Optimum Nozzle Research Articles

Numerical studies on structure optimization and flow characteristics of a hydrogen recirculation ejector under multiple load conditions

Ejectors are ideal hydrogen recirculation devices for PEMFC systems but typically exhibit poor recirculation performance at low loads. For purpose of extending ejector's operating range in vehicular applications, the entraining performance across multiple loads should be focused. In this study, A 40 kW ejector was designed with a 1D theory and optimized using a 2D CFD model. Simulations were conducted to study the influence of various diameter and axial dimensions on the ejector's performance and flow characteristics. The results reveal that as the load increases from 20% to 100%, the suboptimal diffuser exit diameter decreases from 2.5 to 1.5 times the mixing chamber diameter, the optimal nozzle exit position increases from 0.59 to 0.63 times, and the optimal mixing chamber length increases from 2.2 to 4.3 times. A convergent nozzle with a short throat significantly improves low-load entraining performance and achieves the highest performance growth in the variable-nozzle design. Additionally, an optimization method for axial dimensions based on the proposed parameter flow uniformity was established, allowing for precise determination of the optimal dimensions through a few simulations.

Dynamics of non-Newtonian fluid–fiber interactions and void formation mechanism based on fused filament fabrication

Due to the presence of internal defects such as voids in the composites manufactured by material extrusion additive manufacturing (MEX AM), the mechanical properties of the composites are significantly below the theoretical optimum. Under this circumstance, this paper is intended to investigate the effects of nozzle feeding angles and to analyze the void formation and evolution of multiphase flow, in which systematic computational fluid dynamics numerical simulations are conducted. The volume of fluid model and overset grid method are used to simulate the extrusion deposition process of carbon fiber-reinforced polymer composites, and the Carreau model is used to represent the shear-thinning behavior of molten polymer. The numerical method is validated against previously experimental and numerical simulation data. The numerical results show that the key factor leading to void formation is the vortices caused by fiber oscillation. The intense vortex at the front end of the fibers disrupts the interface between molten polymer and air, creating a beneficial condition for air to enter. Nozzle tilting can effectively reduce the probability of void formation by decreasing the fiber oscillation velocity. The results of the present study provide insights into the development and optimization of printer nozzles to enable the printing of longer fibers with less probability of potential void formation.

Computational fluid dynamics (CFD) simulation modeling for the cultivation of microalgal monoculture in axenic enclosed bubble column photobioreactor (BCPBR)

Researchers are more concerned with axenic-enclosed PBRs, where there is less or no chance of contamination during the production of biochemical and highly valuable metabolites, and monocultures of microalgae are being grown more frequently. It is a closed, manufactured vessel that aids in the photosynthesis of microalgal cells using artificial light or sunlight as the energy source. In this study, the bubble column PBR (BCPBR) was selected because it possessed some advantages over other PBRs for the growth of Chlorella vulgaris. The BCPBR system prevents contact between the enclosed microalgal cells and the environment, allowing the culturing of microalgae species that are difficult to grow in open pond systems. To compare BCPBR performance quantitatively, the efficient mixing expected in BCPBR, as discussed in the literature, was applied to the CFD model. The experimental results observed during the cultivation of C. vulgaris with restaurant wastewater (RWW) in BCPBR clearly showed better mixing, high growth, and improved treatment efficiency. CFD analysis was conducted on the evolution of bubbles in the BCPBR. The Pressure-Implicit with Splitting of Operators (PISO) pressure correction method is used for velocity and pressure coupling. A geo-reconstruct approach is used to construct the interface, and a second-order upwind calculation technique is used to determine the flow parameters. Therefore, CFD simulation in this study will contribute to the following aspects: (i) the volume fraction contours and velocity contours are going to validate the experimental study as the homogenous mixing favors the growth and productivity, (ii) To study how the size of the nozzle and inlet velocity affect the turbulence generated by bubbles in a BCPBR to identify the optimal nozzle size and velocity for the required turbulence.

Spray performance simulation and experiment analysis of a greenhouse fixed-pipe twin-fluid cold fogger with different nozzle settings.

