13results about How to "Relatively small error" patented technology

This invention provides a vehicle simulation speed correction method and system, relating to the field of vehicle intelligent dynamics modeling technology. The correction method includes the following steps: S1: Input and process simulation data output from the vehicle dynamics simulation model and corresponding real vehicle test data; S2: Construct a dynamic graph structure representing the interaction between state variables based on a preset physical coupling relationship of the vehicle powertrain; S3: Input the simulation data into a GCN and perform graph convolution operations under the constraints of the dynamic graph structure to extract graph embedding feature sequences representing the spatial dependencies between state variables; S4: Input the graph embedding feature sequences into a TCN and perform temporal convolution operations to learn the dynamic evolution law of state variables in the time dimension and output the correction amount of the vehicle simulation speed; S5: Output the result. Based on this, this invention solves the problem that existing correction methods have various limitations in practical applications.

This invention relates to the field of black carbon aging research technology, and more particularly to an experimental apparatus for black carbon aging research, comprising: a sample introduction system, including a heating tube, a pretreatment tube, an oxidizing gas removal tube, and a drying tube connected in series; a black carbon coating device, including an injection assembly, a coating chamber, a first absorption chamber, a heating removal assembly, and a second absorption chamber connected in sequence; a detection system, connected to the first absorption chamber, the heating removal assembly, and the second absorption chamber; an integrated device, including a mounting box and an aerosol charging device, a first differential migration particle size analyzer, a second differential migration particle size analyzer, and a condensed particulate matter counter disposed within the mounting box; and a control system, disposed within the mounting box, for regulating the sample introduction system, the black carbon coating device, the detection system, and the integrated device. This invention improves the convenience of black carbon research.

This invention relates to a temperature-controlled stress electrochemical metal hydrogen permeation testing device and method. The testing device includes a hydrogen permeation electrolytic cell, a hydrogen efflux electrolytic cell, a first temperature control mechanism, a second temperature control mechanism, a tensile testing machine, a potentiostat, an auxiliary electrode, a reference electrode, and a working electrode. The hydrogen permeation electrolytic cell is equipped with a first temperature control mechanism for controlling the temperature of the hydrogen permeation electrolytic cell, and the hydrogen efflux electrolytic cell is equipped with a second temperature control mechanism for controlling the temperature of the hydrogen efflux electrolytic cell. The sidewalls of the hydrogen permeation electrolytic cell and the hydrogen efflux electrolytic cell are respectively provided with a first connecting pipe and a second connecting pipe. Both the hydrogen permeation electrolytic cell and the hydrogen efflux electrolytic cell are equipped with an auxiliary electrode and a reference electrode. The two ends of the working electrode are respectively connected to the tensile testing machine. The working electrode, the reference electrode, and the auxiliary electrode are respectively connected to the potentiostat. A sample is welded onto the working electrode. The hydrogen-filled surface and the hydrogen-effluxed surface of the sample are sealed to the first connecting pipe and the second connecting pipe through sealing gaskets.

This application discloses a clock synchronization method, apparatus, board, and computer-readable storage medium, relating to the field of network time synchronization technology. The service card encapsulates a device sending timestamp in a first NTP request message sent by the main control card based on the first current service system time to obtain a second NTP request message, which is then sent to the NTP server. Based on the second current service system time, the service card encapsulates a device receiving timestamp in a second NTP response message sent by the NTP server to obtain a first NTP response message. The first NTP response message is then sent to the main control card, allowing the main control card to calculate the network clock deviation between itself and the NTP server based on the first NTP response message, and adjust the main control system time accordingly. This method avoids the problem of large errors between the device sending timestamp and the device receiving timestamp, thus ensuring that the network clock deviation calculated by the main control card will not have significant errors.

