An efficient edge based data structure for the compressible Reynolds-averaged Navier–Stokes equations on hybrid unstructured meshes

An efficient edge based data structure has been developed in order to implement an unstructured vertex based finite volume algorithm for the Reynolds-averaged Navier–Stokes equations on hybrid meshes. In the present approach, the data structure is tailored to meet the requirements of the vertex based algorithm by considering data access patterns and cache efficiency. The required data are packed and allocated in a way that they are close to each other in the physical memory. Therefore, the proposed data structure increases cache performance and improves computation time. As a result, the explicit flow solver indicates a significant speed up compared to other open-source solvers in terms of CPU time. A fully implicit version has also been implemented based on the PETSc library in order to improve the robustness of the algorithm. The resulting algebraic equations due to the compressible Navier–Stokes and the one equation Spalart–Allmaras turbulence equations are solved in a monolithic manner using the restricted additive Schwarz preconditioner combined with the FGMRES Krylov subspace algorithm. In order to further improve the computational accuracy, the multiscale metric based anisotropic mesh refinement library PyAMG is used for mesh adaptation. The numerical algorithm is validated for the classical benchmark problems such as the transonic turbulent flow around a supercritical RAE2822 airfoil and DLR-F6 wing-body-nacelle-pylon configuration. The efficiency of the data structure is demonstrated by achieving up to an order of magnitude speed up in CPU times.     

石墨基液流电池复合双极板

液流电池是一种安全性高、使用寿命长、可扩展的大规模储能系统,可以协助电网调峰储能,提高能源利用率,发展前景广阔。双极板是液流电池的重要组成部分。功能上起到了分隔、串联电池、传导电流、为电堆提供结构支撑等作用。从成本构成角度看,双极板的价格占电堆成本的比重也较大。开发高性能、低成本的双极板对加快液流电池的商业化应用具有重要意义,也是目前业界的迫切需求。虽然文献上报道了许多针对液流电池双极板开发的工作,但是目前高性能、低成本的液流电池双极板产品仍无法充分满足市场需求。本文着重介绍了石墨基复合双极板的研究现状,介绍了材料选择、工艺流程对关键性能的影响,对相关工作进行了评述,并为液流电池双极板的开发提出了建议。     

Prediction of the drag reduction effect of pulsating pipe flow based on machine learning

Prediction of drag reduction effect caused by pulsating pipe flows is examined using machine learning. First, a large set of flow field data is obtained experimentally by measuring turbulent pipe flows with various pulsation patterns. Consequently, more than 7000 waveforms are applied, obtaining a maximum drag reduction rate and maximum energy saving rate of 38.6% and 31.4%, respectively. The results indicate that the pulsating flow effect can be characterized by the pulsation period and pressure gradient during acceleration and deceleration. Subsequently, two machine learning models are tested to predict the drag reduction rate. The results confirm that the machine learning model developed for predicting the time variation of the flow velocity and differential pressure with respect to the pump voltage can accurately predict the nonlinearity of pressure gradients. Therefore, using this model, the drag reduction effect can be estimated with high accuracy.     

Fluid‐structure coupling of linear elastic model with compressible flow models

Cavitation erosion is caused in solids exposed to strong pressure waves developing in an adjacent fluid field. The knowledge of the transient distribution of stresses in the solid is important to understand the cause of damaging by comparisons with breaking points of the material. The modeling of this problem requires the coupling of the models for the fluid and the solid. For this purpose, we use a strategy based on the solution of coupled Riemann problems that has been originally developed for the coupling of 2 fluids. This concept is exemplified for the coupling of a linear elastic structure with an ideal gas. The coupling procedure relies on the solution of a nonlinear equation. Existence and uniqueness of the solution is proven. The coupling conditions are validated by means of quasi‐1D problems for which an explicit solution can be determined. For a more realistic scenario, a 2D application is considered where in a compressible single fluid, a hot gas bubble at low pressure collapses in a cold gas at high pressure near an adjacent structure.     

An approach of dynamic mesh adaptation for simulating 3‐dimensional unsteady moving‐immersed‐boundary flows

In this paper, we present an approach of dynamic mesh adaptation for simulating complex 3‐dimensional incompressible moving‐boundary flows by immersed boundary methods. Tetrahedral meshes are adapted by a hierarchical refining/coarsening algorithm. Regular refinement is accomplished by dividing 1 tetrahedron into 8 subcells, and irregular refinement is only for eliminating the hanging points. Merging the 8 subcells obtained by regular refinement, the mesh is coarsened. With hierarchical refining/coarsening, mesh adaptivity can be achieved by adjusting the mesh only 1 time for each adaptation period. The level difference between 2 neighboring cells never exceeds 1, and the geometrical quality of mesh does not degrade as the level of adaptive mesh increases. A predictor‐corrector scheme is introduced to eliminate the phase lag between adapted mesh and unsteady solution. The error caused by each solution transferring from the old mesh to the new adapted one is small because most of the nodes on the 2 meshes are coincident. An immersed boundary method named local domain‐free discretization is employed to solve the flow equations. Several numerical experiments have been conducted for 3‐dimensional incompressible moving‐boundary flows. By using the present approach, the number of mesh nodes is reduced greatly while the accuracy of solution can be preserved.     

Experimental and numerical analysis of cylindrical turbulators in a double pipe heat exchanger under turbulent flow conditions

In the present work, the use of cylindrical turbulators in a double pipe heat exchanger has been investigated. Cylindrical fin type of turbulators has been placed circumferentially separated by 90° on the outer side of an inner pipe at a regular pitch. Experimental studies were undertaken for different air flow rates in a turbulent regime whose Reynolds number range between 2500 and 10000. Heat transfer characteristics like Nu and friction factor have been experimentally determined. Parametric studies were conducted by changing the pitch and also the orientation of the turbulators. Nu and friction factor were found to increase as the pitch is reduced. A model with alternatively changed orientation outperformed others by exhibiting highest Nu and reduced friction factor.     

Quinones for redox flow batteries

Quinones are electroactive species that have shown great promise for redox flow batteries due to the ability to tune their properties and to act as both negative and positive electrolytes. The following review outlines highlights of work in the last couple of years working to provide materials with higher stability, solubility, and performance. Developments toward stable negolytes have provided opportunities for potential commercial opportunities when paired with alternate chemistries. However, the stability of quinones in high potential electrolytes is still not sufficient and the number of potential quinones limited.