17results about How to "Guaranteed solution accuracy" patented technology

The invention discloses an aircraft body freedom degree flutter time domain analysis method, device and equipment and a medium, and relates to the field of aircraft dynamic aeroelastic analysis, and the method comprises the steps: determining the initial steady state of an aircraft through static balancing by using an aircraft aerodynamic grid model and an aircraft structural grid model; performing motion deformation coupling analysis on the aircraft after the initial disturbance is applied under the initial steady state condition, and determining the displacement of the aircraft surface node relative to the balance position based on the analysis result; updating a pneumatic grid through displacement, obtaining surface aerodynamic force of the aircraft based on the updated pneumatic grid, mapping the aerodynamic force to a structural grid by using a pneumatic structural coupling interface, and obtaining an aerodynamic load; and carrying out motion deformation coupling iteration and pneumatic structure coupling iteration based on the pneumatic load, carrying out coupling time propulsion when a coupling residual error meets a preset condition, judging the dynamic stability of the aircraft according to the displacement in the time propulsion process, and completing the time domain analysis of the degree-of-freedom flutter of the aircraft body. And high-precision analysis of the aircraft is realized.

The invention belongs to the technical field of gear transmission, and discloses a dynamic modeling method of a flexible bevel gear system considering meshing point change, which is used for analyzing vibration response and dynamic stress response characteristic laws of the bevel gear system in a traveling wave resonance state. And further analyzing the traveling wave resonance phenomenon of the spiral bevel gear system in the aero-engine accessory casing. A three-dimensional shell unit and a beam unit are adopted to establish a bevel gear pair finite element entity model. A dynamic model of the flexible bevel gear system considering meshing point changes is established by adopting a substructure modal synthesis method and a rotation modal projection method. The reliability of the provided model is verified through a finite element entity model and an experimental test result. On the basis, dynamic response and vibration stress experiment tests are combined, and the traveling wave resonance phenomenon of the bevel gear system is researched. The research result of the provided model has theoretical significance on design and fault monitoring of the aero-engine bevel gear system.

The invention discloses a sparse representation correction method for an aerodynamic thermal radiation effect image, which belongs to the field of digital image processing, and comprises the following steps: constructing an energy functional optimization model with the goal of minimizing the sum of a data fidelity term, an image prior regularization term and a bias field prior regularization term; the data fidelity item is used for measuring the difference between the degraded image and the original clear image and the difference between the degraded image and the bias field; the image prior regularization item is used for measuring the gradient of the original clear image; the bias field B adopts dictionary fitting as B = Wa, W and a are a dictionary and a coefficient vector respectively, and a prior regularization item of the bias field is used for measuring an L1 norm of the coefficient vector a; solving the energy functional optimization model under the constraint that the number of non-zero elements in the coefficient vector a does not exceed a preset threshold value to obtain the coefficient vector a; and reconstructing a bias field B according to B = Wa, and subtracting the bias field B from the degraded image to obtain an original clear image. The correction precision and the corrected image quality of the pneumatic thermal radiation effect image can be improved.

The application relates to the technical field of data center thermal management and intelligent control, in particular to a cold and electricity linkage group control method applied to micro data module center fusion feedforward control and hotspot tracking, which obtains IT load node computing power task scheduling intention sequence, real-time power consumption data, refrigeration terminal operation state and sparse environmental sensing data; a multi-dimensional thermal load feedforward tensor is output through a computing power-heat flow double-driven space-time graph convolution network; a three-dimensional temperature field is reconstructed and a hotspot drift vector field is extracted by fusing a physical information neural network and a fluid mechanics control equation; a model predictive control and multi-agent reinforcement learning fusion decision model with cold energy transmission lag compensation is constructed, and a cold and electricity collaborative action sequence is output; instructions are sequentially issued to realize dynamic matching of cold energy arrival and power consumption peak. The application deeply couples computing power scheduling and refrigeration control, feedforward predicts thermal load change, realizes accurate on-demand cooling and hotspot advance suppression, and significantly improves energy efficiency and thermal safety level.

