13results about How to "Improve calculation stability" patented technology

The invention belongs to the technical field of intelligent seismic exploration, and particularly relates to a sparse active source constrained non-ideal illumination passive source seismic wave field intelligent reconstruction method, so as to solve the problems of false events and coherent noise under the condition of non-ideal distribution of underground passive seismic sources. In order to improve the reconstruction effect of a passive source seismic wave field under a non-ideal illumination condition, the method builds an improved U-Net network, so that the U-Net network can intelligently extract data features and derive an attention mechanism along two independent dimensions of a channel and a space in the network, and multiplies the attention mechanism by an input feature map, so that the reconstruction effect of the passive source seismic wave field is improved. Self-adaptive feature refinement is carried out, so that the purpose of carrying out intelligent reconstruction on passive source data is achieved; by learning the trained deep learning network, the sparse active source seismic record constrains the passive source seismic data prediction network, passive source data reconstruction which shares a measuring line with the active source under the sparse active source condition is realized, and the multi-dimensional deconvolution reconstruction effect and the calculation stability are improved.

This invention relates to the fields of computational mechanics and rock engineering, and particularly to a numerical simulation method for end-anchored rock mass engineering based on DDDA (Digital Directed Amplification and Analysis). The method includes: constructing a circular element discontinuous deformation analysis numerical model according to actual engineering conditions; performing discontinuous deformation analysis numerical calculations; analyzing the calculation results of the unanchored model to preliminarily determine the anchoring scheme; performing discontinuous deformation analysis numerical calculations again; determining whether the model contains unstable blocks, adjusting the anchoring scheme, and repeating the aforementioned steps until the model stabilizes, thus completing the design of the rock mass engineering anchoring scheme. This invention establishes a numerical simulation method capable of accurately simulating the interaction between anchor bolts (anchor cables) and rock mass, and integrating anchoring scheme design, stability assessment, and dynamic parameter optimization functions. It achieves accurate prediction of the deformation and failure behavior of anchored rock mass and optimizes anchoring design, featuring high simulation accuracy and strong practicality.

The present invention belongs to the field of numerical forecasting technology, and discloses a GRAPES-REPS regional ensemble forecasting method and system. The GRAPES-REPS regional ensemble forecasting method includes: 0.1 degree horizontal resolution GRAEPS-REPS ensemble forecasting test parameters and model determination; GRAPES-REPS lateral boundary perturbation construction; China GRAPES-REPS regional ensemble forecasting business system construction. The present invention improves the ETKF initial value perturbation scheme and optimizes the boundary perturbation uncertainty scheme, improves the forecasting system discreteness and regional ensemble forecasting system performance, thereby meeting the business application requirements of China's regional ensemble forecasting system, and targetedly produces and provides weather forecasting services. The present invention provides 1h interval ensemble forecasting products of different levels and different forecasting time effectiveness for meteorological stations at all levels in China, provides guidance and reference for weather forecasting, and facilitates model developers to improve the performance of ensemble forecasting systems.

The invention discloses a numerical calculation method and system for turbulent combustion difference diffusion of mixed multiple fuels, and belongs to the field of turbulent combustion numerical simulation. Comprising the following steps: establishing a small flame table based on a one-dimensional hedging flame equation, parameterizing a thermodynamic state space into a function of a mixed fraction and a reaction process variable through a mapping algorithm, deducing a difference diffusion term of a multi-fuel component, and establishing and solving a difference diffusion double-equation small flame model control equation suitable for the multi-fuel component under a large vortex simulation framework; discretizing the processing model and coupling a pressure-velocity field; in the process, the same method is used for comparing a small flame model simulation result which does not consider the difference diffusion effect so as to highlight the influence of the difference diffusion effect. According to the method, a difference diffusion two-equation model is expanded to a multi-fuel mixing working condition, dual-fuel turbulence diffusion flame of hydrogen-ammonia mixing combustion is taken as an example, the mass fraction and temperature distribution of main components are compared through a prior method and a posterior method, and the influence of the difference diffusion effect is quantitatively analyzed.

This invention discloses an intelligent projection positioning and drilling accuracy control system for blast holes at tunnel faces, belonging to the field of tunnel drilling and blasting construction technology. It aims to solve the technical problems of inaccurate blast hole positioning and large drilling direction deviations in existing tunnel face systems, leading to low construction efficiency. The key technical points are: the control system includes a structured light projector mounted on a tunnel drilling and blasting trolley, at least two industrial cameras, a fiber optic shape demodulation module, and a controller. A fiber optic shape sensing unit is installed inside the drill rod at the end of the drill arm of the drilling and blasting trolley; the structured light projector projects structured light, the industrial cameras acquire binocular images, the fiber optic shape demodulation module calculates the curvature and torsion angle sequence of the sensing unit, and the controller controls the drill arm drive mechanism to correct the drill bit position and direction through 3D reconstruction, coordinate comparison, and real-time deviation adjustment. This invention achieves intelligent positioning and drilling accuracy control of blast holes at tunnel faces, improving the accuracy and efficiency of tunnel drilling and blasting construction.

