输油管线硫化腐蚀研究
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摘要
近年来,随着我国进口及国内开采含硫原油的增多,输油管线腐蚀加剧,穿孔现象时有发生,管线使用寿命严重缩短。输油管线的硫化腐蚀研究有助于评估管线的使用寿命、减少能源浪费和环境污染,具有较高的研究价值。
本论文模拟管输含硫原油的现场工况条件,实验室运用高温高压反应釜,辅以失重法,测定不同典型含硫原油在不同输送条件下的16Mn钢管材试样的腐蚀速率,建立输送不同酸值、不同含硫量原油在不同输送温度、不同输送压力、不同流速条件下的管线腐蚀速率数据库。通过扫描电子显微镜(SEM)对试样腐蚀形貌进行观察,通过X射线荧光光谱对试样表面腐蚀产物进行成分鉴定,通过电化学方法结合挂片失重法对不同状况下的腐蚀产物膜进行定性评价,对比分析不同条件下腐蚀产物膜的成膜情况,结合测定的管材腐蚀速率,揭示含硫原油对输油管线的腐蚀规律。研究表明:硫含量和酸值是影响输油管线内腐蚀的主要因素,温度和流速是次要因素,压力对管线的腐蚀速率影响不大;实验条件范围内,原油的硫含量越大,其腐蚀性越强;随着原油酸值的增大,管材的腐蚀速率明显增强;温度越高腐蚀产物膜对试样的保护作用越强,同时各种腐蚀性物质在腐蚀产物膜中的扩散速率也越大,后一种作用强于前一种作用,管材试样表现出温度越高,腐蚀速率越大的腐蚀规律;动态原油比静态原油具有更强的腐蚀性,在特定的流速下管材的腐蚀速率存在最大值。
在管线腐蚀速率数据库基础之上,运用BP神经网络开发管线剩余寿命预测软件;根据管线的修建、运营等相关费用,计算输送含硫原油相应的管线腐蚀经济损失,并开发软件的相应功能。
In recent years, our country is increasing the import and intestine output of crude oil with high sulphur content year by year. The perforation phenomenons of pipeline occur frequently, and pipeline’s using life is cut down seriously. The sulphur corrosion research of oil pipeline contributes to assesse pipeline’s using life, decrease energy dissipation and environmental pollution, which has high research value.
The high temperature high pressure reaction still was used in laboratory to simulate the scene operating mode condition. The corrosion rate of 16Mn pipe steel was measured in different typical sour crude oil under different transportation conditions. A corrosion rate database of pipeline was built when different kind of oil with different sulphur content and different acid number under different transportation temperature, different pressure and different speed of flow. The specimen surface appearance was observed through the scanning electronic microscope (SEM), and the ingredient of corrosion product on the test specimen surface was appraised through X-Ray Fluorescence Spectrometer(XRF). The qualitative analysis of corrosion product film was got through electro-chemical means and weight loss method in order to compare the corrosion product film under different situations. The pipeline’s corrosion disciplinarian was revealed combined with corrosion rate. The research shows that sulphur content and acid value was the main reasons of the internal corrosion, temperature and flow velocity was the secondary cause, and pressure had little influence on the corrosion rate; the more sulphur content was, the stronger the crude oil was within the limit of experimental condition; the pipeline’s corrosion rate increased obviously with the acid value increasing; the higher temperature was, the stronger corrosion product’s protectiveness became, and the bigger diffusion rate of all kinds of corrosive materials, and the latter effort fact was stronger than the former, so the pipeline’s corrosion rate increased with the temperature increasing; the dynamic crude oil had stronger corrosivity than static oil, and there was a maximum value according to certain flow velocity.
On the base of the corrosion rate database, a predict software for the remaining lifetime of pipeline was programmed using BP neural network. The corresponding economic loss of transportation sour crude oil was calculated according to related expense about pipeline's construction, operation and so on. The economic loss computation function was also developed in the software.
本论文模拟管输含硫原油的现场工况条件,实验室运用高温高压反应釜,辅以失重法,测定不同典型含硫原油在不同输送条件下的16Mn钢管材试样的腐蚀速率,建立输送不同酸值、不同含硫量原油在不同输送温度、不同输送压力、不同流速条件下的管线腐蚀速率数据库。通过扫描电子显微镜(SEM)对试样腐蚀形貌进行观察,通过X射线荧光光谱对试样表面腐蚀产物进行成分鉴定,通过电化学方法结合挂片失重法对不同状况下的腐蚀产物膜进行定性评价,对比分析不同条件下腐蚀产物膜的成膜情况,结合测定的管材腐蚀速率,揭示含硫原油对输油管线的腐蚀规律。研究表明:硫含量和酸值是影响输油管线内腐蚀的主要因素,温度和流速是次要因素,压力对管线的腐蚀速率影响不大;实验条件范围内,原油的硫含量越大,其腐蚀性越强;随着原油酸值的增大,管材的腐蚀速率明显增强;温度越高腐蚀产物膜对试样的保护作用越强,同时各种腐蚀性物质在腐蚀产物膜中的扩散速率也越大,后一种作用强于前一种作用,管材试样表现出温度越高,腐蚀速率越大的腐蚀规律;动态原油比静态原油具有更强的腐蚀性,在特定的流速下管材的腐蚀速率存在最大值。
在管线腐蚀速率数据库基础之上,运用BP神经网络开发管线剩余寿命预测软件;根据管线的修建、运营等相关费用,计算输送含硫原油相应的管线腐蚀经济损失,并开发软件的相应功能。
In recent years, our country is increasing the import and intestine output of crude oil with high sulphur content year by year. The perforation phenomenons of pipeline occur frequently, and pipeline’s using life is cut down seriously. The sulphur corrosion research of oil pipeline contributes to assesse pipeline’s using life, decrease energy dissipation and environmental pollution, which has high research value.
