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This research conducted an experiment on DNAPL contamination in a saturated porous medium within a three-dimensional sandbox and performed synchronized dynamic monitoring using electrical resistivity tomography(ERT). The resistivity images obtained from ERT were used to determine the spatial distribution of DNAPL contaminants, which were then compared with the numerical simulation model established in the sandbox experiment. The absolute value of the relative error in the diameter of the DNAPL distribution area obtained from the numerical simulation and the DNAPL distribution area determined by the ERT monitoring ranged from 2.00% to 27.50% across different spatial locations. The absolute value of the relative error in the diameter of the DNAPL distribution area obtained from the numerical simulation and the DNAPL distribution area determined by the ERT monitoring ranged from 2.7% to 40.58% at different time points. The results demonstrate the feasibility of using the numerical simulation software Petrasim to predict the distribution range of DNAPL contamination in saturated sandy soil.

, correspAuthors=Han-le LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jun-jie JIANG, Wen-han CAO, Han-le LIU), CN=ArticleExt(id=1241057231865704803, articleId=1241057224466952964, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=三维砂槽中DNAPL入渗过程电阻率成像及数值模拟, columnId=1234106386565624579, journalTitle=中国环境科学, columnName=水污染与控制, runingTitle=null, highlight=null, articleAbstract=

在三维砂箱中进行了饱和多孔介质中重非水相液体(DNAPL)的污染实验,并利用电阻率成像法(ERT)进行了同步的动态监测,获得DNAPL污染物空间分布的电阻率变化值图像,再根据砂箱实验建立数值模拟模型,与ERT测得的电阻率结果进行对比验证.结果表明:在不同空间上由数值模拟得到DNAPL污染物分布区域与ERT监测圈定的DNAPL污染物分布区域范围直径相对误差的绝对值为2.00%~27.50%.在不同时间点上由数值模拟得到DNAPL污染物分布区域与ERT监测圈定的DNAPL污染物分布区域范围直径相对误差的绝对值为2.7%~40.58%.结果说明了Petrasim程序预测三维饱和砂土中DNAPL污染分布范围的可行性.

, correspAuthors=刘汉乐, authorNote=null, correspAuthorsNote=
* 责任作者,教授,
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蒋俊杰(1999-),男,广西桂林人,桂林理工大学硕士研究生,主要从事砂土有机污染修复研究.发表论文1篇..

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蒋俊杰(1999-),男,广西桂林人,桂林理工大学硕士研究生,主要从事砂土有机污染修复研究.发表论文1篇..

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蒋俊杰(1999-),男,广西桂林人,桂林理工大学硕士研究生,主要从事砂土有机污染修复研究.发表论文1篇..

