The cooling efficiency of flat film was measured using a high-precision infrared thermal imager, and the film cooling efficiency between double-cross-row holes and single row holes is compared. The interaction between film holes and the influence of blowing ratio (M=0.65, 1.0, 1.5) and density ratio (DR=1.0, 1.5) on the cooling efficiency was analyzed. Moreover, the flow field with film cooling was compared using numerical calculation methods. The results show that, with the increase of the blowing ratio, the cooling efficiency of the single row holes decreases while that of the double-cross-row holes improved greatly, but the film coverage effect at the spanwise direction deteriorates. Increasing the density ratio will improve the cooling performance. However, the influence of double rows of film holes and blow ratio is much higher on the cooling effectiveness, compared with the density ratio. For the double rows of film holes cooling, the cooling jet forms a reverse kidney-shaped vortex downstream of the holes, which will prevent the jet blowing away from the cooling wall.

In wind turbines, the aerodynamic efficiency of wind turbines is closely related to the aerodynamic performance of excellent airfoils. Taking the conventional airfoil of wind turbine as the research object, combined with airfoil parametric modeling and self-adaptive genetic algorithm, the high performance optimized airfoil is obtained. The fitting accuracy of the conventional NACA63418 airfoil is compared between the CST method and the improved Hicks-Henne type function method, and then the Hicks-Henne type function method is selected to model the NACA63418 airfoil. The automatic calculation of aerodynamic characteristics of airfoil is realized by the coupling of self-adaptive genetic algorithm and XFOIL software, and the design efficiency of airfoil is improved. It broadens the train of thought and improves the design efficiency for the theoretical design of airfoils.

Under oceanic conditions, the coolant in the loop of a floating nuclear reactor (FNR) experiences periodic fluctuations, which affects the system’s thermal and hydraulic characteristics. A combination of theoretical derivation and numerical simulation is employed to investigate the velocity and temperature distribution characteristics within a pipe under pulsating flow conditions. Moreover, the influence of different numerical simulation boundary conditions on the velocity and temperature distribution in a circular tube under pulsating flow is compared. The results show that, under high-frequency pulsating flow conditions, laminar flow inside the pipe will experience backflow near the wall, and the wall effect will increase with the pulsation frequency. Using pulsating velocity inlet and pressure outlet as numerical simulation boundary conditions fails to predict this backflow phenomenon. However, employing fluctuating pressure inlet and flow outlet effectively captures the backflow occurrence in high-frequency pulsating flow. Concurrently, the temperature within the pipe fluctuates under pulsating flow conditions, and the amplitude of temperature fluctuations gradually decreases when the pulsation frequency increases. Numerical simulation can well simulate the temperature distribution in the pipe under pulsating flow conditions, with an error of less than 2%.The research results can provide reference for non-stationary numerical simulation methods.

Accurate carbon emissions data of gas units is one of the guarantees to ensure carbon trading. Many gas units recently installed online gas chromatography devices, so that the carbon emission is able to be real-time monitored from fuel part. For units that are not equipped with flue gas CO₂ monitoring system or have no enough equipment space, conversion with flue gas O₂ concentration is one of the feasible paths to monitor carbon emission from flue gas part. But whether direct measurement or conversion monitoring methods, there is still a lack of sufficient research on the deviation of continuous monitoring data from the fuel part and flue gas part. Therefore, for the gas units without capability to directly monitor flue gas CO₂ in the short term, this study takes the historical data of an F-class gas-steam combined cycle unit for the simulation, and conducts continuous simulation monitoring and analysis based on the conversion with flue gas O₂ concentration and online gas chromatography. It is found that there is no stable sorting rule of the monthly data and the relative deviation between different calculation methods. All the relative deviation of annual data is less than 5%. The correlation between δ_{RD,R,fluegas-flue-h} and the O₂ concentration of CEMS is the highest. The deviation of carbon emission amount in the unit is mainly in the stable combustion section with a load ratio of more than 55%. In accordance with current standards or specifications, the O₂ concentration of CEMS and the wet flue gas flow rate at the chimney outlet is most likely to cause the deviation of carbon emission amount from the fuel part and flue gas part. Under the existing technical specifications, the carbon emission from fuel part and flue gas part can be monitored in real time, which can be used for analysis on trend, but only the uncertainty of result from fuel part is below 5%. For gas units, the carbon emission monitored at fuel part is more appropriate, and the method monitoring the flue gas part may be more suitable for coal-fired units.

In order to meet the demand of estimating regional heat load for cogeneration enterprises, an estimation method using elastic network regression model is proposed. Firstly, the influencing factors of the actual heating heat index are analyzed to determine the input parameters of the model. Then, based on the actual operation data of 123 residential areas in Xi’an in the heating season from 2022 to 2023, the estimation model is established, and it is proved that the accuracy of the model is higher than that of Lasso regression and ridge regression models. Finally, part of the communities in Xi’an are selected to form a verification set to verify the elastic network regression model. The verification results show that, the elastic network regression model combines the advantages of Lasso regression and ridge regression, and has higher prediction accuracy than the conventional machine learning model. The MAE and goodness of fit of the model are 1.150 and 0.953, respectively, indicating that the method can accurately estimate the actual heating heat index with different parameters, and can meet the actual engineering needs of cogeneration enterprises.