The high temperature high pressure reaction still was used in laboratory to simulate the scene operating mode condition. The corrosion rate of 16Mn pipe steel was measured in different typical sour crude oil under different transportation conditions. A corrosion rate database of pipeline was built when different kind of oil with different sulphur content and different acid number under different transportation temperature, different pressure and different speed of flow. The specimen surface appearance was observed through the scanning electronic microscope (SEM), and the ingredient of corrosion product on the test specimen surface was appraised through X-Ray Fluorescence Spectrometer(XRF). The qualitative analysis of corrosion product film was got through electro-chemical means and weight loss method in order to compare the corrosion product film under different situations. The pipeline’s corrosion disciplinarian was revealed combined with corrosion rate. The research shows that sulphur content and acid value was the main reasons of the internal corrosion, temperature and flow velocity was the secondary cause, and pressure had little influence on the corrosion rate; the more sulphur content was, the stronger the crude oil was within the limit of experimental condition; the pipeline’s corrosion rate increased obviously with the acid value increasing; the higher temperature was, the stronger corrosion product’s protectiveness became, and the bigger diffusion rate of all kinds of corrosive materials, and the latter effort fact was stronger than the former, so the pipeline’s corrosion rate increased with the temperature increasing; the dynamic crude oil had stronger corrosivity than static oil, and there was a maximum value according to certain flow velocity.
On the base of the corrosion rate database, a predict software for the remaining lifetime of pipeline was programmed using BP neural network. The corresponding economic loss of transportation sour crude oil was calculated according to related expense about pipeline's construction, operation and so on. The economic loss computation function was also developed in the software.
引文
[1]张文驹.国际石油市场变异与中国的能源战略[J].中国国土资源经济, 2009, 22(7): 4-9
[2]李兴,马源.美俄中东能源战略比较分析[J].国际观察, 2009, 1(40): 40-48
[3]贡璐,安尼瓦尔·阿木提,吕光辉,等.关于构建中国新疆与中亚能源战略通道的思考[J].新疆金融, 2009, 1(5): 27-29
[4]章远.我国能源战略若干问题的思考[J].中外能源, 2009, 14(7): 6-9
[5]汤一溉.再论中国通向中亚的石油天然气能源战略通道[J].干旱区地理, 2008, 31(4): 615-623
[6]董全庚,王西.论中国的能源战略决策[J].科技情报开发与经济, 2007, 17(3): 118-120
[7]张抗.石油进口大幅增长对我国经济发展的影响分析[J].中外能源, 2009, 14(8): 11-14
[8]悄勇.论石油与中国经济[J].知识经济, 2009, 1(5): 27
[9]黄健柏,江飞涛,陈伟刚.我国原油、成品油进口行为特征的实证研究[J].系统工程, 2007, 25(6): 84-88
[10]田春荣. 2006年中国石油进出口状况分析[J].国际石油经济, 2007, 15(3): 14-21
[11]黄璘.我国原油进口依存度增至55%能源安全加重[J].当代化工, 2008, 37(6): 646
[12]卜全民,温力,姜虹,等.炼制高硫原油对设备的腐蚀与安全对策[J].腐蚀科学与防护技术, 2002, 14(6): 362-364
[13]黄璘.新供应国的出现将改变中国原油进口格局[J].商业周刊, 2009, 1(5): 91
[14]刘树明,张亮,关凯书.渗铝钢耐饱和H2S溶液腐蚀的研究[J].腐蚀科学与防护技术, 2007, 19(5): 316-318
[15]李莉.输送含硫原油产生的腐蚀问题[J].油气储运, 2008, 27(5): 34
[16]田松柏,汪申.含硫原油腐蚀评价研究的进展[J].炼油设计, 2000, 30(7): 23-25
[17]G C Laredo, C R López, R Eálvarez, et al. Naphthenic acids, total acid number and sulfur content profile characterization in Isthmus and Maya crude oils[J]. Fuel, 2004, 83(11-12): 1689-1695
