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神經(jīng)網(wǎng)絡(luò)法預(yù)測汽車輪胎的微觀與宏觀性能

發(fā)布時間:2018-02-11 04:28

  本文關(guān)鍵詞: 設(shè)計參數(shù) 有限元模擬 神經(jīng)網(wǎng)絡(luò) 輪胎構(gòu)型 出處:《現(xiàn)代橡膠技術(shù)》2016年05期  論文類型:期刊論文


【摘要】:有限元(FE)分析已成為輪胎行業(yè)虛擬研究輪胎備受青睞的工具,因為它能模擬輪胎胎體的接合部細節(jié)。然而,在輪胎設(shè)計開發(fā)中應(yīng)用有限元分析依然非常耗時,且花費不菲。在此,對應(yīng)用各種人工神經(jīng)網(wǎng)絡(luò)(ANN)結(jié)構(gòu)來預(yù)測輪胎性能進行了評估,以便選擇最有效和最高效的結(jié)構(gòu)。這樣我們可在用花費高得多的全過程有限元分析進行證實預(yù)測的性能之前,以花費不多的費用進行廣泛的參數(shù)研究,以便優(yōu)化輪胎設(shè)計。
[Abstract]:Finite element (FEE) analysis has become a popular tool in tire virtual research because it can simulate the joint details of tire carcass. However, the application of finite element analysis in tire design and development is still time-consuming. And it's expensive. Here, we evaluate the performance of tires using a variety of artificial neural network (Ann) structures. In order to select the most effective and efficient structure, we can carry out extensive parametric studies at a low cost to optimize the tire design before verifying the predicted performance with a much more expensive finite element analysis of the whole process.
【分類號】:U463.341;TP183
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本文編號:1502204

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