Mass Flow Rate Research Articles

Thermal management for microelectronic chips under non-uniform heat flux with supercritical CO2

With the rapid growth of information technology and the evolution in the use of microelectronic chips, these components are facing major challenges of high heat dissipation and inhomogeneous heat flux. To address the hotspot issues, a combination of microchannel heat sinks (MCHS) with cavity-rib designs and supercritical fluids is a potential solution. This study compares the thermo-hydraulic properties of water and supercritical carbon dioxide (sCO2) under various boundary conditions and hotspot locations during non-uniform heating. The results showed that sCO2 can effectively improve temperature uniformity along the heat sink in the presence of hotspots as compared to water. Considering a mass flow rate of 600 kg/(m2·s), the inhomogeneity index of the basal temperature of sCO2 is found to be 0.24, significantly lower than 4.22 for water. This indicates that sCO2 eliminates hot spots by rapidly increasing specific heat capacity near the pseudo-critical temperature. Furthermore, it is noted that maintaining the operating temperature of sCO2 near the pseudo-critical temperature can increase the specific heat capacity of the fluid in a short time, in addition to reducing the corresponding density and viscosity. Consequently, the entropy generation rate of sCO2 under ideal conditions is 46.6 % of that of water. Therefore, the proposed combination of a microchannel of complex structure and sCO2 in this study is demonstrated to effectively reduce the influence of hot spots and improve the overall thermal performance of heat sinks.

Flow-field analysis and performance assessment of rotating detonation engines under different number of discrete inlet nozzles

This study explores in depth rotating detonation engines (RDEs) fueled by premixed stoichiometric hydrogen/air mixtures through two-dimensional numerical simulations including a detailed chemical kinetic mechanism. To model the spatial reactant non-uniformities observed in practical RDE combustors, the referred simulations incorporate different numbers of discrete inlet nozzles. The primary focus here is to analyze the influence of reactant non-uniformities on detonation combustion dynamics in RDEs. By systematically varying the number of reactant injection nozzles (from 15 to 240), while maintaining a constant total injection area, the study delves into how this variation influences the behavior of rotating detonation waves (RDWs) and the associated overall flow field structure. The numerical results obtained here reveal significant effects of the number of inlets employed on both RDE stability (self-sustaining detonation wave) and performance. RDE configurations with a lower number of inlets exhibit a detonation front with chaotic behavior (pressure oscillations) due to an increased amount of unburned gas ahead of the detonation wave. This chaotic behavior can lead to the flame extinguishing or decreasing in intensity, ultimately diminishing the engine's overall performance. Conversely, RDE configurations with a higher number of inlets feature smoother detonation propagations without chaotic transients, leading to more stable and reliable performance metrics. This study uses high-fidelity numerical techniques such as adaptive mesh refinement (AMR) and the PeleC compressible reacting flow solver. This comprehensive approach enables a thorough evaluation of critical RDE characteristics including detonation velocity, fuel mass flow rate, impulse, thrust, and reverse pressure waves under varying reactant injection conditions. The insights derived from the numerical simulations carried out here enhance the understanding of the fundamental processes governing the performance of RDE concepts.

Dynamic analysis for ultra-supercritical boiler water wall considering uneven heat flux distribution and combustion instability

The dynamic characteristics of water-cooled wall are of great significance to the evaluation of the safety and flexibility for the boiler during peak shaving process. However, few dynamic studies considered the uneven heat flux distribution on the water-cooled wall, let alone the variable heat load caused by the combustion instability. In this paper, a segmented dynamic model is developed for the water-cooled wall of a 660 MW ultra supercritical boiler. The model is validated under steady and dynamic working conditions, respectively. Then, the step responses of the steam temperature in different flow loops under different load conditions are comparatively studied under the disturbances of single-parameter changes. In the cases of 10 % step decrease of either the feedwater temperature, the heat load or the feedwater mass flowrate, the outlet steam temperature is influenced greatly by the step decreased feedwater temperature under 100 % BMCR condition, while it is impacted most by the step decreased feedwater mass flow under 50 % THA condition. Under these disturbances, the outlet steam temperature of the tube with higher heat loads has larger variation and longer response time. In addition, the simulated combustion instability by the sinusoidal fluctuating heat load on the water wall is employed to explore the influences of the flame fluctuation amplitude and frequency to the water wall. The maximum steam temperature rises with the increase in amplitude but drops with the frequency of flame fluctuation. The thresholds for the flame fluctuation amplitude and frequency are obtained under different load conditions.