[18]雷阿利,冯拉俊,马小菊.几种不同材料在含硫介质中的腐蚀性[J].中国腐蚀与防护学报, 2007, 27(2): 65-69
[19]O Yépez. Influence of different sulfur compounds on corrosion due to naphthenic acid[J]. Fuel, 2005, 84(1): 97-104
[20]王永忠.原油管线腐蚀原因分析[J].石油化工安全技术, 2004, 20(4): 35-37
[21]王为民.国内外石油管道输送技术发展综述[J].管道技术与设备, 1997, 1(4): 4-8
[22]J L Kennedy. Oil and gas pipeline fundamentals[M]. South Sheridan: Pennwell Publishing Company, 1993: 3-6
[23]茹慧灵.油气管道保护技术[M].北京:石油工业出版社, 2008: 1-2
[24]袁方.成品油管道输送的优势及发展[J].石油库与加油站, 2006, 15(4): 37-39
[25]涂小华,王修杰.石油工业中管道的腐蚀与防腐[J].江西化工, 2006, 1(4): 266-267
[26]洪政甫,文学,吴巍,等.油气管道的腐蚀监测、检测及安全评估[J].全面腐蚀控制, 2004, 18(5): 34-36
[27]杨莜蘅.油气管道安全工程[J].北京:中国石化出版社, 2005: 4-1
[28]廖可喜.油气管道剩余寿命的预测[D].南充:西南石油大学, 2001: 4-12
[29]孔昭瑞.现代安全理念与油气管道的安全保障体系[J].油气储运, 2001, 20(8): 41-42
[30]严大凡,翁勇基,董少华.油气长输管道风险评价与完整性管理[M].北京:化学工业出版社, 2005: 45-53
[31]邓津洋,马夏康,引谢平.长输管道安全[M].北京:化学工业出版社, 2004: 68-69
[32]胡润宇,孙志刚,焦茗,等.长输管线防腐技术介绍[J].石油与装备, 2009, 1(4): 62-63
[33]陈静,贺三,袁宗明,等.管线钢应力腐蚀开裂[J].管道技术与设备, 2009, 1(1): 45-46
[34]张亮,李晓刚,杜翠薇,等.管线钢应力腐蚀影响因素的研究进展[J].腐蚀科学与防护技术, 2009, 21(1): 62-65
[35]杨建炜,张雷,丁睿明,等.管线钢在湿气介质中的H2S/CO2腐蚀行为研究[J].材料工程, 2008, 1(11): 49-53
[36]饶兴鹤.炼油厂工艺管线腐蚀失效及选材[J].石油化工腐蚀与防护, 2001, 18(5): 35-37
[37]贾思洋,孙成,王佳,等.剥离涂层下管线钢腐蚀研究进展[J].腐蚀科学与防护技术, 2007, 19(3): 211-214
[38]鲍庆春,徐辉.浅谈石油行业工业动火施工的危险性与安全监控[J].安全.健康和环境, 2002, 2(7): 17-18
[39]蓝于海,王晓云.输油管线工程地下水环境影响评价模型的应用研究[J].能源与环境, 2008, 1(6): 57-58
[40]陆仁艳,孙厚超.油气长输管道工程对沿线生态环境的影响及保护措施[J].能源与环境, 2008, 1(2): 85-87
[41]丁德武,赵杉林,张振华,等. Fe(OH)3的高温硫腐蚀产物氧化自燃性影响因素研究[J].腐蚀科学与防护技术, 2007, 19(3): 186-188
[42]李萍,翟玉春,李建东,等.含硫油品储罐腐蚀产物硫化亚铁自燃性的研究[J].腐蚀科学与防护技术, 2004, 16(6): 401
[43]P Li, J D Li, S L Zhao, et al. Research on the danger of fires in oil tanks[J]. Fire Safety Joumal, 2005, 40(5): 331
[44]张清,李全安,文九巴. CO2/H2S对油气管材的腐蚀规律及研究进展[J].腐蚀与防护, 2003, 24(7): 277-281
[45]杨波,田松柏,赵杉林.不同形态硫化合物腐蚀行为的研究[J].腐蚀科学与防护技术, 2004, 16(6): 385-388
[46]崔新安,贾鹏林.高硫原油加工过程中的腐蚀与防护[J].石油化工腐蚀与防护, 200l, 18(1): 1-10
[47]董绍平,张康达. 16MnR、316L钢在含硫原油中的腐蚀性研究[J].石油化工腐蚀与防护, 2001, 18(5): 54-57
[48]房丽华,孙世军.石油加工中的硫腐蚀与防护[J].辽宁化工, 2000, 29(4): 224-226
[49]林海潮,余家康.含硫原油炼制过程中活性硫腐蚀[J].腐蚀科学与防护技术, 2000, 12(6): 341-345
[50]王凤平,许适群.含硫原油加工过程中的硫腐蚀[J].石油化工腐蚀与防护, 2001, 18(6): 35-38
[51]黄靖国,刘小辉.常减压蒸馏装置的硫腐蚀问题及对策[J].石油化工腐蚀与防护, 2002, 19(3): 1-5
[52]寇杰,惠军福.流动腐蚀研究进展[J].油气田地面工程, 2007, 26(10): 4-5
[53]孙丽,李长俊,彭善碧,等. CO2腐蚀影响因素研究[J].管道技术与设备, 2008, 1(6): 35-37
[54]李春福,邓洪达,崔世华. NT80SS钢在高含H2S/CO2环境中的腐蚀行为[J].中国腐蚀与防护学报, 2009, 29(3): 225-229
[55]张中祥,孙冬柏,俞宏英,等. 16Mn钢在模拟油田采出介质中的腐蚀行为研究[J].材料保护, 2008, 41(1): 13-14
[56]张中祥,孙冬柏,俞宏英,等.油田采出液管道内壁流动腐蚀行为研究[J].管道技术与设备, 2007, 17(4): 39-40
[57]张雷,丁工,刘志德,等.温度对X65管线钢湿气CO2腐蚀的影响[J].石油与天然气化工, 2008, 37(1): 48-51
[58]刘志德,黄黎明,杨仲熙,等.高含硫环境中地面集输管线材质腐蚀影响因素[J].天然气工业, 2004, 24(12): 122-123
[59]李金波,左剑恶.温度和硫离子对N80钢CO2腐蚀电化学行为的影响[J].腐蚀科学与防护技术, 2009, 21(1): 44-47
[60]石振东,赵杉林,李萍,等.元素硫高温腐蚀产物氧化自燃性影响因素的研究[J].中国安全科学学报, 2008, 18(4): 151-156
[61]张爱显,朱庆云.常减压蒸馏装置高温部位的腐蚀与防护[J].腐蚀与防护, 2002, 23(8): 373-374
[62]孙召荣.关于锅炉受热面的低温硫腐蚀及其预防初探[J].科技情报开发与经济, 2008, 18(36): 176-177
[63]徐志达,单石灵.加工含硫原油的设备腐蚀与对策[J].腐蚀科学与防护技术, 2004, 16(4): 250-252
[64]高延敏,陈家坚.环烷酸和硫化氢腐蚀体系的热力学分析[J].中国腐蚀与防护学报, 1999, 19(6): 356-362
[65]高延敏,王文.有机酸对A3钢腐蚀的影响[J].腐蚀科学与防护技术, 2002, 14(6): 326-328