High-efficient pesticide application equipment for protected cultivation is scarce. In response, a fixed-pipe twin-fluid clod fogger (FTCF) was proposed as a potential solution. To investigate the optimal nozzle layout and spray performance, a computational fluid dynamics (CFD) model was used to study the airflow distribution and spray deposition of a FTCF with different nozzle settings using the Euler-Lagrange approach. Specifically, two piping configurations, middle-cross-inverted (MCI) and bilateral-malposed-opposite (BMO), were combined with three nozzle spacings (2 m, 3 m, 4 m) resulting in six nozzle settings. Additionally, a greenhouse spray trial was conducted to test the performance of FTCF with the selected nozzle settings and to validate the model. The simulation results revealed that MCI piping configuration exhibited a stronger airflow disturbance compared to BMO configuration, indicating a more significant air-guided effect in the MCI configuration. Combining this finding with the ground droplet distribution analysis of MCI piping configuration, it was observed that MCI-2 m had the lowest coefficient of variation (CV) for ground deposition (20.56%). Consequently, MCI-2 m was determined as the most optimal nozzle setting. Verification results demonstrated a high consistency between experimental and simulated spray deposition results. The FTCF system effectively generated a three-dimensional airflow field throughout the greenhouse environment. Furthermore, jet flow produced by FTCF disrupted the overall airflow pattern within the greenhouse space which facilitated droplet suspension and dispersion. This study provides valuable insights and innovative ideas for enhancing pesticide application technologies in protected cultivations. © 2024 Society of Chemical Industry.

Optimizing Vane Number for Enhanced Performance of Mist Blower Nozzle in Agricultural Spraying

The objective of this study is to optimize the number of vanes equipped in the propeller of a mist blower's nozzle. Performance tests were conducted on the approved sprayer test bed, also known as a patternator, to measure several parameters, including effective spraying discharge, effective spraying width, spraying angle, effective spraying height, effective spraying range, droplet diameter, and droplet density. The vane number was optimized using the weighting method. The results indicate that increasing the number of vanes used is directly correlated with higher values of effective spraying width (ESW), spraying angle, effective spraying range (ESR), and droplet density. Conversely, it is inversely correlated with the value of effective spraying discharge (ESD), effective spraying height (ESH), and droplet diameter. The vane number was optimized using the weighting method. The most effective results in the mist blower performance test are achieved by using 12 vanes. This configuration produces droplets with a diameter of 195.44 ±9.68 μm and a density of 320 ± 17.44 droplets/cm2. The mist blower also has ESW of 136 ± 1.73 cm, ESH of 68.14 ± 4.19 cm, ESD of 4.41 ± 0.14 L/min, and ESR of 5.76 ± 0.04 m. Keywords: Agricultural spraying, Mist blower, Nozzle optimization, Performance evaluation, Vane number.

Comprehensive Evaluation of Printing Process Parameters and Tensile Properties of Coconut Polypropylene Filament Composites in Additive Manufacturing

The printing process parameters are important in producing coconut polypropylene (CcPP) products by filament composite in the additive manufacturing industry. Fused deposition modeling techniques in 3D printing applications have considered multiple parameters to meet good finishing parts. This study uses comprehensive measurements to identify the best printing parameter for evaluating the composite properties. Complete deposition, unwrapping, good finishing, and adequate heat are the qualitative printing process parameters used to finalize the optimum nozzle and bed temperature of the CcPP filament composite. The range between 50⁰C to 80⁰C and 225⁰C to 245⁰C for bed and nozzle temperatures were used to achieve a well surface and successful production. After multiple trials of printing the CcPP filament composite, the optimal bed and nozzle temperatures were found to be 80°C and 230°C, respectively. Two types of infill density were used to analyze the effect on the tensile properties of CcPP filament composite. The result showed that 50% infill density was higher for both 1% and 5% fiber loading than 25% infill density for tensile strength with 15.65 and 22.87 MPa compared to 12.93 and 16.59 MPa. The same pattern as the score of Young’s moduli of 50% infill density was higher than 25% infill density for 1% and 5% fiber loadings with 479.52 and 641.23 MPa compared to 400.17 and 493 MPa. Qualitative and quantitative measurements of printing process parameters and properties help reduce the time and cost and benefit 3D printer users in the industry.

Effects of Nozzle Temperature on Mechanical Properties of Polylactic Acid Specimens Fabricated by Fused Deposition Modeling.