This invention belongs to the field of intelligent seismic exploration technology, specifically relating to an intelligent reconstruction method for passive source seismic wavefields under sparse active source constraints and non-ideal illumination, to address the problems of false phase axes and coherent noise under non-ideal distribution of underground passive sources. To improve the reconstruction effect of passive source seismic wavefields under non-ideal illumination conditions, this method constructs an improved U-Net network, enabling it to intelligently extract data features and derive attention mechanisms along two independent dimensions—channel and space—within the network. The attention mechanism is then multiplied by the input feature map for adaptive feature refinement, achieving intelligent reconstruction of passive source data. Furthermore, a deep learning network, trained through learning, constrains the passive source seismic data prediction network with sparse active source seismic records, enabling the reconstruction of passive source data with co-located active source lines under sparse active source conditions, thus improving the multi-dimensional deconvolution reconstruction effect and computational stability.

The embodiment of the invention discloses a new energy automobile battery pack cooling system joint simulation method and device based on FMI. The method comprises the following steps: constructing a one-dimensional model of the cooling liquid circulation power system based on a Modelica language; configuring a coupling data interface of the constructed one-dimensional model and a three-dimensional CFD model of the battery pack liquid cooling plate, and exporting a one-dimensional FMU model after configuration is completed; constructing a three-dimensional CFD model of the battery pack liquid cooling plate; configuring a coupling data interface of the constructed three-dimensional CFD model and the one-dimensional model, and exporting a three-dimensional FMU model after configuration is completed; and respectively importing the one-dimensional FMU model and the three-dimensional FMU model, connecting a coupling data interface of the one-dimensional FMU model and a coupling data interface of the three-dimensional FMU model, completing joint simulation configuration, and carrying out one-dimensional and three-dimensional joint simulation.

This application discloses a method and apparatus for thyroid cancer analysis based on real-time quantitative PCR. The method includes: acquiring data to be analyzed; determining sample-specific threshold line data based on the data to be analyzed; calculating a corrected Ct value based on dual-inflection-point kinetics based on the sample-specific threshold line data to obtain the final corrected Ct value; and generating a detection result based on the final corrected Ct value. This application significantly improves the linearity of the fluorescence amplification curve, reduces the interference of background noise on the results, and improves the stability of Ct value calculation through optimized curve fitting algorithm processing.

The invention discloses a Conditional DETR image detection method based on graph attention weighting enhancement. The method comprises the steps of preprocessing a data set, constructing a Conditional DETR network, training the Conditional DETR network, storing a model, and testing the Conditional DETR network. The Conditional DETR network model is formed by sequentially connecting a backbone network, an encoder-decoder feature aggregation module and a prediction network in series, the backbone network takes ResNet50 as the backbone network to extract image features, and the image features are used for input of an encoder in the feature aggregation module; the encoder-decoder feature aggregation module is formed by connecting a self-attention mechanism module and a cross attention mechanism module in series; and the prediction network performs classification and regression prediction by using encoder-decoder output features, so that accurate detection of a target is realized. The method has the advantages of high detection precision, strong robustness and the like, and can be used for target detection of images.

The application discloses a three-dimensional numerical simulation method for a CEL-based shaped energy jet perforation and casing penetration, and relates to the technical field of oil and gas well completion and stimulation measures. The method comprises the following steps: a three-dimensional finite element model is established; according to the symmetry of geometry and load, symmetric boundary conditions or full model boundary conditions are applied to the three-dimensional finite element model; material parameter assignment is performed on the perforating bullet, the perforating gun and the casing respectively; an Euler-Lagrange coupling relationship between the Euler domain and the Lagrange entity is established, and a contact relationship between the Lagrange entities is established; the model is divided into zones for meshing; time-history calculation results of jet forming, penetration perforation and casing response are obtained; the calculation results are post-processed; and parameterized calculation of the charge weight, the geometry of the shaped charge liner, the blind hole structure of the perforating gun, the size and material parameters of the casing is carried out. The application provides a calculable basis for the structure optimization of the perforating bullet and the mechanical safety evaluation of the casing.

The invention discloses a water gauge reading method based on deep learning. The method comprises the following steps: acquiring the height information of a water gauge and the target height information of an E character; obtaining a target image, and recognizing the position of a water gauge and the position of an angular point to correct the target image; carrying out instance segmentation on an E-character target in the corrected image to obtain a recognition frame coordinate and a segmentation result of the E-character target; sorting the E-character targets from top to bottom according to the coordinates of the recognition frame, respectively calculating y coordinate value giant change times of horizontal projections of the E-character targets in the vertical direction according to segmentation results, and judging whether the E-character targets are complete or not according to the giant change times; if the updated coordinates of the identification frame exceed the position of the water gauge, the E-word target is judged to be an incomplete E-word target connected with the water surface, and the effective number of the E-word target is calculated; and calculating the current water level according to the sum of the copies of all the E-shaped targets, the height of the water gauge and the height of the E-shaped targets. According to the invention, human errors can be avoided, the influence of environmental factors on water level measurement can be overcome, and the accuracy and reliability of water level detection are greatly improved.

The invention discloses a neutron transport parallel computing method and computing device for optimizing transverse leakage item processing, and belongs to the field of nuclear power. According to the neutron transport parallel computing method for optimizing transverse leakage item processing, a boundary flow weighted by a second-order Legendre polynomial is introduced in the computing process of a single segment, adjacent segments are updated in combination with the boundary neutron flow, all the segments are traversed through parallel computing, and updated segment neutron flux, eigenvalue keff and neutron source items are obtained. And substituting the updated data back to the calculation model for iteration to obtain a final calculation result. According to the method, the high-order expansion coefficient of the transverse leakage item of the node is obtained based on the single node model, and the calculation stability is improved while the calculation precision is ensured.