[66]曹玉亭,申海平.石油加工中的环烷酸腐蚀及其控制[J].腐蚀科学与防护技术, 2007, 19(1): 45-48
[67]叶荣.原油加工过程中氯化物腐蚀防治探讨[J].广东化工, 2006, 33(4): 9-12
[68]张鑫,张一凡,王世宏,等.氯及氯化物对设备的腐蚀及防护[J].石油化工设备, 2003, 32(5): 67-68
[69]刘伟明,张汉谦,屈朝霞,等.大型原油储罐用钢腐蚀性能的研究进展[J].腐蚀科学与防护技术, 2008, 20(6): 448-453
[70]S X Li, S R Yu, H L Zeng, et al. Predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model[J]. Journal of Petroleum Science and Engineering, 2009, 65(3-4): 162-166
[71]F Caleyo, J L González, J M Hallen. A study on the reliability assessment methodology for pipelines with active corrosion defects[J]. International Journal of Pressure Vessels and Piping, 2002, 79(1): 77-86
[72]S X Li, H L Zeng, S R Yu, et al. A method of probabilistic analysis for steel pipeline with correlated corrosion defects[J]. Corrosion Science, 2009, 51(12): 3050-3056
[73]M S G Chiodo, C Ruggieri. Failure assessments of corroded pipelines with axial defects using stress-based criteria: Numerical studies and verification analyses[J]. International Journal of Pressure Vessels and Piping, 2009, 86(2-3): 164-176
[74]A P Teixeira, C G Soares, T A Netto. Reliability of pipelines with corrosion defects[J]. International Journal of Pressure Vessels and Piping, 2008, 85(4): 228-237
[75]罗富绪.国外油气管道剩余使用寿命的预测和评估[J].油气储运, 2001, 20(1): 54-56
[76]M Ahammed, R E Melchers. Probabilistic analysis of underground pipelines subject to combined stresses and corrosion[J]. Engineering Structures, 1997, 19(12): 988-994
[77]A Cosham, P Hopkins, K A Macdonald. Best practice for the assessment of defects in pipelines-corrosion[J]. Engineering Failure Analysis, 2007, 14(7): 1245-1265
[78]李桂杰,柴艳丽.管道剩余使用寿命的预测和评估[J].国外油田工程, 2001, 17(8): 68
[79]杨静,马国光,张友波.含硫管道腐蚀预测方法[J].油气储运, 2006, 25(10): 55-58
[80]毕文军,王黎.油气管道的低周腐蚀疲劳研究及剩余寿命预测[J].腐蚀与防护, 2007, 28(5): 235-237
[81]郝芸,帅建,郭园.油气管道疲劳寿命预测[J].石油工业技术监督, 2008, 24(8): 35-36
[82]罗金恒,赵新伟,张华,等.腐蚀管道剩余寿命预测方法[J].管道技术与设备, 2006, 1(5): 37-39
[83]邱保文,袁泽喜,周桂峰.油气管线裂纹型缺陷的疲劳寿命预测[J].武汉科技大学学报:自然科学版, 2009, 32(3): 247-250
[84]廖柯熹,姚安林.长输管道失效保障树分析[J].长输管道失效保障树分析[J]. 2001, 20(1): 27-30
[85]莫剑.压力容器及管道剩余寿命的评估方法[J].化工装备技术, 2004, 25(5): 32-35
[86]周方勤.在役输气管道腐蚀剩余寿命预测技术研究[D].南充:西南石油大学, 2006: 28-50
[87]刘海峰,周方勤,罗文华,等.用概率统计分析压力管道最大腐蚀坑深研究[J].石油机械, 2003, 31(11): 14-17
[88]李鹤林,赵新伟,吉玲康.油气管道失效分析与完整性管理[J].油气储运, 2005, 24(12): 1-7
[89]俞树荣,李建华,李淑欣,等.埋地管道腐蚀剩余寿命预测概率模型[J].中国安全科学学报, 2008, 18(6): 11-15
[90]D J Haswell. The Pipeline Life Cycle[J]. Pipes and Pipelines International, 1999, 44 (6): 5-21
[91]赵金州,喻西崇,李长俊.缺陷管道适用性评价技术[M].北京:中国石化出版社, 2005: 42-45
[92]程远鹏,白羽,李小艳,等.埋地输油管道腐蚀剩余寿命预测[J].压力容器, 2009, 26(2): 30-34
[93]冯邵艳.哈萨克斯坦原油性质及加工方案研究[D].兰州:兰州大学, 2007: 10-19
[94]丁国平,刘秀清,郭志军.原油硫含量与馏分油的收率及硫分布的相关性研究[J].当代化工, 2008, 37(2): 142-145
[95]郁军荣.原油加工过程中硫分布的研究[J].石油化工技术经济, 2009, 25(1): 20-23
[96]冯邵艳.哈萨克斯坦原油性质及加工方案研究[D].兰州:兰州大学, 2007: 13-21
[97]别东生.含硫原油加工技术问答[M].北京:中国石化出版社, 2008: 1-9
[98]周仲柏,陈永言.电极过程动力学基础教程[M].武汉:武汉大学出版社, 1989: 177-179
[99]E Q Thomas, Y A Liu,查金荣,等.人工智能在化学工程中的应用[M].北京:中国石化出版社, 1994: 2-3
[100]张立明.人工神经网络的模型和应用[M].上海:复旦大学出版社, 1993: 98-227
[101]焦李成.神经网络计算[M].西安:西安电子科技大学出版社, 1993: 25-56
[102]周新,周露,李翔,等. Matlab神经网络仿真与应用[M].北京:科学出版社, 2003: 1-21
[103]徐秉挣,张百灵,韦岗.神经网络理论与应用[M].广州:华南理工出版社, 1994: 2-18
[104]蒋宗礼.人工神经网络导论[M].北京:高等教育出版社, 2001: 1-23
