基于拟合归元函数的车用玄纤复合材料热性能的快速预测

doi:10.12141/j.issn.1000-565X.250122

摘要/Abstract

摘要：

传统的基于大量试验与经验的新材料研发过程效率低、周期长、成本高，而将高效试验技术与快速计算模拟预测协调融合的智能方法可极大缩短新材料研发与工程应用周期并降低成本。短切玄武岩纤维增强聚乳酸（BF/PLA）复合材料天然绿色环保可降解，作为汽车部分内外饰等零部件的理想替代材料之一，具有广阔发展空间。为研究不同纤维参数配比对BF/PLA复合材料热性能的影响机制，快速开发适宜的车用零部件材料，该文对多种纤维参数配比下BF/PLA复合材料的热性能分别进行试验，通过数据相关性分析，探讨了不同纤维参数配比对复合材料热性能的影响；利用三因素方差分析方法F值提出纤维参数拟中心化方法，建立玻璃化转变温度和结晶度与中心化变量间的拟合归元函数；基于拟合归元函数和多项式指导函数，将所拓展的新的纤维质量分数、直径和长度参数配比代入，得到玻璃化转变温度和结晶度在新的纤维质量分数、直径和长度参数配比下的中心化变量，并利用拟合归元函数得新参数配比下BF/PLA复合材料的玻璃化转变温度和结晶度，完成利用拟合归元函数预测更多纤维参数配比下复合材料热性能的预测，得到的决定系数分别为0.887 0和0.855 1，且预测精度在实际工程可接受范围内。对某车企实际车型车门内板的热性能进行有限元分析，将预测数据模拟结果与原车模拟结果进行对比，结果表明，利用该文所提方法所选较优配比复合材料的热性能略优，且研发效率显著提升，验证了所提方法的有效性，为未来车用复合材料的快速开发、降低成本、选择替代和绿色设计提供了重要理论指导和方法参考。

关键词: 玄武岩纤维, 聚乳酸, 拟合归元函数, 热性能, 汽车车门内板

Abstract:

The traditional process of new material development, heavily reliant on extensive experimentation and empirical knowledge, suffers from low efficiency, prolonged cycles, and high costs. Integrating efficient experimental techniques with rapid computational simulation and prediction through intelligent methods can significantly shorten the R&D and engineering application cycle while reducing costs. Chopped basalt fiber-reinforced polylactic acid (BF/PLA) composites, being naturally green, environmentally friendly, and biodegradable, represent an ideal alternative material for automotive interior and exterior components with considerable development potential. In order to study the influence of different fiber parameter ratios on the thermal properties of BF/PLA composites and facilitate rapid development of suitable automotive component materials, this study first conducted experiments on the thermal properties of BF/PLA composites under various fiber parameter ratios. Through data correlation analysis, the effects of different fiber parameter ratios on composite thermal properties were examined. Using F-values from three-factor ANOVA, a fiber parameter quasi-centralization method was proposed, establishing fitted regression functions between glass transition temperature/crystallinity and centralized variables. Based on these regression functions and polynomial guiding functions, new ratios of fiber mass fraction, diameter, and length parameters were incorporated to obtain centralized variables for glass transition temperature and crystallinity under the new parameter ratios. The glass transition temperature and crystallinity of BF/PLA composites with new parameter ratios can be obtained by fitting regression function, and the thermal properties of composites with more fiber para-meter ratios can be predicted by fitting regression function, and the determination coefficients are 0.887 0 and 0.855 1 respectively, with prediction accuracy within practically acceptable engineering ranges. Finite element analysis of thermal performance for a vehicle door inner panel demonstrated slightly superior thermal properties using the optimized composite material selected through the proposed method, along with significantly improved R&D efficiency, validating the effectiveness of the approach. This provides important theoretical guidance and methodological reference for rapid development, cost reduction, material substitution, and green design of future automotive composites.

Key words: basalt fiber, polylactic acid, fitting regression function, thermal property, inner panel of automobile door

中图分类号:

TB332

王童, 马玉朋, 赵阳. 基于拟合归元函数的车用玄纤复合材料热性能的快速预测[J]. 华南理工大学学报(自然科学版), 2025, 53(12): 172-182.

WANG Tong, MA Yupeng, ZHAO Yang. Rapid Prediction of Thermal Properties of Automotive Basalt Fiber Composites Based on Fitting Regression Function[J]. Journal of South China University of Technology(Natural Science Edition), 2025, 53(12): 172-182.