This paper investigates the effect of nozzle temperature, from 180 to 260 °C, on properties of polylactic acid (PLA) samples manufactured by fused deposition modeling (FDM) technology. The main objective of this research is to determinate an optimum nozzle temperature relative to tensile, flexural and compressive properties of printed specimens. After manufacturing, the samples exhibit an amorphous structure, without crystallization effects, independently of the fabrication temperature. In order to determine the influence of printing temperature on mechanical properties, uniaxial tensile, three-point flexural and compression strength tests were carried out. The obtained results suggest that a relative low printing temperature could reduce the material flow and decrease the density of the final prototype, with a negative effect on both the quality and the mechanical properties of the pieces. If temperature increases up to 260 °C, an excess of material can be deposited, but with no significant negative effect on mechanical parameters. There is an optimum nozzle temperature interval, depending on the considered piece and test, for which mechanical values can be optimized. Taking into account all tests, a recommended extruder temperature interval may be identified as 220-240 °C. This range encompasses all mechanical parameters, avoiding the highest temperature where an excess of material was observed. For this printing temperature interval, no significant mechanical variations were appreciated, which corresponds to a stable behavior of the manufactured specimens.

Prediction of gas-solid nozzle performance based on CFD and response surface methodology

In this work, structural parameters and performance prediction of fan nozzles for powder spraying are investigated. Computational Fluid Dynamics (CFD) was used to simulate the working process of the grooved fan nozzle. A Box-Behnken experimental model was developed to analyze the effects of the structural parameters on the nozzle air flow stability and working performance, taking the nozzle structural parameter contraction angle (α), the ratio of outlet to inlet diameter (d/D), the ratio of outlet diameter to length (L2/d), and the half angle of the “V”– shaped groove (β). The air flow stability and working performance of nozzle were evaluated through coefficient of variation (Cv) and standard deviation (SD). Using multiple regression analysis, the prediction model of Cv and SD on the structural parameters is established. It was obtained that: with the increase of the diameter and length of the nozzle outlet, the spray angle of the nozzle decreases. As the “V”– shaped groove angle increases, the powder spray angle decreases. The effects of structural parameters on Cv are d/D, α, β, and L2/d in ascending order, and on SD are d/D, α, β, and L2/d in ascending order. In addition, the influence of the interaction of each structural parameter on Cv and SD was obtained. This study can provide a reference for the design and structural optimization of fan nozzles for powder spraying.

Shape optimization of annular transonic thrust nozzles via genetic algorithm and adjoint method

In this research, the idea of combining the genetic algorithm and adjoint method was proposed to leverage the benefits of both approaches to improve the accuracy of thrust nozzle shape optimization. Although the genetic algorithm can search the entire design space to approach the global optimum, its computational cost increases considerably with the number of design variables. Meanwhile, the adjoint method is unaffected by the design variables, but it cannot achieve the global optimum directly and relies on the initial guess geometry. To address these challenges, a genetic algorithm was initially employed to approximate the global optimal geometry of a thrust nozzle with a conical center body parameterized by a Bezier curve. A MATLAB code integrated the geometry parameterization, genetic algorithm, and Fluent R2 2021 flow solver. The resulting geometry was then considered as the initial guess for the adjoint method, which accurately achieved the final optimal geometry with increased control points. The genetic algorithm aimed to maximize the thrust coefficient as the objective function, while the adjoint solver aimed to minimize the axial velocity variance at the nozzle outlet as the cost function. Three distinct constraints were incorporated in the optimization process, and the influence of the center body shape on the results was thoroughly examined to consider all possible geometries throughout the optimization procedure. The findings revealed that the conical center body effectively adjusted the flow angle at the exit, significantly affecting the thrust force. Both optimization steps reduced the average velocity and increased the average pressure at the nozzle exit, enhanced the mass flow rate, and finally increased the thrust force. The genetic algorithm and adjoint method contributed to 3 % and 0.6 % increases, respectively, in the thrust force, resulting in a thrust coefficient of 96.15 % for the final optimized nozzle.

