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PHD疏浚淤泥堆场大应变非线性固结分析

潘毅, 李传勋

潘毅, 李传勋. PHD疏浚淤泥堆场大应变非线性固结分析[J]. 岩土工程学报, 2024, 46(11): 2295-2304. DOI: 10.11779/CJGE20230290
引用本文: 潘毅, 李传勋. PHD疏浚淤泥堆场大应变非线性固结分析[J]. 岩土工程学报, 2024, 46(11): 2295-2304. DOI: 10.11779/CJGE20230290
PAN Yi, LI Chuanxun. Large-strain nonlinear consolidation of dredged sludge yards with PHDs[J]. Chinese Journal of Geotechnical Engineering, 2024, 46(11): 2295-2304. DOI: 10.11779/CJGE20230290
Citation: PAN Yi, LI Chuanxun. Large-strain nonlinear consolidation of dredged sludge yards with PHDs[J]. Chinese Journal of Geotechnical Engineering, 2024, 46(11): 2295-2304. DOI: 10.11779/CJGE20230290

PHD疏浚淤泥堆场大应变非线性固结分析  English Version

基金项目: 

国家自然科学基金面上项目 42377183

详细信息
    作者简介:

    潘毅(1998—),男,硕士研究生,主要从事岩土工程方面的研究工作。E-mail: 2212123026@stmail.ujs.edu.cn

  • 中图分类号: TU411

Large-strain nonlinear consolidation of dredged sludge yards with PHDs

  • 摘要: 已有的工程实践和室内模型试验均表明铺设水平排水板(Prefabricated Horizontal Drains, PHDs)可有效加快疏浚淤泥的固结。但目前自重作用下能全面反映疏浚淤泥特性的PHD处理疏浚淤泥堆场的大应变固结理论尚缺乏系统性研究。针对底层铺设PHD的疏浚淤泥堆场具有平面渗流、竖向应变的特点,基于Gibson大应变固结理论,考虑疏浚淤泥的非线性压缩和渗透特性,建立PHD处理的疏浚淤泥堆场大应变非线性固结模型,并应用有限差分法获得该模型的解答。通过与疏浚淤泥自重作用下未设置PHD的大应变固结模型解答开展对比分析,验证了PHD处理疏浚淤泥堆场大应变非线性固结模型及其解答的可靠性。在此基础上,分析了不同影响因素对疏浚淤泥堆场大应变固结的影响。分析发现:铺设率达到一定值后就可达到与底部完全透水边界相同的固结速率,且该值随堆放高度的增加而曲线减小;堆放高度分别为1,5 m时,PHD最佳铺设率分别约为50%,27%;堆放高度对PHD处理堆场的固结速率影响较大,可通过增设PHD层数以加快堆场的固结速率;淤泥压缩指数一定时,固结速率随渗透指数的增大而增大;渗透指数保持不变时,固结速率随压缩指数的增大而减小。
    Abstract: Engineering practices and indoor model tests indicate that laying prefabricated horizontal drains (PHDs) can effectively accelerate the consolidation of dredged sludge yards. However, the large-strain self-weighted consolidation theory of dredged sludge yards with PHDs, in which the characteristics of dredged sludge can be fully considered, lacks systematic researches. In this study, based on the Gibson's large-strain consolidation theory and considering the nonlinear compressibility and permeability of dredged sludge, a large-strain nonlinear consolidation model for PHD-treated sludge yards with planar seepage and vertical strain is established, and the solution for this model is obtained by the finite difference method. The reliability of the large-strain nonlinear consolidation model and its solution for the PHD-treated sludge yards is verified by comparing with that for the large-strain self-weighted consolidation of dredged sludge yards without PHDs. On this basis, the influences of different factors on large-strain consolidation behaviors of dredged sludge yards are investigated. The results show that: (1) The consolidation rate can be achieved at the same level as the fully permeable boundary at the bottom once the rate of laying PHDs reaches a certain value, and the optimal rate of laying PHDs decreases with the increase of the stacking height of dredged sludge yards. (2) The optimal rates of laying PHDs are 50% and 27% for stacking heights of 1 and 5 m, respectively. (3) The stacking height has a great influence on the consolidation rate of yards treated with PHDs, and the consolidation rate of yards can be accelerated by increasing the number of PHD layers. (4) The consolidation rate increases with the increase of the permeability index when the compression index keeps fixed. (5) The consolidation rate decreases with the increase of the compression index when the permeability index remains constant.
  • 河道疏浚、湖泊清淤以及港口航道建设等不可避免地产生大量疏浚淤泥,资源化利用是处置疏浚淤泥的根本出路[1-4]。由于疏浚淤泥具有较差的物理和力学性能(如高含水量、高压缩性、强度和承载能力低等),资源化利用前往往仍需对其脱水处置[5]。鉴于处理费用、处理设备、处理规模的限制,目前实际中仍以场地堆放为主。但在自然条件下淤泥堆场的自重固结往往需要较长时间,受到外部气候影响大,场地周转时间长。因此,工程中需对淤泥堆场进行处理以达到快速有效脱水的目的。

    目前常采用的处置方式为打设竖向排水板PVDs (Prefabricated Vertical Drains)以提供排水通道。但其存在的主要问题:①PVD随土体沉降发生弯折变形,导致其后期排水效率较差,底部疏浚淤泥不能完成脱水固结;②疏浚淤泥早期强度较低,难以实现PVD的机械施工[6-7]