[105]H. Simon. Neural Networks: A Comprehensive Foundation[M]. Printice Hall, 1994: 2-15
[106]M Minsky, S Papert. Perceptrons[M]. MIT Press, 1969: 1-12
[107]聂永萍.人工神经网络与计算机[J].重庆邮电学院学报, 1998, 10(4): 33-86
[108]黄明智,马邕文,万金泉,等.污水处理中人工神经网络应用研究的探讨[J].环境科学与技术, 2008, 31(3): 131-135
[109]陈蕴博,左秀荣,王淼辉,等.人工神经网络在钢铁材料研究中的应用[J].材料导报, 2009, 23(7): 1-4
[110]庞春江,高婉青.基于模糊混沌神经网络的人脸识别算法[J].计算机应用, 2008, 28(6): 1549-1551
[111]夏远景,陈淑花,薛路舟,等.超高压处理牡蛎灭菌实验研究及人工神经网络模拟[J].现代食品科技, 2009, 25(5): 530-533
[112]李朝安.电力系统周负荷模型辨识和预报[J].中国电机工程学报, 1998, 8(3): 31-36
[113]L F Hoogerheide, J F Kaashoek, H K van Dijk. On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks[J]. Journal of Econometrics, 2007, 139(1): 154-180
[114]Z D Wang, Y R Liu, X H Liu. State estimation for jumping recurrent neural networks with discrete and distributed delays[J]. Neural Networks, 2009, 22(1): 41-48
[115]S Ghosh-Dastidar, H Adeli. A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection[J]. Neural Networks, 2009, 22(10): 1419-1431
[116]R Setiono, B Baesens, C Mues. A note on knowledge discovery using neural networks and its application to credit card screening[J]. European Journal of Operational Research, 2009, 192(1): 326-332
[117]L J Lancashire, C Lemetre, G R Ball. An introduction to artificial neural networks in bioinformatics-application to complex microarray and mass spectrometry datasets in cancer studies[J]. Briefings in Bioinformatics, 2009, 10(3): 315-329
[118]D Shanthi, Z G Sahoo, N Saravanan. Evolving connection weights of artificial neural networks using genetic algorithm with application to the prediction of stroke disease[J]. International Journal of Soft Computing, 2009, 4(2): 95-102
[119]A Elshafie, O Karim, M R Taha. Non-Linear Prediction Model for Scour and Air Entrainment Based Static Neural Network Approach[J]. European Journal of Scientific Research, 2009, 27(3): 400-416
[120]M Torres, C Hervás, C García. Multinomial logistic regression and product unit neural network models: Application of a new hybrid methodology for solving a classification problem in the livestock sector[J]. Expert Systems with Applications, 2009, 36(10): 12225-12235
[121]L E Besaw, D M Rizzo, M Kline, et al. Stream classification using hierarchical artificial neural networks: A fluvial hazard management tool[J]. Journal of Hydrology, 2009, 373(1-2): 34-43
[122]J F Mas, J J Flores. The application of artificial neural networks to the analysis of remotely sensed data[J]. International Journal of Remote Sensing, 2008, 29(3): 617-663
[123]张立明.人工神经网络的模型和应用[M].上海:复旦大学出版社, 1993: 98-227
[124]闻新,周露,王丹力,等. MATLAB神经网络应用设计[M].北京:科学出版社, 2000, 210-225
[2]李兴,马源.美俄中东能源战略比较分析[J].国际观察, 2009, 1(40): 40-48
[3]贡璐,安尼瓦尔·阿木提,吕光辉,等.关于构建中国新疆与中亚能源战略通道的思考[J].新疆金融, 2009, 1(5): 27-29
[4]章远.我国能源战略若干问题的思考[J].中外能源, 2009, 14(7): 6-9
[5]汤一溉.再论中国通向中亚的石油天然气能源战略通道[J].干旱区地理, 2008, 31(4): 615-623
[6]董全庚,王西.论中国的能源战略决策[J].科技情报开发与经济, 2007, 17(3): 118-120
[7]张抗.石油进口大幅增长对我国经济发展的影响分析[J].中外能源, 2009, 14(8): 11-14
[8]悄勇.论石油与中国经济[J].知识经济, 2009, 1(5): 27
[9]黄健柏,江飞涛,陈伟刚.我国原油、成品油进口行为特征的实证研究[J].系统工程, 2007, 25(6): 84-88
[10]田春荣. 2006年中国石油进出口状况分析[J].国际石油经济, 2007, 15(3): 14-21
[11]黄璘.我国原油进口依存度增至55%能源安全加重[J].当代化工, 2008, 37(6): 646
