Page 116 - 《爆炸与冲击》2026年第4期
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第 46 卷                李般若,等: 基于GNN的爆炸压力时空分布预测模型                                 第 4 期


               参考文献:
               [1]   SHIRBHATE  P  A,  GOEL  M  D.  A  critical  review  of  blast  wave  parameters  and  approaches  for  blast  load  mitigation  [J].
                    Archives of Computational Methods in Engineering, 2021, 28(3): 1713–1730. DOI: 10.1007/s11831-020-09436-y.
               [2]   REMENNIKOV A M, MENDIS P A. Prediction of airblast loads in complex environments using artificial neural networks
                    [M]. Southampton: WIT Press, 2006.
               [3]   REMENNIKOV A M, ROSE T A. Predicting the effectiveness of blast wall barriers using neural networks [J]. International
                    Journal of Impact Engineering, 2007, 34(12): 1907–1923. DOI: 10.1016/j.ijimpeng.2006.11.003.
               [4]   BEWICK B, FLOOD I, CHEN Z. A neural-network model-based engineering tool for blast wall protection of structures [J].
                    International Journal of Protective Structures, 2011, 2(2): 159–176. DOI: 10.1260/2041-4196.2.2.159.
               [5]   KHANDELWAL M, KANKAR P K. Prediction of blast-induced air overpressure using support vector machine [J]. Arabian
                    Journal of Geosciences, 2011, 4(3): 427–433. DOI: 10.1007/s12517-009-0092-7.
               [6]   HARANDIZADEH H, ARMAGHANI D J. Prediction of air-overpressure induced by blasting using an ANFIS-PNN model
                    optimized by GA [J]. Applied Soft Computing, 2021, 99: 106904. DOI: 10.1016/j.asoc.2020.106904.
               [7]   LI Q L, WANG Y, SHAO Y D, et al. A comparative study on the most effective machine learning model for blast loading
                    prediction: from GBDT to Transformer [J]. Engineering Structures, 2023, 276: 115310. DOI: 10.1016/J.ENGSTRUCT.2022.
                    115310.
               [8]   PANNELL J J, RIGBY S E, PANOUTSOS G. Physics-informed regularisation procedure in neural networks: an application
                    in  blast  protection  engineering  [J].  International  Journal  of  Protective  Structures,  2022,  13(3):  555–578.  DOI:  10.1177/
                    20414196211073501.
               [9]   BACCIU D, ERRICA F, MICHELI A, et al. A gentle introduction to deep learning for graphs [J]. Neural Networks, 2020,
                    129: 203–221. DOI: 10.1016/j.neunet.2020.06.006.
               [10]   PFAFF T, FORTUNATO M, SANCHEZ-GONZALEZ A, et al. Learning mesh-based simulation with graph networks [C]//
                    Proceedings of the 9th International Conference on Learning Representations. OpenReview. net, 2021.
               [11]   HEYLMUN J, VONK P, BREWER T. BlastFoam theory and user guide [Z]. Synthetik Applied Technologies, 2019.
               [12]   邓国强, 张蒙蒙, 高伟亮. 强作用下几种空气状态方程比较分析 [J]. 防护工程, 2021, 43(5): 1–7. DOI: 10.3969/j.issn.1674-
                    1854.2021.05.001.
                    DENG  G  Q,  ZHANG  M  M,  GAO  W  L.  Comparative  analysis  on  several  air  EOSs  under  strong  action  [J].  Protective
                    Engineering, 2021, 43(5): 1–7. DOI: 10.3969/j.issn.1674-1854.2021.05.001.
               [13]   NEEDHAM C E. Blast waves [M]. Berlin: Springer, 2010.
               [14]   RETTENMAIER  D,  DEISING  D,  OUEDRAOGO  Y,  et  al.  Load  balanced  2D  and  3D  adaptive  mesh  refinement  in
                    OpenFOAM [J]. SoftwareX, 2019, 10: 100317. DOI: 10.1016/j.softx.2019.100317.
               [15]   GROVES C E, ILIE M, SCHALLHORN P. Interpolation method needed for numerical uncertainty analysis of computational
                    fluid dynamics [C]//Proceedings of the 52nd Aerospace Sciences Meeting. National Harbor: AIAA, 2014: 1433. DOI: 10.2514/
                    6.2014-1433.
               [16]   蒋晓庆. 双钢板-混凝土组合板抗接触爆炸性能研究 [D]. 南京: 河海大学, 2024.
               [17]   赵铮, 陶钢, 杜长星. 爆轰产物    JWL  状态方程应用研究 [J]. 高压物理学报, 2009, 23(4): 277–282. DOI: 10.3969/j.issn.
                    1000-5773.2009.04.007.
                    ZHAO Z, TAO G, DU C S. Application research on JWL equation of state of detonation products [J]. Chinese Journal of High
                    Pressure Physics, 2009, 23(4): 277–282. DOI: 10.3969/j.issn.1000-5773.2009.04.007.
               [18]   熊展, 巨圆圆, 张春辉, 等. 舱内爆炸冲击波载荷特性试验研究 [J]. 舰船科学技术, 2023, 45(22): 8–12. DOI: 10.3404/
                    j.issn.1672-7649.2023.22.002.
                    XIONG Z, JU Y Y, ZHANG C H, et al. Experimental research on loading characteristics of blast shock wave in cabin [J]. Ship
                    Science and Technology, 2023, 45(22): 8–12. DOI: 10.3404/j.issn.1672-7649.2023.22.002.
               [19]   NGO T D, MENDIS P A, GUPTA A, et al. Blast loading and blast effects on structures–an overview [J]. Electronic Journal of
                    Structural Engineering, 2007(1): 76–91. DOI: 10.56748/ejse.671.
               [20]   李臻, 刘彦, 黄风雷, 等. 接触爆炸和近距离爆炸比冲量数值仿真研究 [J]. 北京理工大学学报, 2020, 40(2): 143–149. DOI:
                    10.15918/j.tbit1001-0645.2019.049.


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