Design and performance analysis of a piezoelectric jetting dispensing valve

In order to meet the requirements of high frequency, high precision, and micro-scale dispensing in the field of microelectronics packaging, a piezoelectric jetting dispensing valve based on two-stage displacement amplifying mechanism was proposed. First, the overall structure and working principle of the proposed piezoelectric jetting valve were described. The displacement amplifying mechanism was designed, and the mathematical relationship between the output displacement and the structural parameters was established. In addition, the performance and the structural size of the displacement amplifying mechanism were analyzed and optimized by using the finite element analysis software. The influences of driving pressure, glue viscosity, needle displacement, and other parameters on droplet diameter and jetting velocity in the process of dispensing were simulated and analyzed. In order to obtain the optimal nozzle structure, the changing curves of glue flowing velocity with different nozzle seal forms, nozzle cone angles, and outlet inner diameters were compared and analyzed. Finally, the prototype of the piezoelectric jetting dispensing valve was machined, and experimental study was performed. The influence laws of driving pressure, glue viscosity, driving voltage, and other parameters on the diameter of droplet were explored. The performance of the prototype was evaluated from three aspects of dispensing frequency, consistency, and minimum dispensing droplet diameter. Results show that the highest dispensing frequency is 230 Hz, the deviation of dispensing consistency is ±8.77%, and the minimum dispensing droplet diameter is 0.54 mm. The experimental results verify the high frequency, consistency, and micro-scale dispensing performance of the piezoelectric jetting dispensing valve based on the displacement amplifying mechanism, which provides a reference for the research of piezoelectric high-frequency jetting dispensing.

Multi-objective optimization of a porous diverter plate for a liquid-cooled micro-jet heat sink via surrogate modeling

This work reports on the optimization of a porous diverter plate for a micro-jet heat sink to obtain the optimum jet nozzle diameter and flow opening ratio, which play a significant role in the cooling characteristics of heat sinks for electronic chips. An artificial neural network (ANN) model was used to optimize and predict the sensitivity of different parameters (coolant flow rate, opening ratio, and jet nozzle diameter) on the operation of the heat sink design. It was found that smaller opening ratios and jet nozzle diameters in the range of 2.0–3.2 mm had a positive effect on improving the heat sink's thermal performance. Moreover, the diverter plate's opening ratio had a major sensitivity to pumping power, while the jet nozzle diameter had the lowest sensitivity. Finally, the overall cooling characteristics of all the designs were evaluated using the PPTR parameter, and the results demonstrate that the porous diverter plate with an opening ratio of 0.08 and a jet nozzle diameter of 1.81 mm yielded the optimum design for the porous diverter plate of the heat sink.

Toward Virtual Testing of Unmanned Aerial Spraying Systems Operating in Vineyards

In recent times, the objective of reducing the environmental impact of the agricultural industry has led to the mechanization of the sector. One of the consequences of this is the everyday increasing use of Unmanned Aerial Systems (UAS) for different tasks in agriculture, such as spraying operations, mapping, or diagnostics, among others. Aerial spraying presents an inherent problem associated with the drift of small droplets caused by their entrainment in vortical structures such as tip vortices produced at the tip of rotors and wings. This problem is aggravated by other dynamic physical phenomena associated with the actual spray operation, such as liquid sloshing in the tank, GPS inaccuracies, wind gusts, and autopilot corrections, among others. This work focuses on analyzing the impact of nozzle position and liquid sloshing on droplet deposition through numerical modeling. To achieve this, the paper presents a novel six degrees of freedom numerical model of a DJI Matrice 600 equipped with a spray system. The spray is modeled using Lagrangian particles and the liquid sloshing is modeled with an interface-capturing method known as Volume of Fluid (VOF) approach. The model is tested in a spraying operation at a constant velocity of 2 m/s in a virtual vineyard. The maneuver is achieved using a PID controller that drives the angular rates of the rotors. This spraying mission simulator was used to obtain insights into optimal nozzle selection and positioning by quantifying the amount of droplet deposition.

Multi-objective aerodynamic optimization of expansion–deflection nozzle based on B-spline curves

An expansion–deflection nozzle (EDN) is an altitude-compensated nozzle that can accommodate a wide range of nozzle pressure ratio (NPR) variations. An EDN design with good thrust performance under both high- and low-NPR conditions can effectively improve the launch capability of the vehicle. In this study, a multi-objective aerodynamic optimization design is developed considering the performance of the EDN in both open and closed wake modes. The design method of the outer wall and pintle of the EDN is developed using B-spline curves. The design variables are the coordinates of the control points of the curves, and the objective functions are the thrust efficiencies of the EDN at NPRs of 30 and 400. The nozzle thrust is obtained using a Reynolds Averaged Navier–Stokes (RANS) equation solver and validated by experimental results. A radial basis function neural network and a non-dominated sorting genetic algorithm II (NSGA-II) are used to construct the surrogate model and search for the Pareto front, respectively. The relationship between the nozzle contour geometry and the nozzle thrust characteristics of the four optimised individuals on the Pareto front is discussed and analysed. The results demonstrate the effectiveness of the multi-objective optimization design for an EDN. One of the optimized designs improved the thrust efficiency at NPR = 30 by 3.5 % while improving the thrust efficiency at NPR = 400 by 0.6 %. Moreover, to ensure superior performance of the EDN in both operating modes, the nozzle length and pintle ending angle must be designed as a compromise, whereas a larger nozzle exit angle is favoured for both conditions. This study demonstrates the potential of the B-spline method for nozzle optimization design.

