In this study, a novel experimental setup is proposed for which a column filled with glass beads and parallelepiped-shaped limestone beams is used to reconstruct a multiple fracture limestone media. The proposed setup produces asymmetric breakthrough curves (BTCs) that are consistent with the shape expected from the past field and lab-scale studies. Three transport experiments have been conducted under fast, medium, and slow flow velocity conditions.

The research focuses on parameter and state estimation using Bayesian inference via Markov Chain Monte Carlo (MCMC) sampler, investigating the degree to which three models of transport through fractured media can reproduce the experimental results under the three flow conditions. The first transport model, named ADE, is based on the equivalent porous medium (EPM) approach and corresponds to the linear advection dispersion equation (ADE). The second model, named FOMIM (first-order mobile immobile), is based on the mobile/immobile approach and uses the dual porosity model with a linear first-order transfer between mobile and immobile regions. The third model, named NLMIM (non-linear mobile-immobile), uses a nonlinear transfer function between these two regions.

The results of the three models show that almost all the unknown model input parameters can be well-estimated with narrow confidence intervals using the MCMC method. With respect to state estimation, the ADE model fails to reproduce correctly the tail of the BTCs observed under slow and medium flow conditions. The FOMIM model improves the tailing of the BTCs, but significant discrepancies remain between simulated and measured concentrations. The NLMIM model with velocity-dependent parameters is the only model that captures BTCs under all three conditions of slow, medium, and fast flow velocities.

在这项研究中，提出了一种新颖的实验装置，其中使用填充有玻璃珠和平行六面体形石灰石梁的柱子来重建多裂缝石灰岩介质。所提出的设置产生了与过去现场和实验室规模研究预期的形状一致的不对称突破曲线 (BTC)。已经在快速、中等和慢速流速条件下进行了三个传输实验。

该研究侧重于通过马尔可夫链蒙特卡罗(MCMC) 采样器使用贝叶斯推理进行参数和状态估计，研究三种通过断裂介质的传输模型在三种流动条件下重现实验结果的程度。第一个传输模型，名为 ADE ，基于等效多孔介质 (EPM) 方法，对应于线性对流扩散方程 (ADE)。第二个模型，名为 FOMIM（一阶移动不动），基于移动/不动方法，并使用双孔隙度模型，在移动和不动区域之间进行线性一阶转移。第三个模型，命名为 NLMIM（非线性移动-不动），在这两个区域之间使用非线性传递函数。

三个模型的结果表明，几乎所有未知的模型输入参数都可以使用 MCMC 方法以窄置信区间很好地估计。关于状态估计，ADE 模型无法正确再现在慢速和中等流量条件下观察到的 BTC 尾部。FOMIM 模型改善了 BTC 的拖尾，但模拟浓度和测量浓度之间仍存在显着差异。具有速度相关参数的 NLMIM 模型是唯一能够在慢、中和快流速所有三种条件下捕获 BTC 的模型。