Analyzing and Predicting the CL-20 Detonation Reaction Mechanism Based on Artificial Intelligence Algorithm

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CL-20 Detonation Reaction Mechanism Based on Artificial Intelligence Algorithm</title> <meta name="description" content="Analyzing and Predicting the CL-20 Detonation Reaction Mechanism Based on Artificial Intelligence Algorithm"> <meta name="keywords" content="energetic material detonation reaction, first-principle molecular dynamics simulation of multiscale shock technique, neural network, CL-20"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar 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class="card-body"><strong>Paper Count:</strong> 87407</div> </div> </div> </div> <div class="card publication-listing mt-3 mb-3"> <h5 class="card-header" style="font-size:.9rem">Analyzing and Predicting the CL-20 Detonation Reaction Mechanism Based on Artificial Intelligence Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kaining%20Zhang">Kaining Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Lang%20Chen"> Lang Chen</a>, <a href="https://publications.waset.org/abstracts/search?q=Danyang%20Liu"> Danyang Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jianying%20Lu"> Jianying Lu</a>, <a href="https://publications.waset.org/abstracts/search?q=Kun%20Yang"> Kun Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Junying%20Wu"> Junying Wu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In order to solve the problem of a large amount of simulation and limited simulation scale in the first-principle molecular dynamics simulation of energetic material detonation reaction, we established an artificial intelligence model for analyzing and predicting the detonation reaction mechanism of CL-20 based on the first-principle molecular dynamics simulation of the multiscale shock technique (MSST). We employed principal component analysis to identify the dominant charge features governing molecular reactions. We adopted the K-means clustering algorithm to cluster the reaction paths and screen out the key reactions. We introduced the neural network algorithm to construct the mapping relationship between the charge characteristics of the molecular structure and the key reaction characteristics so as to establish a calculation method for predicting detonation reactions based on the charge characteristics of CL-20 and realize the rapid analysis of the reaction mechanism of energetic materials. <iframe src="https://publications.waset.org/abstracts/168381.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=energetic%20material%20detonation%20reaction" title="energetic material detonation reaction">energetic material detonation reaction</a>, <a href="https://publications.waset.org/abstracts/search?q=first-principle%20molecular%20dynamics%20simulation%20of%20multiscale%20shock%20technique" title=" first-principle molecular dynamics simulation of multiscale shock technique"> first-principle molecular dynamics simulation of multiscale shock technique</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=CL-20" title=" CL-20"> CL-20</a> </p> <a href="https://publications.waset.org/abstracts/168381/analyzing-and-predicting-the-cl-20-detonation-reaction-mechanism-based-on-artificial-intelligence-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168381.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">113</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a 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Analyzing and Predicting the CL-20 Detonation Reaction Mechanism Based on Artificial Intelligence Algorithm