8results about How to "Guaranteed solution accuracy" patented technology

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.

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 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.