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tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, orderNo=2, keyword=电阻率成像), Keyword(id=1241057235799962239, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, orderNo=3, keyword=饱和砂土), Keyword(id=1241057235955151502, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, orderNo=4, keyword=数值模拟)], refs=[Reference(id=1241057241059619764, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, doi=null, pmid=null, pmcid=null, year=2019, volume=375, issue=null, pageStart=233, pageEnd=240, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=Engelmann C, Händel F, Binder M, journalName=Journal of Hazardous Materials, refType=null, unstructuredReference=Engelmann CHändel FBinder M,et al. 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Water Resources Research202157(11). e2021WR031366., articleTitle=Mapping and monitoring of DNAPL source zones with combined direct current resistivity and induced polarization: A field-Scale numerical investigation, refAbstract=null)], funds=[Fund(id=1241057240724075422, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, awardId=42277192, language=CN, fundingSource=国家自然科学基金资助项目(42277192), fundOrder=null, country=null), Fund(id=1241057240862487464, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, awardId=null, language=CN, fundingSource=第三期广西高等学校千名中青年骨干教师培养计划, fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241057232230609298, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, xref=null, ext=[AuthorCompanyExt(id=1241057232251580820, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, companyId=1241057232230609298, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Engineering Research Center of Watershed Protection and Green Development, Guangxi Key Laboratory of Environmental Contaminant Control Theory and Technology, Guilin University of Technology, Guilin 541006, China), AuthorCompanyExt(id=1241057232276746650, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, companyId=1241057232230609298, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=桂林理工大学,广西环境污染控制理论与技术重点实验室,流域保护与绿色发展广西高校工程研究中心,广西 桂林 541006)])], figs=[ArticleFig(id=1241057236173255338, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Fig.1, caption=Schematic diagram of the three-dimensional sandbox model set-up, figureFileSmall=r5yxp1GOyroywsqWe+SFlw==, figureFileBig=D8GeLVslEKzqj3sPDlVo7g==, tableContent=null), ArticleFig(id=1241057236492022454, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=图1, caption=三维砂箱实验示意, figureFileSmall=r5yxp1GOyroywsqWe+SFlw==, figureFileBig=D8GeLVslEKzqj3sPDlVo7g==, tableContent=null), ArticleFig(id=1241057236768846545, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Fig.2, caption=Schematic diagram of electrode measuring points, figureFileSmall=aofDy2k02WzMRHeVR8Kc3A==, figureFileBig=FvRB4jOHoeQA1Xlz8G2D6Q==, tableContent=null), ArticleFig(id=1241057236873704156, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=图2, caption=电极测点示意, figureFileSmall=aofDy2k02WzMRHeVR8Kc3A==, figureFileBig=FvRB4jOHoeQA1Xlz8G2D6Q==, tableContent=null), ArticleFig(id=1241057236999533285, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Fig.3, caption=Comparison of resistance change value image in the z-direction with the simulated DNAPL saturation image at 420min, figureFileSmall=cfTaK7Jbopy0Hx+gEhnGcg==, figureFileBig=ViywTTwnFgg13+Qr/IvqLA==, tableContent=null), ArticleFig(id=1241057237133751021, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=图3, caption=420min时z方向上电阻率变化值图像与模拟的DNAPL饱和度图像对比, figureFileSmall=cfTaK7Jbopy0Hx+gEhnGcg==, figureFileBig=ViywTTwnFgg13+Qr/IvqLA==, tableContent=null), ArticleFig(id=1241057237280551673, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Fig.4, caption=Schematic diagram of sand box section line, figureFileSmall=PaZgzP/iGEgdIAoi1V7OAQ==, figureFileBig=gA/XQ4vWp+TijBvbRzGbQQ==, tableContent=null), ArticleFig(id=1241057237418963719, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=图4, caption=砂箱剖面线示意, figureFileSmall=PaZgzP/iGEgdIAoi1V7OAQ==, figureFileBig=gA/XQ4vWp+TijBvbRzGbQQ==, tableContent=null), ArticleFig(id=1241057237532209938, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Fig.5, caption=Comparison chart of resistance change value and saturation values on the profile line, figureFileSmall=J2awcZlhQLaqoV67q2xJOQ==, figureFileBig=cdrSAJjkiSDhFiZ838AeMg==, tableContent=null), ArticleFig(id=1241057237733536546, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=图5, caption=剖面线上电阻率变化值与饱和度值对比

(a)横剖面线x=0.5m,z=0.05m;(b)横剖面线x=0.5m,z=0.15m;(c)横剖面线x=0.5m,z=0.25m;(d)纵剖面线y=0.4m,z=0.05m;(e)纵剖面线y=0.4m,z=0.15m;(f)纵剖面线y=0.4m,z=0.25m

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(a)横剖面线a-a1;(b)纵剖面线b-b1

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Main parameters in numerical model

, figureFileSmall=null, figureFileBig=null, tableContent=
孔隙度饱和渗透率(m2颗粒比重相对渗透率函数Stone模型毛管压力Parker模型
SwrSnrSgrn1Smn2agnanw
0.367.8×10-1118600.10.020.0130.11.510050
), ArticleFig(id=1241057240061375343, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=表1, caption=

数值模型中主要参数

, figureFileSmall=null, figureFileBig=null, tableContent=
孔隙度饱和渗透率(m2颗粒比重相对渗透率函数Stone模型毛管压力Parker模型
SwrSnrSgrn1Smn2agnanw
0.367.8×10-1118600.10.020.0130.11.510050
), ArticleFig(id=1241057240199787382, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Table 2, caption=

