Spray Model Research Articles

Productivity model and experiment of field crop spraying by plant protection unmanned aircraft.

Traditional agricultural production requires numerous human and material resources; however, agricultural production efficiency is low. The successful development of plant protection unmanned aerial vehicles (UAVs) has changed the operation mode of traditional agricultural production, saving human, material, and financial resources and significantly improving production efficiency. To summarize the process of improving the productivity of plant protection UAVs, this study established a productivity calculation model of UAVs based on the time composition of the UAV agricultural plant protection process, including spraying, turning, replenishment, and transfer times. The time required for the unmanned aircraft application process was counted through years of tracking the application process of eight different plant protection unmanned aircraft. Plot lengths of 100, 300, 500, 700, 1,000, 1,500, 2,000, 2,500, 3,000, and 3,500 m were established to calculate the theoretical productivity. The results showed that the productivity of different types of plant protection UAVs increased with an increase in plot length in the range of 100 to 1,500 m; however, when the plot length reached a certain value, the productivity growth rate slowed down or even decreased slightly. Simultaneously, based on the working area per 10,000 mu, the recommended plot length and the number of configured models for different models were recommended. If the plant protection UAV was distinguished by electric and oil power, the time utilization rate of electric plant protection UAVs was 72.7%, and the labor productivity was 56.4 mu/person·h. In contrast, the time utilization rate of the heavy load oil-powered plant protection unmanned aircraft was 86%, and the labor productivity was 63.5 mu/person ·h. This study can support plant protection UAV enterprises to optimize equipment efficiency, provide evaluation methods for the operation efficiency assessment of plant protection UAVs, provide a reference for the selection of plant protection UAVs, and provide a basis for field planning.

Research of numerical simulation for HVAF thermal spraying process on rotational roll

AbstractHVAF thermal spraying has the characteristics of low spraying temperature, high coating density, and strong corrosion resistance. It is widely used in the aerospace, iron–steel metallurgy, national defense and military industry, petrochemical industry, and other fields for manufacturing protection and repair strengthening, which has achieved significant economic benefits. In this study, a numerical model of HVAF thermal spraying on a circular roll was established by the computational fluid dynamics method. The characteristics of the spraying flame, evolution of the gas composition mass fraction, and influence of the spraying parameters on particle flight behaviors were calculated and revealed. Based on the dynamic mesh method, the effect of roll speed on the spraying flame characteristics and particle flight behaviors was analyzed. Calculations show that the spraying flame is extruded at the Laval nozzle and the speed rapidly increases to 805 m/s, which increases to a supersonic speed through the barrel. The flame flow rises rapidly reaching the surface of the roll, which is 780 m/s. The highest temperature is in the combustion chamber, and the flame temperature of the airshed is a damped vibration. The flame covers the surface of the roll to preheat it, and the flame temperature there decreases layer by layer from the inside to outside. The particle diameter significantly effects the powder flight behavior. The flame velocity increases with the barrel length increasing. The flame temperature up to the peak when the barrel length is 190 mm. As the rotation speed of the roll increases, the temperature, velocity, and pressure of the flame flow on the roll surface change in a certain extent. The particle spatter will be increased with the rotational speed increasing of the roll, which little affects the particle temperature.

Generalized data-driven optimal path planning framework for uniform coverage missions using crop spraying UAVs

Unmanned aerial vehicle (UAV) based crop spraying has become a popular alternative in the field of precision agriculture. One of the key goals of UAV based spraying is achieving spray coverage that is as uniform as possible to ensure maximum spray efficacy. Most of the existing studies in the literature focus on analysing the effects of spraying parameters on the uniformity of coverage distribution using experimental studies. However, in this work, we propose a novel generalized data-driven optimal path-planning framework aimed at finding the optimal operational flight parameters (flight speed and pass widths) for a lawnmower coverage path plan to meet the specified spray coverage rate while ensuring the uniformity. The framework takes a spray distribution model as an input and computes the optimal operational parameters for the coverage path plan to minimize coverage non-uniformity without making any assumptions on the UAV type. Furthermore, we also propose a neural network structure using Gaussian kernel neurons to design the spraying model using experimental data. The neural network structure makes no assumption about the type of UAV, onboard nozzle placement, or the flight parameters. The accuracy of the modelling solution only depends on the quality of the training data. In other words, higher diversity of the training data in terms of the flight and spraying parameters would result in a modelling solution that is more representative of the spraying distribution and consequently improve the quality of the operational parameters obtained from the proposed optimization framework. In this work, we present a case study to demonstrate the use case and test the performance of the proposed framework via simulation and experiments using the DJI AGRAS-T10 drone. The results showed that the optimal pass-width solutions for low forward speeds were similar to optimizing the positioning of the nozzles on a boom sprayer to achieve uniform coverage. Whereas, at high speeds, the pass-width was comparatively higher as the spread of the effective coverage over each pass increased. A discussion contextualized in the case study is provided to highlight the salient features and limitations of the proposed framework.