This application provides a core-shell structure microwave absorbing material and its thickness optimization design method and application, relating to the field of electromagnetic wave absorbing materials technology. The core-shell structure microwave absorbing material comprises a sheet-like magnetic metal core and a silica shell covering the core, the silica shell being prepared via a sol-gel method. The optimization design method includes: obtaining the intrinsic electromagnetic parameters of the constituent materials; constructing a single-particle simulation model with shell thickness as the variable; calibrating the simulation parameters through a decoupling-testing-verification iterative process; optimizing the solution for the optimal thickness based on the calibration model with the goal of maximizing the effective absorption bandwidth of reflection loss; and finally determining the optimal thickness range through experimental verification. This application achieves synergistic optimization of microwave absorption performance and corrosion resistance, solving the problems of long development cycles and high costs associated with traditional trial-and-error methods. The designed core-shell structure microwave absorbing material can be widely used in fields such as electronic equipment shielding, stealth technology, and microwave anechoic chambers.

The present application belongs to the technical field of material calculation and high-throughput screening, and particularly relates to a kind of ABN2 type silicon nitride sintering aid thermal conductivity prediction screening method. Wherein, the prediction method comprises: obtaining ABN2 type nitride data, screening stable structure according to formation energy threshold value;Adopt "labeled training-unlabeled prediction" phased strategy, utilize graph neural network to fill in the missing B and G;Introduce the improved Slack model based on elastic anisotropy structure correction factor fs Calculation of lattice thermal conductivity κ. The screening method is based on the predicted κ value, and the thermal performance of silicon nitride ceramic is sorted according to the regulation and control requirements of output. The present application designs the correction factor for the strong anisotropic structure characteristics of ABN2 type nitride, significantly improves the prediction accuracy of thermal conductivity, and greatly improves the data coverage by machine learning to fill in the parameters, forming a complete high-throughput screening scheme from parameter filling, thermal conductivity calculation to sintering aid application output.

This invention discloses a non-inertial navigation mobile indoor volume measurement and 3D reconstruction method, equipment, and computer-readable medium, belonging to the interdisciplinary field of precision engineering measurement, computer vision, and digital twin technology. The method includes the following steps: S1, dynamic scanning data acquisition; S2, adaptive data augmentation and cleaning; S3, trajectory and depth calculation based on motion continuity constraints; S4, cross-sectional topology construction and closure constraints; S5, 3D solid modeling preserving volume characteristics; and S6, precise volume calculation based on the solid model. This invention employs the aforementioned non-inertial navigation mobile indoor volume measurement and 3D reconstruction method, equipment, and computer-readable medium, and through a single-line 2D LiDAR combined with innovative algorithms, achieves mobile high-precision volume measurement and high-fidelity 3D reconstruction of irregular indoor spaces under low-cost hardware conditions.

This utility model discloses a rice cooker temperature detection device, relating to the field of rice cooker temperature detection technology, including a temperature sensor, a rice cooker lid, and a rice cooker ECU. This utility model uses a temperature sensor sealed to the lid, with the sensor probe extending into the pot. After being sealed to the lid by a sealing ring, the internal temperature is not leaked out, ensuring a small error between the temperature detected by the sensor and the actual temperature inside the pot. The sensor probe is a high-precision NTC thermistor, encased in a high-efficiency stainless steel probe shell. A shell fixing plate is provided on the probe shell to fix it to the rice cooker lid, ensuring accurate positioning of the temperature sensor probe. The other end is connected to the rice cooker ECU via a wiring harness connector, feeding back the temperature detected by the sensor probe to the ECU. The ECU then instructs the thermostat to adjust the internal temperature of the rice cooker during operation, facilitating precise control of the internal temperature, improving the fluffiness and texture of the rice.

The present application provides a kind of converter energy consumption and carbon emission diagnosis and optimization method based on production rhythm, belong to steel metallurgical process intelligent diagnosis technical field.Input with converter process production rhythm parameter, operating parameter and material structure parameter, oxygen consumption, converter gas recovery and steam recovery are predicted by long short-term memory network, and energy consumption and carbon emission of current converter working condition are calculated accordingly;Based on multidimensional production data, the reference working condition is obtained by clustering algorithm;The deviation index between the current working condition and the reference working condition is constructed and the working condition is diagnosed, and the influencing factors are sorted according to the contribution degree;On this basis, the converter production is optimized combined with working condition deviation and influence weight.This method uses entropy weight method, integrates energy efficiency and carbon emission index, constructs working condition evaluation system, selects the reference working condition with optimal energy efficiency and carbon emission by clustering algorithm, and realizes converter production optimization.