The application relates to an aircraft aerodynamic shape design method and system based on a partial differential equation, which comprises the following steps: obtaining the aerodynamic shape parameters of an aircraft and equation parameters of a partial differential equation and inputting a large language model constructed in advance; judging whether a closed-form analytical solution of the partial differential equation exists according to the equation parameters, outputting an analytical formula if the closed-form analytical solution exists, analyzing an obstacle factor if the closed-form analytical solution does not exist, judging whether transformation is needed based on the obstacle factor, simplifying the partial differential equation based on a transformation method, continuously analyzing the feasibility of operator splitting if transformation is not needed, generating a hybrid solver code if the feasibility of operator splitting is available, performing numerical stability analysis if the feasibility of operator splitting is not available, generating stability parameters and a pure numerical solver code, solving the partial differential equation based on the pure numerical solver code and outputting flow field data, and further optimizing the aerodynamic shape of the aircraft. Compared with the prior art, the application has the advantage of high quality of generated solvers.

This invention discloses a large-scale power grid simulation method, program product, and storage medium based on algebraic multigrid optimization. The method includes: parsing the netlist of a large-scale power grid to establish a power grid topology matrix; extracting global feature vectors based on the netlist and the power grid topology matrix; compressing the power grid topology matrix to obtain a compressed feature matrix; constructing and training a regression model, which is used to predict the solution time based on the compressed feature matrix, global feature vectors, and coarsening parameters; using the minimum output of the regression model as the objective function, and employing simulated annealing to find the optimal coarsening parameters; establishing a power grid simulation system Ax = b; and solving the power grid simulation system using the algebraic multigrid method with the optimal coarsening parameters to obtain the power grid unknown vectors, thus realizing large-scale power grid simulation. This invention improves solution efficiency and reduces memory consumption while ensuring accuracy.

This invention discloses a solution to the joint path and destination planning problem based on a distributed generalized Nash equilibrium algorithm. First, the joint path and destination planning problem is modeled, transforming it into a non-cooperative game model. This model includes the objective function of each electric vehicle, global coupling constraints, and local constraints. Second, pseudo-gradients are used to transform the game model into a VI problem, introducing edge-based consistency constraints and a heterogeneous step size mechanism. Based on fixed-point iteration and proximal gradient operator theory, a distributed solution algorithm under complete information is proposed. Then, a global estimate of the plans of other users is introduced, proposing a distributed solution algorithm under partial information. This invention avoids the construction of double random matrices through edge-based consistency constraints, and can maintain solution accuracy while meeting low computational requirements when more users participate in the game model.

The invention provides an automatic deployment WiFi access point information map construction method and system. The method comprises the following steps: analyzing channel change characteristics, analyzing energy distribution of a signal on a time axis, identifying an energy concentration area, and obtaining a highest point of energy PLCR; establishing a correlation among the energy highest point PLCR, the human body movement speed and the human body position, obtaining and utilizing a model prediction framework, carrying out reverse solution on a track, fusing human body movement constraints and spatial constraints into a simulation data set, and utilizing the speed constraint in the movement constraints to derive a feasible region of the target position, so as to obtain the target position. Calculating a feature data set according to the simulation trajectory sequence, training to obtain a data-driven framework model, and processing to obtain a prediction trajectory; and carrying out similar SAGE iterative solution, and carrying out iterative optimization on the parameter estimation value by utilizing an SAGE algorithm until a preset convergence condition is met. The technical problems that large-scale deployment difficulty is large, dependence on specific antenna layout restricts system adaptability, and modeling and positioning operation precision is low are solved.