Research on input parameter optimization for NOx deep learning prediction model

Optimizing the input parameters for NOx prediction model is instrumental in enhancing the precision and efficacy of the prediction model. This paper focuses on the input variables of the data-driven diesel engine NOx prediction model. According to the diesel engine NOx generation mechanism, at first relevant variables are selected, then the similarity method and parameter sensitivity method are compared to optimize the input variables. Firstly, this paper conducted a real-road emission test of a heavy-duty diesel vehicle, and proposed a data-driven deep learning model for predicting diesel engine NOx emissions based on the experimental data. The experimental data were processed using an Attention-Mechanism based Convolutional Neural Networks-Long Short-Term Memory (AM-CNN-LSTM) model. Subsequently, input parameters were selected according to the sensitivity weights assigned to each parameter in the preliminary model. This approach refined the modeling data and excluded variables not pertinent to NOx emission prediction. The AM-CNN-LSTM model prediction performance has been improved with 2% increase of model R2 as well as the model training time is reduced by 23%, and the types of parameters required to train the model are reduced by 50%. It accomplished this by effectively reducing data dimensions, discarding non-essential variables for NOx prediction, and diminishing computational complexity. Six input parameters were identified as pivotal in reconstructing the modeling data for accurate NOx prediction: engine speed, torque, EGR valve position, exhaust flow rate, air mass flow rate, and oil temperature. In optimizing the NOx prediction model, it is crucial to determine an optimal number of input parameters. Excessive parameters do not enhance model accuracy, while an insufficient number impairs the model’s ability to precisely emulate the NOx generation process, leading to diminished predictive accuracy.

Quantitative analysis of hydrogen leakage flow measurement and calculation in the on-board hydrogen system pipelines

The mass flow rate of hydrogen leakage directly affects hydrogen diffusion and concentration distribution. In this paper, a test platform was constructed to measure mass flow rates during hydrogen leakage in the supply pipelines of the on-board hydrogen system. Hydrogen leakage tests were conducted under two different conditions. Mass flow rates were measured for tube fittings with various loosening angles and hydrogen supply pressures. The data were then fitted to extrapolate mass flow rates of hydrogen leakage beyond the tested conditions. Additionally, mass flow rates were measured for hydrogen supply pipelines with small holes of different shapes and sizes. The effects of pipeline size, hydrogen supply pressure, hole shape, and size on the hydrogen leakage mass flow rate were analyzed. Hydrogen leakage flow coefficients were corrected, and the accuracy of three calculation methods for hydrogen leakage flow was compared and analyzed based on the test results. The results provide a foundation for future numerical simulation models of hydrogen leakage diffusion.

A novel bionic lotus leaf channel liquid cooling plate for enhanced thermal management of lithium-ion batteries