Numerical analysis of convective heat loss from a cylindrical–hemispherical receiver using a glass cover and an air curtain

AbstractIt is imperative to mitigate the convective heat loss from the receiver to improve the overall efficiency of the parabolic dish concentrator. In this study, the reductions of convective heat loss from the cylindrical‐hemispherical receiver are numerically analyzed and the model was validated by the experimental data from literature. In the first case, the impact of the glass cover on convective heat loss is examined under conditions of both natural and forced convections at various receiver orientations (γ = 0°, 30°, 60°, and 90°). Numerical results clearly demonstrate that the use of a glass cover significantly reduces the intrusion of surrounding air into the receiver cavity which leads to an enhancement of the stagnation zone inside the cavity and, as a consequence, a noticeable reduction in convective heat loss is observed. To perform analysis of the receiver with glass cover under forced convective condition, the wind velocities over the receiver are considered in the range of 1–6 m/s. The maximum reduction of convective heat loss using the glass cover is achieved to be 58.44% with wind velocity of 5 m/s at γ = 60°. In the second case, the influence of air curtain at the receiver aperture under natural convective heat loss conditions is analyzed. The analysis incorporates three variables: receiver orientation (γ = 0°–60°), nozzle width ( = 0.002–0.004 m), and nozzle outlet velocity ( = 0.5–3.5 m/s). The results show that the air curtain minimizes the outflow of receiver inside air and results in an improvement in the stagnation zone inside the cavity. The maximum effectiveness of the air curtain is found to be 43.2% at nozzle width of = 0.004 m and nozzle velocity of = 1.5 m/s at receiver orientation of 60°. It is also noteworthy that the optimal nozzle velocity decreases with the increase of nozzle widths.

A user-centered smart inhaler algorithm for targeted drug delivery in juvenile onset recurrent respiratory papillomatosis treatment integrating computational fluid particle dynamics and machine learning

Recurrent respiratory papillomatosis (RRP) is a chronic condition primarily affecting children, known as juvenile onset RRP (JORRP), caused by a viral infection. Antiviral medications have been used to reduce the need for frequent surgeries, slow the growth of papillomata, and prevent disease spread. Effective treatment of JORRP necessitates targeted drug delivery (TDD) to ensure that inhaled aerosolized drugs reach specific sites, such as the larynx and glottis, without harming healthy tissues. Using computational fluid particle dynamics (CFPD) and machine learning (ML), this study (1) investigated how drug properties and individual factors influence TDD efficiency for JORRP treatment and (2) developed personalized inhalation therapy using an ML-empowered smart inhaler control algorithm for precise medication release. This algorithm optimizes the inhaler nozzle position and diameter based on drug and patient-specific data, enhancing drug delivery to the larynx and glottis. CFPD simulations show that particle size significantly affects deposition fractions in the upper airway, emphasizing the importance of particle size selection. Additionally, optimal nozzle diameter and delivery efficiency depend on particle size, inhalation flow rate, and release time. The ML-based TDD strategy, employing a classification and regression tree model, outperforms conventional inhalation therapy by achieving a higher delivery efficiency to the larynx and glottis. This innovative concept of an ML-empowered smart inhaler represents a promising step toward personalized and precise pulmonary healthcare through inhalation therapy. It demonstrates the potential of AI-driven smart inhalers for improving the treatment outcomes of lung diseases that require TDD at designated lung sites.

Analysis of the dust cleaning performance of a branch-type nozzle.