    针对上述PVD的不足,学者们提出使用水平排水板(PHD)处理疏浚淤泥堆场。Shinsha等[8]研究指出铺设PHD可边堆放边固结,现场试验结果表明其处理疏浚淤泥的总量可达到堆场总容积的1.1倍。王海燕等[9]研究了PHD在某疏浚淤泥吹填场地的应用,并与PVD处理的场地作对比,结果表明使用PHD的加固效果明显优于PVD。周洋等[10]通过室内模型试验,将PHD和PVD真空预压法进行对比研究,证明PHD能够与疏浚淤泥协同沉降,从而有效避免排水板的弯折问题,并且该试验也表明,PVD固结单元与PHD固结单元中的边界条件有明显的差别。

    既然PHD在处理疏浚淤泥堆场方面存在一定优势,且能够取得较好的加固效果,那么深入研究PHD处理疏浚淤泥堆场的大应变固结问题具有重要的理论和实际意义。陈征等[11]对分布式排水通道固结模型开展研究,其模型实质与PHD固结模型相类似,并获得了分布式排水固结模型的小应变固结解答。此外,Chai等[12]通过将固结单元转化为轴对称模型或平面应变模型给出半经验性的真空预压固结分析方法。在此基础上,Chai等[13]提出了真空预压下PHD处理吹填土的大应变固结模型,然而上述理论均忽略了淤泥土体自重作用的影响。同时,李传勋等[14]通过整理大量吹填土室内试验数据发现:应用半对数坐标系中的线性关系描述高压缩性疏浚淤泥的非线性压缩和渗透特性往往存在一定偏差。

    事实上,在堆场运转周期允许的条件下,铺设PHDs后可不施加真空预压而仅靠疏浚淤泥自重达到脱水固结效果。Lee等[15]获得饱和软土线性自重固结解析解,但其忽视了土体固结中的非线性压缩渗透特性。蒲诃夫等[16]基于分段线性法,建立了能同时考虑饱和软土大应变效应和材料参数非线性变化的自重固结模型。但以上疏浚淤泥自重固结均未对淤泥土层开展任何处理,同时采用的非线性本构关系亦不能反映淤泥的真实压缩渗透特性。为加快自重下堆场的固结速率,可在堆场底部间隔一定距离铺设PHDs,此时堆场底部边界为间隔式透水边界,但目前对该工况下的堆场自重固结还鲜见报道。

    以PHD处理的疏浚淤泥堆场自重固结模型研究为出发点,在讨论疏浚淤泥非线性压缩和渗透特性的基础上,采用大应变几何条件建立了发生平面渗流、竖向应变的疏浚淤泥堆场自重固结模型并获得其解答。在验证模型可靠性的基础上,对PHD铺设间距、堆放高度及土体非线性特性参数对固结性状的影响开展分析,为今后PHD处理疏浚淤泥堆场的实际工程提供一定的理论支撑。

    Butterfield[17]通过室内压缩试验发现高压缩性土的压缩曲线在e - lgσ坐标系中会出现曲线段,并提出能更佳反映其压缩特性的非线性关系为

    lg(1+e1+e0)=lg(σ0σ)Ic (1)

    式中:σ为土体有效应力;e为土体孔隙比;σ0为初始有效应力;e0为初始孔隙比;Ic为土体的压缩指数。为进一步说明该非线性关系对淤泥的适用性,对已有文献[1819]中吹填淤泥、冲填淤泥压缩实验结果进行拟合,结果如图 1所示,可发现高压缩性淤泥在lg(1+e) - lgσ坐标系中具有非常好的线性关系。

    图  1  高压缩性淤泥的非线性压缩曲线
    Figure  1.  Nonlinear compression curves of sludge with high compressibility

    曾玲玲等[20]分析多组固结渗透试验数据发现:当土体应变超过20%时,淤泥渗透系数与孔隙比在双对数坐标系比其在半对数坐标系中具有更好的线性关系。李传勋等[14]在此基础上对大量高压缩性软土渗透试验数据开展分析,进一步表明下式所示的非线性关系能更好地描述其非线性渗透特性:

    kvkv0=(1+e1+e0)α (2)

    式中:kv为土体渗透系数;kv0为土体初始渗透系数;α为渗透模型参数,其值等于土体渗透指数的倒数。该关系式不仅能有效描述一般黏性土的非线性渗透关系,而且其更好地描述高压缩性淤泥的非线性渗透关系。文献[14]对此已开展了大量试验数据的验证并给出了相应模型参数的变化范围,限于篇幅,这里不再对该非线性渗透关系深入地展开论证。

    图 2(a)所示,堆场中淤泥堆放高度为H,堆场四周设置的围堰使堆场内淤泥仅发生竖向应变。将宽度为b的PHD以间距(L+b)在堆场底面等间距铺设。由于PHD的存在,导致计算单元内发生平面渗流。但也正因PHD的等间距铺设,可选取单个PHD及其上土体作为计算单元计算。如图 2(b)所示,计算单元水平方向坐标轴为x,竖直方向坐标轴为a,单元左边界为x=0,右边界为x=L+b,单元底部排水板部分为透水边界,排水板之外的底部边界为不透水边界,计算单元两侧均为不透水边界,单元顶部为完全透水边界。

    图  2  堆场自重固结及计算单元示意图
    Figure  2.  Schematic diagram of self-weighted consolidation and calculation unit of yards

