高岭土微粒固载成核微生物固化粗砂强度

马国梁; 何想; 路桦铭; 吴焕然; 刘汉龙; 楚剑; 肖杨

doi:10.11779/CJGE202102009

高岭土微粒固载成核微生物固化粗砂强度 English Version

马国梁^{1, 2,},
何想^{1, 2},
路桦铭^{1, 2},
吴焕然^{1, 2},
刘汉龙^{1, 2, 3},
楚剑⁴,
肖杨^{1, 2, 3, ,}

1.
重庆大学土木工程学院,重庆　400045
2.
重庆大学山地城镇建设与新技术教育部重点实验室,重庆400045
3.
库区环境地质灾害防治国家地方联合工程研究中心（重庆）,重庆　400045
4.
南洋理工大学土木与环境工程学院,新加坡　639789

基金项目:

国家自然科学基金项目 51922024

中央高校基本科研业务费项目 2019CDQYTM031

重庆市研究生科研创新项目 CYB19012

详细信息

作者简介:
马国梁（1990— ）,男,博士研究生,主要从事微生物土加固机理方面的研究工作。E-mail：magl09@163.com

通讯作者:
肖杨, E-mail: hhuxyanson@163.com

中图分类号: TU43
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出版历程
- 收稿日期: 2020-06-24
- 网络出版日期: 2022-12-04
- 刊出日期: 2021-01-31

Strength of biocemented coarse sand with kaolin micro-particle improved nucleation

MA Guo-liang^{1, 2,},
HE Xiang^{1, 2},
LU Hua-ming^{1, 2},
WU Huan-ran^{1, 2},
LIU Han-long^{1, 2, 3},
CHU Jian⁴,
XIAO Yang^{1, 2, 3, ,}

1.
School of Civil Engineering, Chongqing University, Chongqing 400045, China
2.
Key Laboratory of New Technology for Construction of Cities in Mountain Area, Chongqing University, Chongqing 400045, China
3.
National Joint Engineering Research Center of Geohazards Prevention in the Reservoir Areas (Chongqing), Chongqing 400045, China
4.
School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore

摘要

摘要: 提出一种基于微粒固载成核的微生物固化技术（MICPMPIN）,用于改善微生物诱导碳酸钙沉淀（MICP）固化粗砂的力学特性,即在灌浆前给菌液中加入一定量的高岭土形成微生物固载胶体,然后将微生物固载胶体与反应液混合形成MICP浆体（MICPCS）,利用自重渗流法加固粗砂。试验结果表明新型MICPMPIN固化粗砂的强度比传统MICP固化粗砂的强度高。其他条件相同时,MICPMPIN固化粗砂的强度随高岭土掺量的增加而增加,随微生物固载胶体含量的增大而增加,且每间隔1次灌入MICPCS时固化粗砂的强度较高。高岭土本身提供的胶结强度不能使砂柱成型,可忽略不计,其作用主要是辅助成核,增加有效碳酸钙沉淀量,并减小试样孔隙比从而增强固化粗砂的效果。MICPMPIN固化粗砂的湿强度也大于传统MICP固化粗砂的湿强度,且高岭土的掺入显著增强了固化粗砂的抗软化能力。
- MICP /
- 粗砂 /
- 高岭土 /
- MICP浆体 /
- 微粒固载成核
Abstract: A new treatment, microbially induced calcium carbonate precipitation (MICP) with micro-particle improved nucleation (MICPMPIN), is introduced to improve the performance of MICP technology for the stabilization of coarse sand. A certain amount of kaolin is augmented into the bacterial suspensions to obtain immobilized bacterial slurry, then the bacterial slurry is mixed with cementation solution to form MICP-clay slurry (MICPCS) and percolated through the coarse-sand specimens under gravity. The results show that the unconfined compressive strength (UCS) of MICPMPIN-treated specimens is higher than that of MICP-treated ones. When other conditions are the same, the UCS increases with the increasing dosage of kaolin and volume ratio of immobilized bacterial slurry. The specimens with higher UCS can be obtained by grouting MICPCS every two cycles. The cementation of pure kaolin is so small that the stabilized specimen cannot be a solid. The main contribution for the higher UCS of kaolin is the nucleation that is formed by kaolin, the increment in the amount of effective precipitates, and the decrement in the amount of pore. The wet UCS of the MICPMPIN-treated specimens is larger than that of the conventional MICP treated ones, and the softening resistance is also improved by adding kaolin into the MICP process.
- MICP /
- coarse sand /
- kaolin /
- MICP-clay slurry /
- micro-particle improved nucleation

