發(fā)布時(shí)間：2018-03-15 12:42

  本文選題：天然屑粒式橡膠瀝青　切入點(diǎn)：正交試驗(yàn)設(shè)計(jì)　出處：《長(zhǎng)沙理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：天然屑粒式橡膠改性瀝青是以印尼TMA公司生產(chǎn)的Superflex(福萊斯)改性劑與基質(zhì)瀝青經(jīng)過(guò)一定的加工而制得的改性瀝青,改性后的瀝青高溫性能優(yōu)良,但是目前國(guó)內(nèi)對(duì)天然屑粒式橡膠改性瀝青的研究并不多,其改性機(jī)理值得我們進(jìn)一步的研究。本文主要圍繞天然屑粒式橡膠改性瀝青性能評(píng)價(jià)指標(biāo)、最佳制備工藝研究、高低溫性能改善情況進(jìn)行展開。首先參考國(guó)內(nèi)外研究現(xiàn)狀,對(duì)橡膠改性瀝青性能評(píng)價(jià)指標(biāo)進(jìn)行探討,并確定了適合于天然屑粒式橡膠改性瀝青性能評(píng)價(jià)的指標(biāo),并對(duì)瀝青基瀝青混合料的試驗(yàn)方法進(jìn)行了相關(guān)介紹。接下來(lái)考察了不同加工條件對(duì)改性瀝青性能的影響,并通過(guò)合理選取影響因素、因素水平、評(píng)價(jià)指標(biāo),采用正交試驗(yàn)設(shè)計(jì)方法對(duì)改性瀝青制備工藝進(jìn)行考察,明確了天然屑粒式橡膠改性劑摻量和加工溫度是影響改性瀝青性能的顯著因素,確定了獲得最佳性能的天然屑粒式橡膠改性瀝青的加工條件是180℃,攪拌時(shí)間60min,改性劑摻量15%。然后通過(guò)DSR實(shí)驗(yàn)、三大指標(biāo)、黏度試驗(yàn)、老化試驗(yàn)等對(duì)不同天然屑粒式橡膠摻量的改性瀝青、基質(zhì)瀝青、SBS瀝青性能進(jìn)行對(duì)比,分析天然屑粒式橡膠改性瀝青的性能改善程度與改善機(jī)理,結(jié)果顯示天然屑粒式橡膠改性瀝青在摻量達(dá)到15%后,性能與SBS改性瀝青的性能接近,尤其是高溫性能比較突出,耐老化能力也比較優(yōu)良。同時(shí)進(jìn)行了熱重分析實(shí)驗(yàn),分析了改性前后瀝青性質(zhì)的差異并對(duì)天然屑粒式橡膠改性機(jī)理進(jìn)行探討。之后對(duì)納米CaCO3/天然屑粒式橡膠復(fù)合改性瀝青進(jìn)行了相關(guān)的研究,選用A、B、C、D四種不同粒徑的納米CaCO3與天然屑粒式橡膠復(fù)合改性,對(duì)改性后的瀝青性能進(jìn)行評(píng)價(jià)。采用模糊神經(jīng)網(wǎng)絡(luò)對(duì)改性后瀝青的性能進(jìn)行預(yù)測(cè),使用MATALAB編程,實(shí)現(xiàn)基于模糊網(wǎng)絡(luò)的瀝青材料PG分級(jí)臨界溫度及175-C黏度評(píng)價(jià)算法,并且通過(guò)訓(xùn)練后的神經(jīng)網(wǎng)絡(luò)能夠很好地預(yù)測(cè)一定加工條件下瀝青的性能,誤差很小,這說(shuō)明神經(jīng)網(wǎng)絡(luò)在預(yù)測(cè)改性瀝青的性能方面是適用的。
[Abstract]:Natural rubber crumb modified asphalt production in Indonesia's TMA Superflex (Fores) modified asphalt and asphalt modifier after processing and preparation, excellent high temperature performance of modified asphalt, but there is not much research on natural rubber crumb modified asphalt, the the modification mechanism is worth further research. This paper mainly focuses on the natural rubber crumb modified asphalt performance evaluation index, the optimal preparation process research, high and low temperature performance improvement started. The first reference to domestic and foreign research present situation, carries on the discussion to the rubber modified asphalt performance evaluation index, and to determine the suitable natural debris rubber modified asphalt performance evaluation index, and test method of asphalt base asphalt mixture are introduced. Then the effects of different processing conditions on the performance of the modified asphalt, and through Reasonable selection of factors, factors, evaluation index, orthogonal test design method of modified asphalt preparation technology was investigated, the natural rubber crumb modified temperature of agent dosage and processing are significant factors that influence the performance of modified asphalt, the best performance of natural crumb rubber modified grain type asphalt processing conditions of 180 DEG C, stirring time 60min, modifier dosage 15%. and then through the DSR experiment, the three indicators, the viscosity test and aging test of modified asphalt, crumb rubber with different natural content of matrix asphalt, SBS asphalt performance comparison, analysis and mechanism of improving the performance of natural chip level grain type rubber modified asphalt is improved, the results indicated that natural type crumb rubber modified asphalt in volume reached 15%, close to the performance and performance of SBS modified asphalt, especially high temperature performance is outstanding, anti-aging ability is better Good. At the same time the thermogravimetric analysis experiment, analyzes the difference of the modified asphalt properties before and after the mechanism of the natural rubber crumb modified nano CaCO3/ were discussed. After the natural rubber crumb modified asphalt is studied, using A, B, C, D four different particle size the nano CaCO3 and natural rubber crumb modified. To evaluate the performance of modified asphalt. The fuzzy neural network is used to predict the performance of the modified asphalt, the use of MATALAB programming, implementation of PG fuzzy neural network classification of asphalt materials, critical temperature and 175-C viscosity evaluation algorithm based on neural network, and through training after the good prediction performance of certain processing conditions of asphalt, the error is very small, which shows the performance of neural network in the prediction of the modified asphalt is applicable.

【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U414
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本文編號(hào)：1616075