    (1)淤泥为均质、饱和,土颗粒和水均不可压缩。

    (2)堆场四周围堰的限制致使淤泥仅发生竖向变形,铺设PHD使计算单元内发生平面渗流。

    (3)应用如前所述的双对数坐标系中的线性关系描述淤泥的非线性压缩渗透特性。

    (4)淤泥中水的渗流服从Darcy定律。

    (5)将PHD视为理想水平排水井,此时堆场自重固结属于典型的平面应变固结问题。

    图 3为拉格朗日坐标系中堆场自重固结示意图。竖向以自重作用方向为正方向。图 3(a)为拉格朗日坐标系初始时刻示意图,堆场顶面记为a=0,堆场底面记为a=H图 3(b)t时刻流动坐标系示意图,初始构型中坐标a在流动坐标系中t时刻距离基准面的距离为ξ=ξ(a,t)。根据Gibson等[21]大应变固结理论可知,aξ之间关系为

    ξa=1+e1+e0 (3)
    图  3  Lagrangian坐标系中淤泥自重固结分析示意图
    Figure  3.  Schematic diagram of self-weighted consolidation in Lagrangian coordinate system

    式中:e=e(a,t)为初始构型坐标at时刻的土层孔隙比;e0=e(a,t)为初始构型坐标a处土层初始孔隙比。初始构型a处土层在自重作用下总应力为

    σ(a)=γw(Gs1)a1+e00 (4)

    式中: \sigma (a) 为自重作用下土层的总应力; {G_{\text{s}}} 为土体颗粒相对质量密度;{\gamma _{\text{w}}}为水的重度。

    图 4所示,流动坐标系中单元体ξ方向上流入的孔隙水流量qξ

    {q_{\mathtt{ξ }}} = \frac{e}{{1 + e}}(v_{\mathtt{ξ }}^{\text{w}} - {v_{\text{s}}}){\text{d}}x 。 (5)
    图  4  单元体渗流示意图
    Figure  4.  Schematic diagram of seepage in soil element

    式中:v_{\mathtt{ξ }}^{\text{w}}{v_{\text{s}}}分别为孔隙水与土颗粒沿ξ方向上的真实流速。

    流出的孔隙水流量qξ+dqξ

    {q_{\mathtt{ξ }}} + {\text{d}}{q_{\mathtt{ξ }}} = \left\{ {\frac{e}{{1 + e}}(v_{\mathtt{ξ }}^{\text{w}} - {v_{\text{s}}}) - \frac{\partial }{{\partial \xi }}\left[ {\frac{e}{{1 + e}}(v_{\mathtt{ξ }}^{\text{w}} - {v_{\text{s}}}){\text{d}}\xi } \right]} \right\}{\text{d}}x。 (6)

    单元体ξ方向上的流量差dqξ

    {\text{d}}{q_{\mathtt{ξ }}} = - \frac{\partial }{{\partial \xi }}\left[ {\frac{e}{{1 + e}}(v_{\mathtt{ξ }}^{\text{w}} - {v_{\text{s}}})} \right]{\text{d}}\xi {\text{d}}x。 (7)

    流动坐标系中单元体x方向上流入的孔隙水流量qx

    {q_x} = \frac{e}{{1 + e}}v_x^{\text{w}}{\text{d}}\xi 。 (8)

    式中:v_x^{\text{w}}为孔隙水沿x方向上的真实流速。

    流出的孔隙水流量qx+dqx

    {q_x} + {\text{d}}{q_x} = \left\{ {\left( {\frac{e}{{1 + e}}} \right)v_x^{\text{w}} + \frac{\partial }{{\partial x}}\left[ {\left( {\frac{e}{{1 + e}}} \right)v_x^{\text{w}}} \right]{\text{d}}x} \right\}{\text{d}}\xi 。 (9)

    单元体x方向上的流量差dqx

    {\text{d}}{q_x} = \frac{\partial }{{\partial x}}\left( {\frac{e}{{1 + e}}v_x^{\text{w}}} \right){\text{d}}x{\text{d}}\xi 。 (10)

    根据单元体流入与流出的流量差等于单元体体积改变量可得

    \begin{array}{c} - \frac{1}{{1 + e}}\frac{{\partial e}}{{\partial t}}{\text{d}}\xi {\text{d}}x = - \frac{\partial }{{\partial \xi }}\left[ {\frac{e}{{1 + e}}\left( {v_{\mathtt{ξ }}^{\text{w}} - {v_{\text{s}}}} \right)} \right]{\text{d}}\xi {\text{d}}x +\\ \frac{\partial }{\partial x}\left(\frac{e}{1+e}{v}_{x}^{\text{w}}\right)\text{d}x\text{d}\xi \text{ }。 \end{array} (11)

    同时引入Darcy定律,式(11)可改写为

    \frac{1}{{1 + e}}\frac{{\partial e}}{{\partial t}} = \frac{1}{{{\gamma _{\text{w}}}}}\frac{\partial }{{\partial \xi }}\left( {{k_{\mathtt{ξ }}}\frac{{\partial u}}{{\partial \xi }}} \right) + \frac{1}{{{\gamma _{\text{w}}}}}\frac{\partial }{{\partial x}}\left( {{k_x}\frac{{\partial u}}{{\partial x}}} \right)。 (12)

