本文關(guān)鍵詞：核電結(jié)構(gòu)材料應(yīng)力腐蝕開裂裂紋擴(kuò)展速率預(yù)測　出處：《天津大學(xué)》2014年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 環(huán)境耦合致裂模型 人工神經(jīng)網(wǎng)絡(luò)模型 應(yīng)力腐蝕開裂 Alloy 600 304不銹鋼 裂紋擴(kuò)展速率

【摘要】：輕水堆核電站冷卻回路材料的應(yīng)力腐蝕開裂是威脅核電站安全運(yùn)行的重要因素之一。由于該現(xiàn)象的嚴(yán)重性,普遍性以及由此而引發(fā)的各種安全,經(jīng)濟(jì)問題,所以有必要建立一種預(yù)測應(yīng)力腐蝕開裂裂紋擴(kuò)展速率的模型,這種模型的建立將有益于核電站經(jīng)濟(jì)效益的提升,同時增加核電站的安全性。因?yàn)檫@種模型能夠指導(dǎo)核電站以合適的方式運(yùn)行,在降低風(fēng)險(xiǎn)的同時節(jié)約不必要的開支。建立了沸水堆環(huán)境下304不銹鋼沿晶應(yīng)力腐蝕開裂裂紋擴(kuò)展速率數(shù)據(jù)庫。建立了適用于該環(huán)境下裂紋擴(kuò)展速率預(yù)測的人工神經(jīng)網(wǎng)絡(luò)模型,并使用實(shí)驗(yàn)數(shù)據(jù)對其訓(xùn)練。結(jié)果表明,人工神經(jīng)網(wǎng)絡(luò)能夠有效地預(yù)測多種不同變量對裂紋擴(kuò)展速率的影響�；谏窠�(jīng)網(wǎng)絡(luò)的訓(xùn)練結(jié)果,對環(huán)境耦合致裂模型進(jìn)行改進(jìn),使其能夠預(yù)測敏化度對裂紋擴(kuò)展速率的影響。環(huán)境耦合致裂模型和人工神經(jīng)網(wǎng)絡(luò)模型的預(yù)測結(jié)果吻合良好。通過對影響變量進(jìn)行敏感性分析,得出沸水堆環(huán)境中304不銹鋼的應(yīng)力腐蝕開裂主要是一種電化學(xué)現(xiàn)象,同時機(jī)械參數(shù)和材料微觀結(jié)構(gòu)對其也有重要影響。建立了壓水堆環(huán)境中alloy 600沿晶應(yīng)力腐蝕開裂裂紋擴(kuò)展速率的數(shù)據(jù)庫。建立相應(yīng)的人工神經(jīng)網(wǎng)絡(luò)模型并使用實(shí)驗(yàn)數(shù)據(jù)對其訓(xùn)練。結(jié)果表明,人工神經(jīng)網(wǎng)絡(luò)模型較好的預(yù)測了各個影響變量對裂紋擴(kuò)展速率的影響作用。對環(huán)境耦合致裂模型進(jìn)行擴(kuò)展,并將其應(yīng)用于壓水堆環(huán)境中alloy 600的應(yīng)力腐蝕開裂預(yù)測。預(yù)測結(jié)果很好的解釋了應(yīng)力強(qiáng)度因子、溫度和屈服強(qiáng)度等對裂紋擴(kuò)展速率的影響。使用fuzzy curve方法對alloy 600的數(shù)據(jù)分析得出,壓水堆環(huán)境下alloy 600的沿晶應(yīng)力腐蝕開裂機(jī)械參數(shù)作用明顯,而電化學(xué)參數(shù)和微觀結(jié)構(gòu)的影響次之。使用環(huán)境耦合致裂模型分析了沸水堆環(huán)境中304不銹鋼沿晶應(yīng)力腐蝕過程中影響變量的隨機(jī)誤差對裂紋擴(kuò)展速率分布的影響。結(jié)果表明,只有腐蝕電位的隨機(jī)誤差能夠改變裂紋擴(kuò)展速率分布的形式,而當(dāng)所有的影響變量服從正態(tài)分布時,相應(yīng)的裂紋擴(kuò)展速率的分布也服從正態(tài)分布。
[Abstract]:Stress corrosion cracking (SCC) of LWR cooling loop materials is one of the important factors threatening the safe operation of nuclear power plants. Due to the seriousness of the phenomenon, universality and various safety and economic problems. Therefore, it is necessary to establish a model to predict the stress corrosion cracking crack growth rate, which will benefit the economic efficiency of nuclear power plant. At the same time increase the safety of nuclear power plants, because this model can guide the operation of nuclear power plants in the right way. The database of crack growth rate of 304 stainless steel intergranular stress corrosion cracking under boiling water reactor environment was established, and the person suitable for prediction of crack growth rate in this environment was established. Neural network model. The results show that the artificial neural network can effectively predict the influence of different variables on the crack growth rate. The environmental coupling cracking model is improved. It can predict the effect of sensitivity on crack growth rate. The prediction results of environmental coupled fracture model and artificial neural network model are in good agreement. Sensitivity analysis of the influence variables is carried out. It is concluded that the stress corrosion cracking of 304 stainless steel in boiling water reactor environment is mainly an electrochemical phenomenon. At the same time, the mechanical parameters and the microstructure of materials also have an important effect on it. The alloy in PWR environment has been established. The corresponding artificial neural network model is established and the experimental data are used to train the 600 intergranular stress corrosion cracking crack growth rate database. The artificial neural network model can well predict the effect of each influence variable on the crack growth rate. It is applied to predict the stress corrosion cracking of alloy 600 in PWR environment. The prediction results explain the stress intensity factor well. The effect of temperature and yield strength on the crack growth rate is analyzed by using fuzzy curve method to analyze the data of alloy 600. The mechanical parameters of intergranular stress corrosion cracking (SCC) of alloy 600 under pressurized water reactor (PWR) environment are obvious. The influence of electrochemical parameters and microstructure on the crack growth rate distribution of 304 stainless steel during intergranular stress corrosion (SCC) was analyzed by using the environmental coupled fracture model (ECCM) in the process of intergranular stress corrosion (SCC) of 304 stainless steel in boiling water reactor (BWR). Impact. Results show. Only the random error of corrosion potential can change the form of crack growth rate distribution, and when all the influence variables are applied to normal distribution, the distribution of corresponding crack growth rate is also normal distribution.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TM623.7
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本文編號：1424620