Comparison of pollution zone diameters determined by resistance change value and saturation on the profile line at t=420min

, figureFileSmall=null, figureFileBig=null, tableContent=
z深度(m)剖面线电阻率变化值二阶导确定污染区直径Dρ(m)模拟饱和度确定污染区直径DH(m)绝对误差(m)相对误差(%)
0.05x=0.5m0.500.510.012.00
0.05y=0.4m0.400.510.1127.50
0.15x=0.5m0.470.480.012.13
0.15y=0.4m0.460.480.024.35
0.25x=0.5m0.480.44-0.04-8.33
0.25y=0.4m0.510.42-0.09-17.65
), ArticleFig(id=1241057240304644988, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=表2, caption=

t=420min时剖面线上电阻率变化值和饱和度确定的污染区直径对比

, figureFileSmall=null, figureFileBig=null, tableContent=
z深度(m)剖面线电阻率变化值二阶导确定污染区直径Dρ(m)模拟饱和度确定污染区直径DH(m)绝对误差(m)相对误差(%)
0.05x=0.5m0.500.510.012.00
0.05y=0.4m0.400.510.1127.50
0.15x=0.5m0.470.480.012.13
0.15y=0.4m0.460.480.024.35
0.25x=0.5m0.480.44-0.04-8.33
0.25y=0.4m0.510.42-0.09-17.65
), ArticleFig(id=1241057240430474118, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=EN, label=Table 3, caption=

Comparison of pollution zone diameters determined by resistance change value and saturation on the profile line(z=0.05m)

, figureFileSmall=null, figureFileBig=null, tableContent=
时间(min)剖面线电阻率二阶导数Dρ(m)模拟污染物范围DH(m)绝对误差(m)相对误差(%)
60x=0.5m0.360.32-0.04-11.11
60y=0.4m0.480.33-0.15-31.35
120x=0.5m0.370.380.012.7
120y=0.4m0.690.41-0.28-40.58
180x=0.5m0.420.440.024.76
180y=0.4m0.620.44-0.18-29.03
240x=0.5m0.510.44-0.07-13.73
240y=0.4m0.440.460.024.55
300x=0.5m0.410.480.0717.07
300y=0.4m0.450.480.036.67
360x=0.5m0.490.48-0.01-2.04
360y=0.4m0.390.490.125.64
), ArticleFig(id=1241057240560497553, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057224466952964, language=CN, label=表3, caption=

剖面线上电阻率变化值和饱和度确定的污染区直径对比(z=0.05m)

, figureFileSmall=null, figureFileBig=null, tableContent=
时间(min)剖面线电阻率二阶导数Dρ(m)模拟污染物范围DH(m)绝对误差(m)相对误差(%)
60x=0.5m0.360.32-0.04-11.11
60y=0.4m0.480.33-0.15-31.35
120x=0.5m0.370.380.012.7
120y=0.4m0.690.41-0.28-40.58
180x=0.5m0.420.440.024.76
180y=0.4m0.620.44-0.18-29.03
240x=0.5m0.510.44-0.07-13.73
240y=0.4m0.440.460.024.55
300x=0.5m0.410.480.0717.07
300y=0.4m0.450.480.036.67
360x=0.5m0.490.48-0.01-2.04
360y=0.4m0.390.490.125.64
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三维砂槽中DNAPL入渗过程电阻率成像及数值模拟
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蒋俊杰 , 曹文翰 , 刘汉乐 *
中国环境科学 | 水污染与控制 2025,45(5): 2513-2519
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中国环境科学 | 水污染与控制 2025, 45(5): 2513-2519
三维砂槽中DNAPL入渗过程电阻率成像及数值模拟
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蒋俊杰 , 曹文翰, 刘汉乐*
作者信息
  • 桂林理工大学,广西环境污染控制理论与技术重点实验室,流域保护与绿色发展广西高校工程研究中心,广西 桂林 541006
  • 蒋俊杰(1999-),男,广西桂林人,桂林理工大学硕士研究生,主要从事砂土有机污染修复研究.发表论文1篇..

