8 results about "Method of characteristics" patented technology

The application discloses a water hammer protection method based on a multi-preference constraint multi-objective optimization algorithm, and comprises the following steps: constructing a pipeline water hammer pressure calculation model based on fluid mechanics equations, solving by using a characteristic line method, and obtaining two pairs of characteristic line compatibility equations; selecting decision variables, fitting four target functions, and connecting the four target functions into an MSCMOEA algorithm; judging a calculation stage by a relationship between a current iteration number and a maximum iteration number, selecting a model meeting a triggering condition in models I, II and III according to a current feasible solution ratio, optimizing, iterating until a termination condition is met, and outputting a pareto optimal solution set. The application aims to realize multi-objective optimization of a water hammer protection scheme on the basis of ensuring stable operation of an engineering, further ensure engineering safety, and effectively reduce engineering cost.

The invention discloses a wing structure dynamics uncertainty solving method based on a symplectic characteristic line method, and belongs to the technical field of structural dynamics uncertainty analysis. The method comprises the following steps: firstly, establishing a cantilever beam model of a wing structure, determining uncertain parameters, and constructing a generalized probability density evolution equation; selecting a representative sample point according to the parameter probability distribution and calculating an assigned probability; thirdly, converting a structural kinetic equation into a Hamiltonian system form, and gradually solving a characteristic line by utilizing a characteristic line method of a hyperbolic equation and combining a symplectic algorithm; and translating the initial condition along the feature line to obtain the probability density distribution of each sample point, and finally superposing all sample point results to obtain a probability density function of the system response. According to the method, the feature line solving precision is improved by introducing the symplectic algorithm, the characteristics of the Hamiltonian system are better maintained, and the precision of dynamic uncertainty analysis of the wing structure is effectively improved.

This invention provides a method, system, and device for detecting and locating leaks in water supply pipes based on a probabilistic model and nonlinear filtering. The method includes: acquiring information about the water supply pipeline, such as the length, diameter, friction, and elastic modulus of each pipe; constructing a pure hydraulic model based on the water supply network information; solving the continuity and momentum equations of the water supply network using the method of characteristics; establishing a probabilistic multiple leakage model based on the circumferential stress and yield stress of the pipes, combined with the solution of the differential equation system, to determine the location and quantity of leaks in the pipeline; and using nonlinear filtering to estimate the state space in a noisy environment to achieve real-time correction and prediction of leaks. This invention considers the situation of multiple leaks in the water supply network and the water pressure difference between horizontal and non-horizontal pipes. Starting from a pure hydraulic model, it effectively solves the original partial differential equation system using the method of characteristics, effectively reducing the high false alarm rate problem of deterministic models.

The invention discloses a water-drive reservoir full-grid scale automatic history fitting method based on disturbance pulse inversion, and belongs to the technical field of reservoir numerical simulation. The method comprises the following steps: simulating a discrete seepage field as a time-streamline set based on a streamline; solving the water phase seepage equation by using a characteristic line method to obtain a saturation propagation control equation along a streamline; constructing a water saturation disturbance transmission mechanism, establishing error mapping with the water content of the production well, and forming a linear equation set; solving a least square problem by taking a water content fitting error as a constraint to obtain an optimal correction of a saturation field; updating a saturation field and generating a new streamline, and iterating until fitting reaches the standard; and correcting the permeability field based on the injection-production well time sequence correlation coefficient and the production well pressure prediction error. The method has the characteristics of insensitivity to initial saturation, high inversion efficiency and high fitting precision, and is suitable for historical fitting and prediction of large-scale complex water-drive reservoirs.

The application discloses a water drive reservoir full-grid scale automatic history matching method based on disturbance pulse inversion and belongs to the technical field of reservoir numerical simulation. The method is characterized in that: a time-flow line set is obtained by discretizing a seepage field by using streamline simulation; a saturation propagation control equation along a flow line is obtained by using a characteristic line method to solve a water phase seepage flow equation; a water saturation disturbance transmission mechanism is constructed; a water cut error mapping with a production well is established and a linear equation set is formed; a saturation field optimal correction amount is obtained by solving a least square problem with a water cut fitting error as a constraint; a saturation field is updated and new flow lines are generated according to the saturation field; and iteration is performed until the fitting reaches a standard; and a permeability field is corrected based on a time sequence correlation coefficient of injection and production wells and a production well pressure prediction error. The application has the characteristics of being insensitive to an initial saturation, high inversion efficiency and high fitting precision, and is suitable for large-scale complex water drive reservoir history matching and prediction.

The invention provides a rapid calculation method for solving a flow field of a thrust vectoring nozzle, and relates to the technical field of flow field simulation. The invention provides a quick calculation method for solving a vector nozzle flow field, which comprises the following steps of: dividing a flow field solving domain of a vector nozzle into a subsonic velocity section and a supersonic velocity section, and solving a relevant partial differential equation of the flow field of the subsonic velocity section and the supersonic velocity section of the vector nozzle flow field according to regions based on an aerodynamic method; and solving the subsonic velocity section by applying a one-dimensional flow method to obtain sound velocity line information of the rear part of the nozzle, inputting the sound velocity line information as an initial boundary condition into a characteristic line method, and solving the supersonic velocity section of the nozzle by using the characteristic line method, so that the rapid calculation of the vector nozzle flow field is achieved. According to the rapid calculation method for solving the thrust vectoring nozzle flow field, the problems that traditional computational fluid mechanics is long in time consumption and large in computational resource consumption are effectively avoided, and the calculation efficiency is effectively improved.

The present application relates to the technical field of integrated energy system optimization scheduling, and discloses a method for unit commitment of an integrated electricity-heat system based on an interior point Benders decomposition, which comprises the following steps: firstly, a mixed integer linear programming model is constructed, and decision variables such as power unit start-stop / scheduling, heat system output and heat supply network temperature are determined, so as to minimize the total operation cost of the system, integrate multiple constraint conditions, and use the method of characteristics to analyze the partial differential equation of pipe temperature conduction, thereby improving the accuracy of dynamic temperature description; and secondly, the model is solved by combining the improved Benders decomposition algorithm of the interior point method, so as to realize parallel solving of the main problem and the sub-problem. Through simulation verification of an IEEE standard system, the method can realize collaborative optimization scheduling of the electricity-heat system, adapt to wind power uncertainty, ensure the stability of the system, reduce the operation cost and improve the energy utilization efficiency.

The invention relates to the technical field of optimal scheduling of an integrated energy system, and discloses an electric heating integrated energy system unit combination method based on interior point Benders decomposition. The method comprises the following steps: firstly, constructing a mixed integer linear programming model, determining decision variables such as power unit start-stop / scheduling, thermodynamic system output and heat supply network temperature, aiming at minimizing the total operation cost of the system, integrating multiple constraint conditions, analyzing a pipeline temperature conduction partial differential equation by adopting a characteristic line method, and improving the temperature dynamic description accuracy; and the model is solved through an improved Benders decomposition algorithm combined with an interior point method, and parallel solving of the main problem and the sub-problems is achieved. Through IEEE standard system simulation verification, the method can realize electric-thermal system collaborative optimization scheduling, adapts to wind power uncertainty, guarantees system stability, reduces operation cost, and improves energy utilization efficiency.