21 results about "Numerical methodology" patented technology

The invention relates to a wellbore multiphase flow model numerical solution and gas-liquid distribution state inversion method and system, and belongs to the technical field of petroleum engineering, and the method comprises the steps: 1, constructing and training a physical information neural network for drilling wellbore multiphase flow dynamic simulation and overflow gas distribution state inversion; determining input and output of the physical information neural network; determining a loss function of the physical information neural network; training a physical information neural network; 2, designing an adaptive optimization algorithm, optimizing the final solution precision and convergence speed of the physical information neural network, and obtaining an adaptive physical information neural network; designing an adaptive activation function; designing a self-adaptive sampling mechanism based on residual errors; 3, based on the self-adaptive physical information neural network, numerical solution and gas-liquid distribution state inversion of the shaft multiphase flow model are achieved. According to the method, the problem that a traditional numerical method usually needs high-precision grid division and a large number of computing resources is effectively solved.

The invention discloses a two-way rocket launching window searching method, system and device and a medium, and the method comprises the steps: rapidly calculating two nearest launching windows of an ascending orbit and a descending orbit of a rocket according to the attributes of a central body, target orbit plane parameters, the geographic coordinates of launching points and the flight duration of the rocket; according to the method, the problem is converted into numerical calculation based on space geometry, the crossing moment is directly solved by using the geometrical relationship between the normal vector of the orbital plane and the inertial position vector of the launching point location and adopting efficient numerical methods such as dichotomy and the like, and complex dynamic iteration is avoided. According to the method, the calculated amount is greatly reduced, rapid searching of the launching window is achieved, the method is suitable for an interstellar detection task scene needing rapid response or multiple times of calculation, and the real-time performance of task planning is remarkably improved.

The invention discloses a three-dimensional flow field prediction method based on deep learning, and the method constructs a novel deep learning network RKAN-3D through collaborative integration of a nonlinear learnable activation function module and an attention-enhanced residual convolution module in combination with an indirect prediction strategy, and achieves the precise modeling of a complex three-dimensional flow field. Wherein the non-linear learnable activation function module can adaptively capture multi-scale non-linear features in a three-dimensional flow field, and the expression ability of the model to a complex flow phenomenon is enhanced; the attention enhancement residual convolution module effectively improves the perception and modeling precision of the model on local flow characteristics in a three-dimensional space structure by focusing a key flow field area. In order to overcome the high-dimensional challenge of directly predicting the state of the whole flow field, an incremental learning mechanism is introduced, and the capturing capability and generalization performance of the model on complex flow characteristics are effectively improved by gradually evolving the dynamic process of the flow field. Experimental results show that the reasoning speed of the proposed network is improved by two orders of magnitude compared with that of a traditional numerical method, and the network shows excellent prediction precision and robustness in typical three-dimensional flow field prediction tasks such as spheres and cylinders.

The invention provides an airfoil profile streaming flow field rapid prediction method based on a Fourier neural operator, and belongs to the field of intelligent fluid mechanics. According to the method, machine learning and computational fluid mechanics are deeply fused, the future flow field state is rapidly predicted through a series of input and output data, and the calculation efficiency of the method is far higher than that of a traditional numerical method. According to the method, the calculation task of several hours or even several days of traditional computational fluid mechanics simulation can be shortened to the second level, the optimization iteration period of aircraft appearance design is greatly accelerated, and the dependence and cost of research and development on wind tunnel tests and high-performance calculation are remarkably reduced.

The present application relates to the field of intelligent control and optimization, and discloses a kind of energy consumption dynamic management method, comprising the following steps: S1, the mathematical model of energy system is constructed, and the state space and control space of energy system are defined;S2, and the stability of energy system state is analyzed by Lyapunov function;S3, the optimal control law of system is obtained by solving HJB equation;S4, design Kalman type state estimator;S5, model parameters are converted between micro and macro levels, for the consistency of energy and constraint conditions between scales;S6, the HJB equation is discretized and solved using numerical method;S7, the performance of the system is verified by simulation and experiment.The effect of automatic avoidance of high electricity price operation interval, budget overrun warning and adaptive cost optimization is achieved by constructing stochastic dynamics energy consumption model, HJB optimal control solution and cross-scale energy consumption mapping, dynamic prediction and optimal scheduling control of energy consumption behavior under different loads, different electricity prices and different budget upper limits.