[12]卜全民,温力,姜虹,等.炼制高硫原油对设备的腐蚀与安全对策[J].腐蚀科学与防护技术, 2002, 14(6): 362-364
[13]黄璘.新供应国的出现将改变中国原油进口格局[J].商业周刊, 2009, 1(5): 91
[14]刘树明,张亮,关凯书.渗铝钢耐饱和H2S溶液腐蚀的研究[J].腐蚀科学与防护技术, 2007, 19(5): 316-318
[15]李莉.输送含硫原油产生的腐蚀问题[J].油气储运, 2008, 27(5): 34
[16]田松柏,汪申.含硫原油腐蚀评价研究的进展[J].炼油设计, 2000, 30(7): 23-25
[17]G C Laredo, C R López, R Eálvarez, et al. Naphthenic acids, total acid number and sulfur content profile characterization in Isthmus and Maya crude oils[J]. Fuel, 2004, 83(11-12): 1689-1695
[18]雷阿利,冯拉俊,马小菊.几种不同材料在含硫介质中的腐蚀性[J].中国腐蚀与防护学报, 2007, 27(2): 65-69
[19]O Yépez. Influence of different sulfur compounds on corrosion due to naphthenic acid[J]. Fuel, 2005, 84(1): 97-104
[20]王永忠.原油管线腐蚀原因分析[J].石油化工安全技术, 2004, 20(4): 35-37
[21]王为民.国内外石油管道输送技术发展综述[J].管道技术与设备, 1997, 1(4): 4-8
[22]J L Kennedy. Oil and gas pipeline fundamentals[M]. South Sheridan: Pennwell Publishing Company, 1993: 3-6
[23]茹慧灵.油气管道保护技术[M].北京:石油工业出版社, 2008: 1-2
[24]袁方.成品油管道输送的优势及发展[J].石油库与加油站, 2006, 15(4): 37-39
[25]涂小华,王修杰.石油工业中管道的腐蚀与防腐[J].江西化工, 2006, 1(4): 266-267
[26]洪政甫,文学,吴巍,等.油气管道的腐蚀监测、检测及安全评估[J].全面腐蚀控制, 2004, 18(5): 34-36
[27]杨莜蘅.油气管道安全工程[J].北京:中国石化出版社, 2005: 4-1
[28]廖可喜.油气管道剩余寿命的预测[D].南充:西南石油大学, 2001: 4-12
[29]孔昭瑞.现代安全理念与油气管道的安全保障体系[J].油气储运, 2001, 20(8): 41-42
[30]严大凡,翁勇基,董少华.油气长输管道风险评价与完整性管理[M].北京:化学工业出版社, 2005: 45-53
[31]邓津洋,马夏康,引谢平.长输管道安全[M].北京:化学工业出版社, 2004: 68-69
[32]胡润宇,孙志刚,焦茗,等.长输管线防腐技术介绍[J].石油与装备, 2009, 1(4): 62-63
[33]陈静,贺三,袁宗明,等.管线钢应力腐蚀开裂[J].管道技术与设备, 2009, 1(1): 45-46
[34]张亮,李晓刚,杜翠薇,等.管线钢应力腐蚀影响因素的研究进展[J].腐蚀科学与防护技术, 2009, 21(1): 62-65
[35]杨建炜,张雷,丁睿明,等.管线钢在湿气介质中的H2S/CO2腐蚀行为研究[J].材料工程, 2008, 1(11): 49-53
[36]饶兴鹤.炼油厂工艺管线腐蚀失效及选材[J].石油化工腐蚀与防护, 2001, 18(5): 35-37
[37]贾思洋,孙成,王佳,等.剥离涂层下管线钢腐蚀研究进展[J].腐蚀科学与防护技术, 2007, 19(3): 211-214
[38]鲍庆春,徐辉.浅谈石油行业工业动火施工的危险性与安全监控[J].安全.健康和环境, 2002, 2(7): 17-18
[39]蓝于海,王晓云.输油管线工程地下水环境影响评价模型的应用研究[J].能源与环境, 2008, 1(6): 57-58
[40]陆仁艳,孙厚超.油气长输管道工程对沿线生态环境的影响及保护措施[J].能源与环境, 2008, 1(2): 85-87
[41]丁德武,赵杉林,张振华,等. Fe(OH)3的高温硫腐蚀产物氧化自燃性影响因素研究[J].腐蚀科学与防护技术, 2007, 19(3): 186-188
[42]李萍,翟玉春,李建东,等.含硫油品储罐腐蚀产物硫化亚铁自燃性的研究[J].腐蚀科学与防护技术, 2004, 16(6): 401
[43]P Li, J D Li, S L Zhao, et al. Research on the danger of fires in oil tanks[J]. Fire Safety Joumal, 2005, 40(5): 331
[44]张清,李全安,文九巴. CO2/H2S对油气管材的腐蚀规律及研究进展[J].腐蚀与防护, 2003, 24(7): 277-281
[45]杨波,田松柏,赵杉林.不同形态硫化合物腐蚀行为的研究[J].腐蚀科学与防护技术, 2004, 16(6): 385-388
[46]崔新安,贾鹏林.高硫原油加工过程中的腐蚀与防护[J].石油化工腐蚀与防护, 200l, 18(1): 1-10
[47]董绍平,张康达. 16MnR、316L钢在含硫原油中的腐蚀性研究[J].石油化工腐蚀与防护, 2001, 18(5): 54-57
[48]房丽华,孙世军.石油加工中的硫腐蚀与防护[J].辽宁化工, 2000, 29(4): 224-226
[49]林海潮,余家康.含硫原油炼制过程中活性硫腐蚀[J].腐蚀科学与防护技术, 2000, 12(6): 341-345
[50]王凤平,许适群.含硫原油加工过程中的硫腐蚀[J].石油化工腐蚀与防护, 2001, 18(6): 35-38
[51]黄靖国,刘小辉.常减压蒸馏装置的硫腐蚀问题及对策[J].石油化工腐蚀与防护, 2002, 19(3): 1-5
[52]寇杰,惠军福.流动腐蚀研究进展[J].油气田地面工程, 2007, 26(10): 4-5
[53]孙丽,李长俊,彭善碧,等. CO2腐蚀影响因素研究[J].管道技术与设备, 2008, 1(6): 35-37
[54]李春福,邓洪达,崔世华. NT80SS钢在高含H2S/CO2环境中的腐蚀行为[J].中国腐蚀与防护学报, 2009, 29(3): 225-229
[55]张中祥,孙冬柏,俞宏英,等. 16Mn钢在模拟油田采出介质中的腐蚀行为研究[J].材料保护, 2008, 41(1): 13-14
[56]张中祥,孙冬柏,俞宏英,等.油田采出液管道内壁流动腐蚀行为研究[J].管道技术与设备, 2007, 17(4): 39-40
[57]张雷,丁工,刘志德,等.温度对X65管线钢湿气CO2腐蚀的影响[J].石油与天然气化工, 2008, 37(1): 48-51
[58]刘志德,黄黎明,杨仲熙,等.高含硫环境中地面集输管线材质腐蚀影响因素[J].天然气工业, 2004, 24(12): 122-123
[59]李金波,左剑恶.温度和硫离子对N80钢CO2腐蚀电化学行为的影响[J].腐蚀科学与防护技术, 2009, 21(1): 44-47