    式中:kξkx分别为淤泥的竖向渗透系数和水平渗透系数;u为自重引发的超静孔隙水压力。

    根据式(3),控制方程(12)可转换为拉格朗日坐标系中应用初始构型表达的控制方程为

    \frac{1}{{1 + e}}\frac{{\partial e}}{{\partial t}} = \frac{1}{{{\gamma _{\text{w}}}}}\frac{{1 + {e_0}}}{{1 + e}}\frac{\partial }{{\partial a}}\left[ {\frac{{{k_{\mathtt{ξ }}}\left( {1 + {e_0}} \right)}}{{1 + e}}\frac{{\partial u}}{{\partial a}}} \right] + \frac{1}{{{\gamma _{\text{w}}}}}\frac{\partial }{{\partial x}}\left( {{k_x}\frac{{\partial u}}{{\partial x}}} \right) 。 (13)

    由于自重固结过程中土中总应力\sigma (a)保持不变,根据有效应力原理可得

    \frac{{\partial e}}{{\partial t}} = \frac{{{\text{d}}e}}{{{\text{d}}\sigma '}}\frac{{\partial \sigma '}}{{\partial t}} = - \frac{{{\text{d}}e}}{{{\text{d}}\sigma '}}\frac{{\partial u}}{{\partial t}} 。 (14)

    将式(14)代入式(13)可得

    \begin{array}{l} - \frac{1}{{1 + {e_0}}}\frac{{{\text{d}}e}}{{{\text{d}}\sigma '}}\frac{{\partial u}}{{\partial t}}\\ = \frac{1}{{{\gamma _{\text{w}}}}}\frac{\partial }{{\partial a}}\left[ {\frac{{{k_{\mathtt{ξ }}}\left( {1 + {e_0}} \right)}}{{1 + e}}\frac{{\partial u}}{{\partial a}}} \right] + \frac{1}{{{\gamma _{\text{w}}}}}\frac{{1 + e}}{{1 + {e_0}}}\frac{\partial }{{\partial x}}\left( {{k_x}\frac{{\partial u}}{{\partial x}}} \right) 。 \end{array} (15)

    将式(1),(2)代入式(15),可得PHD处理疏浚淤泥堆场大应变非线性自重固结控制方程为

    \begin{array}{c} \frac{{\partial u}}{{\partial t}} = \frac{{{k_{{\mathtt{ξ }}0}}}}{{{\gamma _{\text{w}}}}}\frac{{{{\sigma '}_0}}}{{{I_{\text{c}}}}}{\left( {\frac{{\sigma '}}{{{{\sigma '}_0}}}} \right)^{{I_{\text{c}}} + 1}}\frac{\partial }{{\partial a}}\left[ {{{\left( {\frac{{\sigma '}}{{{{\sigma '}_0}}}} \right)}^{ - {I_{\text{c}}}(\alpha - 1)}}\frac{{\partial u}}{{\partial a}}} \right] +\\ \frac{{{k_{x0}}}}{{{\gamma _{\text{w}}}}}\frac{{{{\sigma '}_0}}}{{{I_{\text{c}}}}}\left( {\frac{{\sigma '}}{{{{\sigma '}_0}}}} \right)\frac{\partial }{{\partial x}}\left[ {{{\left( {\frac{{\sigma '}}{{{{\sigma '}_0}}}} \right)}^{ - {I_{\text{c}}}}}^\beta \frac{{\partial u}}{{\partial x}}} \right] 。 \end{array} (16)

    式中:kξ0kx0分别为淤泥在竖直方向上和水平方向上的初始渗透指数;\alpha \beta 分别为淤泥在竖直方向上和水平方向的双对数渗透模型参数,其倒数为淤泥渗透指数。

    PHD处理的疏浚淤泥在自重固结过程中上表面为透水边界,即

    u(0,x) = 0 (0 \leqslant x \leqslant L + b) 。 (17)

    堆场底部铺设PHD区域视为透水边界,未铺设PHD区域则视为不透水边界,即

    u(H,x) = 0 \left( {\frac{L}{2} \leqslant x \leqslant \frac{L}{2} + b} \right)\text{,} (18)
    {\left. {\frac{{\partial u}}{{\partial a}}} \right|_{a = H}} = 0 \left(0\le x < \frac{L}{2}\text{,}\frac{L}{2}+b < x\le L+b\right) 。 (19)

    考虑PHD等间距铺设,由于对称性可将计算单元之间的边界视为不透水边界,即

    {\left. {\frac{{\partial u}}{{\partial x}}} \right|_{x = 0}} = {\left. {\frac{{\partial u}}{{\partial x}}} \right|_{x = L + b}} = 0 。 (20)

    图 3(a)所示,由于疏浚淤泥在自重固结开始时,不存在有效应力,其自重应力均由超静孔压承担,故超静孔隙水压力的初始条件为

    u(a,0) = \frac{{{\gamma _{\text{w}}}({G_{\text{s}}} - 1)a}}{{1 + {e_0}}} 。 (21)