The invention discloses a low-rank decomposition image non-uniformity stripe correction method and system, and belongs to the technical field of digital image processing. In the process of correcting an image to be corrected, an energy functional optimization model with the purpose of minimizing the sum of a data fidelity term, an image priori term and a stripe priori term is constructed, and on the basis of the discovery that a non-uniform stripe has consistency on each column, after a rank-one constraint is applied to a stripe matrix, the non-uniform stripe is corrected, so that the correction precision of the image to be corrected is improved. The model is decomposed and solved to realize reconstruction of stripe noise and image correction, so that an image with a non-uniform stripe can be accurately corrected, and the quality of the reconstructed image is improved; meanwhile, the method can accurately correct images containing different types of non-uniform stripe noise, and is wide in application range.

The invention relates to the technical field of electric energy metering, and discloses a charging gun metering error monitoring method based on an energy router, and the method comprises the following steps: obtaining the data of a charging gun and an energy router; and calculating the line loss and the line loss rate of the charging station. And identifying line loss rate abnormal points and eliminating corresponding data. Windowing is carried out, weighted accumulation is carried out on data in a window, and sample data are traversed when one sample point is slid every time; and establishing a linear model to solve a charging gun error coefficient, and monitoring a charging gun metering error. According to the method, the line loss rate is calculated through the data of the energy router and the charging gun based on the node sampling data at the interval of 15 minutes, after abnormal value processing is performed on the line loss rate through the 3 sigma principle, accumulation summation is performed on the original electric quantity data in a sliding window mode, and meanwhile, the problem that the importance of sample data after each group of sliding windows is different in an actual application scene is considered. Weights are given to the sampling data after window sliding, the solving precision of the error coefficient of the charging gun is further improved, and accurate detection of the abnormal charging gun is guaranteed.

This invention relates to a load-balancing-based constellation communication-navigation coupled task scheduling method, belonging to the field of aerospace mission planning technology. It primarily improves resource allocation efficiency under equipment-level constraints and addresses the challenge of ensuring communication task completion while meeting the geometric accuracy requirements of navigation services. The invention uses satellite ephemeris data and mission requirement parameters as input to construct a multi-objective mixed integer linear programming (MILP) model. The optimal binary allocation variables are then obtained through a MILP solver, and the service satellites and service time slots for each mission are extracted to generate a scheduling table. This invention avoids the problem of navigation mission failure caused by communication tasks occupying multi-satellite convergence windows in separate planning. Simulations show that the overall mission completion rate is improved by an average of 12.3 percentage points, and the load variation coefficient is reduced by 66%–88%.

This invention provides a thermal simulation method for analyzing thermoelectric cooling integrated packaging systems. The method includes: decomposing the computational domain into thermoelectric and non-thermoelectric regions based on the physical characteristics of the thermoelectric cooling integrated packaging system; employing a one-dimensional adaptive segmentation technique for the thermoelectric region to simplify the three-dimensional thermoelectric arm into a one-dimensional structure, and approximating the temperature-dependent parameters as constants within each segment to establish a port macromodel for the thermoelectric region; constructing a spatially perceptual neural network for the non-thermoelectric region, using a dual-branch architecture to extract spatial heat flow features and global features, and establishing a port macromodel for the non-thermoelectric region; establishing the connection between the thermoelectric and non-thermoelectric regions through the temperature and heat flow continuity conditions at the ports, and performing iterative solutions; and reconstructing the temperature distribution of the non-thermoelectric region based on the heat flow density at the ports. This invention significantly improves the simulation efficiency of thermoelectric cooling integrated packaging systems while ensuring computational accuracy.

The invention discloses a reactive voltage optimization control method for an electricity-gas interconnection integrated energy system, belongs to the technical field of power system optimization control, and is used for solving the technical problem that the reactive power optimization method in the prior art neglects the reactive power output characteristics of a new energy unit and a coupling element. According to the invention, after the reactive power output of the new energy unit and the coupling element gas turbine is considered in the electric-gas interconnection integrated energy system IEGS, the system voltage deviation is effectively reduced; it is proved that combined dispatching of the gas turbine and the P2G can improve the absorption capacity of the wind turbine generator of the system, and the economic cost is reduced. According to the method, the reactive voltage optimization model of the electrical-pneumatic interconnected integrated energy system is converted into the mixed integer second-order cone programming model by using the second-order cone relaxation method, so that the solving precision and rate are ensured.