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* 责任作者,教授,
Electrical resistivity tomography and numerical simulation of DNAPL infiltration process in three-dimensional sand box
Jun-jie JIANG , Wen-han CAO, Han-le LIU*
Affiliations
  • Engineering Research Center of Watershed Protection and Green Development, Guangxi Key Laboratory of Environmental Contaminant Control Theory and Technology, Guilin University of Technology, Guilin 541006, China
出版时间: 2025-05-20
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在三维砂箱中进行了饱和多孔介质中重非水相液体(DNAPL)的污染实验,并利用电阻率成像法(ERT)进行了同步的动态监测,获得DNAPL污染物空间分布的电阻率变化值图像,再根据砂箱实验建立数值模拟模型,与ERT测得的电阻率结果进行对比验证.结果表明:在不同空间上由数值模拟得到DNAPL污染物分布区域与ERT监测圈定的DNAPL污染物分布区域范围直径相对误差的绝对值为2.00%~27.50%.在不同时间点上由数值模拟得到DNAPL污染物分布区域与ERT监测圈定的DNAPL污染物分布区域范围直径相对误差的绝对值为2.7%~40.58%.结果说明了Petrasim程序预测三维饱和砂土中DNAPL污染分布范围的可行性.

重非水相液体  /  电阻率成像  /  饱和砂土  /  数值模拟

This research conducted an experiment on DNAPL contamination in a saturated porous medium within a three-dimensional sandbox and performed synchronized dynamic monitoring using electrical resistivity tomography(ERT). The resistivity images obtained from ERT were used to determine the spatial distribution of DNAPL contaminants, which were then compared with the numerical simulation model established in the sandbox experiment. The absolute value of the relative error in the diameter of the DNAPL distribution area obtained from the numerical simulation and the DNAPL distribution area determined by the ERT monitoring ranged from 2.00% to 27.50% across different spatial locations. The absolute value of the relative error in the diameter of the DNAPL distribution area obtained from the numerical simulation and the DNAPL distribution area determined by the ERT monitoring ranged from 2.7% to 40.58% at different time points. The results demonstrate the feasibility of using the numerical simulation software Petrasim to predict the distribution range of DNAPL contamination in saturated sandy soil.