Hot compression bonding behavior and constitutive model of spray deposited 2195 Al-Cu-Li alloy

Hot compression bonding (HCB) tests of spray deposited 2195 Al-Cu-Li alloy were carried out under different temperatures and strain rates when the sample chamber was vacuumized to 1.0 × 10−3 Torr. The constitutive models and processing map during HCB process were established, and interfacial microstructure, especially the oxide film evolution and bonding mechanism of this alloy were investigated. The results showed that this alloy possesses both good bondability and stable deformation ability in three deformation parameter regions, with a temperature of 500 °C and strain rates of 0.01–0.05s−1 and 1–10s−1, and temperature of 430–470 °C and strain rate of 0.05–0.55 s−1. The interface of this alloy forms oxide film even under near vacuum environment, and the oxide films are predominantly amorphous Al2O3 and nanocrystalline of γ-Al2O3, and a small amount of Li2CO3, Al(OH)3, MgAl2O4. The strain rate influences bonding mechanism dramatically, when samples are compressed at high strain rate, the interfacial healing was highly dependent on microplastic deformation and mechanical interlock around the interface. While compressed at low strain rate, the interfacial healing was mainly dependent on grain boundary bulging or particle-stimulated nucleation, grain boundary migration and dynamic recrystallization (DRX).

Optimization-Design and Atomization-Performance Study of Aerial Dual-Atomization Centrifugal Atomizer

The aerial atomizer is the most essential component of the plant protection UAV (unmanned aerial vehicle). However, the structural optimization of existing aerial atomizers lacks comprehensive consideration of spray parameters and structural parameters, and there is a shortage of available atomizer spray models, resulting in the unstable effect of UAV application. In our previous work, an aerial dual-atomization centrifugal atomizer was developed. In order to obtain an aerial atomizer with good atomization effect and its atomization model, structural optimization at different rotation speeds and flow rates of the atomizer, and its atomization performance, are studied in this paper. Firstly, with the droplet volume median diameter (VMD) and spectral width (SRW) as the evaluation index, through the single-factor, Plackett–Burman and Box–Behnken tests, the influence of rotation speed, flow rate, tooth number and tooth shape were studied. The regression models of the droplet VMD and SRW were established using multiple quadratic regression fitting of the test data. Secondly, in order to achieve the lowest droplet VMD and SRW, the response surface method and post-hoc multiple comparison method were used to obtain the optimized structure of the atomizer’s rotation ring at different rotation speeds (600–7000 r/min) and flow rates (500–1000 mL/min). Lastly, with the effective swath width (ESW) of the optimized atomizer as the evaluation index, through the Box–Behnken test, the influence of rotation speed, flow rate and spray height were studied. The multiple quadratic regression model of ESW was established with the test data. The test results indicated that rotation speed, flow rate and tooth number had a significant effect on droplet VMD and SRW; tooth shape had no significant effect on the droplet VMD and SRW, however, the square tooth shape had the best atomization effect; and rotation speed, flow rate and spray height had a significant effect on ESW. The optimized structural parameters were tooth shape: square, and tooth number: 20. The determination coefficient R2 of the regression model of VMD, SRW and ESW were 0.9976, 0.9770 and 0.9974, respectively, which indicates that the model was accurate, and can evaluate and predict the spray effect. This paper provides an optimized dual-atomization centrifugal atomizer, and its regression models of VMD, SRW and ESW for UAV applications can provide a reference for efficient UAV spraying.

