.png){kind=icon}
.png){kind=icon}
Return
Modelling saline intrusion using dynamic mesh optimization with parallel processing
.png){kind=icon}
OA
AI
DOI：10.1016/j.advwatres.2022.104189.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Saline intrusion (SI) in coastal aquifers is a global problem with the potential to contaminate groundwater used by over a billion people. Numerical modelling of SI in coastal aquifers is a key tool for risk assessment, aquifer management and resource regulation, but is extremely challenging because the mixing zone across the saline front is often very narrow, extending over metres or 10's metres, yet the saline front itself may extend laterally over a large (i.e. many km) three-dimensional (3D) domain. Moreover, the aquifer may be highly heterogeneous, further complicating the movement and geometry of the front. We test here the use of dynamic mesh optimization (DMO) in a parallel computational framework to simulate SI with higher accuracy and lower computational cost compared to fixed-mesh approaches. The framework uses a double control-volume-finite element (DCVFE) method and is implemented in the open-source Imperial College Finite Element Reservoir SimulaTor (IC-FERST), but could be implemented in other FE-based simulators. We confirm accuracy and convergence using test cases based on the classic 'Henry' SI problem, demonstrating that solutions obtained using DMO require significantly fewer elements and therefore have much lower computational cost compared to equivalent fixed mesh solutions. We apply the framework to a realistic 3D case study simulating saline intrusion in a heterogeneous chalk aquifer, demonstrating simulation speed-up in excess of 120x. We suggest that parallelized DMO offers significant advantages over existing methods to simulate SI.
Keywords:
Coastal aquifers
Saline intrusion
Numerical modelling
Unstructured mesh
Dynamic mesh optimization
Computational cost
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.2
Papers:
4.5K
Citations:
1.5W