    为便于方程求解,定义如下无量纲参数及变量:Z = \frac{a}{H}X = \frac{x}{{(L + b)}} \kappa = \frac{{{k_{x{\text{0}}}}}}{{{k_{{\mathtt{ξ} 0}}}}} \eta = \frac{H}{{(L + b)}} U = \frac{u}{{{{\sigma '}_0}}} {T_{\text{v}}} = \frac{{{c_{{\text{F0}}}}t}}{{{H^2}}} Q = \frac{{\sigma '}}{{{{\sigma '}_0}}} \lambda = \frac{b}{{L + b}},其中{c_{{\text{F0}}}} = \frac{{{k_{{\mathtt{ξ} 0}}}}}{{{\gamma _{\text{w}}}}}\frac{{{{\sigma '}_0}}}{{{I_{\text{c}}}}};无量纲参数λ表征为PHD的铺设面积与堆场总面积之比,即铺设率。将无量纲参数代入控制方程式(16)得

    \frac{\partial U}{\partial {T}_{\text{v}}}={(Q)}^{{I}_{\text{c}}+1}\frac{\partial }{\partial Z}\left[{(Q)}^{-{I}_{\text{c}}(\alpha -1)}\frac{\partial U}{\partial Z}\right]+\kappa {\eta }^{2}Q\frac{\partial }{\partial X}\left[{(Q)}^{-{I}_{\text{c}}}{}^{\beta }\frac{\partial U}{\partial X}\right]。 (22)

    对应的边界条件式(17)~(20)可改为

    {\left. U \right|_{Z = 0}} = 0 (0 \leqslant X \leqslant 1) \text{,} (23)
    {\left. U \right|_{Z = 1}} = 0 \left( {\frac{{1 - \lambda }}{2} \leqslant X \leqslant \frac{{1 + \lambda }}{2}} \right)\text{,} (24)
    {\left. {\frac{{\partial U}}{{\partial Z}}} \right|_{Z = 1}} = 0 (0 \leqslant X < \frac{{1 - \lambda }}{2}\text{,}\frac{{1 + \lambda }}{2} < X \leqslant 1)\text{,} (25)
    {\left. {\frac{{\partial U}}{{\partial X}}} \right|_{X = 0}} = {\left. {\frac{{\partial U}}{{\partial X}}} \right|_{X = 1}} = 0。 (26)

    对应的初始条件式(21)改为

    {\left. U \right|_{{T_{\text{v}}} = 0}} = \frac{{{\gamma _{\text{w}}}H{\text{(}}{G_{\text{s}}} - 1{\text{)}}Z}}{{(1 + {e_0}){{\sigma '}_0}}} (0 \leqslant Z \leqslant 1)。 (27)

    式(22)为二阶变系数偏微分方程。如使用显式差分格式求解,虽便于计算但稳定性较差;若改用隐式格式或Crank-Nicolson格式,其对应线性方程组的系数矩阵不再是三对角矩阵,不能使用追赶法求解[22]。因此,本节采用交替方向隐式(ADI)格式求解。

    图 5所示,对无量纲化的计算单元划分网格,沿竖向划分J等份,步长为\Delta Z,则Z向第j节点坐标为Zj=j \Delta Z j=0,1,…,J-1,J+1。沿水平方向划分I等份,其步长为\Delta X,则X向第i节点坐标为Xi=i \Delta X i=-1,0,…,I1I1+1,…I2-1,I2,…,II+1。其中网格I1I2间为水平排水板,其边界为透水性边界。同时,将时间域划分为多个微小时段,记第 m 个微小时间段的步长为 \Delta {T_{{\text{v}}m}} ,则 \Delta {T_{{\text{v}}m}} = {T_{\text{v}}}_m - {T_{{\text{v}}m - 1}} ,其中 {T_{\text{v}}}_m 为第m时段的终止时刻, {T_{{\text{v}}m - 1}} 为第m时段的初始时刻,m=1, 2, 3, …。

    图  5  计算单元的离散网格
    Figure  5.  Discretization grid of calculation unit

    首先,在时间间隔({T_{{\text{v}}m}},{T_{{\text{v}}m}} + \Delta {T_{{\text{v}}m}}/2)对式(22)在Z方向取隐式差分,X方向取显式差分,可得如下的差分方程:

    \begin{array}{l} U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} - U_{j,i}^m = \mu {(Q_{j,i}^m)^{{I_{\text{c}}} + 1}}{(Q_{j + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2},i}^m)^{ - {I_{\text{c}}}(\alpha - 1)}}(U_{j + 1,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} - U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}) + \hfill \\ {\text{ }}\mu {(Q_{j,i}^m)^{{I_{\text{c}}} + 1}}{(Q_{j - {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2},i}^m)^{ - {I_{\text{c}}}(\alpha - 1)}}(U_{j - 1,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} - U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}) + \hfill \\ {\text{ }}\kappa \tau {\eta ^2}Q_{j,i}^m{(Q_{j,i + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}^m)^{ - {I_{\text{c}}}\beta}} (U_{j,i + 1}^m - U_{j,i}^m) + \hfill \\ \kappa \tau {\eta ^2}Q_{j,i}^m{(Q_{j,i - {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}^m)^{ - {I_{\text{c}}}\beta}} (U_{j,i - 1}^m - U_{j,i}^m) 。 \end{array} (28)