[60]石振东,赵杉林,李萍,等.元素硫高温腐蚀产物氧化自燃性影响因素的研究[J].中国安全科学学报, 2008, 18(4): 151-156
[61]张爱显,朱庆云.常减压蒸馏装置高温部位的腐蚀与防护[J].腐蚀与防护, 2002, 23(8): 373-374
[62]孙召荣.关于锅炉受热面的低温硫腐蚀及其预防初探[J].科技情报开发与经济, 2008, 18(36): 176-177
[63]徐志达,单石灵.加工含硫原油的设备腐蚀与对策[J].腐蚀科学与防护技术, 2004, 16(4): 250-252
[64]高延敏,陈家坚.环烷酸和硫化氢腐蚀体系的热力学分析[J].中国腐蚀与防护学报, 1999, 19(6): 356-362
[65]高延敏,王文.有机酸对A3钢腐蚀的影响[J].腐蚀科学与防护技术, 2002, 14(6): 326-328
[66]曹玉亭,申海平.石油加工中的环烷酸腐蚀及其控制[J].腐蚀科学与防护技术, 2007, 19(1): 45-48
[67]叶荣.原油加工过程中氯化物腐蚀防治探讨[J].广东化工, 2006, 33(4): 9-12
[68]张鑫,张一凡,王世宏,等.氯及氯化物对设备的腐蚀及防护[J].石油化工设备, 2003, 32(5): 67-68
[69]刘伟明,张汉谦,屈朝霞,等.大型原油储罐用钢腐蚀性能的研究进展[J].腐蚀科学与防护技术, 2008, 20(6): 448-453
[70]S X Li, S R Yu, H L Zeng, et al. Predicting corrosion remaining life of underground pipelines with a mechanically-based probabilistic model[J]. Journal of Petroleum Science and Engineering, 2009, 65(3-4): 162-166
[71]F Caleyo, J L González, J M Hallen. A study on the reliability assessment methodology for pipelines with active corrosion defects[J]. International Journal of Pressure Vessels and Piping, 2002, 79(1): 77-86
[72]S X Li, H L Zeng, S R Yu, et al. A method of probabilistic analysis for steel pipeline with correlated corrosion defects[J]. Corrosion Science, 2009, 51(12): 3050-3056
[73]M S G Chiodo, C Ruggieri. Failure assessments of corroded pipelines with axial defects using stress-based criteria: Numerical studies and verification analyses[J]. International Journal of Pressure Vessels and Piping, 2009, 86(2-3): 164-176
[74]A P Teixeira, C G Soares, T A Netto. Reliability of pipelines with corrosion defects[J]. International Journal of Pressure Vessels and Piping, 2008, 85(4): 228-237
[75]罗富绪.国外油气管道剩余使用寿命的预测和评估[J].油气储运, 2001, 20(1): 54-56
[76]M Ahammed, R E Melchers. Probabilistic analysis of underground pipelines subject to combined stresses and corrosion[J]. Engineering Structures, 1997, 19(12): 988-994
[77]A Cosham, P Hopkins, K A Macdonald. Best practice for the assessment of defects in pipelines-corrosion[J]. Engineering Failure Analysis, 2007, 14(7): 1245-1265
[78]李桂杰,柴艳丽.管道剩余使用寿命的预测和评估[J].国外油田工程, 2001, 17(8): 68
[79]杨静,马国光,张友波.含硫管道腐蚀预测方法[J].油气储运, 2006, 25(10): 55-58
[80]毕文军,王黎.油气管道的低周腐蚀疲劳研究及剩余寿命预测[J].腐蚀与防护, 2007, 28(5): 235-237
[81]郝芸,帅建,郭园.油气管道疲劳寿命预测[J].石油工业技术监督, 2008, 24(8): 35-36
[82]罗金恒,赵新伟,张华,等.腐蚀管道剩余寿命预测方法[J].管道技术与设备, 2006, 1(5): 37-39
[83]邱保文,袁泽喜,周桂峰.油气管线裂纹型缺陷的疲劳寿命预测[J].武汉科技大学学报:自然科学版, 2009, 32(3): 247-250
[84]廖柯熹,姚安林.长输管道失效保障树分析[J].长输管道失效保障树分析[J]. 2001, 20(1): 27-30
[85]莫剑.压力容器及管道剩余寿命的评估方法[J].化工装备技术, 2004, 25(5): 32-35
[86]周方勤.在役输气管道腐蚀剩余寿命预测技术研究[D].南充:西南石油大学, 2006: 28-50
[87]刘海峰,周方勤,罗文华,等.用概率统计分析压力管道最大腐蚀坑深研究[J].石油机械, 2003, 31(11): 14-17
[88]李鹤林,赵新伟,吉玲康.油气管道失效分析与完整性管理[J].油气储运, 2005, 24(12): 1-7
[89]俞树荣,李建华,李淑欣,等.埋地管道腐蚀剩余寿命预测概率模型[J].中国安全科学学报, 2008, 18(6): 11-15
[90]D J Haswell. The Pipeline Life Cycle[J]. Pipes and Pipelines International, 1999, 44 (6): 5-21
[91]赵金州,喻西崇,李长俊.缺陷管道适用性评价技术[M].北京:中国石化出版社, 2005: 42-45
[92]程远鹏,白羽,李小艳,等.埋地输油管道腐蚀剩余寿命预测[J].压力容器, 2009, 26(2): 30-34
[93]冯邵艳.哈萨克斯坦原油性质及加工方案研究[D].兰州:兰州大学, 2007: 10-19
[94]丁国平,刘秀清,郭志军.原油硫含量与馏分油的收率及硫分布的相关性研究[J].当代化工, 2008, 37(2): 142-145
[95]郁军荣.原油加工过程中硫分布的研究[J].石油化工技术经济, 2009, 25(1): 20-23
[96]冯邵艳.哈萨克斯坦原油性质及加工方案研究[D].兰州:兰州大学, 2007: 13-21