Numerical Simulation of the Trajectory of UAVs Electrostatic Droplets Based on VOF-UDF Electro-Hydraulic Coupling and High-Speed Camera Technology

The electrostatic spray technology can significantly improve the utilization rate of liquid medicine under the operation characteristics of unmanned aerial vehicles (UAVs) with small load and low spray volume. To explore the settlement law of electrostatic droplets, further improve the amount of droplets deposited in target crops, and reduce the loss of missing target, this study adopted the method of combining numerical simulation and high-speed photography to study the movement characteristics of electrostatic droplets of UAV induction conical electrostatic nozzle. Based on the droplet spatial dynamics theory, a user-defined function and volume of fluid (UDF-VOF) multiphase spray model is established to simulate the trajectory of electrostatic droplet. TEMA software is used to analyze the droplet motion image under electrostatic field, and the characteristic parameters, such as trajectory and velocity are obtained. Theoretical analysis and spray test results show that the main factors affecting electrostatic droplet settlement are charging voltage, droplet falling distance, and airflow velocity. The optimal charging voltage of electrostatic droplet is 14 kv, the maximum charge-mass ratio is 1.04 mC/kg, and the average particle size is 209.77 μm. The numerical simulation results show that spray height, charging voltage, and lateral wind speed have significant effects on droplet sedimentation. The results of high-speed camera analysis show that the induced electric field causes the droplet to adsorb the target crop, resulting in the droplet movement trajectory deflection.

Comprehensive assessment of methanol as an alternative fuel for spark-ignition engines

A promising pathway to defossilize the operation of spark-ignition engines is to use methanol as a fuel. This clean alternative liquid energy carrier offers major efficiency and emission benefits compared to gasoline. Its high knock-resistance and high heat of vaporization allow knock-free operation at high compression ratios while maintaining low emissions of nitrogen oxides. In addition, it is the simplest alcohol to synthesize and the distribution infrastructure for existing liquid fuels can be used. Previous research on mixture formation and combustion of methanol in passenger car sized spark-ignition engines is limited, reported on various experimental configurations, and mainly focused on one particular aspect. This study sets out to provide a coherent evaluation of the mixture formation and performance of methanol in a spark-ignition engine in comparison to gasoline by successively addressing and combining fundamental and optical spray measurements, engine experiments and complementing numerical analyses all with matching boundary conditions for these aspects. First, a theoretical analysis regarding the primary spray break-up behavior was performed using methanol and the gasoline surrogate iso-octane, which showed a comparable atomization performance between the two fuels. This theoretical result was then experimentally validated under realistic engine operating conditions on a low-pressure chamber by means of shadowgraph imaging. These investigations showed no notable differences in spray penetration length and spray angle between methanol and gasoline under the same boundary conditions. However, under realistic engine operation, the spray penetration length of methanol increased by up to 64.5% due to the increased injection duration required because of its lower energy content. In a next step, methanol was experimentally studied on a thermodynamic single-cylinder research engine with a compression ratio of 10.8. Using the same fuel injector, the combustion and emission behavior was investigated in comparison with gasoline. A load variation at an engine speed of 2500 1/min and a variation of the relative air/fuel ratio at the same engine speed and a net indicated mean effective pressure of 16 bar were performed. Depending on the engine load, methanol achieved 7%–24% higher net indicated efficiencies and a 9 bar higher maximum load compared to gasoline. At lean-burn operation, methanol not only enabled higher net indicated efficiencies exceeding 45%, however, also an extended lean-burn limit of 0.1 units. The experimental engine investigations were complemented with 0D/1D simulations, which showed that especially the wall heat transfer and the burn duration are significantly lower in the case of methanol. Finally, 3D computational fluid dynamics simulations were performed using a newly developed methanol spray model which showed that an increased fuel mass impinges the combustion chamber walls with methanol. However, toward the end of compression, the methanol wall film dropped to the level of gasoline.

Dynamic performance analysis and thermal modelling of a novel two-phase spray cooled rack system for data center cooling

Cooling systems in information technology (IT) equipment account for the greatest share of direct energy consumption in data centers. Conventional air-cooling schemes are thermally inefficient and energy intensive as they require large temperature difference between heat source and cooling medium. To overcome the aforementioned drawbacks of air-cooling, a “chillerless” novel spraying architecture which has the capability of performing high heat flux cooling, is highly scalable and easily adaptable by modern data centers is proposed in this paper. To demonstrate the scalability and performance of this new cooling scheme, a full-scale spray cooled rack system which has the capacity of housing up to 12 server units is developed. The dynamic performance of the spray cooled rack system under variable ambient temperature is studied. It is found that the ambient temperature strongly affects the spray cooling performances and the chamber pressure stability. A grey box model of the system is established. The newly developed model has successfully predicted the temperature variation on both the water side and spray cooling side with reasonable accuracy. Our model sets the foundation for predictive control of the chamber pressure and workload management of the spray cooling scheme for application in large-scale data centers.

Numerical study on liquid ammonia direct injection spray characteristics under engine-relevant conditions

This paper reports on CFD modeling of the fuel/air mixing characteristics of liquid ammonia under direct injection engine-relevant conditions. Several questions are addressed including, whether the widely used Lagrange particle tracking (LPT) spray models developed for traditional fossil fuels are suitable for ammonia spray, whether certain improvement of the current models should be introduced, and under what conditions the improvement of models needs to be considered. It is found that liquid ammonia spray characteristics can be well reproduced by the current Lagrange-based spray models under non-flash boiling conditions. However, there are obvious gaps between measurements and predictions under strong flash boiling conditions. A strong flash boiling region is found near the nozzle while its intensity decreases downstream due to the significant cooling effect of ammonia spray, and initial superheat degree defined as the ratio of ambient pressure to the saturation vapor pressure at initial fuel temperature, can be adopted to determine the boundary of flash boiling model that needs to be employed in the modeling of liquid ammonia spray. Spray included angle is a crucial parameter within the LPT simulation framework to reproduce the collapse effect for multi-plume sprays. The flash model considering only the evaporation promotion effect cannot replicate the ammonia spray characteristics and it does not result in obvious differences compared with the results from the normal evaporation model. Liquid ammonia is a thermal sensitive fuel and has a strong tendency of flash boiling, and a more accurate flash boiling model that considers the thermal breakup effect should be proposed to accurately predict ammonia fuel/air mixing characteristics under wide engine-relevant conditions.

Large Eddy Simulation of Gasoline Sprays in a Lagrangian–Eulerian Framework Using the High-Order Spectral Element Method

Abstract Predicting the spray evolution using simulations requires accurate modeling of the turbulent gas-phase flow field. In this study, the high-order spectral-element method (SEM), implemented in the code Nek5000, was used to provide highly resolved solutions to the turbulent flow field. Spray modeling capabilities were implemented into the Nek5000 code. The spray is modeled in a Lagrangian–Eulerian (LE) framework, where the liquid is represented by discrete parcels of droplets. The method for coupling liquid and gas in the context of SEM is described, which allows for very fine meshes to be used without affecting the stability of the solution. Large-eddy simulations (LES) of the eight-hole ECN Spray G gasoline injector were conducted. Numerical results are compared against experimental data for liquid penetration, droplet size and gas velocity. The morphology of the multiplume spray is compared against experimental data. The effect of different spray injection inputs is analyzed. It was found that using a plume direction of 33 deg and an injection cone angle of 30 deg produced the best results overall. This work shows the applicability of SEM for spray modeling applications, where use of a high-order flow solver can help us understand the multiplume spray aerodynamics and how it leads to plume collapse under certain conditions. Results also highlight the need for tuning spray input parameters in the LE framework, even when high-fidelity gas flow solutions are possible.

Artificial neural network models for phase equilibrium predictions under engine trans/supercritical spray conditions

Engine spray models based on phase equilibrium have made great progress in simulating trans/supercritical engine spray processes, but there are inherent weaknesses in terms of efficiency and stability for the conventional phase equilibrium algorithm due to the iterative schemes for solving complex nonlinear equations. The low efficiency of the conventional algorithm limits the amount of detail that can be considered in the simulation, while the instability may lead to unphysical results or even simulation divergence. In this work, a method based on artificial neural networks (ANNs) was developed as a potential alternative to the conventional algorithm applied in the engine spray models to achieve fast and robust phase equilibrium calculations. Three ANNs were constructed, including isothermal-isobaric-ANN (TPn-ANN), isenthalpic-isobaric-ANN (HPn-ANN) and adiabatic-mixing-temperature-ANN (AMT-ANN). The latter two models combined with TPN-ANN can be applied to heat and mass transfer flow and adiabatic mixing problems, respectively, to achieve the prediction of phase equilibrium temperature, phase stability and phase splitting. The current work shows that the ANN method leads to significant efficiency improvements while maintaining almost the same accuracy as the conventional algorithm. Analysis of execution time for a high-fidelity n-dodecane spray simulation shows that the conventional phase equilibrium calculation can take up to 70% of total computational time, which can be reduced to negligible levels with the current proposed ANN approach.

Математическое моделирование потока капель распыливающего устройства

The paper presents the results of mathematical modeling, numerical and laboratory experiments aimed at developing an optical method for estimating the size distribution of droplets in a spray. The optical method is based on analyzing the brightness of light reflected by drops of a liquid. The ob-ject of study was a spray of a transparent liquid (distilled water) produced by a centrifugal axisym-metric nozzle. It is known that the intensity (brightness) of light reflected by a drop is proportional to the surface area of the drop, and for spherical drops, accordingly, to the square of the drop’s di-ameter (hereinafter, the terms intensity and brightness are used as synonyms). For a more detailed representation of the patterns of this dependence in the case of a flow of droplets, we considered a mathematical model representing the spray as a flow of spherical particles with parameterization of almost all significant properties: arbitrary distribution of droplets in size and speed as well as changes in these characteristics over time during the movement of drops along the flow. We ob-tained formulas and tested a mathematical model of nozzle spray that takes into account the change in droplet density due to the scattering of droplets in the spray cone and the inhomogeneity of veloc-ity fields. The zone of possible cessation of droplet fission was determined.

POST PROCESSING METHOD FOR SIMULATED LAGRANGIAN SPRAY FIELD BASED ON MIE SCATTERING THEORY

Numerical simulation and experiment are the two main methods in the investigation of spray and atomization. Some crucial parameters of simulation models are supposed to be calibrated using corresponding experimental data. However, direct comparisons between simulation data and experimental results might be confusing when focusing on spray boundaries or penetration, as the light scattering physics during imaging is always likely to be ignored in computational fluid dynamics (CFD) post-processing. In many cases, CFD provides invisible droplets, resulting in variance in the boundary confirming process. Previous studies discussed backlit conditions in Euler-based simulations to identify spray boundaries, but for most commonly used Lagrangian-based simulations, which are often coupled with Mie scattering experiments, this topic remains undiscussed. In Lagrangian-based methods, droplets are treated as discrete particles, where scattering plays a more crucial role. In this study, light intensity analysis based on Mie scattering theory and intensity integration focusing on Lagrangian field has been presented, aiming to adjust simulation data of spray coincides with Mie scattering image as much as possible on the theoretical base. It is found that particle size and in-parcel numbers are related to the scattering intensity of droplet particles. the correlated CFD data using Mie scattering theory are tested to be theoretically similar with Mie scattering imaging results compared with raw simulation data, making the comparison between datasets reasonable, which makes adequate preparations for the calibration of spray models.

Effect of Intake Conditions and Nozzle Geometry on Spray Characteristics of Group-Hole Nozzle

The group-hole nozzle concept is proposed to meet the requirement of nozzle hole minimization and reduce the negative impact of poor spatial spray distributions. However, there are limited researches on the effects of intake conditions and nozzle geometry on spray characteristics of the group-hole nozzle. Therefore, in this study, an accurate spray model coupled with the internal cavitating flow was established and computational fluid dynamics (CFD) simulations were done to study the effects of intake conditions and nozzle geometry on spray characteristics of the group-hole nozzle. Experimental data obtained using high-speed digital camera on the high-pressure common rail injection system was used to validate the numerical model. Effects of intake conditions (injection pressure and temperature) and nozzle geometry (orifice entrance curvature radius and nozzle length) on the flow and spray characteristics of the group-hole nozzle were studied numerically. The differences in Sauter mean diameter (SMD), penetration length and fuel evaporation mass between single-hole nozzle and group-hole nozzle under different nozzle geometry were also discussed. It was found that the atomization performance of the group-hole nozzle was better than that of the single-hole nozzle under same intake conditions, and the atomization effect of the short nozzle was better than that of the long nozzle. With increase in the orifice entrance curvature radius, the average velocity and turbulent kinetic energy of the fuel increased, which was conducive to improving the injection rate and flow coefficient of the nozzle. Meanwhile, the penetration length and SMD value rose, while evaporation mass dropped. When the ratio of the orifice entrance curvature radius (R) to the diameter of injection hole (D) was 0.12, the spray characteristics reached a constant state due to elimination of cavitation. Conclusions were made based on these. This study is expected to be a guide for the design of the group-hole nozzle.

Numerical Modeling and Experimental Investigation of Spray Combustion Process in Regenerative Liquid Propellant Mortar

AbstractRegenerative liquid propellant guns (RLPGs) have been studied for many years. However, the presence of large pressure oscillations is observed in almost each RLPG firing. In order to push forward the liquid propellant application in guns, a low pressure firing system called regenerative liquid propellant mortar (RLPM) is developed. The multiphase multidimensional fluid‐dynamics model is presented to research the interior ballistic properties of RLPM. A high‐speed liquid sheet spray model is presented for the annular jet in RLPM based on the linear stability analysis and surface wave breakup theory. In addition to the jet atomization, the droplets secondary breakup is considered. The experiments on a 60 mm RLPM test fixture are carried out, and the results indicate that the liquid propellant combustion oscillations are effectively suppressed. The spray and combustion processes have been simulated for the 60 mm RLPM which are in agreement with the experimental data well. Numerical results indicate an important benefit for the RLPM that the muzzle velocity is improved by increasing the charge quantity while the maximum chamber pressure remains unchanged.

Numerical Optimization of the EGR Rate and Injection Timing with a Novel Cavitation Model in a Diesel Engine Fueled with PODE/Diesel Blends

Polyoxymethylene dimethyl ether (PODE) is one of the most promising alternative fuels for diesel engines with a high cetane number, high oxygen content, and no C-C bonds. In this paper, a new spray model with a novel cavitation sub-model is adopted in order to create a numerical model suitable for engine simulation fueled with PODE/diesel blends. The effects of the blending ratio, injection timing, and EGR rate on the combustion and emission characteristics are investigated by the simulation. The simulation results show that the self-restoring oxygen properties of PODE can efficiently improve the combustion, causing a higher in-cylinder temperature, and therefore, higher NOx emissions. Additionally, with the increase in the blending ratio, the increase in the oxidation activity of PODE/diesel blends and the improvement of atomization are conducive to reducing soot emissions. Then, the injection timing and EGR rate are optimized. The numerical results suggest that the NOx emissions decrease initially and then increase; however, soot emissions decrease monotonically with the delay of the injection timing. When the volume blending ratio is 15%, the emission performance is best when the injection timing is between 710 °CA and 715 °CA. The increase in EGR rate can effectively reduce the in-cylinder temperature and control the NOx emissions, but the excessive EGR rate leads to higher soot emissions and a deteriorated combustion process. Therefore, an EGR rate in the range of 0.0 to 0.2 has a better comprehensive emission performance from the perspective of controlling both the NOx and soot emissions.

Analysis of liquid surface deformation and breakups using three-dimensional high-speed data recorded with a single camera