    其次,在时间间隔({T_{{\text{v}}m}} + \Delta {T_{{\text{v}}m}}/2,{T_{{\text{v}}m}} + \Delta {T_{{\text{v}}m}})对式(22)在Z方向取显式差分,X方向取隐式差分,可得如下的差分方程

    \begin{array}{l} U_{j,i}^{m + 1} - U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} = \kappa \tau {\eta ^2}Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}{(Q_{j,i + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})^{ - {I_{\text{c}}}\beta }}(U_{j,i + 1}^{m + 1} - U_{j,i}^{m + 1}) + \hfill \\ {\text{ }}\kappa \tau {\eta ^2}Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}{(Q_{j,i - {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})^{ - {I_{\text{c}}}\beta }}(U_{j,i - 1}^{m + 1} - U_{j,i}^{m + 1}) + \hfill \\ {\text{ }}\mu {(Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})^{{I_{\text{c}}} + 1}}{(Q_{j + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2},i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})^{ - {I_{\text{c}}}\left( {\alpha - 1} \right)}}(U_{j + 1,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} - U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}) + \hfill \\ \mu {(Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})^{{I_{\text{c}}} + 1}}{(Q_{j - {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2},i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})^{ - {I_{\text{c}}}\left( {\alpha - 1} \right)}}(U_{j - 1,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} - U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}) 。 \end{array} (29)

    式中: \mu = \frac{{\Delta {T_{\text{v}}}}}{{2{{(\Delta Z)}^2}}} \tau = \frac{{\Delta {T_{\text{v}}}}}{{2{{(\Delta X)}^2}}} U_{j,i}^m Q_{j,i}^m {T_{\text{v}}}_m 时刻在网格节点(XiZj)处的超静孔压无量纲值和有效应力无量纲值; U_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} 分别为({T_{{\text{v}}m}} + \Delta {T_{{\text{v}}m}}/2)时刻在网格节点(XiZj)处的超静孔压无量纲值和有效应力无量纲值; Q_{j \pm {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2},i}^m = \frac{{(Q_{j \pm 1,i}^m + Q_{j,i}^m)}}{2} Q_{j,i \pm {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}^m = \frac{{(Q_{j,i \pm 1}^m + Q_{j,i}^m)}}{2} Q_{j \pm {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2},i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} = \frac{{(Q_{j \pm 1,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} + Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})}}{2} Q_{j,i \pm {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} = \frac{{(Q_{j,i \pm 1}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}} + Q_{j,i}^{m + {1 \mathord{\left/ {\vphantom {1 2}} \right. } 2}})}}{2}

    求解条件式(23)~(27)应用离散点可分别表达为

    U_{0,i}^m = 0 ( i = 0,1, \cdots ,I ) \text{,} (30)
    U_{J,i}^m = 0 (i = {I_1},{I_1} + 1, \cdots ,{I_2}) \text{,} (31)
    U_{J + 1,i}^m = U_{J - 1,i}^m (i = 0,1, \cdots ,{I_1} - 1\text{,}i = {I_2} + 1,{I_2} + 2, \cdots ,I)\text{,} (32)
    U_{j, - 1}^m = U_{j,1}^m (j = 0,1, \cdots ,J) \text{,} (33)
    U_{j,I - 1}^m = U_{j,I + 1}^m (j = 0,1, \cdots ,J) \text{,} (34)
    U_{j,i}^0 = \frac{{{\gamma _{\text{w}}}H({G_{\text{s}}} - 1)}}{{(1 + {e_0}){{\sigma '}_0}}}j\Delta Z ( j = 0,1, \cdots ,J , i = 0,1, \cdots ,I )。 (35)

    在求得土中超静孔压解答的基础上,可得到土层的最终沉降值{S_\infty }

    {S_\infty } = H - \int_0^H {{{\left( {\frac{{{{\sigma '}_\infty }}}{{{{\sigma '}_0}}}} \right)}^{ - {I_{\text{c}}}}}{\text{d}}a} 。 (36)

    {T_{\text{v}}}_m 时刻土层的沉降值 {S_{{\text{t}}m}}

    {S_{{\text{t}}m}} = H - \frac{H}{J}\sum\limits_{j = 0}^{J - 1} {{{\left( {\frac{{\bar Q_j^m + \bar Q_{j + 1}^m}}{2}} \right)}^{ - {I_{\text{c}}}}}} 。 (37)

    式中: \bar Q_j^m = \frac{1}{{I{\text{ + }}1}}\sum\limits_{i = 0}^I {\left( {1 + \frac{{{\gamma _{\text{w}}}H({G_{\text{s}}} - 1)}}{{(1 + {e_0})}}j\Delta Z - U_{j,i}^m} \right)} j = 0, \cdots ,J - 1 。故按变形定义的平均固结度为{U_{{\text{st}}}} = {{{S_{{\text{t}}m}}} \mathord{\left/ {\vphantom {{{S_{{\text{t}}m}}} {{S_\infty }}}} \right. } {{S_\infty }}}

    土体最终有效应力沿深度在初始构型中分布面积 {A_\infty }

    {A_\infty } = \int_0^H {\sigma (a)} = \frac{{{\gamma _{\text{w}}}({G_{\text{s}}} - 1)}}{{2(1 + {e_0})}}{H^2} 。 (38)

    {T_{\text{v}}}_m 时刻土层平均有效应力沿深度分布面积{A_{{\text{t}}m}}

    {A_{{\text{t}}m}} = \frac{{{\gamma _{\text{w}}}({G_{\text{s}}} - 1)}}{{2(1 + {e_0})}}{H^2} - \frac{{{{\sigma '}_0}H}}{J}\sum\limits_{j = 0}^{J - 1} {\frac{{\bar U_j^m + \bar U_{j + 1}^m}}{2}} 。 (39)