Battery Thermal Management Systems (BTMS) are pivotal in safeguarding the safety, efficiency, and lifespan of electric vehicles. In this study, we propose a bionic lotus leaf (BLL) channel liquid-cooled plate to mitigate temperature accumulation issues observed during lithium-ion battery (LIB) discharge. The primary objective is to enhance heat dissipation and achieve uniform temperature distribution within LIBs. We investigated the impact of different interior configurations and mass flow rates on individual lithium-ion battery (LIB) temperatures using single-variable analysis. Our findings indicate that higher inlet mass flow rates effectively lower the temperature increase in individual LIBs, albeit at the cost of inducing a significant pressure drop.The optimal parameter combination is determined through orthogonal analysis. Specifically, the channel angle (α) and inlet mass flow rate (M) are found to significantly influence the maximum temperature (Tmax) of LIBs. The number of channels (N) is optimized to enhance temperature distribution and reduce maximum temperature variation (ΔTmax) within LIBs. Furthermore, adjusting the channel width (D) substantially mitigated pressure drop (ΔP) in the BLL channel liquid cooling plate, thereby improving hydraulic pump efficiency. The identified optimal combination (M = 1.0 g s-1, N = 4, D = 2.5 mm, α = 90°) ensures that Tmax remains below 29.732 °C even during a 5C discharge, a critical requirement. Compared to a traditional serpentine channel with equivalent heat transfer area and inlet mass flow, the optimized BLL channel showed a decrease in Tmax by 0.776 °C, ΔTmax reduction by 2.445 °C, and ΔP reduced to only 43.44 % of that in the serpentine channel. The BLL channel proposed in this research can serve as a valuable reference for BTMS.

Thermodynamic analysis of supercritical CO2 power generation system for waste heat recovery with impurities in CO2

Waste heat recovery from gas turbines is an effective method for meeting the demand for a more efficient and cleaner energy system with decreased CO2 emissions and lower environmental pollution. The supercritical CO2 Brayton cycle is a promising power conversion system for waste heat recovery. The advantage of the supercritical CO2 Brayton cycle can be attained based on its physical characteristics. However, when another fluid is mixed as an impurity in a system using pure CO2, physical characteristics of working fluid was changed and operation at the design point can be challenging. Therefore, it is important to verify the purity of CO2 and understand the effect of impurities in CO2 in advance. This study examined the effects of impurities in the working fluid of a supercritical CO2 power generation system for actual demonstration facilities. The effect of impurity, a CO2-based mixture, in a supercritical CO2 power generation system on waste heat recovery from an LM500 gas turbine was investigated. A purity test of industrial grade CO2, which was noted as 99.9 % pure by the supplier, was conducted to verify the composition of the working fluid. The results of the purity test showed that the supplied CO2 consisted of 99.076 % CO2 along with nitrogen, argon, oxygen, water, and methane. Based on the results of the purity test, sensitivity analyses of the CO2-based binary mixtures and industrial mixtures were performed. A design point analysis was conducted for the CO2-based industrial mixture in comparison with pure CO2, which has cycle efficiency of 16.15 %, gross power of 510.03 kW, mass flow rate of 12.55 kg/s, and waste heat recovery of 2119.06 kW. In the case of fixed waste heat with mass flow rate of 14.417 kg/s, the cycle efficiency decreased by 0.39 % and gross power increased by 66.14 kW. In the case of fixed mass flow rate with 1844.598 kW waste heat, the cycle efficiency decreased by 0.32 % and gross power decreased by 9.84 kW. In addition, the influence of the performance of the major components on the system performance was investigated.

EXPERIMENTAL INVESTIGATION AND CFD SIMULATION OF THE ORIFICE FLOW METER TO MEASURE TWO-PHASE FLOW

In this study, an investigation is conducted to examine various methods for measuring the two-phase flow of water and air. The two-phase flow loop and its equipment, including the orifice flow meter, were designed and manufactured in accordance with relevant standards. By employing the orifice flow meter in the two-phase flow loop and determining the total mass flow rate of the two-phase flow passing through it, the pressure drop of the orifice flow meter was determined for different values of the flow rate and volume fractions of the water and air phases in the two-phase flow. The Reynolds number of the two-phase flow ranged from 700 to 11000, while the air volume fraction ranged from 10% to 45%. We observed that, for the orifice flow meter, the slope of the discharge coefficient variation in relation to the two-phase flow Reynolds number was higher at low Reynolds numbers, where a laminar flow pattern was established. As the two-phase flow Reynolds number increased, the flow pattern transitioned from laminar to plug flow, resulting in a decrease in the slope. The orifice flow meter under two-phase flow conditions was simulated using computational fluid dynamics (CFD) with different turbulence models. The results indicated that the k-epsilon RNG turbulence model yielded more accurate results compared to other turbulence models. This study provides a foundation for the measurement of two-phase flows in the oil and gas industries.