To solve the problem of uneven dust cleaning in filter cartridges, a simple and easy-to-install "branch-type" nozzle structure was designed to improve cleaning efficiency. In this study, numerical simulations, range analysis methods, orthogonal experimental design, back-blowing experiments, and powder cleaning experiments were conducted. By choosing the back-blowing uniformity as the evaluation index for cleaning performance, with the flow distribution coefficient A, length of branch pipe B, and outlet diameter of main pipe C as the factors, and ignoring the interaction between factors, an orthogonal experiment was designed to simulate the fluid flow field of nine different nozzle structures installed in the back-blowing model. The results were analyzed using range analysis methods, and the optimal nozzle structure parameter combination was determined to be A = 50%/40%/10%, B = 70 mm, and C = 18 mm. Based on the back-blowing experiment, the accuracy of the simulation results was verified, and the back-blowing uniformity was improved by 50.12%. In the powder cleaning experiment, a new method of measuring the mass of dust shaken off by a single pulse of cleaning to calculate the residual dust on the filter cartridge, rather than removing the filter cartridge and weighing it, was found to reduce experimental errors and make the conclusions more solid and convincing. The results showed that the "branch-type" nozzle increases the cleaning efficiency by 37.6% compared with no nozzle installed, proving that the "branch-type" nozzle can reduce the number of reverse cleaning required and extend the cleaning interval, thus optimizing the cleaning performance of the dust collector.

The Optimum Nozzle Exit Position and the Behaviour of a Turbulent Flow in an Ejector Designed for Natural Draft Burner

The Optimum Nozzle Exit Position and the Behaviour of a Turbulent Flow in an Ejector Designed for Natural Draft Burner

Devising a method to design supersonic nozzles of rocket engines by using numerical analysis methods

The object of research is supersonic nozzles of liquid-propellant rocket engines. The work considers the problem of the lack of an effective method for profiling the supersonic contour of the nozzle, which will generate maximum thrust. For its solution, a method is proposed, the essence of which is approximating the nozzle contour with a power-law polynomial and determining the values of its coefficients by solving a multidimensional minimization problem using numerical modeling methods. The expression for the axial component of the thrust with the opposite sign at the specified values of atmospheric pressure and radius at the nozzle section was chosen as the objective function in this paper. Using the proposed method, contours of optimal nozzles were obtained based on polynomials of powers 2, 3, and 4, which were compared with nozzles obtained by the generally accepted Rao method. The maximum value of the relative deviation modulus calculated during the comparison did not exceed 3 %, which allows us to assert the correctness of the obtained results. The existence of such a discrepancy is explained by the difference in the numerical modeling method used. In contrast to the method of characteristics common in similar problems, the method of finite volumes of the Godunov type was used in the work. This has made it possible to reduce the sensitivity of the calculation to initial and boundary conditions and make decisions regardless of the flow regime of combustion products. In addition, the use of the extended cells method for the integration of finite volumes at the boundary of the calculation domain significantly reduced the total time of solving the problem of profiling the contour of the optimal nozzle

Seal vibrissa-based three-fourths open-jet wind tunnel nozzle optimization

This study investigated the effects of using bionics in reducing the low-frequency fluctuation phenomenon in three-fourths open-jet automobile wind tunnels. Low-frequency fluctuation in these wind tunnels can cause pulsations of velocity and pressure in the test section, leading to measurement accuracy reduction. The unique shape of the seal vibrissa had been demonstrated to effectively suppress vortex-induced vibrations. Here the wind tunnel nozzle was optimized with seal-vibrissa-shaped protrusions. The effects and corresponding mechanism of seal-vibrissa-shaped nozzle toward jet shear layer vortex structures and low-frequency fluctuation phenomenon were analyzed. A 1:15 scaled three-fourths open-jet wind tunnel was used in the study. The results indicated that after the implementation of the seal-vibrissa-shaped nozzle, the turbulence intensity was decreased at the bottom of the test section and the pressure and velocity fluctuations were effectively suppressed. The three-dimensional vortex structures separating from the surface of vibrissa destroyed the original two-dimensional vortex structures produced by the original nozzle. Many small vortex structures with dispersed frequencies and energies were formed, which decreased the low-frequency fluctuations. The study showed that the seal-vibrissa-shaped nozzle had the potential of inhibiting the large-scale vortex separation in the jet shear layer, which could effectively reduce the low-frequency fluctuations.

Optimal design and research for nozzle governing turbine of compressed air energy storage system

The air storage pressure of the compressed air energy storage system gradually decreases during the energy release process. In order to make the turbine work efficiently in non-design conditions, it is necessary to adopt a reasonable air distribution method for the turbine. In this paper, the orthogonal experimental design is carried out on the inlet pressure of the nozzle under different base pressure. Based on the response surface method, the optimal nozzle governing method corresponding to different base pressure under required output work conditions is obtained by multi-island genetic algorithm. The optimal NG method can improve the w by up to 9.2 % compared with throttle governing. To meet the output work requirement, an optimal NG method should have as few nozzles as possible and more nozzles with the same inlet pressure as the BP.