    式中: \bar U_j^m = \frac{1}{{I{\text{ + }}1}}\sum\limits_{i = 0}^I {U_{j,i}^m} j = 0, \cdots ,J - 1。故按孔压定义的平均固结度{U_{{\text{pt}}}} = {{{A_\infty }} \mathord{\left/ {\vphantom {{{A_\infty }} {{A_{{\text{t}}m}}}}} \right. } {{A_{{\text{t}}m}}}}

    Pu等[23]采用半对数坐标系中的线性关系描述土体的非线性压缩渗透关系,获得淤泥自重作用下大应变固结的数值解。将该文献中的半对数模型参数通过换算可得到双对数坐标系中的淤泥非线性压缩渗透模型参数:H=5.0 m,Gs=2.78,{e_0}=5.0,{I_{\text{c}}}=0.071,\alpha =10.80,{k_{{\mathtt{ξ} 0}}}=6.91×10-8 m/s,{\sigma '_0}=0.2 kPa。解答的验证及固结性状分析均采用次土体参数,且淤泥土体渗透各向同性,即\kappa = 1。当未铺设PHD(\lambda =0%)时,本文自重固结模型可退化为单面排水情况下淤泥一维自重固结模型。同理,当PHD完全铺设(\lambda =100%)时,此模型可退化为双面排水情况下的淤泥自重固结模型。将以上两种情况下数值解与已有的淤泥自重大应变固结解进行对比分析,以验证本文模型计算的可靠性。如图 6所示,将两种情况下本文计算的淤泥堆场平均固结度与Pu等[23]计算的平均固结度Ust对比分析,可发现两种情况下的固结曲线完全重合,初步验证了本文固结模型的可靠性。此外,将本文计算结果与文献[23]中0.1,1,2 a的超静孔压沿深度分布开展对比分析,如图 7(a)(b)所示,从图 67中可发现本文计算计算结果与Pu等[23]的计算结果完全重合,这进一步验证了本文固结模型的可靠性。

    图  6  不同排水条件下平均固结度Ust变化曲线
    Figure  6.  Variation curves of average consolidation degree under different drainage conditions Ust
    图  7  不同排水条件下超静孔压随深度变化曲线
    Figure  7.  Comparative curves of excess pore water pressure under different drainage conditions

    堆场高度H=5 m,排水板宽度b=0.1 m保持不变的情况下,图 8为不同PHD铺设率\lambda 下淤泥土层平均固结度Upt随时间的变化曲线。可发现同一时刻淤泥土层平均固结度随PHD板间距的减少而增大,说明堆场底部铺设更密集的PHD可有效减小渗流路径从而加快疏浚淤泥的固结速率。当铺设率大于25%时,淤泥土层的平均固结度随着铺设间距的减小而明显加快;但当铺设率小于25%时,淤泥土层的平均固结速率随着铺设间距的减小而不再发生明显变化。当铺设率为50%时,铺设PHD的淤泥土层平均固结速率基本与底面完全透水边界下自重固结的固结曲线相重合,此时增设PHD不再对固结速率产生影响。而实际工程中更关注施工周期对堆场运转的影响,即对应工况到达一定固结度时所消耗的时间。铺设率为25%时,其到达90%固结度的时间与铺设率为50%时相比,所需时间的差值仅为30 d。这种性状意味着当堆场高度为5 m时,25%的铺设率更接近PHD最佳铺设率(约为27%)。

    图  8  铺设率λ对平均固结度Upt的影响
    Figure  8.  Influences of laying rate of PHDs on average degree of consolidation Upt

    所谓PHD最佳铺设率就是在堆放高度一定的条件下,最终工期达到与双面排水条件相差无几时所对应的铺设率。可以发现,当淤泥堆放高度发生变化时,底层PHD最佳铺设率也必然发生变化。图 9给出了淤泥堆场堆放高度与最佳铺设率间的关系曲线,最佳铺设率随着堆放高度增加而呈现出曲线减小的趋势,堆放高度从10 m减小到1 m,最佳铺设率大约从20%增加至50%。

    图  9  最佳铺设率随高度变化曲线
    Figure  9.  Variation of optimum laying rate with height

    前述分析发现堆放高度对淤泥固结速率有较大影响,图 10为铺设率\lambda = 12.5\% 及堆放高度分别为1.0,2.0 m时超静孔压在计算单元内的分布情况(t=50 d)。铺设PHD加快周围淤泥土层的超静孔压消散,从而加快土层的固结速率。在相同铺设率下,堆放高度1.0 m时疏浚淤泥底部超静孔压的消散速率明显快于高度2.0 m的工况。为进一步分析堆放高度对淤泥自重固结的影响,分别计算堆放高度H为1.0,2.0,3.0,5.0 m下的沉降量和平均固结度随时间变化曲线,如图 11所示。初始厚度为1.0,2.0,3.0,5.0 m时,堆场的最终沉降分别为0.13,0.33,0.55,0.80,1.05 m,沉降过程如图 11(a)所示。堆放高度越大,最终沉降量也越大,原因主要在于即使应变相同,沉降值也会随高度增大而增大,更何况堆放高度的增大导致自重应力增大,进而发生的应变值也会增大。堆放高度越高,淤泥层固结速率越慢,如图 11(b)所示,当淤泥土层厚度为1 m时,其完成90%自重固结所需时间为115 d;当淤泥土层厚度分别为2,3,4,5 m时,自重固结完成90%需要时间分别为1 m淤泥土层所需时间的2.67倍、4.86倍、7.37倍和10.27倍。原因在于堆放高度越高,竖向排水距离也越长,土层完成自重固结所需时间越长。

