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Nonlinear statistical models are useful where the change patterns are very complex in nature. These models find wide applications in various fields as most of the real-world problems are nonlinear and show complex behaviors. Nonlinear models can capture more accurately the complex patterns, interactions, and transformations that take place as compared to linear models. However, there are many challenges like finding the best fit, model estimations, interpretation and validation of the results. When an explosive detonates, it creates a shock wave that propagates in supersonic speed in the given medium. The main thrust in explosive research is to select the nonlinear model that can capture the shape patterns of the explosion dynamics more accurately with least possible loss of information. Model development for blast characteristic plays a crucial role in design and development of high explosives for military applications. In this work, nonlinear statistical models are developed for air blast characteristics of various PBX based compositions. These compositions are based on RDX/HMX and HTPB/energetic binders which are considered as next generation military explosives. It was observed that the trend for pressure versus stand-off distances obtained for small scale as well as large scale experimental data were more or less consistent with the modified Sadovaskiy model. The pressure-time curve of the air blast of aluminized high explosives can be represented by the modified Friedlander model equation. It is observed that all the estimations are well within the deviation of ±10%. The R2 values were found to be in the range 0.90 to 0.99 which demonstrated that the model equation represented the data well with an acceptable level of accuracy. Further, the higher adjusted R2 value and lower values of MAE, MSE, and RMSE indices showed the goodness-of-fit of the models. This paper highlights the usefulness of nonlinear statistical models in the field of high explosive as a strategic tool for development of powerful military explosives and also in designing of blast-resistant platforms for defense applications.

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Non-Linear Statistical Models for Air Blast Characteristics of Aluminized Explosive

  • 会议论文

  • 发表日期：

    2026年

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  • Abhay Kumar Mahanta

摘要

Nonlinear statistical models are useful where the change patterns are very complex in nature. These models find wide applications in various fields as most of the real-world problems are nonlinear and show complex behaviors. Nonlinear models can capture more accurately the complex patterns, interactions, and transformations that take place as compared to linear models. However, there are many challenges like finding the best fit, model estimations, interpretation and validation of the results. When an explosive detonates, it creates a shock wave that propagates in supersonic speed in the given medium. The main thrust in explosive research is to select the nonlinear model that can capture the shape patterns of the explosion dynamics more accurately with least possible loss of information. Model development for blast characteristic plays a crucial role in design and development of high explosives for military applications. In this work, nonlinear statistical models are developed for air blast characteristics of various PBX based compositions. These compositions are based on RDX/HMX and HTPB/energetic binders which are considered as next generation military explosives. It was observed that the trend for pressure versus stand-off distances obtained for small scale as well as large scale experimental data were more or less consistent with the modified Sadovaskiy model. The pressure-time curve of the air blast of aluminized high explosives can be represented by the modified Friedlander model equation. It is observed that all the estimations are well within the deviation of ±10%. The R2 values were found to be in the range 0.90 to 0.99 which demonstrated that the model equation represented the data well with an acceptable level of accuracy. Further, the higher adjusted R2 value and lower values of MAE, MSE, and RMSE indices showed the goodness-of-fit of the models. This paper highlights the usefulness of nonlinear statistical models in the field of high explosive as a strategic tool for development of powerful military explosives and also in designing of blast-resistant platforms for defense applications.