Investigation of diesel particulate filter performance under typical failure conditions

Diesel particulate filter (DPF) is one of the most effective particulate reduction components in diesel engine aftertreatment systems. However, prolonged utilization of a DPF might result in a deterioration in performance or even failure, such as ash-clogging, melting, breakage, and catalyst deactivation. It is crucial to conduct research on DPF performance degradation across a series of partially failed conditions. In this study, the morphology and chemical composition of the ash in the DPF samples were characterized. The effects of degree-varying clogging and unplugged-breakage failure on exhaust characteristics as well as DPF temperature, filtration and pressure drop characteristics were investigated. Finally, the sensitivity differences between DPF performance parameters and failure index parameters were examined using a canonical correlation analysis (CCA). When four factors were considered, the ash loading index and breakage index had the greatest impact on DPF temperature difference and filtration efficiency, while the exhaust mass flow rate had the greatest impact on pressure drop. Besides, the influence of the DPF inlet temperature on the pressure drop, filtration efficiency, and temperature difference was not significant. These findings contribute to the prediction of DPF performance in partially failed conditions and the development of DPF failure diagnosis methods.

Optimizing the performance parameters of vacuum evaporation technology for management of anaerobic digestate in a waste water treatment plant using fuzzy MCDM method

Evaporation technology in waste water treatment plants is used to treat excess liquid digestate, eventually reaping the essential nutrients from the process. In the present study, the input conditions have been optimized for implementing and achieving optimal performance of the digestate evaporation technology used in waste water treatment plants by employing fuzzy multi-criteria decision making method. Three input parameters, namely the Temperature, the Pressure, and the Mass Flow rate, each at three levels are considered. Experiments are conducted as per the Taguchi’s L9 standard orthogonal array. The performance of the evaporator is examined based on a few response characteristics, such as payback period, thermal energy consumption, power consumption and cost per unit of electricity. Temperature's impact on multi performance stands out significantly, contributing the most (70.52 %), followed by mass flow rate (18.95 %), and pressure (5.37 %). Result of the study reveals that within the investigated range of input parameters, temperature at 80 ℃, pressure at 0.3 bar and mass flow rate at 20 kg/h is the optimal combination. The results of the present study will help in enhancing the efficiency and effectiveness of the evaporation process, leading to improved digestate treatment that supports circular economy initiatives.

A novel dual-split layout for transcritical CO2 power cycle adapted to variable heat sources

Transcritical CO2 power cycle is widely used as the bottom cycle of natural gas engine to recover waste heat. However, owing to the large variation in waste heat sources caused by changes in engine operating conditions, the adaptability of the CO2 power cycle is poor, reflected in severe performance deterioration in thermal match, components and system power output. Hence, to improve the adaptability of the CO2 power cycle to wide-range fluctuation in heat sources, a novel dual-split configuration is proposed in this paper. The freedom of regulation is effectively enhanced by the supplementary split branches, and the mass flow rate through different heat exchangers can be actively adjusted with high flexibility. Furthermore, off-design performance models and a calculation procedure are built to present the off-design performance of the different cycles under the engine operational profile. The results indicate that the proposed configuration can improves the adaptability of the CO2 cycle to fluctuating heat sources effectively. Specifically, for all engine operational conditions, the invalidated operating region was contracted from eight to four points, with the engine coolant and exhaust gas utilisation rates exceeding 90 % and 97.4 % respectively. In addition, under low engine operating conditions, the cycle pressure ratio and mass flow rate were maintained at relatively high values, contributing to enhanced pump and turbine efficiencies. The maximum net power output increased by 8.3 kW, and the minimum brake-specific fuel consumption decreased by 16.9 %.