This invention discloses an intelligent simulation and computation method for complex chemical reactions. Combining multimodal data fusion, deep learning models, and physically constrained networks (PINNs), along with reinforcement learning optimization strategies, it achieves efficient and accurate prediction of reaction processes and intelligent control of reactor parameters. The method first constructs a reaction model using graph neural networks (GNNs) and physically constrained neural networks (PINNs), embedding core equations from chemical kinetics, mass transfer, and fluid dynamics to ensure the prediction results conform to physical laws. Then, based on the proximal strategy optimization (PPO) algorithm, it achieves real-time optimization of reaction conditions, dynamically adjusting operating parameters such as temperature, pressure, and flow rate to maximize reaction conversion, selectivity, and energy efficiency. This invention can be widely applied to chemical reaction systems such as catalytic reactions, multiphase reactors, microchannel reactors, and drug synthesis, significantly improving computational efficiency and accuracy, reducing the computation time of traditional methods, and providing intelligent online optimization and control solutions for industrial chemical reaction processes.

This invention provides a method for establishing a calculation model for the total gas content of high-temperature, high-pressure methane-bearing rocks, belonging to the field of geophysical logging and reservoir evaluation technology in oil and gas exploration. The method includes the following steps: preparing aqueous solutions of dissolved methane-bearing formations with different proportions, and measuring the resistivity of these solutions; obtaining a formation hydroelectric response model based on multivariate linear coupling fitting of data from multiple experimental conditions; constructing a gas abundance model containing only dissolved gas when the water saturation Sw=1; and constructing a total gas abundance model with both dissolved and free gas when the water saturation Sw<1. The relationship between resistivity and gas abundance is established and compared with core resistivity to determine the gas abundance of the core. The reliability of the model is verified in an implementation case. This invention avoids the problem of directly measuring gas content in traditional pressure-dissolved gas reservoirs, and helps improve the accuracy of gas content identification and evaluation in exploration and development wells.

Embodiments of the present application provide a distributed photovoltaic aggregation model and a modeling method. The method comprises: extracting first data required for distributed photovoltaic modeling from a power grid business system, the first data at least including capacity parameters, control parameters, electrical parameters with distribution transformers and line data, and power grid topology structure of the distributed photovoltaic; determining a target cluster number K of the distributed photovoltaic and load units for aggregation modeling according to a clustering effectiveness evaluation index based on the first data; clustering the first data by using a clustering algorithm with the target cluster number K as the cluster number, and dividing K distributed photovoltaic and load units; performing a data aggregation operation for each distributed photovoltaic and load unit, and generating aggregation model parameters of each distributed photovoltaic and load unit; and constructing a distributed photovoltaic aggregation model based on the aggregation model parameters. The simulation accuracy is improved, the labor cost is saved, and the demand of high-penetration distributed photovoltaic for large power grid stability analysis is met.

The application discloses an H-ADCP installation position optimization method based on cross-section traversal scanning, which comprises the following steps: 1) selecting a cross-section to be installed, using a sailing ADCP to measure flow and synchronously observing water level under different water level stages or flow velocity stages, and calculating the average flow velocity of each cross-section; 2) importing the flow velocity data into a cross-section terrain model, dividing candidate units, traversing and extracting representative flow velocities, and generating a flow field and a standard deviation distribution diagram; and 3) comprehensively analyzing and determining the final position through multi-dimensional quantitative evaluation of flow velocity standard deviation, random uncertainty and correlation coefficient, combined with on-site conditions such as terrain adaptability and interference degree. The method disclosed by the application has high site selection efficiency and is suitable for H-ADCP installation site selection in rivers, lakes and other water areas, and is helpful to improve the online monitoring accuracy of river flow.