Analyzing the deformation of liquid surfaces to better understand, for example, wave generation in oceanology or the formation of industrial spray systems, requires a series of three-dimensional snapshots that temporally resolve such events. This requirement is challenging, especially when applied to transient liquid surfaces that deform rapidly. A technique called Fringe Projection-Laser Induced Fluorescence (FP-LIF), developed by the authors, generates three-dimensional surface reconstructions of irregular liquid structures using snapshots recorded via a single camera only. In this article, FP-LIF is associated, for the first time, with a high-speed detection system, allowing the three-dimensional visualization of liquid surface deformation and breakups at a kHz frame rate. The technique is applied here at 20 kHz for imaging the complete development of a wide hollow-cone water spray and analyzing, in detail, the transition from early injection to stabilization. The three-dimensional image series covered a total time window of 300 ms (6000 frames). It is observed during the first 100 ms that the initial liquid jet deforms into a stable tulip shaped sheet. Then, between 100 and 180 ms, the tulip shape gradually grows until its stabilization corresponds to the final conical shaped sheet. Once the stabilization is reached, the fluctuation of the final spray-angle—ranging from 40° to 50°—is extracted by post-processing 1000 consecutive three-dimensional images, providing a detailed analysis of the radial symmetry of the spray over time and three-dimensional space. The results provided in this article are relevant for the validation of Computational Fluid Dynamics spray models.

CFD modeling of MEA-based CO2 spray scrubbing with computational-effective interphase mass transfer description

Great concerns for global warming and stringent regulations have spurred the development of feasible technologies to reduce CO2 emissions from the power generation sector. In thermal power plants, spray scrubbing is one of the most used methods for separating gaseous pollutants, which inspires the idea of applying spray scrubbing in CO2 capture. However, this new idea still necessitates investigation, particularly in developing a novel modeling tool. This motivates us to present the CFD modeling of CO2 spray scrubbing using MEA solution in this work. CO2 spray scrubbing is a complex process. Herein, the established model combines the multiphase flow with interphase transfer and chemical reactions in the Euler-Lagrange framework. To efficiently describe the interphase mass transfer, we proposed a new method based on the thermodynamic consistency between the CO2 equilibrium pressure and the enthalpy of CO2 absorption. Validated by the experimental data, this method can achieve an acceptable balance between accuracy and computational cost. The zwitterion mechanism was employed to describe the chemical reactions. Kinetic analysis shows that E = (1 +Ha2)0.5 can reasonably evaluate the enhancement factor value in a wide range of MEA concentrations. Additionally, the effects of operating parameters on CO2 removal were numerically studied, focusing on mass transfer characteristics. Therefore, the proposed numerical model will be beneficial for facilitating the deployment of CO2 spray scrubbing in the power sector, and the numerical results provide helpful information for design and optimization.

A machine learning framework for evaluating the biodiesel properties for accurate modeling of spray and combustion processes

The environment-friendly nature of biodiesel coupled with its inherent compression ignition fuel characteristics like better ignition quality, and fuel bound oxygen may reduce sooting combustion, and attract wide attention. The variation of thermophysical properties with temperature is essential for accurately modeling the combustion and emission characteristics of biodiesel fuelled diesel engines. Hence, the current paper attempts to predict the thermo-physical properties such as density, viscosity, specific heat, thermal conductivity, latent heat of vaporization, vapor pressure, mass diffusivity etc., and their variation with respect to the temperature following a machine learning approach for biodiesel fuels. Twenty feedstock samples are chosen for predicting the biodiesel thermo-physical properties and are validated with the available experimental data within a maximum error of 14 %. To evaluate the thermo-physical properties of a variety of feedstock, the predicted data are used for training an artificial neural network (ANN) and the developed ANN function is used for generating the various thermophysical properties of biodiesel fuels based on their composition and temperature. A good agreement is observed between the predicted and ANN results with a maximum mean absolute percentage error of 10 %. Hence in the current work, a collective mathematical modeling approach is proposed to accurately determine the spray and combustion-related fuel properties. The proposed model provides the various liquid and vapor properties and their variation with temperature which could be effectively employed for detailed spray and biodiesel-combustion modeling. An exhaustive data generation of eleven major liquid and vapour properties of twenty biodiesel fuels within the actual temperature range from 300 K to their respective critical temperature is presented.

Mathematical model for spray drying process

Mathematical model for co-current spray dryer is developed . The model is axisymmetric dimensional model and two way coupling .It includes the mass, momentum, and heat transfer for a single drying droplet as well as for drying medium . The system used is water-air. The model used a system of equations to compute the axial and radial distribution of droplet diameter, its velocity , temperature and rate of evaporation , and air temperature , humidity and velocity in spray drying chamber . The model includes a system of non linear first order differential equations as a function of the axial distance of the spray drying chamber . The results obtained from the model are shown to be in agreement with experimental results.