通过爆障相互作用减轻爆炸载荷

IF 2.1 Q2 ENGINEERING, CIVIL
Omar Ghareeb Alshammari, Obed Samuelraj Isaac, S. Clarke, S. Rigby
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引用次数: 3

摘要

阻碍冲击波通过是减轻障碍物下游冲击压力的有效方法。为此,人们广泛研究了冲击波与简化结构形状(如圆柱体)之间的相互作用,以了解障碍物周围的复杂流动模式。图案包括入射波、衍射波和下游区域中的其他二次波的干涉区。这样的区域导致爆破波参数发生重大变化。本研究旨在确定和研究有助于减轻圆柱形障碍物下游产生的爆炸载荷的因素,包括地面和障碍物旨在保护的刚性壁目标上的爆炸载荷。该数值研究的输入还用于开发基于人工神经网络(ANN)模型的快速预测方法。研究发现,圆柱体的大小、冲击波的强度、圆柱形障碍物的位置和目标长度都对下游复杂流场的发展和反射目标上的脉冲衰减有显著影响。确定了一些关键的缓解机制,即阴影和干扰,并讨论了它们的起源和意义。使用缩放输入参数训练的ANN模型可以成功地预测这种反射目标上的脉冲值。使用该模型来预测以前看不见的配置的响应(对于ANN)提供了极好的相关性,从而证明了这种快速运行的工具的高保真度,以及它预测各种波柱相互作用在减轻爆炸载荷方面的有效性的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mitigation of blast loading through blast–obstacle interaction
Obstructing the passage of blast waves is an effective method of mitigating blast pressures downstream of the obstacle. To this end, the interaction between a blast wave and a simplified structural shape, such as a cylinder, has been widely investigated to understand the complex flow pattern that ensues around the obstacle. The patterns include the interference zones of the incident wave, the diffracted wave, and other secondary waves in the downstream region. Such zones are responsible for causing significant modifications to the blast wave parameters. This research aims to identify and study the factors that serve to mitigate the resulting blast loads downstream of a cylindrical obstacle – both on the ground, and on a rigid wall target that the obstacle is aiming to protect. Inputs from this numerical study are also used to develop a fast-running predictive method based on an artificial neural network (ANN) model. It was found that the size of the cylinder, the strength of the blast wave, the position of the cylindrical obstruction, and the target length, all have remarkable effects on the development of the complex flow-field downstream, and on the impulse mitigation on a reflective target. A number of key mitigation mechanisms are identified, namely shadowing and interference, and their origins and significance are discussed. An ANN model trained using scaled input parameters could successfully predict impulse values on such a reflective target. Using this model to predict the response of previously unseen configurations (for the ANN) gave excellent correlation, thereby demonstrating the high fidelity of this fast-running tool, and its ability to predict the effectiveness of various wave-cylinder interactions in mitigating blast loading.
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来源期刊
CiteScore
4.30
自引率
25.00%
发文量
48
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