This invention relates to the field of space debris environment modeling technology, specifically to a short-term evolution method for continuum disintegration debris based on numerical methods. The method includes: Step 1, establishing an initial distribution model of disintegration debris, including a disintegration debris velocity increment model and a numerical model of the initial distribution of disintegration debris; Step 2, sampling feature points of the continuum using a gradient-based sampling method, selecting the top N samples with the highest L2 norm scores of the gradient vectors as feature points of the continuum to be evolved; Step 3, processing the continuum equations using numerical solutions, considering the six orbital roots and four perturbation factors to perform short-term evolution of feature points; Step 4, reconstructing the final state distribution of disintegration debris using a Student's t-mix model. This invention fills the gap in previous research in this field, which only focused on ultra-short-term and long-term evolution, and has the beneficial technical effects of requiring fewer samples, having lower computational costs, shorter computation time, higher result accuracy, and stronger robustness.

The application provides a wharf rock-embedded pile critical pile length calculation method and system, relates to the critical pile length calculation technical field, through the deep integration and data calibration of numerical simulation and physical test, a high-fidelity comprehensive parameter database is constructed, and a continuous mapping relationship of the critical length-diameter ratio about the base rock strength and the inclination is established. First, numerical analysis is carried out under multiple working conditions, then physical model test is carried out under representative working conditions, the test data are used to construct a correction model to calibrate all simulation results, so that the accuracy of the end resistance ratio prediction is significantly improved. The application effectively solves the dual limitations that the pure numerical method lacks entity verification and the pure theoretical method is difficult to simulate the complex pile-rock contact behavior, through systematically diffusing the discrete test information into the comprehensive simulation data, the stress mechanism of the inclined rock-embedded pile is accurately described, and it is ensured that the mapping relationship established subsequently can truly reflect the physical law under the multi-factor coupling.

The invention discloses a subsurface erosion simulation numerical method based on a semi-implicit two-phase substance point method, and relates to the technical field of geotechnical engineering numerical simulation, and the method comprises the following steps: generalizing unsaturated easily subsurface-eroded accumulated soil into a two-phase multi-component medium based on a mixture theory; establishing a solid-liquid double-phase double-layer grid system; establishing a core control equation of seepage subsurface erosion in the soil body; transferring the material point information of the solid phase and the liquid phase to corresponding background grid nodes in the double-layer grid system; applying a boundary condition on a background grid of the double-layer grid system, and carrying out semi-implicit solution on the core control equation; mapping the obtained node speed to a substance point; judging whether the relative velocity of the solid phase and the liquid phase exceeds a seepage velocity threshold value or not; state variable information carried by the two-phase substance points is updated; correcting permeability and saturation; and judging and calculating whether the specified time is up or whether the soil body reaches the yield limit. The method provided by the invention has important theoretical and engineering practical values for solving the difficulty in simulating the subsurface erosion disaster of the accumulated soil.

This invention discloses a numerical method for predicting aerodynamic forces of long-span bridges based on the vortex structure of the flow field, belonging to the field of bridge wind engineering. The method first uses computational fluid dynamics to simulate and generate the velocity field and vortex structure information of the flow field; then, based on the vortex diagram method, it determines the geometric boundary conditions, constructs and solves the assumed potential equation, and calculates the vortex vector; finally, it calculates the additional mass force, vortex pressure, viscous pressure, and frictional force through integration, synthesizing the total aerodynamic force. Combining flow field information and aerodynamic forces, it can analyze the contribution of different vortex structures, is applicable to both single-box girder and multi-box girder bridges, and features accurate results, high efficiency, and low resource consumption. It can be used for the analysis of flow separation aerodynamic mechanisms, solving the problem that traditional pressure integration methods cannot analyze the influence of the flow field.

The invention provides a numerical method for transient thermal simulation of a core particle integration system, and the method comprises the steps: decomposing the whole system into a plurality of modules according to the function and structural characteristics of the core particle integration system; converting a time domain heat conduction control equation in each module into a Laguerre domain; extracting heat transfer characteristics of each module based on a Laguerre domain heat conduction equation, and establishing a corresponding Laguerre macro model; taking the Laguerre macro model as an equivalent boundary condition, and solving the transient thermal response of each module in an order stepping mode by adopting a finite volume method. According to the method, on the premise that the calculation precision is guaranteed, the calculation complexity of the space domain and the time domain is reduced at the same time through the Laguerre macro model, the simulation efficiency is remarkably improved, and calculation resource consumption is reduced.

The application discloses a kind of plate pile embedded stability evaluation method of foundation pit considering unsaturated effect.Model test and numerical simulation results show that the failure sliding surface of foundation pit is the combination of curve and straight line, and the combination is not yet applied to the research of unsaturated foundation pit stability at present.Based on the upper limit principle of limit analysis, a kind of horizontal piece half analytical analysis method is proposed, the external power done by unsaturated soil gravity is calculated using this method, and based on the maximum energy consumption principle, the explicit semi-analytical solution of the moment of the lowest way of internal support point by active and passive earth pressure is obtained, and then the stability safety factor of plate pile embedded foundation pit is obtained.The semi-analytical analysis method constructed by the application has the advantages of analytical method and numerical method, effectively combines the unsaturated soil strength theory with limit analysis method, can reasonably explain the strengthening mechanism of suction effect, and has certain practical guiding significance for guiding the design and excavation of foundation pit under complex conditions.

