Application of an h-adaptive finite element model for wind energy assessment in Nevada

Pepper, Darrell W.; Wang, Xiuling

doi:10.1016/j.renene.2006.08.011

Cited by 17 publications

(5 citation statements)

References 14 publications

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“…The terrain surface plot, topographic contours, and tower locations are shown for the region near Whitney Mountain in central NV in Figure 12a,b [26].…”

Section: Comparison Resultsmentioning

confidence: 99%

A Localized Meshless Technique for Generating 3-D Wind Fields

Pepper

Gonzalez

2018

Computation

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Abstract:A localized meshless method is used to simulate 3-D atmospheric wind fields for wind energy assessment and emergency response. The meshless (or mesh-free) method with radial basis functions (RBFs) alleviates the need to create a mesh required by finite difference, finite volume, and finite element methods. The method produces a fast solution that converges with high accuracy, establishing 3-D wind estimates over complex terrain. The method does not require discretization of the domain or boundary and removes the need for domain integration. The meshless method converges exponentially for smooth boundary shapes and boundary data, and is insensitive to dimensional constraints. Coding of the method is very easy and can be done using MATLAB or MAPLE. By employing a localized RBF procedure, 3-D wind fields can be established from sparse meteorological data. The meshless method can be easily run on PCs and hand-held mobile devices. This article summarizes previous work where the meshless method has successfully simulated 3D wind fields over various environments, along with the equations used to obtain the simulations.

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“…The terrain surface plot, topographic contours, and tower locations are shown for the region near Whitney Mountain in central NV in Figure 12a,b [26].…”

Section: Comparison Resultsmentioning

confidence: 99%

A Localized Meshless Technique for Generating 3-D Wind Fields

Pepper

Gonzalez

2018

Computation

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“…After determining the indicator, the process of mesh refinement, as the second step in adaptive technique, can be executed. In general, adaptive methods can be roughly classified into three categories (Pirzadeh, 2000;Pepper and Wang, 2007): grid movement (r-refinement), grid enrichment (h-refinement), and local solution enhancement (p-refinement). Each method has its own merits and shortcomings (Pepper and Wang, 2007;Li et al, 2010).…”

Section: Mesh Refinement Processmentioning

confidence: 99%

“…This paper is organized as follows: in Section 2, the governing equations and methodologies for numerical discretization are briefly described. Section 3 depicts the solution-adaptive mesh refinement approach which involves the selection of the adaptation function and the h-refinement strategy (Pepper and Wang, 2007) based on body-fitted quadrilateral/hexahedral mesh. Section 4 presents three numerical examples to validate the present approach.…”

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confidence: 99%

A total energy-based adaptive mesh refinement technique for the simulation of compressible flow

Xu¹,

Chen²,

Han³

et al. 2023

Front. Energy Res.

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In this paper, an adaptive mesh refinement technique is presented for simulation of compressible flows, which can effectively refine the mesh in the regions with shock waves and vortices. The present approach uses the total energy per unit volume as an indicator to capture the shock waves and vortical structures. In the approach, an h-refinement strategy is adopted. To save the computational effort, the flow variables on the new mesh are obtained from the previous step by interpolation, which ensures that the problem is always solved on the refined mesh. Both inviscid and viscous compressible flows are considered in this work. Their governing equations are, respectively, Euler equations and Navier–Stokes equations associated with the implementation of the Spalart–Allmaras turbulence model. The cell-centered finite volume method and Jameson scheme are chosen to carry out spatial discretization, and the five-stage Runge–Kutta scheme is applied to discretize the temporal derivative. The present approach is applied to simulate three test problems for its validation. Numerical results show that it can effectively capture the shock waves and vortices with improvement in solution accuracy.

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“…A very extended dynamical downscaling model is the PSU/NCAR fifthgeneration Mesoscale Model (MM5) which calculates atmospheric characteristics in a regional scale (NCAR, 2011). In wind resource assessment, the MM5 output is frequently used as initial and boundary conditions of microscalar models which insert local considerations in the mesoscalar simulation (Fueyo et al, 2010;Pepper and Wang, 2007).…”

Section: Nwp Datamentioning

confidence: 99%