Explicit, a corresponding SMA material model is established in the finite element software, and the stability and the calculation efficiency of the model are verified through the single-axis cyclic loading and unloading analysis of the hexahedral unit.
And step 3: determining model parameters:
determining model parameters of the SMA material model created in the step 2 according to the experimental data in the step 1; the model parameters include elastic constant, thermal constant, phase transition temperature, initial state parameter, steady state parameter, and evolution rate parameter.
The elastic constant is identified by linear elastic experimental data on a stress-strain curve graph, the thermal constant is obtained by consulting the existing literature, the phase transition temperature is identified by a Differential Scanning Calorimetry (DSC), the initial state parameter is identified by a 1 st cyclic internal stress-strain curve, the stable state parameter is identified by a stabilized stress-strain curve, and the evolution rate parameter is identified by a cyclic loading and unloading stress-strain curve, as shown in fig. 1.
And 4, step 4: establishing a finite element model:
establishing a geometric model of the SMA wave spring driver according to the geometric parameters, and dividing a finite element grid by using 8-node solid units; defining material parameters according to the established material model and the model parameters, and defining analysis steps, displacement boundaries, thermal boundaries and an initial temperature field; periodic cyclic force loads are applied.
In the embodiment, a geometric model (shown in fig. 2) of the SMA wave spring is established in CAD software CATIA, the spring has the thickness of 1mm, the width of 3.6mm, the inner diameter of 40mm and the outer diameter of 47.2mm, and 8 waves with the amplitude of 4mm are included; an 8-node Explicit linear thermal coupling reduction integral unit is applied to the Explicit finite element software ABAQUS/Explicit to divide meshes of a geometric model; carrying out finite element analysis by using an explicit thermodynamic coupling analysis step; the initial temperature on the wave spring is defined as 50 ℃, the node of the trough position restrains the axial displacement, and the node of the crest position applies 50 periodic cyclic loading and unloading processes from 0 to 32N within 50 seconds.
And 5: and (3) simulation result analysis:
outputting a finite element analysis result, drawing martensite volume fraction, temperature, stress and strain data on a finite element software post-processing module, and analyzing a thermodynamic phenomenon caused by pre-service training on the SMA wave spring driver: the method comprises the steps of phase change domain expansion, temperature change, internal stress concentration and residual deformation accumulation, and obtains a martensite volume fraction evolution rule, a maximum temperature rise value and temperature influence rule, an internal stress concentration point and maximum internal stress value, a residual deformation distribution cloud picture and a maximum residual deformation value.
In the embodiment, a phase change field, a temperature field, a stress field and a deformation field cloud chart of the SMA wave spring driver in the training process are drawn by an ABAQUS/Explicit post-processing module; obtaining the expansion of the phase transformation domain and the martensite volume fraction evolution law through the martensite volume fraction cloud picture on the spring and the martensite volume fraction evolution law of the crest unit (as shown in figure 3); obtaining the specific position of stress concentration and the maximum internal stress value through a stress cloud graph on the spring and a stress-strain curve graph (shown in figure 4) of a crest unit; the final configuration of the trained spring and its residual strain profile are obtained from the force-displacement plot of the residual deformation and point of application of force on the trained spring (as shown in fig. 5).
Step 6: establishing a geometric correction model
Selecting the geometric dimension of the SMA wave spring driver as a parameter, and carrying out parametric finite element simulation on the pre-service training process of the SMA wave spring driver under different dimension conditions according to the step 4 and the step 5; establishing a quantitative relation between the geometric parameters and the residual deformation according to the simulation result; and establishing a geometric correction model of the SMA wave spring actuator based on the quantitative relation, and introducing the residual deformation in the pre-service training process into the design optimization process of the SMA wave spring actuator as a design factor.