HTML全文

0. 引言

灌注桩具有地质适应性强、承载力高等特点,是目前工程建设中最主要的基础形式,广泛应用在桥梁工程中^[1-5]。在桥梁服役过程中,由于环境和外部荷载作用,桥梁桩基水下部分会出现混凝土剥落、破损、断裂等质量问题^[6-8],三维成像声呐技术能够直观准确的识别桩基水下及泥面以上部分的结构病害情况,因此基于三维成像声呐的水下试验和点云数据处理技术研究对确保整个桩基工程的质量和安全具有重要意义^[9-10]。目前三维成像声呐的研究基本上处于设备硬件研发和实际应用的范围,尚缺少“模型试验-数据处理-工程应用”系统性的研究,本文基于三维声呐点云的模型试验,进行了水下目标物缺陷识别、尺寸测量以及点云数据后处理方法研究和桥梁桩基现场试验,充分验证了三维成像声呐在桥梁桩基水下部分检测的适用性,为该技术应用于水下结构检测提供了参考。

1. 试验

1.1 试验设备

试验由美国BlueView公司研制开发三维成像声呐系统对点云数据进行采集,系统硬件部分包括声呐发生器、云台、三角支架、计算机等组成。

1.2 试验方案

试验共设计3个试件,圆柱体混凝土试块2个,带缺陷圆柱体木质试件1个,试件尺寸见表1。试验主要研究三维成像声呐对水下不同材质、不同尺寸、以及不同缺陷结构形式的识别和测量效果。

表 1 试件尺寸参数

Table 1. Size parameters of specimens

序号	试件编号	形状	材质	尺寸r×h/cm	备注
1	WSC - ^#1	圆柱体	混凝土	2.5×10.0	—
2	WSC -^#2		混凝土	5.0×15.0	—
3	WSW-^#3		木质	15×100.0	带缺陷

下载: 导出CSV

| 显示表格

为减少环境对声呐数据采集造成影响,选择在平面尺寸为21 m×50 m,深度1.8 m的水池中进行声呐试验,并在试验目标物底下垫上粗糙多孔的防滑垫,目的在于减少声波在瓷砖表面发生较强反射,从而获得更加准确的数据。

2. 数据处理

试验通过三维成像声呐发射固定频率声波波束,在触及目标物后接收到反射声波,从而获得目标物的外形轮廓坐标数据,最后生成点云图像。由于外部环境影响,原始点云图像存在较多的噪点,如图1所示。

图 1 试件点云原始数据

Figure 1. Original data of point cloud of specimens

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为了更好的分析三维成像声呐对水下结构的识别和测量效果,本文提出了数据后处理方案：①人工删减原始数据,去除大面积噪点；②对单次采集点云数据进行滤波处理,对原始数据进行压缩并去除离散点；③对处理后的图像进行尺寸测量。

2.1 点云滤波处理

本文根据点云噪声特征进行不同的滤波处理。

（1）半径滤波通过统计一定半径区域内点的个数来去除离散点。可依据点云的不同特征定义多种条件,定义条件为点在x,y和z维度下的取值同时满足某个值域,则可以在指定3D空间内对点云进行裁剪。假设有n个点云,对这部分点云进行半径滤波。设定近邻点数量为k,半径为r。然后遍历每一个点云。i=1,2,…,n。以第i个点云为圆心,在其r半径内,若有k个点云,则该第i个点云将被保留；若其r半径内,点云个数少于k个,则该第i个点云将被去除。

（2）体素滤波主要对点云数据进行压缩,在保证点云图像主体结构不变的情况下减少点的数量。用于密集型点云的预处理中,以加快后续配准、重建等操作的执行速度。

（3）高斯统计滤波是最常用的滤波处理方式,通过统计某个点于相邻点之间的平均距离来去除离散点。设定去除离散噪点前的点云集合为 $A =$ ${a_{i},$ $i = 1, 2, n}$ ,去除噪声后点云集合 $A^{'} = {a_{i}, i = 1, 2, m}$ 。用b_i表示a_i到邻域中k个点的平均距离。算法中A所有点到其各自邻域的平均距离服从高斯分布且形状由均值和标准差决定。令所估计点平均距离a为其标准差,则记为 $S (μ, σ)$ ,且有如下公式：

