In this work, we study two scenarios of the Universe filled by a perfect fluid following the traditional dark energy and a viscous fluid as dark matter. In this sense, we explore the most simple case for the viscosity in the Eckart formalism, a constant, and then, a polynomial function of the redshift. We constrain the phase-space of the model parameters by performing a Bayesian analysis based on Markov Chain Monte Carlo method and using the latest data of the Hubble parameter (OHD), Type Ia Supernovae (SNIa) and Strong Lensing Systems. The first two samples cover the region \(0.01<z<2.36\). Based on AIC, we find equally support of these viscous models over Lambda-Cold Dark Matter (LCDM) taking into account OHD or SNIa. On the other hand, we reconstruct the cosmographic parameters (q, j, s, l) and find good agreement to LCDM within up to \(3\sigma \) CL. Additionally, we find that the cosmographic parameters and the acceleration-deceleration transition are sensible to the parameters related to the viscosity coefficient, making of the viscosity an interesting physical mechanism to modified them.

在这项工作中，我们研究了宇宙的两种情况，这些情况是遵循传统暗能量的理想流体和作为暗物质的粘性流体填充的。从这个意义上讲，我们探索了Eckart形式主义中最简单的粘度情况，即常数，然后是红移的多项式函数。我们通过基于马尔可夫链蒙特卡罗方法进行贝叶斯分析，并使用哈勃参数（OHD），Ia型超新星（SNIa）和强透镜系统的最新数据来约束模型参数的相空间。前两个样本覆盖区域\（0.01 <z <2.36 \）。基于AIC，考虑到OHD或SNIa，我们发现这些粘性模型同样优于Lambda-Cold Dark Matter（LCDM）。在另一方面，我们重建cosmographic参数（q，  j，  s，  l）并在不超过\（3 \ sigma \） CL的情况下找到与LCDM的良好协议。另外，我们发现，宇宙学参数和加速-减速转变对与粘度系数有关的参数很敏感，这使粘度成为修改它们的有趣的物理机制。