Advanced model for a non-adiabatic capillary tube considering both subcooled liquid and non-equilibrium two-phase states of R-600a: {FR}Modèle avancé pour un tube capillaire non adiabatique prenant en compte à la fois les états de liquide sous-refroidi et de deux phases en non-équilibre du R-600a.

Previous empirical correlations have largely failed to predict the mass flow rate variations of R-600a during the transient pull-down operation of household refrigerators. This shortcoming is attributed to the fact that these correlations were developed for specific thermodynamic states of the refrigerant at the capillary inlet, whereas the thermodynamic state varies during transient operations, particularly involving non-equilibrium two-phase states. To address these limitations, a novel model has been developed. This model comprises two distinct sub-models corresponding to the refrigerant state at the capillary tube inlet: one for the subcooled liquid state and the other for the non-equilibrium two-phase state. These sub-models are integrated to account for the transitions in the thermodynamic state of R-600a at the capillary inlet. The integrated model demonstrates excellent agreement with observed variations in the R-600a mass flow rate during the pull-down operation of actual refrigerators. The mean absolute percentage error between the measured and estimated mass flow rates is approximately 10% over the entire period of pull-down operations tested under various environmental conditions.

Predictive modeling of flow characteristics in supersonic separators using machine learning

In the pursuit of cleaner energy sources, pre-processing fuel streams is crucial before distribution. Challenges arise during this process, leading to operational issues and diminished transmission efficiency. Among different technologies, supersonic separators are the ones that separate undesired components from the main gas stream more effectively. Precise forecasting of nozzle flow rate and shockwave location at a low cost can markedly enhance the efficiency of manufacturing and rating. In this research, the one-dimensional method has been developed to solve flow equations simultaneously by implementing equations of state. CFD has been used for the verification of the developed model, and the effect of different equations of state is investigated. Results show that the one-dimensional model significantly reduces the calculation time. Different EOSs result in up to 2.0 % and 3.5 % variation in the prediction of shock location and the mass flow rate, respectively.A machine learning methodology is employed to predict the location of shockwaves and the choked flow rate at an even lower cost. A dataset of 160 entries, generated using Peng Robinson's EOS, serves as the basis for this analysis. Prediction tasks are executed using Random Forest, k-nearest Neighbors, and Multilayer Perceptron models. While all three models demonstrate proficiency in data interpolation with R2 scores up to 0.9962 and 0.9951 for the shockwave location and mass flow rate, respectively, discerning their performance in extrapolation appears contingent on the specific case. In the case of extrapolation, Multilayer Perceptron and k-Nearest Neighbors show better match to one-dimensional results.

The mechanism of proppant transport dynamic propagation in rough fracture for supercritical CO2 fracturing

Supercritical CO2 fracturing technology has shown great potential for enhancing production in unconventional reservoirs. It is essential to clarify the transport mechanism of proppant under the dynamic propagation conditions within rough fractures. A realistic rough fracture model is reconstructed, and Computational Fluid Dynamics simulations are conducted to track proppant movement during fracture propagation. The typical transport characteristics of proppant within rough fractures are revealed, and the effects of fracture propagation rate, proppant density, mass flow rate, particle size, sand ratio, and temperature on the support effect are discussed. The results show that the flow channels formed by sand carrying fluid in rough fractures are complex, with fracture propagation changing some flow channels. The proppant forms an irregular sand bed interspersed with unfilled areas, and complex flow characteristics are generated. The increase in fractal dimension increases the resistance in the fluid flow process and affects the movement of the proppant, which tends to create unfilled areas. Low density and size of proppant can improve the proppant placement length. In a certain temperature range, high temperature injection of sand carrying fluid can improve the proppant placement effect. In addition, the low sand ratio and high mass flow rate pumping can be used to form the dominant channel, followed by pumping with a high sand ratio and low mass flow rate for effective support.