图/表 22

图1

图2

图3

图4

表1

由DSC曲线所得的复合材料热性能参数"

试样	熔化过程				结晶过程			$X c / %$
试样	$θ g$ /°C	$θ o m$ /°C	$θ p m /$ °C	$∆ H m /$ （J·g^-1 ）	$θ o c$ /°C	$θ p c /$ °C	$∆ H c$ /（J·g^-1 ）	$X c / %$
13-7-10BF/PLA	57.635 1	156.033 9	165.818 3	26.384	119.452 7	111.024 2	-25.742	62.277 1
13-7-20BF/PLA	57.952 6	155.963 9	164.392 3	26.155	119.570 6	111.164 7	-20.241	62.360 2
13-7-30BF/PLA	58.328 3	156.530 5	165.726 3	21.643	119.979 4	111.854 6	-20.338	64.486 9
13-7-40BF/PLA	58.651 9	156.171 2	164.831 0	17.153	120.576 5	112.868 3	-19.556	65.786 7
13-7-50BF/PLA	58.471 7	155.638 8	164.146 7	17.008	122.898 5	114.709 8	-14.515	67.791 4
13-7-60BF/PLA	58.218 8	155.528 4	164.129 4	8.840	123.112 5	114.185 4	-16.035	66.868 2
15-7-10BF/PLA	57.492 2	165.348 2	165.348 2	28.036	121.076 0	111.516 0	-23.931	62.087 2
15-7-20BF/PLA	57.918 5	153.962 0	166.103 0	24.371	119.095 7	110.705 8	-23.424	64.240 5
15-7-30BF/PLA	58.234 3	155.153 5	166.232 0	20.598	119.243 9	111.451 1	-22.550	66.279 5
15-7-40BF/PLA	58.512 3	164.804 3	164.804 3	16.296	119.266 9	111.332 4	-22.220	69.025 0
15-7-50BF/PLA	58.311 4	155.808 0	164.808 7	15.463	120.166 1	111.684 0	-18.034	72.036 5
15-7-60BF/PLA	58.106 2	157.471 4	165.298 1	12.682	123.413 1	115.576 3	-14.020	71.779 5
17-7-10BF/PLA	57.416 8	156.519 3	164.950 4	29.320	120.725 7	112.910 3	-26.193	66.323 7
17-7-20BF/PLA	57.828 0	154.390 0	165.730 7	23.366	119.559 3	110.888 1	-26.332	66.798 3
17-7-30BF/PLA	58.187 0	155.702 3	164.611 7	26.889	119.939 2	111.498 6	-17.884	68.775 7
17-7-40BF/PLA	58.451 1	155.279 4	164.767 0	21.407	119.899 9	111.346 0	-17.710	70.102 1
17-7-50BF/PLA	58.207 7	157.433 6	164.677 2	26.031	120.972 5	113.230 2	-7.832	72.824 3
17-7-60BF/PLA	58.057 0	156.904 2	165.069 5	14.992	131.015 5	127.403 1	-31.522	71.317 2

表1

图5

图6

图7

表2

三因素方差分析"

来源	平方和	自由度	均方和	$F$ 值
$D$	$S D$	$s - 1$	$M S D = S D s - 1$	$F D = M S D M S E$
L	$S L$	$t - 1$	$M S L = S L t - 1$	$F L = M S L M S E$
$C$	$S C$	$r - 1$	$M S C = S C r - 1$	$F C = M S C M S E$
$E$	$S E$	$r s t m - 1$	$M S E = S E r s t m - 1$
$T$	$S T$	$n - 1$

表2

表3

表4

图8

图9

图10

图11

图12

表5

表6

图13

图14

图15

图16

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来源	平方和	自由度	均方	F值	显著性
D	0.305	2	0.152	0.027 9	<0.001
L	1.825	2	0.912	0.165 1	<0.001
C	7.315	5	1.463	0.264 1	<0.001
误差	0.244	44	0.006
总计	183 796.184	54

来源	平方和	自由度	均方	F值	显著性
D	17.442	2	8.721	5.227	<0.001
L	23.172	2	11.586	8.570	<0.001
C	296.821	5	59.364	43.910	<0.001
误差	59.486	44	1.454
总计	238 361.474	54

参数	数值
质量分数/%	40
体积分数/%	22.2
弹性模量/GPa	22.5
泊松比	0.34
热导率/（W·m^-1·K^-1）	0.10
比热容/（J·kg^-1·K^-1）	1 460
热膨胀系数/（μm·m^-1·K^-1）	52.0
密度/（kg·m^-3）	1 570
体积模量/GPa	25.0
剪切模量/GPa	8.4
屈服强度/MPa	90
抗拉强度/MPa	95