$μ = \frac{\sum_{i = 1}^{n} S_{i}}{n}$ ,

(1)

$σ = \frac{\sum_{i = 1}^{n} {(S_{i} - μ)}^{2}}{n}$ 。

(2)

所有位于（μ-std×σ,μ+std×σ）范围外的点即可认为是大尺度噪声点,设k值为估算平均距离的邻域点大小,标准差倍数控制筛选阈值。设目标点坐标为（X_m,Y_m,Z_m）,领域内某点N坐标为（X_n,Y_n,Z_n）,则

$S_{N} = \sqrt{{(X_{m} + X_{n})}^{2} + {(Y_{m} + Y_{n})}^{2} + {(Z_{m} + Z_{n})}^{2}}$ ,

(3)

$\bar{s} = \frac{\sum_{n = 1}^{K} S_{N}}{k}$ 。

(4)

S_N服从一个位置参数μ、尺度参数为 $σ$ 的概率分布,且其概率密度函数为

$f (S_{N}) = \frac{1}{\sqrt{2 π σ}} exp (- \frac{{(S_{N} - μ)}^{2}}{2 σ^{2}})$ ,

(5)

$S_{max} = (\bar{s}) + n σ \cdot std$ ,

(6)

式中,std为标准差倍数阈值。

对点云原始数据进行大面积噪点人工删减后再经上述滤波处理得到图2所示点云图像,点云图像能够清晰反映设备扫描侧的形状轮廓。

图 2 原始数据经滤波处理后点云图像

Figure 2. Point cloud images of original data after filtering

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2.2 尺寸测量

点云滤波处理后,对点云图像进行切面处理,选择一个剖面测量试件尺寸。对试件WSC - ^#1、WSC - ^#2两个试件进行尺寸测量,如图3所示,经滤波处理后对点云图像进行测量,测得圆柱高度分别为15,10 cm与试件实际尺寸基本吻合,由于测量过程存在主观因素影响,试验结果存在一定误差,但误差能够保持在厘米级,完全满足工程应用需求。

图 3 试件WSC - ^#1及WSC - ^#2尺寸测量

Figure 3. Dimensional measurements of WSC - ^#1 and WSC - ^#2

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对带缺陷圆柱体木桩WSW-^#3试件的高度和缺陷尺寸进行测量,试件及缺陷尺寸如图4所示。

图 4 WSW -^#3试件模型及缺陷尺寸

Figure 4. Model and defect sizes of WSW - ^#3

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为方便试件点云图像尺寸测量,将桩的点云图旋转90°,右侧为桩底,左侧为桩顶,下侧为缺陷侧,尺寸测量如图5所示,测量结果见表2。

图 5 试件WSW-^#3尺寸测量

Figure 5. Measurements of specimen sizes of WSW-^#3

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表 2 缺陷圆柱试件尺寸测量数据

Table 2. Measured data of defective specimens

序号	位置	实际尺寸	测量尺寸	误差
1	下部缺陷宽度	10	10	0
2	下部缺陷深度	5	4	1
3	缺陷距离	30	29	1
4	上部缺陷宽度	5	3	2
5	上部缺陷深度	10	11	1

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| 显示表格

测量结果表明：点云图像能够清晰显示缺陷位置,对数据后处理后的点云图像进行测量,试件各个部位测量尺寸与实际尺寸误差在2 cm以内,满足实际工程测量精度需求。

3. 工程应用

某高速桥梁左幅建成于1994年,桥梁下部结构为桩柱式桥台,桩柱式桥墩,墩柱直径1.0 m,桩基直径1.2 m。现场采用声学可视化检测技术对水下结构进行检测,并在检测完成后进行抽水验证。

选取其中一根桩基进行声纳扫测分析,原始点云数据如图所示,进行大面积噪点人工删减和软件滤波处理后,得到点云图像如图所示,数据后处理后的点云图像能够清晰显示桩基轮廓。对点云图像断面进行测量,桩基础部分点云断面缩小,结合设计图纸判断该桩基存在混凝土大面积剥落现象。

