- 中文核心期刊
- CSCD中国科学引文数据库来源期刊
- 中国科技核心期刊
- 中国机械工程学会材料分会会刊
| Citation: |
CAO Wenxuan, SHI Zhenyu, ZOU Bin, WANG Jilai, ZHANG Chengpeng, XI Jianren. Design and Development of Database and Machine Learning Property Prediction Platform of C/SiC Composites[J]. Materials and Mechanical Engineering, 2024, 48(5): 51-61. DOI: 10.11973/jxgccl202405009
|
With MySQL Workbench 8.0 as the database platform and adopting a three-layer browser/server architecture, a C/SiC composite database system based on Web interface and machine learning technology was developed by PyCharm 2022. The system included material database and machine learning model, and had the functions of information query, addition, modification, deletion and search, as well as support information management, design analysis view, case-based reasoning aided design, user and system management for material component structure, preparation process, test performance and other stages of material research and development. The machine learning model was trained based on the neural network regression algorithm, the mechanical properties of materials were predicted by the microstructure parameters of materials, and the influence weights of different microstructure parameters were evaluated and deployed in the system platform. The machine learning model was invoked through the Web user interface to predict the tensile modulus and the flexural modulus of the reserved validation set data. The results show that the accuracy of machine learning models in predicting material mechanical properties reached about 95%, and the trained predictive model exhibited good accuracy and generalization capability.
| [1] |
董士博碳/碳化硅复合材料的高温力学性能研究哈尔滨哈尔滨工业大学2021董士博 ．碳/碳化硅复合材料的高温力学性能研究[D]．哈尔滨：哈尔滨工业大学,2021.
DONG S BStudy on high temperature mechanical properties of C/SiC compositesHarbinHarbin Institute of Technology2021DONG S B. Study on high temperature mechanical properties of C/SiC composites[D]. Harbin: Harbin Institute of Technology, 2021.
|
| [2] |
ZHANG X H, DU B H, HU P, et al. Thermal response, oxidation and ablation of ultra-high temperature ceramics, C/SiC, C/C, graphite and graphite-ceramics[J]. Journal of Materials Science & Technology, 2022, 102: 137-158.
|
| [3] |
赵正爽面向材料基因组的材料信息学技术研究成都电子科技大学2017赵正爽 ．面向材料基因组的材料信息学技术研究[D]．成都：电子科技大学,2017.
ZHAO Z SMaterials genome initiative oriented materials informatics technology researchChengduUniversity of Electronic Science and Technology of China2017ZHAO Z S. Materials genome initiative oriented materials informatics technology research[D]. Chengdu: University of Electronic Science and Technology of China, 2017.
|
| [4] |
XIE J X, SU Y J, ZHANG D W, et al. A vision of materials genome engineering in China[J]. Engineering, 2022, 10: 10-12.
|
| [5] |
贾丹润滑材料数据库平台设计及机器学习性能预测方法研究北京机械科学研究总院2021贾丹 ．润滑材料数据库平台设计及机器学习性能预测方法研究[D]．北京：机械科学研究总院,2021.
JIA DResearch on method of database platform design and machine learning performance prediction of lubricating materialsBeijingChina Academy of Machinery Science and Technology2021JIA D. Research on method of database platform design and machine learning performance prediction of lubricating materials[D]. Beijing: China Academy of Machinery Science and Technology, 2021.
|
| [6] |
王绍青,叶恒强 ．晶体材料基因组问题第一原理计算研究[J]．科学通报,2013,58（35）：3623-3632.
WANG S Q, YE H Q. First-principles calculation of crystalline materials genome[J]. Chinese Science Bulletin, 2013, 58(35): 3623-3632.
|
| [7] |
CHUN D M, KIM H J, LEE J C, et al. Web-based material database for material selection and its application programming interface (API) for CAD[J]. Key Engineering Materials, 2007, 345/346: 1593-1596.
|
| [8] |
SAAL J E, KIRKLIN S, AYKOL M, et al. Materials design and discovery with high-throughput density functional theory: The open quantum materials database (OQMD)[J]. JOM, 2013, 65(11): 1501-1509.
|
| [9] |
夏晴,殷国富,胡晓兵,等 ．基于Web技术的工程材料数据库系统的开发[J]．机械,2005,32（4）：55-57.
XIA Q, YIN G F, HU X B, et al. Development of engineering material database system on web[J]. Machinery, 2005, 32(4): 55-57.
|
| [10] |
成博,弓站朋,邓俊楷,等 ．针刺C/C复合材料结构-工艺-性能一体化软件平台[J]．固体火箭技术,2022,45（5）：807-814.
