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A Fast Running Loading Methodology for Ground Vehicle Underbody Blast Events
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
A full-system, end-to-end blast modeling and simulation of vehicle underbody buried blast events typically includes detailed modeling of soil, high explosive (HE) charge and air. The complex computations involved in these simulations take days to just capture the initial 50-millisecond blast-off phase, and in some cases, even weeks. The single most intricate step in the buried blast event simulation is in the modeling of the explosive loading on the underbody structure from the blast products; it is also one of the most computationally expensive steps of the simulation. Therefore, there is significant interest in the modeling and simulation community to develop various methodologies for fast running tools to run full simulation events in quicker turnarounds of time. This paper discusses investigation of a fast running blast loading methodology wherein the effects of the soil can be adequately captured without having to employ a highly detailed and computationally intensive soil/explosive model, and the interactions thereof (with each other and with the vehicle), in the simulation. The paper will also present a basis of such methodology utilizing the free air-blast loading data that is readily available and implemented in LS-DYNA, the technical approach for matching the buried blast loading patterns using free-air blast datasets and selection of test cases for evaluation and validation. Test cases include simple flat plate with high deformation and a generic vehicle representative of a military ground vehicle. The results from the development and validation of the methodology are presented along with future technical development strategies.
CitationRamalingam, J. and Thyagarajan, R., "A Fast Running Loading Methodology for Ground Vehicle Underbody Blast Events," SAE Technical Paper 2018-01-0620, 2018, https://doi.org/10.4271/2018-01-0620.
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