A high-performance simulation method for heat conduction and thermal stress of embankment in non-homogeneous half-space. Based on the principle of geometric similarity transformation, the method constructs a scaling boundary modeling strategy, introduces a scaling line coordinate system, realizes the spatial mapping of Cartesian coordinates to scaling coordinates, and uses the Jacobian matrix to complete the coordinate transformation of differential operators, thereby accurately representing the non-uniform characteristics of the medium material. The Galerkin method is used to establish the control equation, and the semi-analytical solution technique is used to obtain the temperature field distribution; then the fourth-order Runge-Kutta algorithm is used for reverse iteration to further calculate the thermal stress field caused by the temperature field. The invention can effectively solve the problems of high calculation cost, complex boundary modeling and poor interface continuity of existing numerical methods in non-homogeneous media. It has high computational efficiency, excellent numerical stability and high precision characteristics, and is suitable for thermal-mechanical coupling analysis of complex engineering structures such as multi-layer foundation, embankment-water-foundation coupling system, etc.

The invention provides a satellite material surface charging potential calculation method based on a Bayesian PINN, and relates to the technical field of aircraft application, and the calculation method comprises the steps: constructing a physical information neural network, training a Bayesian physical information neural network model through the fusion of electrostatic field equation constraint and a Bayesian inference framework, and calculating the charging potential of a satellite material surface. Obtaining a trained Bayesian physical information neural network model; acquiring space coordinate data of the surface of the target satellite material; and inputting the space coordinate data into the trained Bayesian physical information neural network model to obtain a potential distribution prediction result of the surface of the target satellite material and a corresponding confidence interval. According to the method, potential distribution and confidence intervals can be rapidly obtained only by inputting space coordinates for new material surface geometrical shapes or boundary conditions, and the tedious process that a traditional numerical method needs to conduct modeling again and large-scale calculation for each new problem is avoided.

The application discloses a kind of composite stratum shield tunnel face stability support analysis methods, it is related to supporting analysis technical field, and the regional division is carried out to face and its front area, the region with similar deformation trend or instability tendency is classified into the same kind, and the different supporting control target is set for each region, the balanced scheduling framework of support and settlement is constructed, before entering risk condition, relevant risk characteristics are extracted, and input safety evaluation model, according to the evaluation result, the preventive correction of face pressure regulation amplitude, advancing rate change slope and grouting strategy is carried out, in the whole analysis and control process, cross-checking is carried out using different dimensional numerical method and field measurement, when difference is found, feedback to balanced scheduling framework, and support strategy is revised again.The analysis method constructs scheduling framework by real-time data and partition classification, combined with safety evaluation and cross-checking, overcomes the deficiency of composite stratum analysis, improves the stability of face and construction safety.

The present application provides a kind of numerical method of limited shear flow in immiscible droplet engulfment behavior, it is related to the technical field of immiscible droplet engulfment behavior, the simulation task based on phase field model and Navier-Stokes equation is established in the present application, the calculation domain is dispersed by finite element method and the physical field is initialized, in each time step, the updated velocity field and phase field data are obtained by coupling solution, then the interface curvature change rate and the vorticity intensity of flow field are comprehensively calculated, the global index representing the dynamic intensity of system is generated, the index is compared with the preset threshold value, the adjustment strategy of next time step is dynamically selected: when the index is higher than the threshold value, smaller step and higher grid resolution are used, otherwise, larger step and lower resolution are used, finally, the solver configuration is automatically reconstructed according to the selected parameters, the simulation is continued under the new adjustment strategy, forming the adaptive numerical simulation cycle, until the simulation is completed and the complete field data of droplet engulfment process is output.

The application discloses a kind of simulation numerical method of latent erosion based on semi-implicit two-phase material point method, and relates to geotechnical engineering numerical simulation technical field, which comprises: based on mixed physics, non-saturated easy latent erosion accumulation soil is generalized as two-phase multi-component medium;Establish solid-liquid two-phase double-layer grid system;Establish the core control equation of internal seepage latent erosion of soil;The material point information of solid phase and liquid phase is transmitted to the corresponding background grid node in double-layer grid system;Boundary conditions are applied on the background grid of double-layer grid system, and the core control equation is semi-implicitly solved;The node velocity obtained is mapped to material point;Judge whether the relative velocity of solid phase and liquid phase exceeds seepage velocity threshold value;Update two-phase material point carrying state variable information;Correct permeability and saturation;Judge whether the calculation reaches specified time or whether soil reaches yield limit.The present application has important theoretical and engineering practical value for solving the simulation problem of accumulation soil latent erosion disaster.