The application discloses a power system random operation scene reduction and accelerated solving method based on target space distance, and belongs to the technical field of power system random optimization scheduling. Firstly, uncertain scene data of wind power, photovoltaic and load and the like are acquired, and a power system random optimization scheduling model is established; subsequently, decision mutual adaptability and target space distance between scenes are calculated according to scheduling results under different scenes, and a target space distance matrix is constructed; a clustering method is adopted to classify scenes, representative scenes are screened and scene probability redistribution is completed; finally, the reduced representative scene set is used to complete random optimization scheduling solving. The application can more accurately retain key scenes which have greater influence on an optimization target, reduce the optimality loss caused by scene reduction, improve the calculation efficiency of random optimization scheduling and the new energy consumption capacity, and can be applied to random operation optimization and scheduling decision of a high-proportion new energy power system.

The present application relates to the technical field of water conservancy and hydropower engineering design, and discloses a dam multi-physical field coupling design method, device, equipment and medium, the present application constructs a heterogeneous hybrid solution architecture of embedding a machine learning model and a numerical solution model which is constrained by a physical control equation, and differentiates model selection based on the difference in the rate of change of each physical field in space and time, fundamentally solving the core contradiction between the low efficiency of traditional pure numerical simulation and the lack of physical constraints in pure data-driven machine learning models which are prone to non-physical solutions; at the same time, through mutual feedback type two-way coupling iteration of the response results of each physical field, the solution efficiency and solution accuracy are simultaneously considered; on this basis, combined with the adaptive screening mechanism of the multi-working-condition differentiated response weight strategy, the design scheme can dynamically adapt to the core needs of different service working conditions, significantly improving the engineering practicability of the design scheme.

The invention discloses a method for solving the dynamic characteristic coefficient of a sliding thrust bearing of a turbocharger, which reduces the limitation of experimental equipment and experimental places on the turbocharger in the process of solving the dynamic characteristic coefficient of the sliding thrust bearing, and ensures the solving precision of the turbocharger. The solved sliding thrust bearing dynamic characteristic coefficient comprises bearing oil film pressure field distribution, bearing oil film rigidity and bearing oil film damping. The fluid calculation of the sliding thrust bearing clearance oil film flow field is carried out through professional fluid calculation software Fluent, and the grid updating of the oil film grid model is realized by adopting a dynamic grid method. And solving the dynamic characteristic coefficient of the sliding thrust bearing, and in consideration of the characteristics that the axial size of a bearing clearance oil film is very small and the requirement for the grid quality in the fluid calculation process is relatively high, improving the grid quality by adopting a grid splicing technology and a structured grid division mode so as to ensure the calculation precision.

The present invention discloses a multi-objective optimization scheduling method for a comprehensive stable hydrogen production system taking into account analysis, which belongs to the field of electrical engineering. The method includes: establishing the relationship between the feed and output of the hydrogen production element according to the mass balance relationship and energy balance relationship of the hydrogen production element; establishing the mass balance equation and energy balance equation of the compression element and the heat exchange element; establishing the balance equation of each element; establishing the operation constraints of the hydrogen production element, the operation constraints of the energy storage element and the stable hydrogen production constraints; establishing a multi-objective optimization scheduling model with the goal of minimizing the total loss of the system and minimizing the total operating cost, and obtaining an optimization problem including the multi-objective optimization scheduling model and system constraints; linearizing the system constraints and scalarizing the multi-objective optimization scheduling model; solving the optimization problem after processing to obtain the optimal scheduling solution. While ensuring the green and stable hydrogen supply, the energy quality of the system is improved.