DNAPL  /  electrical resistivity tomography  /  saturated sand  /  numerical simulation
蒋俊杰, 曹文翰, 刘汉乐. 三维砂槽中DNAPL入渗过程电阻率成像及数值模拟. 中国环境科学, 2025 , 45 (5) : 2513 -2519 .
Jun-jie JIANG, Wen-han CAO, Han-le LIU. Electrical resistivity tomography and numerical simulation of DNAPL infiltration process in three-dimensional sand box[J]. China Environmental Science, 2025 , 45 (5) : 2513 -2519 .
随着有机化合物在工业中的广泛应用,越来越多的重非水相液体(DNAPL)在有机物的释放和运输过程中进入土壤和地下水环境,造成了严重的环境污染问题[1].DNAPL由于其特殊的物理性质和化学性质[2],到达并聚积在底部基岩上形成污染池,成为稳定的长期污染源[3],因此,对地下水中DNAPL监测的研究得到国内外学者的广泛重视[4].由于野外复杂地质条件的不确定性,国内外大部分对DNAPL的研究都在实验室尺度下二维砂箱中进行[5-10].电阻率成像法(ERT)是一种地球物理勘探方法,用于探测地下岩石或土壤的电阻率分布,从而推断地下结构和物性的变化[11].在DNAPL饱和污染位点区域使用ERT,可以通过ERT监测的电阻变化来预测DNAPL分布、迁移[12-15]和修复[16-19]过程.
TOUGH2是可渗透(多孔或裂缝)介质中多相、多组分流体非等温流动的数值模拟器[20].该代码已用于许多应用,包括地热储层工程[21]、碳封存[22]和有机污染物迁移[23]问题.PetraSim是TOUGH2代码的图形后处理程序,它可以通过创建三维网格,应用复杂的边界和初始条件,并指定井用于注入/提取流体或加热,实现对多孔介质和裂隙介质中多组分、多相流体的非等温流动模拟[24-25].相关研究利用PetraSim模拟DNAPL在二维多孔介质模型中的入渗过程,并用DNAPL在二维砂箱中的入渗过程图像进行对比验证,证明使用Petrasim程序探究饱和多孔介质中DNAPL运移行为与污染展布范围是可行的[26],但是没有对Petrasim程序在三维条件下的可行性进行研究.
本文运用ERT对DNAPL在三维均质饱和砂箱中的入渗过程进行了动态监测,获得DNAPL入渗过程的三维动态变化图像,并将其监测结果图像与Petrasim程序的模拟结果图像进行对比,验证模拟结果的可行性,旨在为野外三维条件下预测DNAPL污染迁移和分布提供参考.
室内实验装置是由玻璃制成的三维砂箱,其尺寸为长100cm,宽80cm,高50cm,槽壁厚度0.5cm,实验装置如图1所示.砂箱的左侧设计有9个进水孔,三排三列,最底下的三个孔距离底部12cm,两边的孔与边缘相距20cm,右侧在相同位置也有9个排水孔,用于平衡装置饱水程度.砂箱内主要由粒径为20~60目(0.250~0.850mm)的砂土填充,砂土的干密度为1.86g/cm3.为了防止DNAPL运移至砂箱底部时腐蚀玻璃胶导致漏水,在砂箱底部填充一层1cm厚的黏土.
DNAPL污染物为三氯乙烯(TCE),为了更好地观测TCE的迁移过程,用苏丹Ⅲ染色剂对TCE进行染色.监测设备为高密度电阻率成像仪(型号ERT21B).为了对实验砂箱进行监测,在砂箱表面埋设了60个高6cm,直径0.7cm的电极,每排10个电极,共6排,电极间距为10cm.
实验之前,使用蠕动泵对砂箱进行注水,以每根进水管8mL/min的速率进行注水.在注水结束后,将砂箱静置12h,使其形成稳定的饱和水带,同时使用高密度电阻率仪对砂箱进行第一次电阻值监测.
砂箱静置稳定后,使用注射泵将TCE以3mL/min的速率从砂箱中心距顶部5cm处注入,为了使砂箱水位保持稳定,同时在排水口处排出水.在注入TCE之前先用高密度电阻仪测试砂箱中的电阻率分布,并将其作为注入TCE过程的背景电阻率.在注入TCE过程中使用高密度电阻率仪进行实时监测,每20min测定一组电阻率值,同时记录每组TCE注入的量.整个注入过程共注入了TCE 1000mL,电阻率监测过程持续420min.
利用Zhou等[27]所提出的反演计算方法进行电阻率反演成像,该方法将使用相同电流电极和相同输入电流的所有测量点被定义为一个测量事件,对于每个事件,只需要计算一次前向问题即可得到势.如果测定事件imi个测量值,则可以获得模型和测量之间的mi个电位差值,因此,事件i的第k个测量所产生的扰动值可以表示为:
式中:S为剖分单元总数,元素j处的总的扰动值是各个测量点的总扰动值的叠加,即:
这样就得到了事件i产生的扰动向量Δρi.经过平滑处理后,将扰动向量Δρi添加到初始模型参数中,以更新模型参数.然后对下一个事件重复模型参数的扰动.这样,通过使用每个事件的测量数据来顺序更新模型参数.事件的一个循环构成一次反演迭代.重复此过程,直到总测量数据和建模数据之间的失配减少到可接受的均方根(RMS)水平.在进行反演前,先对砂箱进行六面体微元剖分,剖分单元为0.1m×0.1m×0.1m的六面体,单元总数为400(10×8×5),由于电极测点主要集中在上面三层(图2),所以导出电阻率图像时只使用上面三层的数据.
本研究使用多相流模拟软件PetraSim对三维砂箱中DNAPL污染物迁移过程进行数值模拟.根据室内砂箱实验,本研究建立了一个长100cm,宽80cm,高50cm的网格模型,模型通过均匀剖分形成了10行,8列,5层,共400个网格,每个网格的长宽高均为10cm.模型的顶部为大气边界,底部为零通量边界.在模型X方向上左右侧各设置4个源汇项网格,作为入水口和排水口,在模型顶部中心位置设置污染物的注入点.
本研究使用相对渗透率函数Stone模型[28]和毛细管压力函数Parker[29]模型来进行多相流模拟,模型主要参数设置如表1所示.数值模拟使用的孔隙度与颗粒比重参数与实验用砂保持一致,渗透率由Kozeny-Carman[30]公式确定.
式中:K为渗透率,Φ为孔隙度,C为常数取5,S为比表面积,对于球形颗粒,比表面积可近似为:
式中:dp为颗粒平均粒径,则渗透率的表达式可写为:
对于20~60目(粒径0.250~0.850mm),假设其均匀分布,取平均粒径dp为0.55mm,则渗透率为2×10-10,而实验砂的粒径并不是绝对均匀分布的,因此模拟渗透率参数通过多次模拟试验选取.
模拟假定污染物从模型顶部以的速率发生泄漏,泄漏过程持续420min,模拟过程的污染物泄漏速率与泄漏时长与实际砂箱的污染物注入平均速率与时间保持一致,保证DNAPL泄漏停止后模型区域内DNAPL的总质量与实际砂箱DNAPL的总质量相同.
为了探讨ERT监测DNAPL迁移的有效性,使用surfer软件得到的电阻率变化值图像与模拟得到的饱和度图像进行对比,电阻率变化值的定义为
式中:ρ0为电阻率的初始背景值,即DNAPL污染物注入之前介质的电阻率值,ρt为注入DNAPL污染物之后t时刻介质的电阻率值,得到的电阻率变化值减去了原背景电阻率值的影响,可以更清晰的反映污染物的空间和时间变化情况.分别选取电阻率变化值图像和饱和度图像在空间和时间上的分布进行对比.
在空间分布上选取第420min时的电阻率变化值图像与饱和度图像进行对比,此时已停止注入污染物,砂箱中的DNAPL质量达到最大.由于DNAPL具有高电阻率的特性,所以在电阻率变化值图像中的高电阻率区域即为有DNAPL污染物的区域.从图3可以看出,电阻率变化值图像中心区域的电阻率变化值要高于周边区域的电阻率变化值,在z=0.05m时,图像中心的电阻率变化值在4.2~5Ω⋅m之间,随着深度逐渐降低,中心区域的电阻率变化值逐渐减少,在z=0.25m时中心区域的电阻率变化值降至1.8~2.6Ω⋅m之间.与之相对应,模拟得到的饱和度图像在z=0.05m时中心区域油饱和度位于0.13~0.15之间,在z=0.25m时中心区域的油饱和度位于0.09~0.11之间.
x=0.5m和y=0.4m分别选择一条横剖面线a-a1和一条纵剖面线b-b1进行分析(图4),通过surfer软件获取每个剖面线上的电阻率变化值和饱和度值对比,如图5所示.同一剖面线上电阻率变化值的变化趋势与DNAPL饱和度的变化趋势大致相似,电阻率变化值的峰值位置与DNAPL饱和度的峰值位置大致相同.为了进一步定量分析,在剖面线上取电阻率变化值的二阶导数与模拟的DNAPL饱和度进行对比.
二阶导数是一个数学概念,指的是函数的导数的导数.它反映了函数变化速率的变化情况,即描述了函数图像的凹凸性质.二阶导数的极大值意味着函数图像的弯曲程度或凹凸性在该点发生了显著的变化,即函数图像由凹变凸.本文通过二阶导数来反映电阻率变化值图像上各数值点的变化趋势.ρxρy分别代表横剖面线和纵剖面线上电阻率变化值的二阶导数,剖面线上电阻率变化值的一阶导数反映了电阻率变化值的变化速率,而二阶导数则表示该变化速率的变化情况.在电阻率变化值的分布中,污染物区域与周围非污染区域的边界是电阻率变化值变化速率最快的位置,即二阶导数达到最大值的位置.因此可以通过寻找电阻率变化值二阶导数的最大值来确定“边界点”.通过二阶导数的最大值,可以确定剖面线上非污染区域与污染区域“边界点”的具体位置,两“边界点”之间的距离即为污染区域的直径[19].