    图  10  计算单元的超静孔压力分布
    Figure  10.  Distribution of excess pore pressure in calculation unit
    图  11  堆放厚度对固结性状的影响
    Figure  11.  Influences of sludge height on consolidation behaviors

    堆场铺设率\lambda = 12.5\% 、高度H=5 m时,进一步分析Ic\alpha 对固结性状的影响,如图 1213所示,其中Ic\alpha 的变化范围可参见仇超等[24]的分析结果。由图 12可知,Ic=0.1时,UstUpt都随\alpha 的增大而减小,因为\alpha 与土层渗透指数呈反比,所以当\alpha 越大时,土层的渗透性越小,土层的固结效率也越慢。由图 13可知,\alpha =12时,UstUpt都随Ic的减小而增大,Ic越小土层压缩模量越大,其固结效率越快。需特别说明的是,疏浚淤泥堆场按变形定义的平均固结度要大于按孔压定义的平均固结,即淤泥堆场的沉降变形发展要快于其内超静孔压的消散速率。

    图  12  \alpha 对淤泥平均固结度的影响
    Figure  12.  Influences of \alpha on average degree of consolidation
    图  13  Ic对淤泥平均固结度的影响
    Figure  13.  Influences of Ic on average degree of consolidation

    前面已成功建立了疏浚淤泥堆场底部铺设单层PHD的疏浚淤泥大应变非线性固结模型,利用该模型分析了PHD加速疏浚淤泥的固结机理。对疏浚淤泥铺设PHD的实际工况,该大应变非线性固结模型可在2方面进行拓展。

    (1)淤泥堆放高度对PHD处理堆场的固结影响较大,实际工程中,若待处理的疏浚淤泥量过大,亦可增加PHD铺设层数以加快固结[8]。此时,该大应变固结模型的边界条件式(19)可改写为

    {\left. u \right|_{a = {H_i}}} = 0 \left( {\frac{L}{2} \leqslant x \leqslant \frac{L}{2} + b} \right)。 (40)

    式中:{H_i}为第i层铺设PHD的高度,i = 1,2,3, \cdots ,n

    (2)实际中为进一步加速疏浚淤泥的固结,也常使用真空预压联合PHD处理疏浚堆场[10]。此时大应变固结模型的边界条件式(19)可改写为

    {\left. u \right|_{a = H}} = - P \left( {\frac{L}{2} \leqslant x \leqslant \frac{L}{2} + b} \right)。 (41)

    式中:P为施加的真空度(kPa)。

    建立自重作用下平面渗流、竖向应变的PHD处理疏浚淤泥堆场自重固结模型并获得模型的数值解。在验证解答正确性的基础上,得到4点结论。

    (1)铺设PHD会加快淤泥土层超静孔压的消散速率,淤泥固结速率随铺设率\lambda 的增加而加快。

    (2)当铺设率达到一定值后,再增大铺设率对土层固结速率的提高不再明显,其基本达到与双面完全透水的固结速率,该值为PHD最佳铺设率。PHD的最佳铺设率随着堆放高度增加而曲线减小。

    (3)底层铺设PHD后堆放高度越高,最终沉降量越大,固结速率越慢。在工程实际中,如果堆放高度较高时可通过增设PHD层数以加快其固结速率。

    (4)Ic一定时,土层固结速率随\alpha 减小而加快;\alpha 一定时,土层固结速率随Ic减小而加快。按变形定义的淤泥平均固结度快于按孔压定义的平均固结度,即淤泥的变形发展快于超静孔压的消散过程。

  • 图  1   高压缩性淤泥的非线性压缩曲线

    Figure  1.   Nonlinear compression curves of sludge with high compressibility

    图  2   堆场自重固结及计算单元示意图

    Figure  2.   Schematic diagram of self-weighted consolidation and calculation unit of yards

    图  3   Lagrangian坐标系中淤泥自重固结分析示意图

    Figure  3.   Schematic diagram of self-weighted consolidation in Lagrangian coordinate system

    图  4   单元体渗流示意图

    Figure  4.   Schematic diagram of seepage in soil element

    图  5   计算单元的离散网格

    Figure  5.   Discretization grid of calculation unit

    图  6   不同排水条件下平均固结度Ust变化曲线

    Figure  6.   Variation curves of average consolidation degree under different drainage conditions Ust

    图  7   不同排水条件下超静孔压随深度变化曲线

    Figure  7.   Comparative curves of excess pore water pressure under different drainage conditions

    图  8   铺设率λ对平均固结度Upt的影响

    Figure  8.   Influences of laying rate of PHDs on average degree of consolidation Upt

    图  9   最佳铺设率随高度变化曲线

    Figure  9.   Variation of optimum laying rate with height

    图  10   计算单元的超静孔压力分布

    Figure  10.   Distribution of excess pore pressure in calculation unit

    图  11   堆放厚度对固结性状的影响

    Figure  11.   Influences of sludge height on consolidation behaviors

    图  12   \alpha 对淤泥平均固结度的影响

    Figure  12.   Influences of \alpha on average degree of consolidation

    图  13   Ic对淤泥平均固结度的影响

    Figure  13.   Influences of Ic on average degree of consolidation

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  • 收稿日期:  2023-04-03
  • 刊出日期:  2024-10-31

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