3.1 声呐数据处理及尺寸测量

为测得混凝土剥落厚度和长度,选取桩基竖向断面并对点云图像3个不同位置进行测量,如图6所示,测得剥落厚度为0.12,0.18,0.11 m,平均值为0.14 m；剥落长度为0.93,0.94,0.97 m,平均值为0.95 m。

图 6 桥梁桩基三维成像声呐数据处理

Figure 6. Data processing of bridge pile foundation

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3.2 现场试验验证

为验证声呐数据的测量精确度,在抽水后采用人工进行测量,现场实测混凝土剥落厚度分别为0.15,0.16,0.14 m,平均值为0.15 m；剥落长度分别为1.01,0.99,0.95 m,平均值为0.98 m,现场实测照片如图7所示。

图 7 桥梁桩基水下结构病害现场测量

Figure 7. Field measurements of bridge pile foundation

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通过对比声呐与人工测量数据,两种方法测量混凝土剥落厚度平均值误差在1 cm,剥落长度平均值误差在3 cm,基本满足桥梁检测现场检测需求。

4. 结论

（1）三维成像声呐扫测原始数据存在较多噪点,在经过滤波处理后,能够清晰呈现目标物部分外形轮廓,保留目标物几何信息,并能够较好识别试件缺陷。

（2）对滤波处理后的点云图像尺寸测量结果准确,其中混凝土试件高度测量尺寸与实际基本吻合,带缺陷木桩试件部位尺寸在低于5 cm时,误差较大,尺寸大于10 cm误差较小,整体误差保持在2 cm以内。

（3）三维成像声呐应用于桥梁桩基水下部分的外观完整性检测效果较好,能够直观呈现桩基外观特征,识别桩基外观缺陷。

（4）经过将三维成像声呐的测试数据与现场测量数据对比,三维成像声呐能够较准确测量桩基混凝土剥落厚度,误差在3 cm内,满足工程检测需求。

图 1 试验材料

Figure 1. Test materials

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图 2 制样模具

Figure 2. Moulds for preparating specimens

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图 3 MICPMPIN固化粗砂试样的无侧限抗压强度

Figure 3. UCS of MICPMPIN-treated coarse sand specimens

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图 4 碳酸钙沉淀量及沉淀效率

Figure 4. CaCO₃ contents and precipitation efficiency

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图 5 MICPMPIN固化粗砂高岭土沉淀量

Figure 5. Kaolin contents of MICPMPIN-treated specimens

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图 6 高岭土及碳酸钙沿试样高度分布（间隔1次注入MICPCS,微生物固载胶体含量1/2）

Figure 6. Distribution of kaolin and CaCO₃ along height of specimens (injecting MICPCS with 1/2 immobilized bacterial slurry every 2 times)

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图 7 MICPMPIN固化粗砂试样（间隔1次注入MICPCS,微生物固载胶体含量1/2）的微观结构及其物质组成

Figure 7. Microstructure and chemical composition of MICPMPIN-treated coarse-sand specimens (injecting MICPCS with 1/2 immobilized bacterial slurry every 2 times)

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图 8 高岭土沉淀量对无侧限抗压强度的影响

Figure 8. Effects of kaolin content on UCS

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图 9 菌液浓度对无侧限抗压强度的影响

Figure 9. Effects of bacterial density on UCS

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图 10 高岭土固化试样

Figure 10. Kaolin-stabilized specimens

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图 11 浸泡对MICPMPIN固化粗砂强度的影响

Figure 11. Effects of immersion on UCS of MICPMPIN-stabilized coarse sand

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表 1 MICPCS参数

Table 1 Parameters of MICP-clay slurry

微生物固载胶体含量微生物固载胶体体积/mL 反应液体积/mL 反应液浓度/(mol·L^-1) MICP浆体浓度/(mol·L^-1)

1/2 25.0 25.0 2.00 1.00
1/4 12.5 37.5 1.34 1.00
1/10 5.0 45.0 1.11 1.00

下载: 导出CSV

表 2 MICPMPIN加固粗砂试验设计

Table 2 Test design for stabilizing coarse sand by MICPMPIN

间隔次数高岭土质量浓度/(g·L^-1)
0 10 20 40 100

0 √ √ √ — —
1 √ √ √ √ √
3 √ — √ — √

下载: 导出CSV

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