The application relates to a numerical method, device, computer equipment and storage medium based on a general time root scale Reynolds stress turbulence model. The method comprises the following steps: obtaining a scale equation of turbulence with respect to a scale based on a relationship between a general time root scale and an omega scale according to an omega scale equation of an existing SSG / LRR-omega Reynolds stress model; coupling the scale equation and a known turbulence equation based on the SSG / LRR-omega model to obtain a model; obtaining a RANS equation set, coupling the model, obtaining a coupled equation set, constructing grid data of a turbulent flow field of an aircraft to be simulated when performing numerical simulation of the flow field of the aircraft, performing numerical solution on the coupled equation set according to the grid data, and obtaining a numerical simulation result of the turbulent flow field of the aircraft. When n is a positive integer, the wall boundary condition is strictly 0, and numerical stability can be realized when high-precision discretization or a complex structure / non-structure grid is adopted.

The invention relates to the field of turbomachinery part test and complete machine test, in particular to a lemniscate flow tube design and three-dimensional numerical calculation method, which comprises the following steps of: iteratively calculating flow tube outlet airflow temperature and flow tube outlet airflow density, introducing a flow tube boundary layer correction coefficient, obtaining the diameter of a flow tube through a continuous mass equation, and calculating the flow tube diameter according to the flow tube boundary layer correction coefficient. The method comprises the following steps: constructing a horn mouth profile based on a lemniscate polar coordinate relation, drawing a size line and an auxiliary line of a flow tube in mechanical design software, constructing a boundary line of a grid block in a near-wall area of the horn mouth by an arc curve, generating a flow tube equally-divided grid, performing numerical method and boundary condition setting on the flow tube grid, and solving. The lemniscate flow tube design and three-dimensional numerical calculation method provided by the invention is simple and easy to use, has the characteristics of short time, high calculation precision and the like, and can quickly provide reference for the test scheme design of the whole gas turbine or the compressor part, so that the design risk can be reduced, and the design quality can be improved.

The invention provides a calculation method and system for the critical pile length of a socketed pile of a wharf, relates to the technical field of calculation of the critical pile length, constructs a high-fidelity comprehensive parameter database through depth fusion and data calibration of numerical simulation and a physical test, and establishes a continuous mapping relational expression of a critical length-diameter ratio about bedrock strength and an inclination angle according to the high-fidelity comprehensive parameter database. Firstly, multi-working-condition numerical analysis is carried out, then a representative working condition is selected to carry out a physical model test, and a correction model is constructed by using test data to calibrate all simulation results, so that the accuracy of end-to-resistance ratio prediction is remarkably improved. According to the method, the double limitations that a pure numerical method lacks entity verification and a pure theoretical method is difficult to simulate a complex pile-rock contact behavior are effectively solved, and high-precision description of the stress mechanism of the inclined socketed pile is realized by systematically diffusing discrete test information into comprehensive simulation data; and it is ensured that the subsequently established mapping relational expression can truly reflect the physical law under the multi-factor coupling effect.

The present application relates to a wellbore multiphase flow model numerical solution and gas-liquid distribution state inversion method and system, belonging to the technical field of petroleum engineering, comprising: step 1: constructing and training the physical information neural network of drilling wellbore multiphase flow dynamic simulation and overflow gas distribution state inversion; determining the input and output of the physical information neural network; determining the loss function of the physical information neural network; training the physical information neural network; step 2: designing an adaptive optimization algorithm to optimize the final solution accuracy and convergence speed of the physical information neural network, obtaining an adaptive physical information neural network; designing an adaptive activation function; designing a residual-based adaptive sampling mechanism; step 3: realizing the numerical solution of the wellbore multiphase flow model and the gas-liquid distribution state inversion based on the adaptive physical information neural network. The present application effectively solves the problem that the traditional numerical method usually requires high-precision grid division and a large amount of computing resources.

This invention discloses a method for calculating the bearing capacity of prestressed CFRP slab end-peel failure, belonging to the field of bridge reinforcement technology. The method includes: establishing a finite element model of a prestressed CFRP-reinforced concrete beam at the end based on the fracture phase-field method; determining key parameters affecting peel bearing capacity, such as concrete strength, prestress level, and tensile zone protective layer thickness, through simulation; establishing bending peel bearing capacity sub-models and shear peel bearing capacity sub-models considering the influence of prestress, respectively, based on the parameters; and establishing a bending-shear correlation equation using circular correlation curve fitting to comprehensively evaluate the peel bearing capacity of the slab end section under combined bending and shear action. This invention overcomes the limitations of traditional numerical methods, which require pre-setting failure paths and face difficulties in parameter calibration when simulating complex interface peeling. It can accurately predict the end-peel failure bearing capacity of prestressed CFRP-reinforced beams, providing a reliable basis for engineering design and safety assessment.