[97]别东生.含硫原油加工技术问答[M].北京:中国石化出版社, 2008: 1-9
[98]周仲柏,陈永言.电极过程动力学基础教程[M].武汉:武汉大学出版社, 1989: 177-179
[99]E Q Thomas, Y A Liu,查金荣,等.人工智能在化学工程中的应用[M].北京:中国石化出版社, 1994: 2-3
[100]张立明.人工神经网络的模型和应用[M].上海:复旦大学出版社, 1993: 98-227
[101]焦李成.神经网络计算[M].西安:西安电子科技大学出版社, 1993: 25-56
[102]周新,周露,李翔,等. Matlab神经网络仿真与应用[M].北京:科学出版社, 2003: 1-21
[103]徐秉挣,张百灵,韦岗.神经网络理论与应用[M].广州:华南理工出版社, 1994: 2-18
[104]蒋宗礼.人工神经网络导论[M].北京:高等教育出版社, 2001: 1-23
[105]H. Simon. Neural Networks: A Comprehensive Foundation[M]. Printice Hall, 1994: 2-15
[106]M Minsky, S Papert. Perceptrons[M]. MIT Press, 1969: 1-12
[107]聂永萍.人工神经网络与计算机[J].重庆邮电学院学报, 1998, 10(4): 33-86
[108]黄明智,马邕文,万金泉,等.污水处理中人工神经网络应用研究的探讨[J].环境科学与技术, 2008, 31(3): 131-135
[109]陈蕴博,左秀荣,王淼辉,等.人工神经网络在钢铁材料研究中的应用[J].材料导报, 2009, 23(7): 1-4
[110]庞春江,高婉青.基于模糊混沌神经网络的人脸识别算法[J].计算机应用, 2008, 28(6): 1549-1551
[111]夏远景,陈淑花,薛路舟,等.超高压处理牡蛎灭菌实验研究及人工神经网络模拟[J].现代食品科技, 2009, 25(5): 530-533
[112]李朝安.电力系统周负荷模型辨识和预报[J].中国电机工程学报, 1998, 8(3): 31-36
[113]L F Hoogerheide, J F Kaashoek, H K van Dijk. On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks[J]. Journal of Econometrics, 2007, 139(1): 154-180
[114]Z D Wang, Y R Liu, X H Liu. State estimation for jumping recurrent neural networks with discrete and distributed delays[J]. Neural Networks, 2009, 22(1): 41-48
[115]S Ghosh-Dastidar, H Adeli. A new supervised learning algorithm for multiple spiking neural networks with application in epilepsy and seizure detection[J]. Neural Networks, 2009, 22(10): 1419-1431
[116]R Setiono, B Baesens, C Mues. A note on knowledge discovery using neural networks and its application to credit card screening[J]. European Journal of Operational Research, 2009, 192(1): 326-332
[117]L J Lancashire, C Lemetre, G R Ball. An introduction to artificial neural networks in bioinformatics-application to complex microarray and mass spectrometry datasets in cancer studies[J]. Briefings in Bioinformatics, 2009, 10(3): 315-329
[118]D Shanthi, Z G Sahoo, N Saravanan. Evolving connection weights of artificial neural networks using genetic algorithm with application to the prediction of stroke disease[J]. International Journal of Soft Computing, 2009, 4(2): 95-102
[119]A Elshafie, O Karim, M R Taha. Non-Linear Prediction Model for Scour and Air Entrainment Based Static Neural Network Approach[J]. European Journal of Scientific Research, 2009, 27(3): 400-416
[120]M Torres, C Hervás, C García. Multinomial logistic regression and product unit neural network models: Application of a new hybrid methodology for solving a classification problem in the livestock sector[J]. Expert Systems with Applications, 2009, 36(10): 12225-12235
[121]L E Besaw, D M Rizzo, M Kline, et al. Stream classification using hierarchical artificial neural networks: A fluvial hazard management tool[J]. Journal of Hydrology, 2009, 373(1-2): 34-43
[122]J F Mas, J J Flores. The application of artificial neural networks to the analysis of remotely sensed data[J]. International Journal of Remote Sensing, 2008, 29(3): 617-663
[123]张立明.人工神经网络的模型和应用[M].上海:复旦大学出版社, 1993: 98-227
[124]闻新,周露,王丹力,等. MATLAB神经网络应用设计[M].北京:科学出版社, 2000, 210-225
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