After training, the SMA wave spring with the inner diameter of 40mm and the amplitude of 4mm has axial residual deformation of 0.78mm and radial residual deformation of 0.92 mm. Performing parametric analysis in ABAQUS/Explicit by taking the inner diameter R and the amplitude A as parameters, setting the inner diameter to gradually increase every 1mm from 30mm to 50mm, setting the amplitude to gradually increase every 0.1mm from 3mm to 5mm, and performing finite element simulation of 400 groups to obtain 400 groups of axial residual deformation DaAnd radial residual deformation DrEstablishing a quantitative relationship between the following geometric dimensions and residual deformation by parameter fitting:
Da＝f(R,A)，Dr＝g(R,A) (1)
the relation can be used for predicting the integral residual deformation of the structure in the pre-service training process of the SMA wave spring driver under the condition of given geometric dimensions (inner diameter and amplitude); meanwhile, the inverse function of the relation can be used for determining the inner diameter and the amplitude which should be adopted in the process of designing and manufacturing the SMA wave spring driver so as to meet the geometric parameters and the assembly conditions in the service process.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made in the above embodiments by those of ordinary skill in the art without departing from the principle and spirit of the present invention.

Claims (2)

1. A method for simulating a thermodynamic training process of a shape memory alloy wave spring driver before service is characterized by comprising the following steps of: the method comprises the following steps:
step 1: and (3) measuring the mechanical property of the material:
selecting an SMA wire made of the same material as the wave spring driver to perform a uniaxial periodic cyclic loading and unloading experiment, and measuring the influence rule of the strain rate, the environmental temperature and the maximum stress on the mechanical response of the SMA material to obtain the thermodynamic characteristics of the SMA material under different load conditions, including a stress-strain relation, the maximum residual deformation, the maximum restorable deformation and the stable cycle times;
step 2: establishing a material model:
under the finite deformation and consistency thermodynamic framework, establishing a thermodynamic constitutive model of the SMA material under the condition of periodic cyclic loading and unloading, wherein the thermodynamic characteristics of the SMA which can be characterized by the constitutive model comprise: residual deformation accumulation, material property degradation, temperature and strain rate sensitivity, smooth transition, and thermal coupling;
realizing the numerical development and finite element integration of the constitutive model through a custom material subprogram in finite element software, and creating a corresponding SMA material model in the finite element software;
and step 3: determining model parameters:
determining model parameters of the SMA material model created in the step 2 according to the experimental data in the step 1; the model parameters comprise an elastic constant, a thermal constant, a phase transition temperature, an initial state parameter, a stable state parameter and an evolution rate parameter;
and 4, step 4: establishing a finite element model:
establishing a geometric model of the SMA wave spring driver according to the geometric parameters, and dividing a finite element grid by using 8-node solid units; defining material parameters according to the established material model and the model parameters, and defining analysis steps, displacement boundaries, thermal boundaries and an initial temperature field; applying a cyclic force load;
and 5: and (3) simulation result analysis:
outputting a finite element analysis result, drawing martensite volume fraction, temperature, stress and strain data on a finite element software post-processing module, and analyzing a thermodynamic phenomenon caused by pre-service training on the SMA wave spring driver: the method comprises the steps of expanding a phase change domain, changing temperature, concentrating internal stress and accumulating residual deformation, and obtaining a martensite volume fraction evolution rule, a maximum temperature rise value and temperature influence rule, an internal stress concentration point and maximum internal stress value, a residual deformation distribution cloud picture and a maximum residual deformation value;
step 6: establishing a geometric correction model
Selecting the geometric dimension of the SMA wave spring driver as a parameter, and carrying out parametric finite element simulation on the pre-service training process of the SMA wave spring driver under different dimension conditions according to the step 4 and the step 5; establishing a quantitative relation between the geometric parameters and the residual deformation according to the simulation result; and establishing a geometric correction model of the SMA wave spring actuator based on the quantitative relation, and introducing the residual deformation in the pre-service training process into the design optimization process of the SMA wave spring actuator as a design factor.
2. The method for simulating the pre-service thermodynamic training process of the shape memory alloy wave spring driver according to claim 1, wherein the method comprises the following steps: the geometric dimension of the SMA wave spring driver in the step 6 refers to the inner diameter and amplitude of the SMA wave spring driver.
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