The evaluation of hydrogen production of a multistage cooling system's performance

In the present research, a new cycle of scramjet open recuperator cooling to produce power and hydrogen is presented. In which, the power generation subsection uses the waste heat in the scramjet cooling process as a cycle heat source and produces electric power. In this research, some of the power generated in the cycle is used to power a Polymer Electrolyte Membrane (PEM) electrolyzer that produces hydrogen. An analysis of the energy and exergy has been conducted to assess the system's performance. With a fuel mass flow rate of 0.45 kg/s, the cooling capacity of the system is 10.2 MW, net power production is 4.1 MW, and 45.1 kg/h of hydrogen is produced. The exergy analysis revealed that the PEM electrolyzer had the highest exergy loss at over 48%, followed by the first cooling path at over 32%. The energy and exergy efficiency of the system are 14.2% and 19.2%, respectively. The parametric study indicated that increasing the mass flow rate leads to higher power production and cooling capacity. Additionally, at a constant fuel mass flow rate, power production increases with higher pressure behind the pump.

Experimental Study on the Mass Flow Rate Characteristics of a Fluidized Bed Powder Fuel Feeding System

In this study, a fluidized bed powder fuel feeding system that controls flow using the principle of two-phase gas-solid choking is proposed. Experiments based on real-time weighing methods were conducted to explore the flow rate characteristics under various total pressure and throttle-orifice area conditions. The experimental results showed that as the total pressure increased, the powder flow rate first decreased and then increased. To achieve the same increase in powder mass flow rate by altering the pressure, fine powder requires a greater pressure increment than coarse powder. A choked flow formula based on the gas-solid two-phase nonequilibrium model was derived, for investigating the influence of these two factors on the powder flow rate. Compared with the experimental results, this formula predicts the powder flow rates within a 20 % error margin. This model provides more precise guidance for engineering designs. The studied powder fuel-feeding system was connected to a powder engine, and hot-fire tests were conducted. The results showed that the pressure fluctuation in the powder engine combustion chamber did not exceed 2.5 %, confirming the feasibility and stability of the powder supply in the fluidized bed powder fuel feeding system.

Heat transfer performance of regenerative cooling in the presence of supersonic combustion based on two-way decoupling method

As a promising active cooling method for aero engines, regenerative cooling with endothermic hydrocarbon fuel plays an important role in thermal protection systems. However, simply assuming the thermal boundary conditions for the numerical simulation of regenerative cooling as either Dirichlet or Neumann boundary conditions is often unsuitable, as the combustion process exhibits complex three-dimensional (3D) characteristics. We propose a novel multi-step iterative calculation method in this work to simulate the coupled flow and heat transfer between supersonic combustion in the combustor and regenerative cooling outside. The method captures the main features of the supersonic combustion including different shockwave structures, and generates a realistic 3D distribution of heat flux as the boundary condition for the regenerative cooling study. With improved simulation, the result shows that regenerative cooling significantly reduces the peak temperature of the combustor by 58.5% with a mass flow rate of 1 g/s. A local high-temperature region is observed on the coupled wall inside the combustor near the injector, where the flame is primarily concentrated. Increasing the mass flow rate by 100%, from 1 g/s to 2 g/s, leads to a reduction in the maximum wall temperature by up to 15.7%.

Numerical investigation on cavitation erosion and evolution of choked flow in a tri-eccentric butterfly valve