计算得到的电阻率变化值的二阶导数图像如图6所示,以两个二阶导数的极大值点之间的距离Dρ为电阻率变化值图像确定的污染物直径.以饱和度图像上饱和度为0的点之间的距离DH为饱和度图像确定的污染物直径.两种方法获取的污染区域直径对比如表2所示.由电阻率变化值图像确定的污染区域直径在0.40~0.51m之间,由模拟的饱和度图像确定的污染区域直径在0.42~0.51m之间,两者的相对误差的绝对值为2.00%~27.50%之间.
y=0.35m,z=0.05m剖面上,以60min为时间间隔分别选取7个时间点的电阻率变化值图像与DNAPL饱和度图像进行对比,如图7图8所示.
图7可以看出,在砂箱模型y=0.35m剖面中,砂箱DNAPL注入点处的电阻率变化值随着时间的推移而不断的增大,在第60min时,DNAPL注入点处的电阻率变化值为1.4~2.2Ω·m,到第420min时,DNAPL注入点处的电阻率变化值升至3.4~4.2Ω·m之间.在由模拟得到的DNAPL饱和度图像中,DNAPL注入点处的油饱和度变化特征与电阻率变化值变化特征一致.在第60min时,DNAPL注入点处的油饱和度为0.09~0.1之间,第420min时,DNAPL注入点处的油饱和度上升至0.1~0.11之间.在第120min和第180min时,砂箱左侧部分区域存在电阻率异常区域,可能是受到介质装填的影响,介质存在非均质性.由图8可以看出,在砂箱模型z=0.05m剖面中,第60min时,砂箱中心处的电阻率变化值在1.4~2.2Ω·m之间,随着时间的推移,砂箱中心处的电阻率变化值逐渐升高,到第420min时,砂箱中心处的电阻率变化值升至3.4~4.4Ω·m之间.而由模拟得到的DNAPL饱和度图像在第60min时,砂箱中心处的DNAPL饱和度在0.08~0.1之间,到第420min时,砂箱中心处的饱和度升至0.12~0.14之间.同样将z=0.05m剖面上各时间点的图像作剖面线进行电阻率变化值的二阶导数与饱和度对比,如表3所示,由电阻率变化值图像确定的污染区域直径为0.36~0.69m,由模拟的饱和度图像确定的污染区域直径为0.32~0.49m,两者的相对误差的绝对值在2.7%~40.58%之间.
由电阻率图像圈定的污染物范围与模拟得到的饱和度图圈定的污染物范围存在误差,可能由以下几点引起:(1)反演剖分网格的精度较低,不足以准确反映污染物分布的实际情况.(2)多相流模拟通常假设孔隙结构均匀或按一定模式分布,但实际砂土介质中的孔隙度分布并不均匀,电阻率变化也会因此不均匀.为了减少误差,实现在实际场地中的预测,可以考虑通过增加电极数量和测量密度,优化反演算法[31],联合其他监测技术[32]等减少误差.
3.1 在不同空间上由数值模拟得到DNAPL污染物分布区域与ERT监测圈定的DNAPL污染物分布区域范围直径相对误差的绝对值在2.00%~27.50%之间.说明使用PetraSim模拟软件可以较好地预测DNAPL污染物的空间分布.
3.2 在不同时间点上由数值模拟得到DNAPL污染物分布区域与ERT监测圈定的DNAPL污染物分布区域范围直径相对误差的绝对值在2.7%~40.58%之间.说明使用PetraSim模拟软件可以较好地预测DNAPL污染物随时间变化的趋势.为野外三维条件下监测和预测DNAPL污染物分布奠定了基础,具有重要的应用价值.
  • 国家自然科学基金资助项目(42277192)
  • 第三期广西高等学校千名中青年骨干教师培养计划
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2025年第45卷第5期
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  • 接收时间:2024-11-20
  • 首发时间:2026-03-18
  • 出版时间:2025-05-20
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  • 收稿日期:2024-11-20
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国家自然科学基金资助项目(42277192)
第三期广西高等学校千名中青年骨干教师培养计划
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    桂林理工大学,广西环境污染控制理论与技术重点实验室,流域保护与绿色发展广西高校工程研究中心,广西 桂林 541006

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