CHENG B, GONG Z P, DENG J K, et al. Structure-process-performance integrated software platform for needled C/C composite[J]. Journal of Solid Rocket Technology, 2022, 45(5): 807-814.
|
| [11] |
王景艳,陈明和,王辉,等 ．基于Web技术的Dynaform材料数据库的设计与开发[J]．机械工程材料,2016,40（10）：19-23.
WANG J Y, CHEN M H, WANG H, et al. Design and development of dynaform material database based on web technology[J]. Materials for Mechanical Engineering, 2016, 40(10): 19-23.
|
| [12] |
JIA D, DUAN H T, ZHAN S P, et al. Design and development of lubricating material database and research on performance prediction method of machine learning[J]. Scientific Reports, 2019, 9: 20277.
|
| [13] |
黄光胜,陈建,马世伟,等 ．民机材料工艺知识库系统构建的研究[J]．科技创新导报,2017,14（7）：8-9.
HUANG G S, CHEN J, MA S W, et al. Research on the construction of civil aircraft material process knowledge base system[J]. Science and Technology Innovation Herald, 2017, 14(7): 8-9.
|
| [14] |
ZHANG D P, BADARCH T. Research on principles and problems of computer software database design[J]. American Journal of Computer Science and Technology, 2023, 6(1).
|
| [15] |
王晓辉,王立凯,常亮,等 ．支持强度分析的轻量级材料数据库的设计与开发[J]．计算机应用与软件,2019,36（2）：93-97.
WANG X H, WANG L K, CHANG L, et al. Design and development of lightweight material database supporting strength analysis[J]. Computer Applications and Software, 2019, 36(2): 93-97.
|
| [16] |
任小平,刘战强,万熠,等 ．难加工材料切削数据库系统的研究与开发[J]．工具技术,2009,43（10）：39-41.
REN X P, LIU Z Q, WAN Y, et al. R & D of machining database system for difficult-to-cut materials[J]. Tool Engineering, 2009, 43(10): 39-41.
|
| [17] |
张永奎 ．数据库原理与设计[M]．北京：人民邮电出版社,2019.
ZHANG Y K. Principle of Database[M]. Beijing: The People′s Posts and Telecommunications Press, 2019.
|
| [18] |
JUAN Y F, DAI Y B, YANG Y, et al. Accelerating materials discovery using machine learning[J]. Journal of Materials Science & Technology, 2021, 79: 178-190.
|
| [19] |
吴金泰高强/高模碳纤维增强C/SiC复合材料制备及其性能研究长沙国防科学技术大学2015吴金泰 ．高强/高模碳纤维增强C/SiC复合材料制备及其性能研究[D]．长沙：国防科学技术大学,2015.
WU J TPreparation and properties of high-strength or high-modulus carbon fibers reinforced C/SiC compositesChangshaNational University of Defense Technology2015WU J T. Preparation and properties of high-strength or high-modulus carbon fibers reinforced C/SiC composites[D]. Changsha: National University of Defense Technology, 2015.
|
| [20] |
LI Z Y, DENG Z H, GE Z G, et al. A hybrid approach of case-based reasoning and process reasoning to typical parts grinding process intelligent decision[J]. International Journal of Production Research, 2023, 61(2): 503-519.
|
| [21] |
杨福军,丁涛,付眸,等 ．基于RBAC的权限复杂性与可靠性控制模型研究[J]．计算机应用与软件,2022,39（1）：30-38.
YANG F J, DING T, FU M, et al. RBAC-based authority complexity and reliability control model[J]. Computer Applications and Software, 2022, 39(1): 30-38.
|
| [22] |
高志玉,樊献金,高思达,等 ．基于多模型机器学习的合金结构钢回火力学性能研究[J]．材料导报,2023,37（6）：148-154.
GAO Z Y, FAN X J, GAO S D, et al. Study on tempering mechanical properties of alloy structural steel based on multi-model machine learning[J]. Materials Reports, 2023, 37(6): 148-154.
|
| [23] |
罗磊,邢海峰,王松涛 ．基于机器学习的单孔绝热气膜冷却效率分布预测研究[J]．推进技术,2022,43（4）：218-228.
LUO L, XING H F, WANG S T. Prediction of adiabatic film cooling efficiency distribution of single hole based on machine learning[J]. Journal of Propulsion Technology, 2022, 43(4): 218-228.
|
Supported by: Beijing Renhe Information Technology Co., Ltd. 
DownLoad: