129 results about "Governing equation" patented technology

The present invention relates to the technical field of heat sink structure design, and in particular to a micro-channel heat sink structure design method based on a multi-objective function. The method comprises the following specific steps: S1, constructing a general mathematical description of a topology optimization problem; S2, acquiring input conditions for a specific design scenario, and dividing a topology optimization design domain; S3, establishing a governing equation for a topology optimization model; S4, on the basis of an adjoint method, performing sensitivity analysis of a multi-objective function with respect to design variables; S5, solving the topology optimization model by means of a method of moving asymptotes (MMA); S6, obtaining a two-dimensional flow channel configuration of a heat sink on the basis of contour reconstruction, carrying out finite element analysis of a two-dimensional flow channel structure, and narrowing down the selection range of constraint conditions; and S7, on the basis of a two-dimensional finite element analysis result, constructing a corresponding pseudo-three-dimensional model, carrying out finite element analysis, and determining optimal constraint conditions to obtain a final topology-optimized heat sink configuration. Compared with traditional methods, the present invention can more efficiently solve the problem in respect of heat sink structure optimization under different scenarios.

The invention discloses a two-dimensional wave spectrum intelligent forecasting method based on a physical information neural network, and belongs to the technical field of ocean information prediction.The two-dimensional wave spectrum intelligent forecasting method comprises the steps that basic data are collected, and the basic data comprise high-temporal-spatial-resolution sea surface wind field data and sea wave height data within the research range; historical sea wave data are obtained, ocean and meteorological data closely related to sea wave changes are integrated and processed, and a sea wave forecasting database is constructed; physical constraints are determined according to the sea wave forecasting database; an ANN neural network model is adopted as a basic model, physical constraints are added, the neural network meets the control equation of the mode, and a PINN physical information neural network is constructed; and carrying out interpretability analysis on the model forecasting process and result. According to the method, the sea wave dynamic process and the deep learning method are fused, interpretability is added for deep learning, and the black box problem of the deep learning method is solved.

The invention belongs to the field of engine combustion and computational fluid mechanics, and discloses a novel flame surface turbulence combustion model. A model establishment process: solving a control equation of the diffusion flame surface turbulent combustion model to obtain a diffusion flame surface database; solving a control equation of the premixed flame surface turbulent combustion model to obtain a premixed flame surface database; solving a transport equation of speed, turbulence, mixing fraction and reaction progress variables to obtain flow field parameters; according to the mixing score and the reaction progress variable corresponding to each grid point of the flow field, temperatures and components are obtained in the diffusion and premixing flame surface databases in a table look-up interpolation mode; calculating a weighting function according to the flow field parameter of each grid point; performing weighted averaging on the obtained temperature and components through a weighting function; updating the original temperature and components of the flow field by using the weighted average temperature and components; and iteration is repeated until the flow field converges. The model gives full play to the advantages of diffusion and premixed flame surface turbulent combustion models, and has engineering applicability.

The invention provides a method and equipment for predicting the heat exchange performance of a buried pipe ground source heat pump thermal camouflage system. The method comprises the steps that S1, a multi-physics field coupling heat exchange mathematical model of a buried pipe heat exchange system is established; s2, based on the multi-physics field coupling heat exchange mathematical model, a control equation and boundary conditions are constructed; s3, on the basis of the control equation and the boundary conditions, a multi-physics field numerical model is constructed, and simulation and calibration are carried out; and S4, based on the calibrated numerical model, designing a simulation test and carrying out main control factor analysis to obtain a prediction effect of the heat exchange performance. By establishing a rock-soil body-fluid multi-physical field coupling model, the interaction mechanism of underground heat conduction, working medium flow and ground surface heat radiation is completely represented, and the hiding efficiency of the thermal camouflage system is remarkably improved.

The invention belongs to the technical field of weak compressible large deformation of soft materials, provides a dynamic analysis explicit substance point method for large deformation of weak compressible materials, and provides a brand new numerical calculation method for large deformation research of the weak compressible materials. According to the method, a weak-form control equation is discretized in a total Lagrangian substance point method framework, and challenges caused by grid distortion when a traditional method is used for solving a large deformation problem are avoided. Besides, the invention provides a volume self-locking processing technology based on an F-bar method, the problem of volume locking of the weakly compressible substance in numerical simulation can be simply, conveniently and effectively solved, and the volume self-locking processing technology can be conveniently embedded into an existing substance point method program. Meanwhile, a construction method of a smooth kernel interpolation function is developed, and the problem that the solving precision of a traditional substance point method in a boundary region is reduced can be effectively solved. According to the method, the problem of large deformation of the weak compressible material can be solved in a stable and efficient manner, and a new technical path is provided for research and application in related fields.

The invention discloses a simulation method, device and equipment for predicting flow and deformation of a porous medium and the medium. The method comprises the steps that a computational domain is selected, a corresponding computational grid is generated, and porosity initialization is conducted on the computational domain; determining a time step length and a discrete format, and setting a non-uniform factor to solve a control equation set which comprises a continuity equation, a fluid dynamics equation, a skeleton mechanics equation and a porosity updating equation; and analyzing and displaying a solving result. According to the porous medium flow and deformation simulation method independent of hypothesis and empirical parameters, the method is based on the basic principle of the microcosmic fluid-solid coupling effect, a porous medium fluid-solid coupling body kinetic equation is adopted, the situation that a traditional modeling method depends on volume averaging hypothesis and depends on a multi-phase interaction model is avoided, and the modeling efficiency is improved. The method has cross-scale applicability, and provides a new theoretical basis and prediction means for the development of technologies related to porous medium multiphase dynamics and multi-field coupling problems.

The invention discloses a storm surge artificial intelligence forecasting method based on physical equation constraints, and relates to the technical field of artificial intelligence storm surge forecasting. Comprising the following steps: step 1, collecting multi-source data; step 2, assimilating and preprocessing the data; step 3, realizing a machine learning calculation method of physical loss; step 4, constructing a physical and data co-constrained artificial intelligence model; 5, performing hyper-parameter adjustment by using a random search algorithm, and further optimizing the model; and step 6, carrying out interpretability analysis on the forecasting process and result. According to the invention, three control equations for storm surge calculation are introduced into the machine learning model, so that the dependence on the training data volume is greatly reduced compared with a traditional data-driven intelligent forecasting model; and analyzing the change trend of the physical variables in the forecasting process, carrying out visual display and uncertainty analysis, and solving the problem of uninterpretability of an artificial intelligence forecasting model.

The invention provides a frequency dispersion curve calculation method based on a decoupling type Legendre-Gauss-Labatto spectral element method, and belongs to the technical field of discrete solution of guided wave propagation in a thin plate, and the method comprises the following steps: S1, constructing a wave equation which comprises a Cartesian space coordinate system based on an orthotropic plate, and combining a constitutive equation, a geometrical relationship under the coordinate system and guided wave displacement to obtain a wave dispersion curve; substituting into a control equation when the volume force is zero to obtain an improved three-dimensional elastic wave equation; s2, a differential matrix is constructed, wherein discretization and decoupling are carried out on a wave equation on the basis of a Lagrange interpolation basis function of a Legendre-Gauss-Labatto node; s3, explicitly embedding the stress free boundary condition into the solving process through matrix line transformation, and solving to obtain a frequency dispersion curve, the derivation process is simplified, the boundary and the interior of the material are decoupled, and the physical significance is clearer. And meanwhile, the high-precision advantage of the spectrum method is maintained, and the calculation rate is remarkably improved.

The invention discloses a cooperative regulation and control method for seepage and heat transfer in a heterogeneous medium, and relates to the technical field of heterogeneous media, and the method comprises the following steps: S1, through a logging technology, a seismic exploration technology and a drilling sampling experiment, obtaining spatial distribution parameters of a target heterogeneous medium, constructing a heterogeneous parameter field, and obtaining a heterogeneous parameter field; the spatial distribution parameters comprise permeability distribution data, heat conductivity coefficient distribution data and medium deformation data; and S2, based on the permeability distribution data, the heat conductivity coefficient distribution data and the medium deformation data, establishing a seepage, heat transfer and medium deformation three-field coupling model. Three fields of seepage, heat transfer and medium deformation are coupled and incorporated into a regulation and control system, a mathematical model containing seepage and heat transfer control equations is established, the multi-field interaction process is accurately simulated, the limitation of isolated regulation and control of a traditional method is avoided, and a quantitative theoretical basis is provided for coordinated regulation and control.

The invention relates to the technical field of multi-physics field coupling, in particular to a PINN-based multi-domain physics field parameterization prediction method and device and a storage medium, and the method comprises the steps: obtaining a control equation and boundary conditions of a multi-domain physics field and independent feature parameters of each sub-domain; constructing a trunk branch framework model of a multi-domain physical field through a physical information neural network; the space coordinates and the characteristic parameters of the multi-domain physical field are input into the main branch frame model, and predicted values of a velocity field and a pressure field are generated; carrying out training point sampling on the multi-domain physical field, and training a trunk branch frame model by using point data obtained by sampling to obtain a parameterized model; and predicting a multi-domain actual physical field through the parameterized model. According to the method, the PINN, parameterization input and the control equation of the multi-domain physical field are combined, the actual multi-domain physical field can be efficiently and accurately predicted, the calculation complexity of a traditional numerical method is reduced, and the method is suitable for rapid prediction of the complex parameterization physical field.

The invention provides a method for analyzing fracture performance of interlayer cracks of a composite material, relates to the technical field of material mechanics, and comprises the following steps: providing an analysis method based on the impact fracture problem of the composite material containing the interlayer cracks in a thermal environment, and establishing an expansion finite element model of the composite material containing the interlayer cracks; a control equation of the structure under the impact load effect is solved through a Newmark-Beta method, and the fracture performance of the interlayer cracks of the composite material in the high-temperature environment is effectively simulated. According to the method, the influence rule of parameters such as temperature conditions, material layers, crack lengths and impact loads on the fracture performance of the composite material can be found.

The invention discloses a non-coal measure stratum natural gas displacement mathematical model construction method. The method comprises the following steps that gas migration equations are established, wherein the gas migration equations comprise the step of establishing a rock mass pore gas diffusion motion control equation and the step of establishing a stratum fracture gas seepage equation; establishing a stratum rock mass deformation control equation; establishing a dynamic porosity and permeability change control equation: establishing a rock mass porosity dynamic change equation, establishing a stratum fracture rate dynamic change equation and establishing a permeability dynamic change equation; and establishing a non-coal measure stratum natural gas displacement mathematical model based on the above steps. The non-coal measure stratum natural gas displacement mathematical model is established by combining the non-coal measure stratum natural gas displacement characteristics, and a scheme which is good in treatment effect, low in cost and high in efficiency is provided for non-coal measure stratum natural gas emission.

The present invention relates to the field of detonation wave simulation and calculation. Specifically, it relates to a multifunctional calculation method for detonation wave propagation that integrates data and physical information, suitable for solving various detonation wave propagation scenarios. This method constructs a fully connected neural network by acquiring the position coordinates of sample points and known physical information. This physical information includes the detonation time governing equations, boundary conditions, and propagation direction patterns. Based on this known physical information and other known conditions provided by different scenarios, a total residual is established. By iteratively solving the total residual minimum problem through an optimization algorithm, solutions for different scenarios are achieved, and the solution accuracy meets application requirements.

The phase structure evolution phase field analysis method in the annealing and crystallization process of the amorphous hafnium oxide-based ferroelectric film comprises the following steps: S1, setting a sequence parameter xi according to the evolution process from an amorphous phase to a crystal phase in the annealing process, and setting a sequence parameter eta according to the process of the crystal phase and the crystal phase; s2, a phase field theoretical model is established, the total free energy is the sum of the free energy of the sequence parameter xi and the free energy of the sequence parameter eta, and the free density in the free energy of the sequence parameter eta is obtained through coupling of the sequence parameter xi and the sequence parameter eta; s3, deducing a weak form of the control equation; and S4, compiling the weak form equation into COMSOL finite element software, solving and analyzing the phase structure in the annealing crystallization process of the thin film. According to the method, the sequence parameter xi representing the transformation process from the amorphous phase to the crystalline phase is introduced and coupled with the sequence parameter eta to construct a new free energy equation and a new control equation, the weak form of the control equation is deduced, and the phase structure and the evolution rule of the hafnium oxide-based ferroelectric film at different annealing moments can be dynamically reproduced.

A method for calculating the in-plane nonlinear deformation of an arch structure with axial defects in a Cartesian coordinate system is presented. This method is based on two states of the arch structure's curve element in the Cartesian coordinate system: an ideal axis and an actual axial defect. It derives the changes in the arc length and curvature of the curve element before and after deformation, obtaining expressions for the nonlinear compressive and bending strains in the in-plane of the arch structure with axial defects in the Cartesian coordinate system. The method also derives the nonlinear equilibrium differential equations in the in-plane of the arch structure with axial defects in the Cartesian coordinate system, obtaining solutions that satisfy the mechanical and geometric boundaries of the arch structure with axial defects. Finally, the method derives the nonlinear equilibrium governing equations in the in-plane of the arch structure with axial defects, ultimately obtaining the solution to the nonlinear mechanical problem in the in-plane of the arch structure with axial defects in the Cartesian coordinate system. This method can obtain the essence of the nonlinear mechanical problem of the arch structure with axial defects in the Cartesian coordinate system, filling the gap in the nonlinear strain-displacement expression for the in-plane of the arch structure with axial defects in the Cartesian coordinate system.

This invention discloses a method for calculating the deformation of adjacent pile foundations considering the spatial effect of foundation pit excavation. The method comprises the following steps: First, determining the spatial distribution curve of the lateral deformation of the retaining wall; second, determining the free displacement field of the soil outside the pit induced by the spatial deformation of the foundation pit; and finally, determining the governing equations for the deformation of adjacent pile foundations using the Pasternak foundation and Euler-Bernoulli beam models. This invention takes into account the significant spatial effect of the surrounding soil deformation at different spatial locations of the pile foundation. When the pile foundation is near the center of the foundation pit, the surrounding soil deformation is often large. Therefore, considering the spatial shape of the soil deformation and the spatial distribution of the pile foundation can better reproduce the actual situation of foundation pit excavation and the response of the pile foundation.

This invention belongs to the field of artificial intelligence and system response calculation technology, and provides a method and system for calculating system response based on a generalizable physical information neural network. The technical solution involves establishing a family of differential equations consisting of multiple governing equations based on the physical characteristics of the system to be analyzed, and obtaining the corresponding dataset; constructing a neural network model consisting of a main network and multiple channel networks, where the main network learns the basis functions representing the system response and shares them with all channel networks; each channel network processes a specific differential equation task within the task family and learns the basis function coefficients corresponding to that task; inputting the dataset into the neural network model, training the model by minimizing a loss function containing multiple constraints, and obtaining the optimal solution for the system response under different stimuli based on the trained model. This method can solve complex differential equations more accurately and improve the model's generalization performance on unseen tasks.

The invention provides a wave environment numerical simulation method based on a gravity water wave solution, and the method comprises the steps: constructing a fluctuation generation quantity source item based on the gravity water wave solution, and obtaining a plurality of key parameters of the fluctuation generation quantity source item in combination with a discrete wave spectrum; a basic control equation of a computational domain is established based on Navier-Stokes, a fluctuation quantity generation source item and a wave absorption source item are respectively introduced into equations corresponding to a wave generation area and a wave absorption area, and accurate wave environment numerical simulation can be realized through solving. According to the method, the load range of wave action can be effectively widened, so that the method is suitable for generation of large and steep waves, has high numerical wave generation robustness, and is beneficial to evaluation of load and safety margin of ocean structures.

This invention discloses a chemical nonequilibrium partitioning method based on local Damcole numbers, comprising: S1. Selecting a characteristic length according to the flow field characteristics; S2. Calculating the chemical reaction rate; S3. Calculating the equilibrium components of each component under isochoric and adiabatic reaction conditions using the local thermodynamic physical density and static enthalpy of the flow field; S4. Establishing a local Damcole number that quantifies the relative size of chemical reactions and flow scales; S5. Quantifying the degree of chemical nonequilibrium at different locations in the flow field based on the local Damcole number, thereby establishing a partitioning criterion to divide the flow field into equilibrium, freezing, and nonequilibrium regions; S6. Obtaining a unified dimensionless governing equation system that includes the degree of chemical nonequilibrium based on the local Damcole number.

This disclosure relates generally to high resolution simulation prediction for Computational Fluid Dynamics (CFD). CFD plays a crucial role in comprehending intricate physical phenomena spanning across scientific and engineering domains, hence it is essential to conduct simulations at high mesh resolutions for the governing equation of fluid flow. The current state-of-the-art super-resolution techniques involve reconstructing high-resolution data from down sampled low-resolution is limited to single scenario and does not accurately reflect real-world scenarios. The disclosed techniques enable prediction of fine-resolution data from low-resolution inputs from a variety of real-world CFD scenarios. Further the disclosed technique also identifies the most relevant network architecture for any CFD scenario and enabling accurate prediction of high-resolution data from low-resolution inputs by training the network architecture. Furthermore, the disclosure ensures also the robustness of the disclosed system through uncertainty analysis, encompassing both aleatoric and epistemic uncertainty analyses.

The present invention belongs to the fields of engine combustion and computational fluid dynamics, and discloses a novel flamelet turbulent combustion model. The process of establishing the model is as follows: Solve the governing equations of the diffusion flamelet turbulent combustion model to obtain the diffusion flamelet database; solve the governing equations of the premixed flamelet turbulent combustion model to obtain the premixed flamelet database; solve the transport equations of velocity, turbulence, mixture fraction, and reaction progress variable to obtain the flow field parameters; obtain the temperature and components at each grid point of the flow field by means of table lookup and interpolation in the diffusion and premixed flamelet databases respectively according to the mixture fraction and reaction progress variable corresponding to each grid point of the flow field; calculate the weighting function from the flow field parameters of each grid point; perform weighted averaging on the obtained temperature and components through the weighting function; update the original temperature and components of the flow field with the weighted average temperature and components; repeat the iteration until the flow field converges. The model gives full play to the advantages of the diffusion and premixed flamelet turbulent combustion models and has engineering applicability.

This invention provides a method and device for predicting temperature changes in electronic components based on pentahedral elements. The method includes: meshing the electronic component into pentahedral elements based on its structural parameters; determining the three-dimensional transient heat conduction governing equation and initial algebraic equation for the target region; determining correction terms based on the virtual node domain defined for the pentahedral elements, the Galerkin weight function, the three-dimensional transient heat conduction governing equation, and the initial algebraic equation; correcting the initial algebraic equation based on the correction terms to obtain the target algebraic equation; determining the final algebraic equation based on the target algebraic equation and a preset time interval; solving the final algebraic equation to obtain the transient heat conduction temperature simulation result; adjusting design parameters based on the transient heat conduction temperature simulation result; and implementing optimized design of the electronic component based on the adjusted design parameters.

The invention relates to the technical field of computational fluid mechanics, and discloses a transonic flow numerical simulation method, system and device and a medium, and the method comprises the steps: judging whether a flow field has an area of which the Mach number is greater than a preset value or not; if not, indicating that the whole flow field is a subsonic velocity region and belongs to a shock-wave-free region; if yes, determining that a supersonic speed region exists; judging whether shock waves exist between adjacent grid points or unstructured grid units or not, and if so, dividing a shock wave region and a shock-wave-free region; for the shock wave region, discretizing a space item of the control equation by adopting a TVD format to obtain a TVD format discretization result of the shock wave region; for the shock-wave-free region, discretizing a space item of the control equation by adopting a linear numerical format to obtain a linear format discretization result of the shock-wave-free region; updating the flow field by adopting a time marching method; and if the residual error converges, outputting a simulation result of the transonic flow numerical value. According to the invention, efficient, high-precision and robust transonic flow simulation can be realized.

This invention discloses a PINN flow field modeling method based on wall vortex-triggered sampling, belonging to the field of numerical modeling in fluid mechanics. The method includes the following steps: constructing the flow field solution domain, governing equations, and boundary conditions; establishing a physical information neural network with spatial and temporal coordinates as inputs and velocity and pressure fields as outputs; constructing wall vortex structure quantities based on the wall tangential velocity gradient and local positive Q-vortex structure intensity; converting the wall vortex structure quantities into sampling activation factors using a trigger gate function, and performing adaptive densification sampling in highly sensitive regions using physical residuals; jointly training the network using boundary condition loss, initial condition loss, and equation residual loss; and outputting flow parameters such as velocity, pressure, and wall shear stress. This invention addresses the problem of insufficient prediction accuracy of traditional PINN in the boundary layer, separation region, and wake region, improving the stability and sample utilization efficiency of complex wall flow modeling.

The present invention provides a method for constructing a self-sharpening penetration physics model. The method first models the target plate and obtains its material parameters. Next, the governing equations for target plate penetration are established. The projectile is then modeled and the governing equations for projectile erosion are established. The projectile-target interaction is then described, and the momentum equation for the projectile tail and the penetration pressure equation for the projectile head are established. Finally, the governing equations for projectile erosion, the momentum equation for the projectile tail, and the penetration pressure equation for the projectile head are combined to obtain a self-sharpening penetration physics model. The present invention is well-conceived and can be widely applied to various new self-sharpening armor-piercing materials, efficiently and accurately describing the penetration process.

This invention discloses an efficient transient analysis method for electromagnetic-thermal-fluid multiphysics fields on integrated chips. Focusing on electromagnetic, thermal, and fluid fields as core research objects, and centering on typical scenarios of full electromagnetic-thermal-fluid coupling, it systematically integrates the governing equations, boundary conditions, and constitutive relations of each physical field to construct a unified set of coupled partial differential equations. Under the premise of verifying and satisfying the stability conditions of all physical field discretization schemes, simultaneous numerical solutions for the multiphysics fields are achieved through FDTD. This invention, through multi-faceted synergistic optimization, achieves comprehensive adaptation to complex structures, providing reliable technical support for solving various complex engineering multiphysics coupling problems.

The invention discloses a method for calculating the inherent frequency of a porous two-dimensional functionally graded material framework, and belongs to the technical field of structural design, the framework is simplified into a beam model with two clamped ends, a motion control equation of a porous two-dimensional functionally graded material beam in a humid and hot environment is deduced through a Hamilton principle based on a Timoshenko beam theory, and the inherent frequency of the porous two-dimensional functionally graded material beam is calculated. Simplifying the equation by using a variable separation method; the inherent frequency of the beam is solved by adopting a differential quadrature method; a motion control equation is discretized by utilizing a differential quadrature method discretization principle, then the equation is converted into a matrix form, the problem of solving the motion equation is converted into the problem of solving a matrix eigenvalue by adopting a matrix transformation method, and finally solving is carried out by writing a corresponding program. The corresponding solving program is clear in logic and high in uniformity, the calculation efficiency and precision are greatly improved, and a theoretical reference can be provided for the design of the functional gradient skeleton in the later period.

This invention discloses a method and system for calculating the lateral displacement of an adjacent tunnel caused by bottom heave during foundation pit excavation. The method first calculates the lateral displacement of the soil at any depth at the retaining structure caused by the unloading of the bottom heave, and then, based on the deformation coordination between the soil and the retaining structure, converts it into an equivalent displacement S of the retaining structure. z (z); then, based on the displacement S of the enclosure structure z (z) and the maximum displacement value S reached in the active state a The ratio η is used to obtain the cohesion utilization value, and from this, the non-limit active earth pressure p is obtained based on the theory of non-limit active earth pressure. a Thus, the horizontal unloading stress p1 is obtained, and finally, the additional horizontal stress σ in the tunnel direction is obtained. y Ultimately, the additional horizontal stress σ in the tunnel is... y The load P(x) is obtained, and the governing equation for the tunnel's lateral displacement ω(x) is derived based on the coordination between soil and tunnel displacement. This equation is then expressed in matrix form to calculate the tunnel's lateral displacement ω(x). This calculation method allows for a more accurate assessment of the impact of foundation pit construction on the tunnel structure in practice, providing guidance for foundation pit design and construction.

The invention discloses a low-speed opening wind tunnel background noise prediction method, and relates to the field of aerodynamic noise research, and the method comprises the steps: 1, obtaining the spectral characteristics and frequency of turbulence pulsation in wind tunnel incoming flow, and obtaining the intensity and frequency of vortex waves based on the spectral characteristics and frequency of turbulence pulsation in wind tunnel incoming flow; 2, obtaining the shear layer thickness of a wind tunnel core test section, and obtaining the vortex core radius of the vortex based on the shear layer thickness of the wind tunnel core test section; step 3, calculating vortex wave propagation velocity, vortex convection velocity and vortex intensity based on wind tunnel incoming flow velocity; and 4, performing numerical calculation based on the data obtained in the steps 1 to 3 to obtain a low-speed opening wind tunnel background noise prediction result. Wherein a control equation used in numerical calculation in the step 4 is an improved control equation ignoring a speed gradient item, and the method can accurately predict aerodynamic noise in vortex-dominated complex flow in engineering practice.

This invention discloses a numerical calculation method and system for the interaction between a hydrogen-ammonia blended combustion flame and the wall, belonging to the field of energy and combustion engineering. Addressing the problem that existing models struggle to simultaneously capture differential diffusion effects and wall heat loss, this invention achieves this through the following steps: Solving the governing equations including wall boundary conditions based on direct numerical simulation (DNS) to generate a high-precision dataset; constructing a small flame database containing one-dimensional free-propagating flames (FPP) and head-on quenched flames (HOQ), embedding the wall heat loss effect; mapping the database to a three-dimensional parameter space of mixing fraction, reaction process variables, and normalized enthalpy to form a small flame lookup table; solving the governing parameter equations and outputting the field variables from the lookup table; and verifying the model accuracy by comparing with DNS data. This method significantly improves near-wall flame quenching and NO reduction. x The accuracy of predictions for key processes such as generation provides technical support for the optimized design of hydrogen-ammonia burners.