Fast Prediction Method for Steady‐State Heat Convection

Sun

2017

Energies

Reduced-order modeling approaches for gas flow in dual-porosity dual-permeability porous media are studied based on the proper orthogonal decomposition (POD) method combined with Galerkin projection. The typical modeling approach for non-porous-medium liquid flow problems is not appropriate for this compressible gas flow in a dual-continuum porous media. The reason is that non-zero mass transfer for the dual-continuum system can be generated artificially via the typical POD projection, violating the mass-conservation nature and causing the failure of the POD modeling. A new POD modeling approach is proposed considering the mass conservation of the whole matrix fracture system. Computation can be accelerated as much as 720 times with high precision (reconstruction errors as slow as 7.69 × 10 −4 %~3.87% for the matrix and 8.27 × 10 −4 %~2.84% for the fracture).

“…Substitute Equations (15) and (16) and the boundary conditions to Equations (11) and (12), and the projection equations can be expressed as follows:…”

Section: Model Derivation Via the Typical Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Acceleration of Gas Flow Simulations in Dual-Continuum Porous Media Based on the Mass-Conservation POD Method

Sun

2017

Energies

“…Proper orthogonal decomposition (POD) can reduce computational loads efficiently via a reduced-order model. It has been applied to heated-crude-oil pipe flow [17,18] and other fields [19][20][21]. Ghommem et al [22,23] and Efendiev et al [24] discussed the POD and dynamic mode decomposition method for time-dependent incompressible single-phase flow in highcontrast heterogeneous porous media.…”

Section: Introductionmentioning

confidence: 99%

Acceleration of Gas Reservoir Simulation Using Proper Orthogonal Decomposition

2018

Geofluids

High-precision and high-speed reservoir simulation is important in engineering. Proper orthogonal decomposition (POD) is introduced to accelerate the reservoir simulation of gas flow in single-continuum porous media via establishing a reduced-order model by POD combined with Galerkin projection. Determination of the optimal mode number in the reduced-order model is discussed to ensure high-precision reconstruction with large acceleration. The typical POD model can achieve high precision for both ideal gas and real gas using only 10 POD modes. However, acceleration of computation can only be achieved for ideal gas. The obstacle of POD acceleration for real gas is that the computational time is mainly occupied by the equation of state (EOS). An approximation method is proposed to largely promote the computational speed of the POD model for real gas flow without decreasing the precision. The improved POD model shows much higher acceleration of computation with high precision for different reservoirs and different pressures. It is confirmed that the acceleration of the real gas reservoir simulation should use the approximation method instead of the computation of EOS.

“…The POD technique has been widely used in the study of heat and mass transfer (Wang et al, 2012d). Mahapatra et al (2016) used the POD to assess the energy content of buoyancy-driven flow in an air-filled enclosure under different Ra numbers and switching frequencies.…”

Section: Introductionmentioning

confidence: 99%

Using proper orthogonal decomposition to solve heat transfer process in a flat tube bank fin heat exchanger

Xia

et al. 2017

Adv. Geo-Energ. Res.

Proper orthogonal decomposition (POD) reduced-order model can save computing time by reducing the dimension of physical problems and reconstructing physical fields. It is especially suitable for large-scale complex problems in engineering, such as ground heat utilization, sea energy development, mineral exploitation, multiphase flow and flow and heat transfer with complex structure. In this paper, the POD reduced-order model was used to calculate the heat transfer in a flat tube bank fin heat exchanger. The calculating results of the finite volume method (FVM) were adopted as the snapshot samples. SVD method was used to decompose the samples to obtain a series of bases and corresponding coefficients on sampling conditions. With these coefficients, interpolation method was used to calculate the coefficients on predicting conditions. And the physical field has been reconstructed using the bases and the interpolated coefficients directly.In the calculation of heat transfer unit of flat tube fin heat exchanger, air-side Reynolds number, transverse tube spacing and the fin spacing were chosen as the variables. The results obtained by the POD method are in good agreement with the results calculated by the FVM. Moreover, the POD reduced-order model presented in this paper is more advantageous in comparison with the FVM in terms of accuracy, suitability, and computational speed.Keywords: Proper orthogonal decomposition (POD), POD reduced-order model, flat tube bank fin heat exchanger, interpolation method, reconstructed temperature field.Citation: Wang, Y., Xia, X., Wang, Y., et al. Using proper orthogonal decomposition to solve heat transfer process in a flat tube bank fin heat exchanger.