WeChat Mini Program
Old Version Features

    • Initiation of a Passive Explosive Charge Through a Target with Gaps

    V. A. Ogorodnikov,A. V. Romanov, E. A. Goncharov,A. I. Davydov, I. A. Sviridova

    Combustion Explosion and Shock Waves（2012）

    Institute of Experimental Physics

    Cited 0|Views3
    Abstract
    Experimental data on the measurement of time of passive explosive initiation by an active charge through an inert target with air gaps are presented. Two types of gaps are considered: perpendicular to the passive charge (a slit in the inert target) and parallel to the surface of the passive charge (between the inert target and the passive explosive). In the case of gaps parallel to the surface of the passive explosive charge, two-wave loading of the passive explosive charge created by impacts of thin plates, which are located on the surface of the main target on the side facing the passive explosive charge, is studied. Experimental data are analyzed by numerical calculations with the EGAK software on a Eulerian grid, and the instant of initiation is determined by a criterial parameter F , which is proportional to the energy released in shear strains, when a shock wave passes through the passive explosive charge.
    More
    Translated text
    Key words
    gap,target,passive charge,detonation,overtake,delay
    求助PDF
    上传PDF
    View via Publisher
    Bibtex
    AI Read Science
    AI Summary
    AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
    Example
    Background
    Key content
    Introduction
    Methods
    Results
    Related work
    Fund
    Key content
    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
    Upload PDF to Generate Summary
    Must-Reading Tree
    Example
    Generate MRT to find the research sequence of this paper
    Data Disclaimer
    The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
    Chat Paper
    Summary is being generated by the instructions you defined