High-precision Numerical Simulation Research Articles

High-Precision Numerical Simulation Study of the Aging Precipitation Behavior in Al-Li Alloys Based on Improved Kampmann-Wagner Numerical (KWN) Model

High-Precision Numerical Simulation Study of the Aging Precipitation Behavior in Al-Li Alloys Based on Improved Kampmann-Wagner Numerical (KWN) Model

Investigation of the bubble deflection using graphics processing unit accelerated multiple relaxation time lattice Boltzmann method: The effect of bubble size and liquid viscosity

Bubble deflection is important for bubble motion and bubble mass transfer in multiphase reactors. However, the mechanism triggering the instability is controversial. In this study, we first perform a graphics processing unit-accelerated multiple relaxation time lattice Boltzmann method (MRT-LBM) to simulate the motion process of single bubbles (1.8–8.0 mm) freely rising in stationary liquids with different viscosities. Then, we further analyze the influence of the bubble size and liquid viscosity on the characteristics of the time-dependent bubble motion, including the bubble shape, velocity, and deflection, based on the high-precision numerical simulation results. The results show that the formation and shedding of bubble wake vortices are responsible for the oscillation of the bubble shape. The interaction of bubble wake vortices and bubble shape is the primary cause of bubble deflection. Finally, an empirical model, taking into account the bubble acceleration and deflection angle, is developed to characterize the effect of bubble size and liquid viscosity on the drag coefficient of a rising bubble. This study provides insight into the bubble deflection and the bubble dynamics.

Deep learning-based dispersion prediction model for hazardous chemical leaks using transfer learning

Machine learning has been employed for the rapid and accurate prediction of gas leak dispersion. However, existing models require extensive high-precision numerical simulation datasets, which presents a significant computational challenge. This study proposes a novel method using transfer learning for real-time dispersion prediction of hazardous chemical leaks. A deep learning model is pre-trained using all samples of a specific chemical, followed by fine-tuning with a small subset of samples from another chemical. This process enables the transfer of dispersion models across different chemicals and achieves rapid prediction of dispersion consequences for various chemicals. Optimal model hyperparameters are determined through a genetic algorithm, while the optimal numbers of reused layers and training samples are explored through sensitivity analysis. The proposed transfer learning method significantly reduces numerical computations by 52–74% while maintaining high prediction accuracy. This approach can provide guidance for developing deep learning-based dispersion prediction models for hazardous chemical leaks and help with emergency response strategies.

Wing design optimization and stall analysis with Co-flow Jet active control

Coupled with Co-flow Jet (CFJ) technology, the Non-dominated Sorting Genetic Algorithm II was utilized for the multi-objective combination optimization of an optimized Co-flow Jet wing, based on National Advisory Committee for Aeronautics (NACA) 6421. A high-precision numerical simulation using the delayed detached eddy simulation model was performed on the optimized wing to investigate the three-dimensional flow separation characteristics after static stall. The stall improvement was investigated by adjusting the momentum coefficient of the injection. The results show that the optimized wing exhibits significant improvements in aerodynamic performance and corrected aerodynamic efficiency. At an angle of attack of 10°, the average lift increased by 16.25% and the drag decreased by 27.23% compared to the CFJ6421 wing, while effectively addressing the problem of low modified aerodynamic efficiency of the CFJ wing at lower angles of attack. By utilizing higher momentum and improving the boundary layer control capability, flow separation is effectively suppressed, thus achieving the goal of stall recovery of the CFJ wing.

Numerical study on effect of design parameters of the single-circumferential groove on tip leakage flow reduction in a transonic turbine

In order to investigate the impact of design parameters (depth, width, and location) of the single-circumferential groove (SCG) on tip leakage flow (TLF) reduction in a transonic turbine stage, a systematic investigation was conducted by high-precision numerical simulation method. The numerical results show that the introduction of SCG could improve the stage efficiency (η) of turbine significantly. The optimal design parameters of depth coefficient (ζ), width (W), and location (L) were ζ = 3, W = W3, and L = 20%Cax (where Cax denotes the axial chord of the blade), which could reduce tip clearance leakage rate (m*) by 28.9% and improve the η by 0.56%. The implementation of flow field display methods reveals that the introduction of SCG influences the formation and development of the vortex system at the rotor tip region. The circumferential groove vortex (CGV), induced by SCG, divided the tip leakage vortex (TLV) into two segments TLV_1 and TLV_2 due to its blocking effect. TLV_1 interacted with the passage vortex (PV) and depress the strength of PV. Meantime, TLV_2 would regenerate from the trailing edge of SCG, due to its limited development range and insufficient growth, the strength and scale of TLV_2 were weakened. Given that the TLF passing through SCG flows in an opposite direction to the original TLF, the SCG at appropriate location could lead to a fact that the net flow rate of the leakage flow reached the minimum value, thereby considerably reducing the m* and flow loss caused by TLF.

Radio Telescope Surface Measurement via Deep Learning

This paper proposes a new method for accurately measuring the surface deformation of radio telescope antennas based on deep learning. A deep convolutional neural network is used to predict surface deformations by mapping the near-field intensity of the antenna, instead of relying entirely on a physical model. The proposed method could offer precise measurement of surface deformations in real time with only a single image of near-field intensity pattern. To optimize the deep learning model, a preliminary U-net based deep convolutional neural network (DCNN) model was developed based on a large data set generated by an approximate physical model, a partial differential equation (PDE). The network parameters were then fine-tuned using transfer learning with a small data set obtained by high precision numerical simulation. During this process, the fine-tuning layers that achieved optimal performance for the U-net network was studied. The final results show that the proposed method significantly improves the accuracy of antenna surface deformation recovery. Additionally, singular value decomposition (SVD) technology is employed to denoise the intensity image, which facilitates the application of the proposed method to actual deformation measurement.

Study on a Novel Methodology for Developing the Skeletal Mechanism of RP-3 Aviation Kerosene.

An urgent requirement for high-precision numerical simulation of modern aero-engines is the development of a highly simplified and accurate reaction mechanism for aviation kerosene. However, there is still lack of a reduced mechanism that can effectively capture the low- and high-temperature characteristics of RP-3 aviation kerosene. In light of this, in this study, a novel methodology for developing skeletal mechanism by combining the detailed C0-C4 mechanism and C5-Cn high-carbon molecular skeletal mechanism was proposed and applied. To construct the RP-3 skeletal mechanism, a surrogate fuel consisting of 54% n-dodecane, 22% 2,5-dimethylhexane, 14% 1,3,5-trimethylbenzene, and 10% decalin was utilized. Based on the proposed methodology, a skeletal mechanism comprising 153 species and 858 reactions has been developed. Various combustion characteristics of each surrogate component and the RP-3 aviation kerosene, such as the ignition delay, concentration of material components, laminar flame, and NO emission, were examined to validate the developed mechanism. The proposed methodology in this study offers a novel approach to develop mechanisms for high-carbon fuels. Additionally, the developed skeletal mechanism serves as a foundation for the design and optimization of aero-engines.

An improved acoustic/elastic interface approach for 2D staggered grid finite-difference modeling of Rayleigh waves in the presence of surface topography

Rayleigh waves are generated along the free-surface and their propagation can be strongly influenced by surface topography. Therefore, a critical aspect of Rayleigh-wave study is to understand the wave-propagation behavior in the presence of surface topography. The acoustic/elastic boundary approach was incorporated into a ‘stair-case’ mesh for Rayleigh-wave modeling in the presence of surface topography. The conventional acoustic/elastic boundary approach, however, fails to completely fulfill the free-surface boundary condition at some grid nodes, leading to unphysical simulation results. To solve this problem, we develop a stable acoustic/elastic boundary approach that fully satisfies the free-surface boundary condition by adjusting the free boundary conditions at problematic nodes in the mesh. The accuracy is demonstrated by modeling tests in two-dimensional isotropic models in the presence of surface topography. And compared to the improved vacuum formulation, the proposed method takes less time. Our approach optimizes the free-surface boundary condition and enables the high-precision numerical simulation of Rayleigh waves.

Structural optimization of multistage centrifugal pump via computational fluid dynamics and machine learning method

Abstract To implement energy savings in multistage centrifugal pumps, a return channel is utilized to replace the origin inter-stage flow channel structure, and then a single-objective optimization work containing high-precision numerical simulation, design variable dimensionality reduction, and machine learning is conducted to obtain the optimal geometric parameters. The variable dimensionality reduction process is based on the Spearman correlation analysis method. The influence of 15 design variables of the impeller and return channel is investigated, and seven of them with high-impact factors are selected as the final optimization variables. Thereafter, a genetic algorithm-backpropagation neural network (GA-BPNN) model is used to create a surrogate model with a high-fitting performance by employing a GA to optimize the initial thresholds and weights of a BPNN. Finally, a multi-island genetic algorithm (MIGA) is employed to maximize hydraulic efficiency under the nominal condition. The findings demonstrate that the optimized model’s efficiency is increased by 4.29% at 1.0Qd, and the deterioration of the pump performance under overload conditions is effectively eliminated (the maximum efficiency increase is 14.72% at 1.3Qd). Furthermore, the internal flow analysis indicates that the optimization scheme can improve the turbulence kinetic energy distribution and reduce unstable flow structures in the multistage centrifugal pump.

The influence of the evaporation model on ethanol turbulent jet flame simulation

High-precision numerical simulation of aero-engine combustors requires a suitable evaporation model. At present, quantitative research on the effects of the evaporation model on two-phase turbulence combustion simulation is insufficient. Ethanol has a higher latent heat of evaporation than other fuels like acetone and aero kerosene, thus it is especially sensitive to the evaporation model. This paper uses LES to simulate turbulence in an aero-engine combustor, and TPDF to describe the interaction between turbulence and chemical reactions. Numerical simulation results of the Abramzon-Sirignano (A-S), Spalding, and thick exchange layer (NC-TEL) evaporation models for high-Reynolds number ethanol combustion in two-phase turbulent jet flames are analyzed and compared with experimental data. Results suggest that per unit time, the A-S evaporation model has the largest evaporation mass, followed by the NC-TEL evaporation model, while the Spalding evaporation model has the smallest evaporation mass. Through quantitative analysis of the different evaporation models’ influence on temperature, mixture fraction, and liquid phase distribution, it is found that the A-S evaporation model fits the experimental data better in the central region of jet flame but has worse performance in the other flame regions. The simulation result of the Spalding model is good in the X/D = 10 section, and that of the NC-TEL model shows the best result at X/D > 10 sections and in the outer regions of the jet flame. The maximum difference between the NC-TEL model results and the experimental data was 21.856 % in liquid phase velocity. Hence, the NC-TEL model has the best simulation performance.

An Improved Integrated Numerical Simulation Method to Study Main Controlling Factors of EUR and Optimization of Development Strategy

Gas reservoir numerical simulation is an important method to optimize the development strategy of shale gas reservoirs which has been influenced by the multi-stage fracture. The regular fracture network model was used to build a conventional numerical simulation, in which it was difficult to show the true situation of fracture propagation. However, the physical parameters not only affect the production, but also influence the stimulation effect; moreover, the quality of the fracturing effect also affects the production which causes the input and out parameters to be inaccurate. To solve this problem, the process simulation must be completed from geology to engineering to gas reservoir. The main controlling factors of production are identified with geological and engineering factors such as horizontal stage length, the volume of fracturing fluid, well spacing, production allocation, and proppant mass. Therefore, on the basis of the integrated simulation method of a hydraulic fracturing network simulation and an unstructured grid high-precision numerical simulation, this paper builds an integrated numerical simulation of a shale gas reservoir coupled with geology and engineering to optimize the development strategy with production as the target. Taking four wells of a platform as an example, the EUR (estimated ultimate recovery) has increased by 25% after the optimization of the development strategy.

An efficient finite difference IFWENO-THINC hybrid scheme for capturing discontinuities

The weighted essentially non-oscillatory (WENO) scheme is a famous shock-capturing scheme, but for high-precision numerical simulation, the classical WENO scheme is always considered to have excessive dissipation and insufficient resolution near discontinuities. Improving the accuracy order or reducing the dissipation of the WENO by optimizing the linear weights can effectively improve the resolution of this scheme in the smooth regions. However, under the same method, the improvement of shock-capturing abilities is generally limited and may lead to numerical oscillations. In order to simultaneously improve the resolution in discontinuous regions and ensure the performance of the smooth regions, this study uses the shock detector to combine the tangent of hyperbola for interface capturing (THINC) scheme, which is a better discontinuity-capturing scheme, with a given WENO discretization, such as the improved fast WENO (IFWENO) scheme that equips with high economy and does not loss accuracy at any critical point. The hybrid method in this study is an apriori algorithm, which is more efficient and universal than the method in (Takagi et al. J. Comput. Phys. 452(2022)110899). Additionally, the performance of the THINC scheme in different regions near the discontinuity is analyzed in detail through numerical experiments, and a shock detector that can fully exploit the advantages of the THINC scheme is provided. By using this shock detector, several one-dimensional and two-dimensional numerical cases are employed to verify that the hybrid scheme can greatly improve the performance in discontinuities without affecting the flow structure in the smooth regions, which proves the effectiveness of the proposed shock detector and the excellence of the hybrid IFWENO-THINC scheme.

Numerical Study of Heat and Mass Transfer in the Original Structure and Homogeneous Substitution Model for Three Dimensional Porous Metal Foam

In many applications, such as the miniaturization and cooling of high-power electronics in aerospace, a new thermal management solution is needed, and metal foam radiators may be a valuable solution. In this work, X-ray scanning was applied to obtain the original structure of the metal foam. The real structure calculation model of the metal foam was obtained through a series of modeling, and high-precision numerical simulation was built to study heat and mass transfer in the original structure and homogeneous substitution model for three-dimensional porous metal foam. The distribution of velocity, pressure and temperature field is investigated. The results show that the heat transfer characteristics increase and flow resistance decreases with an increase in the Reynolds number. The heat transfer performance and flow resistance increase with the decrease of porosity. The porous media homogenization model can be consistent with the original real calculation results of metal foam by using appropriate values of resistance coefficient and porosity. The variation of resistance coefficient and porosity with the working condition in the porous homogenization model is identified.

Моделирование волн давления при дефлаграционном горении облаков топливно- воздушных смесей

The paper examines the assumptions underlying a whole group of methods for estimating the parameters of shock waves (pressure waves) during the combustion of spherical fuel-air clouds - the so-called parametric formulas. The formulas allow to determine the parameters of pressure waves from the given energy release and combustion rate. To do this, a complete system of gas-dynamic equations is solved using high-precision numerical simulation. In this case, the combustion front is explicitly distinguished in the form of an infinitely thin discontinuity, on which the laws of conservation of mass, momentum, and energy are satisfied. The results of such a numerical calculation are compared with calculations using the corresponding parametric formulas. Clouds of a stoichiometric mixture hydrogen-air are considered. It is shown that the parametric formulas describe the expansion of clouds of hot products with a good degree of accuracy. Here, there is complete agreement with the direct numerical simulation. It is also shown that the parameters of pressure waves are satisfactorily described both in the calculation by parametric formulas and in direct numerical simulation. In this case, within the cloud, there is a greater increase in pressure than the parametric formulas predict. This is explained by the fact that the assumptions used in the formulas regarding the behavior of the flame front as an impenetrable piston do not fully reflect the physical processes: the combustion front is a semipermeable piston, and some of the mass of the initial mixture still penetrates through it. The third factor considered, which determines the achieved pressures, is the rarefaction wave that occurs in the air after the cloud burns out. This wave propagates in combination with the leading pressure front formed during combustion initiation. The extent of this complex remains practically constant, and its attenuation during spherical propagation is adequately described by the parametric formulas.

Typical case analysis of oilfield tracer testing technology

The development history and principle of interwell tracer testing and single-well tracer testing were investigated, and the application conditions and application advantages of different tracer testing were analyzed through the analysis of two types of tracer testing technologies and test results in the production process of SMi oilfield with medium porosity and low permeability, so as to provide reference for the study of tracer development in the same type of oilfield. Tracer testing technology can master the connection between injection well and production well, effectively judge the connection relationship between Wells, and provide a basis for well pattern adjustment; The seepage velocity of injected fluid in the formation can be directly observed, and the dominant injection direction can be determined, which provides reference for solving the plane contradiction. It can judge whether there is fracture system or high permeability strip, which provides ideas for high precision numerical simulation to avoid risks. It can master the remaining oil situation of single well and judge the washing efficiency of chemical agents effectively on the basis of saving investment.

Research on Wind Wave Simulation Technology based on Potential Flow Theory

The wave environment is the main service environment of surface aircraft in the process of surface duty. In order to comprehensively study the operating characteristics of aircraft under this condition, it is necessary to conduct research on wave parameter modeling methods and simulation technology based on different wave conditions. This paper adopts the three-dimensional potential theory and ball model to calculate the different wave cases. A high-precision numerical simulation method of complex sea conditions is formed by mastering the numerical wave-making technology of typical regular and irregular waves. The result shows that the regular simulation in this paper has a high precision that the wave height and period is in 1% error compared with theory. The calculation error of spectral peak and peak frequency of sea states at all levels are within ± 8%, and the simulation quality of irregular waves meets the calculation requirements.

Nanosecond laser high-precision fabrication of microgrooves on TC4 surface: Morphology simulation and drag reduction performance of microgrooves

With the increasing global awareness of environmental protection, higher requirements are also placed on the fuel consumption rate of aircraft. Microgrooves can reduce the near-wall frictional resistance of aircraft to save fuel, which has become the focus of research in the aviation industry. To realize the low-cost and high-precision fabrication of microgrooves with drag reduction effect, an efficient and high-precision numerical simulation method for nanosecond pulsed laser etching TC4 titanium alloy is studied. A laser processing strategy is formulated. Furthermore, an efficient and high-precision computational fluid dynamics simulation method is studied to verify the drag reduction effect of microgrooves. The research results show that the size error of prepared microgrooves is less than 2%, and their drag reduction rate is as high as 9.6%, which verifies the validity and reliability of the research method in this paper. This work can guide the design of high-density functional microstructures and their high-efficiency and high-precision fabrication. The research results can provide technical parameters for aircraft drag reduction, which has essential engineering practical value.

An electrochemical-thermal coupling model for prismatic lithium-ion batteries over wide temperature range

Accurate and rapid prediction of battery thermal behavior can provide accurate basis for making battery use plan, which is beneficial for alleviating the influence of thermal effect on battery life and safety. A fast numerical solution method of electrochemical-thermal coupling model for prismatic lithium-ion batteries is proposed in this work. Firstly, based on an existing electrochemical single particle model and one-dimensional thermal resistance network, analytical expression of thermal resistance network model in two-dimensional space is obtained by theoretical formula derivation. Then, to calibrate the model parameters at different temperatures, temperature range is divided into several intervals, and optimal parameter sets at different intervals are obtained by excitation response analysis method and multi-group particle swarm optimization algorithm. Finally, to realize the accurate numerical simulation of the model, a double adaptive extended Kalman filter method is applied to further optimize the parameters in real time. Seen from the simulation results over wide temperature range, mean absolute errors of voltage and temperature are less than 30 mV and 0.12 K at −5–55 °C respectively, which indicates the capability of the developed model for high-precision numerical simulation over temperature range for prismatic lithium-ion batteries.

Lunar ephemeris at sub microarcsecond accuracy (LESMA) leads to sub-millimeter positional accuracy of the moon

The most accurate LLR (lunar laser ranging) initiative, named APOLLO (apache point observatory lunar laser-ranging operation) demonstrated millimeter-range positional accuracy in 2009, thus improving LLR by one order-of-magnitude. Since, LLR is a foundational technique in studying gravity, Murphy (principal investigator of APOLLO) stated in 2009, that with this millimeter-range accuracy, the simulation model has been found to be the limiting-factor in extracting the theoretical science results, and hence, we should: (1) develop the science case and expand our ability to model LLR for a new regime of high precision, (2) develop the theoretical tools for honing the science case for submillimeter LLR, and (3) explore which model/code is worth putting our efforts into. (4) Since millimeter-quality data are a recent development, the model effort lags. (5) Finally, we will code-in new physics so that we may simulate sensitivities. In connection with simulation model/code, Murphy stated in 2013, that among the four available LLR simulation models: JPL (jet propulsion laboratory), CfA (the Harvard-Smithsonian center for astrophysics), LU (leibniz University, Hannover, Germany), and IMCCE (Institut de Mecanique celeste et de calcul des Ephemerides, France), the JPL model currently produces weighted RMS (root-mean-square) residuals at ∼18 mm, which is about half of the other models; so, clearly a gap exists from millimeter ranging-precision of APOLLO. Hence, the CfA, LU, and IMCCE are engaged, since 2013, in a stepwise comparative streamlining effort to identify the model-differences, errors, and shortcomings. All the four available LLR simulation models can be classified as GR (general relativity)-astronomers model; they are basically similar. Professor Douglas Currie of the University of Maryland, College Park, NASA Lunar Science Institute, stated in a Conference presentation, in 2012, that Ground stations, that is, the lunar observatories, have improved by a factor of 200, but the agreement between observations and fitted theory has plateaued at ∼2 cm over the past two decades. However, no substantial progress on improving the fit has been reported in the published literature, till date. Based on about a quarter-century of experience in doing high-precision numerical simulation of celestial orbits, the authors have developed LESMA (lunar Ephemeris at sub Microarcsecond accuracy) utilizing the methodology of evolved general relativity (EGR) that has incorporated the following two concepts: (1) Relativistic time for integration and (2) methodology of conservation of magnitude of the angular momentum, MΦ , for Φ-rotation (in addition to the θ-rotation that leads to the rosetting ellipse) of the orbital plane. Incorporation of the two above-mentioned concepts has led to three orders-of-magnitude accuracy-improvement of the computed (1) precession (compared to JPL's DE405) of Lunar orbit, as verified using three independent methods and (2) radial position (compared to JPL's DE430/431) of the Moon. LESMA will enable scientists to make efficient use of research-funds from NASA, etc., for production of new science results from APOLLO. LESMA will also be useful for getting better science results (than Folkner reported {in 2014} submeter accurate Position of the Moon) from the GRAIL (gravity recovery and Interior laboratory) mission (costing 500 million USD), by spending a little more for revisiting the computations, utilizing LESMA data.

Mechanical response and response mechanism of AlSi10Mg porous structures manufactured by laser powder bed fusion: Experimental, theoretical and numerical studies

In order to correctly understand the bearing capacity, failure mode and failure mechanism of AlSi10Mg porous optimized structures at different strain rates under compressive load, a series of experimental and simulative studies were carried out. Through quasi-static and modified Split Hopkinson Pressure Bar (SHPB) experiments, the damage failure modes of the AlSi10Mg porous structures with three different volume fractions are obtained at different strain rates. The stress-strain curves of AlSi10Mg porous structures obtained from the experimental results at different high strain rates show that its mechanical behavior is not sensitive to strain rates. Combined with meso-structure analysis and high-precision numerical simulation, it is found that the shear failure of AlSi10Mg porous structures due to relative dislocation along the inclined section under axial compressive load is the most direct cause of failure, which reveals its failure mechanism. Combining experimental research and theoretical analysis, the energy absorption characteristics and influencing factors of AlSi10Mg porous structures are determined at different strain rates. At the same time, the prediction models of dynamic elastic modulus and dynamic compressive strength of AlSi10Mg porous structures are constructed, which accurately describe the variation law between dynamic elastic modulus, dynamic compressive strength and structural volume fractions. These research works in this paper will provide an important reference for the structure optimal design of lightweight, strong energy absorption and impact resistance.