1 School of Physical Science and Technology, Southwest Jiaotong University, Chengdu 610031, China; 2 Institute of Chemical Materials, China Academy of Engineering Physics (CAEP), Mianyang 621900, China; 3 Beijing Computational Science Research Center, Beijing 100048, China; 4 College of Polymer Science and Engineering, Sichuan University, Chengdu 610065, China
Abstract The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity, which is particularly beneficial for applications in thermal management. The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity, thereby directly influencing the effectiveness of thermal management, including the mitigation of local hot-spot temperatures. This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX (plastic-bonded explosive) matrix, focusing specifically on the thermal management of hot spots. Through finite element method (FEM) simulations, we have explored the impact of graphene filler orientation, proximity to the central heat source, and spatial clustering on heat transfer. Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels, which significantly reduce the temperatures at local hot spots. In a model containing 0.336% graphene by volume, the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material, under a heat flux of 600 W/m. This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers, aiming to improve the thermal management capabilities of HMX-based PBX explosives.
Received: 12 December 2024
Revised: 11 February 2025
Accepted manuscript online: 25 February 2025
PACS:
44.05.+e
(Analytical and numerical techniques)
Fund: Project supported by the National Natural Science Foundation of China (Grant No. U2330208).
Corresponding Authors:
Yuxiang Ni
E-mail: yuxiang.ni@swjtu.edu.cn
Cite this article:
Xuanyi Yang(杨烜屹), Xin Huang(黄鑫), Chaoyang Zhang(张朝阳), Yanqing Wang(王延青), and Yuxiang Ni(倪宇翔) Finite element analysis of the impact of graphene filler dispersion on local hotspots in HMX-based PBX explosives 2025 Chin. Phys. B 34 054401
[1] Mares J, Miller J, Sharp N, et al. 2013 J. Appl. Phys. 113 044904 [2] Chen P, Huang F, and Ding Y 2007 J. Mater. Sci. 42 5272 [3] Liu J, Hao G, Rong Y, et al. 2017 Combust. Explos. Shock Waves 53 744 [4] Tarver C M and Tran T D 2004 Combust. Flame. 137 50 [5] Son S, Berghout H, Bolme C, et al. 2000 Proc. Combust. Inst. 28 919 [6] Lin C, Zeng C,Wen Y, et al. 2019 ACS Appl. Mater. Interfaces 12 4002 [7] Li Y, Wu P, Hua C, et al. 2019 Cent. Eur. J. Energetic Mater. 16 295 [8] Xiao J, Fang G, Ji G, et al. 2005 Chin. Sci. Bull. 50 21 [9] Zhang P, Guo X Y, Zhang J Y, et al. 2014 J. Energetic Mater. 32 278 [10] Peng X, Jiang P, Ouyang Y, et al. 2021 Nanotechnology 33 035707 [11] Wang J, Zhang Z, Shi R, et al. 2020 Adv. Mater. Interfaces 7 1901582 [12] Zhang Y C, Yu W H, and Xu S M 2023 Rare Met. 42 2688 [13] Liu R and Chen P 2018 Mech. Mater. 124 106 [14] Parker G R, Heatwole E M, Holmes M D, et al. 2020 Combust. Flame. 215 295 [15] Zhang C, Ma D, Shang M, et al. 2022 Mater. Today Phys. 22 100605 [16] Ma D, Ding H,Wang X, et al. 2017 Int. J. Heat Mass Transfer 108 940 [17] Yang N, Hu S, Ma D, Lu T and Li B 2015 Sci. Rep. 5 14878 [18] He G, Yang Z, Zhou X, et al. 2016 Compos. Sci. Technol. 131 22 [19] Fu Y, Hansson J, Liu Y, et al. 2020 2D Mater. 7 012001 [20] Wu Z P, Zhang C, Hu S Q, et al. 2023 Acta Phys. Sin. 72 184401 (in Chinese) [21] Liu L, Xu C, Yang Y, et al. 2025 Mater. Horiz. 12 64 [22] Łapińska A, Grochowska N, Antonowicz J, Michalski P, Dydek K, Dużyńska A, Daniszewska A, Ojrzyńska M, Zeranska K and Zdrojek M 2022 Sci. Rep. 12 19038 [23] Shimamura A, Hotta Y, Hyuga H, et al. 2020 Sci. Rep. 10 14926 [24] Wang J, Li C, Li J, et al. 2021 Carbon 175 259 [25] Yang Q, Zhang Z, Gong X, et al. 2020 Heat Mass Transfer 56 1931 [26] Lin C, Nie S, He G, et al. 2020 Compos. Part B Eng. 203 108447 [27] Aurenhammer F and Klein R 2000 Handb. Comput. Geom. 5 201 [28] Gong G, Wei Z, Zhang F, et al. 2022 Environ. Monit. Assess. 194 428 [29] Cao Z, Huang X, Wang Y, et al. 2023 J. Mater. Sci. 58 4668 [30] Huang X, Zhi C, Lin Y, et al. 2020 Mater. Sci. Eng. R Rep. 142 100577 [31] Zhang X X, Yang Z J, Nie F and Yan Q L 2020 Energetic Mater. Front. 1 141
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