The real gas characteristics of supercritical carbon dioxide (S-CO₂) make it difficult to obtain stable convergence results in three-dimensional numerical simulation of S-CO₂ centrifugal compressor, and the time cost of numerical calculation further increases the difficulty of compressor design optimization. To establish a flow calculation method suitable for S-CO₂ centrifugal compressor, three-dimensional numerical simulation is carried out on the compressor to obtain the flow field information and corresponding loss distribution. Then, the one-dimensional loss model is superimposed in the conventional flow line curvature method, and the CO₂ compression factor is calculated in segments along the flow line, thus to reflect the real gas compression process. Comparison between the calculation results and the three-dimensional numerical simulation results shows that, the distribution of meridian relative velocity field and enthalpy obtained by streamline curvature method are consistent with the computational Fluid dynamics (CFD) results. The temperature and pressure data at the blade outlet are close to the CFD results, with errors of 0.23% and 1.08%, respectively, and a difference of 1.5% in total static isentropic efficiency. The results indicate that the performance parameters of S-CO₂ centrifugal compressor impeller can be obtained quickly and accurately by using streamline curvature method.

The conventional flexible retrofit plan for coal motor sets is difficult to eliminate the potential life loss and equipment safety risks caused by frequent and rapid load changes to the thermal system. In order to improve the long-term safety and economy of coal-fired power units participating in deep peak shaving, a “healthy peak shaving” technical route for coal-fired power units based on hydrogen energy storage system is proposed, with a domestic ultra supercritical secondary reheat 1 000 MW coal-fired unit as the application object. The indirect carbon emission reduction significance of peak shaving coal-fired power hydrogen production is demonstrated. On this basis, the matching degree between different hydrogen production processes and the production conditions of coal-fired power plants were analyzed. It was believed that solid oxide electrolysis cell (SOEC) hydrogen production was the comprehensive optimal plan. Based on this, a principle design scheme for SOEC coupled coal-fired power peak shaving was proposed. Finally, a financial analysis was conducted on the new plan using the annual load curve. The calculation results indicate that, the SOEC assisted deep peak shaving of coal-fired power can increase the annual revenue of the example unit by 236 million yuan, and obtain other benefits such as equipment lifespan extension, consumption reduction, and carbon reduction. The relevant conclusions have reference significance for guiding the healthy and safe operation of peak shaving coal-fired power units.

With the increasing annual growth of wind and solar power generation, the issue of power consumption has become increasingly prominent. Meanwhile, high-capacity thermal power plants face relatively high auxiliary power loads, resulting in additional operating costs. To address these issues, a joint optimization dispatch model for wind-PV-thermal-storage for auxiliary power system of thermal power plant is developed based on the concept of multi-energy complementarity. Firstly, the compositional structure of the wind-PV-thermal-storage integrated power supply for auxiliary power of thermal power plants is outlined, prioritizing the supply of auxiliary power loads with wind power and photovoltaic power. Secondly, a wind-PV-thermal-storage integrated power supply optimization scheduling model is developed, taking into account the operating costs of thermal power units at different load rates and the costs associated with wind power, photovoltaic power, and energy storage. A hierarchical analysis method is employed to establish a multi-objective function based on the total cost, wind and solar curtailment costs, and environmental costs, while considering corresponding constraint conditions. Finally, various scenarios are set up to compare and analyze the optimization results of the integrated power supply system for auxiliary power. Experimental results demonstrate that the proposed model for the integrated power supply system can effectively reduce unit operating costs and environmental costs, as well as promote the integration of wind and photovoltaic power.

With the advancement of intelligent mining construction, the number of application systems is gradually increasing, and problems such as incomplete data unification, lack of overall management of the system, and repetitive construction of functions are becoming prominent. To avoid these issues, this article takes the Yimin open coal mine data center as an example to analyze the overall architecture of the coal mine data center in detail. Based on the industrial private cloud development platform and big data technology, an open, continuous integration and deployment data center is established, and it supports high load elastic scaling and meets the concept of intelligent open-pit mine management. The data center solves problems such as difficulty in data collection in the mining field, inability to store data uniformly, isolated business systems, and inability to share data conveniently and in a timely manner among mining surveying professionals. It also comprehensively utilizes the collected equipment and system data to achieve real-time control of production status and equipment status, improving management decision-making ability and means.

H₂S is an important product produced by power plant boilers in the process of low NO_x combustion. To solve the problems that H₂S may cause various hazards to thermal power plants due to its inflammability, strong corrosion and extreme toxicity, tunable diode laser absorption spectroscopy (TDLAS) method combined with multi-pass cell and computer is employed to build an online measurement system for detecting the molar fraction of low-concentration gas. By using this measurement system, accurate online measurement of H₂S in the mixed gas with the molar fraction of 10^–6 magnitude is realized, and the H₂S high-temperature reaction experiment is carried out to explore the influence of experimental temperature and the molar fraction of O₂ in the mixed gas on the reaction. The experimental results show that, under the conditions of pressure of 80 kPa and molar fraction of O₂ ranging from 0 to 5%, the temperature at which H₂S begins to react changes with the molar fraction of O₂. On the whole, the higher the molar fraction of O₂ in the mixed gas, the lower the temperature at which H₂S begins to react. The experimental results can provide some data basis for the generation, transformation and harm control of H₂S in boiler flue gas.