The tri-eccentric butterfly valve is widely utilized in the petrochemical, nuclear, and metallurgy industries due to its robust sealing performance and great pressure resistance. When the local static pressure is lower than the saturation vapor pressure, the fluid phase is transformed into vapor, and cavitation occurs. Cavitation intensifies and the bubbles generated by cavitation severely hinder the flow when the inlet pressure remains constant and the outlet pressure further decreases. This phenomenon is known as choked flow. Choked flow is a derivative phenomenon of cavitation, which seriously threatens the lifetime of valves and the safety of the operation system. In this paper, a multiphase flow of the tri-eccentric butterfly valve is modeled to investigate the choked flow characteristics. The numerical results based on the proposed model are in good agreement with the experiments. The effect of the pressure drop on the mass flow rate and flow coefficient is studied and the liquid pressure recovery factor of the tri-eccentric butterfly is determined at the certain valve opening degree based on the Schnerr and Sauer cavitation model. The relationship between the pressure ratio and choked flow is studied by pressure and velocity contours. The susceptible erosion locations and primary causes of erosion for the butterfly valve at the certain valve opening degree are investigated. By comparison of the distribution of the vapor volume fraction and vortex structures, the spatial correlation between vortex and choked flow is revealed. Meanwhile, the effect of the pressure ratios on the average vapor volume fraction at 70% and 100% valve opening degrees is studied. The evolution of choked flow in the tri-eccentric butterfly is revealed and the cause of choking is pointed out.

Unlocking optimal performance and flow level control of three-phase separator based on reinforcement learning: A case study in Basra refinery

This research explores the application of a new reinforcement learning (RL-based) controller for a three-phase separator connected to a gas turbine. The control of flow levels within the separator directly impacts fluid flow turbulence, especially when the equipment is linked to waste heat gas from the turbine to improve gas quality. The study introduces the novel RL-based controller and validates its effectiveness in real-world conditions using three-phase separators in Basra, Iraq, and through a review of relevant literature. The controller can adapt to inlet conditions such as pressure, temperature, mass flow rate, and incoming heat from the gas turbine. Waste heat recovery from the gas can enhance gas purity but also increase turbulence in water and oil. Maintaining a calm flow while ensuring high-speed flow over the baffle in the middle of the separator is crucial for optimal performance. The study considers two geometrical configurations of the vessel for redesigning the separator at the Basra refinery. The controller was implemented using the groovyBC utility within the OpenFOAM software. This model was then utilized to simulate real-world scenarios at the Basra refinery, displaying faster convergence, more rapid response, and more accurate tracking of the target fluid level. This study marks the initial effort to apply the deep deterministic policy gradient (DDPG) controller in computational fluid dynamic (CFD) work. The findings demonstrated a significant enhancement in separation efficiency by more than 36%, as well as smoother streamlines through the control and maintenance of pressure and velocity over the baffle.

Experimental investigation of seeping gas film cooling effect at downstream wall in hypersonic flow

Generating a seeping gas film through porous material to cover the downstream wall can achieve a large-area thermal protection from aerodynamic heating for the windward surfaces of hypersonic vehicles. This study explores the cooling efficiency of the seeping gas film downstream of the porous wall through experimental research. It introduces a continuous high-temperature wind tunnel heat flux calculation method and investigates the influence of cooling gas injection rate and blowing length on downstream wall cooling efficiency. Additionally, an engineering evaluation of the thermal protection effect of the seeping gas film on the downstream wall of the flat plate boundary layer is conducted. Experimental findings demonstrate that cooling efficiency decreases rapidly along the flow direction, and an increase in the cooling gas injection rate enhances the cooling efficiency downstream of the porous wall, while the attenuation rate of cooling efficiency in the downstream region accelerates with higher injection rates. Moreover, a rise in injection rate results in a reduction of the effectiveness-cost ratio in the upstream region, with the seeping gas film’s effectiveness-cost ratio being relatively high at an injection rate of 0.2 %. Longer blowing lengths enhance the cooling efficiency at the end of the porous wall but accelerate the attenuation rate of cooling efficiency along the flow direction. Conversely, under constant blowing length, a higher injection rate contributes to a faster attenuation rate of cooling efficiency downstream. Assessment of the thermal protection effect for different combinations of blowing lengths (20 ∼ 60 mm) and injection rates (0.1 %∼0.5 %) reveals that layouts featuring shorter blowing lengths and higher injection rates demonstrate superior cooling effects downstream of the porous wall when supplied with the same mass flow rate.