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The purpose of this study is to investigate the coherent structures of pulsed opposing jets by large eddy simulation (LES) model and proper orthogonal decomposition (POD) snapshot method. Flow pulsation as an active flow control method is considered for the enhancement of transport phenomena in impinging jets. The effect of flow pulsation parameters such as pulsation signal shape and frequency on the vortical coherent structures, the energy content of primary modes and their variation are studied numerically.

In this study, flow field of turbulent pulsating opposing jets has been simulated using LES. The result of the simulation in different time steps (snapshots) are stored and POD is applied on the snapshots. In this study, the POD method and calculation of spatial modes has been done using OpenFOAM, and time coefficients have been calculated using a MATLAB code.

The results of this study show that the flow excitation has a great effect on the coherent structure formation and the energy containment of fundamental modes of the flow. When the flow was excited by a harmonic sinusoidal or step function, the turbulent kinetic energy accumulated in the set of primary modes. On the other hand, the pulsed opposing jets had more regularity compared to the steady jets. The shapes, patterns and energy values of dominant modes depended on the inlet pulsation signal. An increase in pulsation frequency leads to an augmentation in energy content of the primary modes.

The predictions may be extended to include various pulsation conditions such as: various amplitudes, Reynolds number and aspect ratio.

The results of this study are a valuable source of information for active control of transport phenomena in opposing jet configurations which is used in different industrial applications such as cooling, combustion, reactors, heating and drying processes.

In this study, the coherent structures and energy content of primary modes was studied for the first time by LES model and POD snapshot method and a comprehensive discussion on numerical results is provided.

The purpose of this paper is to examine entropy generation rate in the flow and temperature field due pulsed impinging jet on to a flat plate. Heat transfer of pulsed impinging jets has been investigated by many researchers. Entropy generation is one of the parameters related to the second law of thermodynamics which must be analyzed in processes with heat transfer and fluid flow in order to design efficient systems. Effect of velocity profile parameters and various nozzle to plate distances on viscous and thermal entropy generation are investigated.

In this study, the flow and temperature field of a pulsed turbulent impinging jet are simulated numerically by the finite volume method with appropriate boundary conditions. Then, flow and temperature results are used to calculate the rate of entropy generation due to heat transfer and viscous dissipation.

Results show that maximum viscous and thermal entropy generation occurs in the lowest nozzle to plate distance and entropy generation decreases as the nozzle to plate distance increases. Entropy generation in the two early phase of a period in the most frequencies is more than steady state whereas a completely opposite behavior happens in the two latter phase. Increase in the pulsation frequency and amplitude leads to enhancement in entropy generation because of larger temperature and velocity gradients. This phenomenon appears second and even third peaks in entropy generation plots in higher pulsation frequency and amplitude.

The predictions may be extended to include various pulsation signal shape, multiple jet configuration, the radiation effect and phase difference between jets.

The results of this paper are a valuable source of information for active control of transport phenomena in impinging jet configurations which is used in different industrial applications such as cooling, heating and drying processes.

In this paper the entropy generation of pulsed impinging jet was studied for the first time and a comprehensive discussion on numerical results is provided.

In the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan.

Based on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan.

The authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs.

Future research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice.

The Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the energy cooperation road unusually tortuous, Kazakhstan in Central Asia has natural geographical and resource advantages, so China–Kazakhstan energy cooperation as a new era of opportunity, providing a strong guarantee for China's political and economic stability. The basic idea of building large-scale nuclear power plants in Balkhash and Aktau is put forward, considering the development strategy of building Kazakhstan into a regional international energy base. This work will be a good inspiration for the investment of nuclear generation.

This study solves the problem of increasing noise by combining Monte Carlo simulation with geometric Brownian motion under complex conditions, adds the measure of investment flexibility and strategic value, constructs the utility function of noise reduction weight based on Gaussian radial basis function and extends the nonlinear problem to the evaluation of nuclear power investment benefit.