18results about How to "Shorten calculation cycle" patented technology

The invention relates to the technical field of vehicle performance testing, and provides a method, a system, equipment and a medium for calculating vehicle traction and braking performance parameters, the method comprises the following steps: acquiring time and periodic data of vehicle speed and level change to construct a data set, and training a linear regression model by using the data set to obtain a linear regression model; the vehicle traction and braking performance parameters can be accurately output, so that a trained model is obtained; secondly, real-time speed pulse change data of the vehicle under different working conditions are collected, and relevant data of speed and level change are extracted from the real-time speed pulse change data; and inputting the extracted data into a trained linear regression model to obtain the traction and braking performance parameters of the vehicle, so as to replace manual calculation and improve the efficiency and the precision. According to the method, a complex manual calculation process can be omitted, the labor cost is saved, and the calculation period is greatly shortened.

The invention, which relates to the technical field of carbon emission calculation, discloses a BIM-based subway engineering muck output and carbon emission calculation system comprising a muck output calculation module, a muck landfill land occupation calculation module, a parameter setting module and a muck carbon emission calculation module. The muck generation amount calculation module is used for automatically obtaining BIM model structure parameter data and automatically calculating the muck generation amount through a subway engineering muck generation amount calculation model; the muck landfill occupied area calculation module is used for automatically calculating the landfill occupied area by combining the landfill proportion, the loosening coefficient and the landfill depth data; the parameter setting module is used for setting various carbon emission factor parameters and energy consumption parameters and laying a data foundation for carbon emission calculation; the muck carbon emission calculation module is used for calculating the muck full-life-cycle carbon emission according to the data of the three modules in combination with a full-life-cycle carbon emission quantitative model; according to the method provided by the invention, the calculation process is optimized, and the calculation period is shortened.

The invention belongs to the technical field of steelmaking, and discloses a method for developing a steelmaking furnace charge consumption cost accounting model, and the specific technical scheme is as follows: 1, determining key data; 2, acquiring and assembling data; 3, calculating and storing a CR / NI grade value; 4, the actual CR / NI grade of production feeding is determined; 5, obtaining the CR / NI grade value of the direct supply material; 6, material conversion unit price calculation; 7, NI / CR alloy correction amount calculation and total cost accounting are carried out; and 8, model display and tendency chart generation: organically combining detailed information such as cost, consumption, furnace charge CR grade, furnace charge NI grade and heat of the stainless steel furnace charge, and accurately calculating the cost per ton of steel of different steel grades through a data integration and treatment technology. And a solid and reliable data support is provided for a plurality of key fields such as product pricing, process design, order optimization, material purchasing, benefit prediction, operation decision and the like.

The application discloses a simulation method for flow heat exchange of a printed circuit board type heat exchanger complete machine, which comprises the following steps: setting physical property parameters of cold and hot channel working substances, selecting a proper physical model, and constructing a single-channel flow resistance model; dividing the cold and hot channels into cold and hot microchannels and cold and hot runner systems, respectively constructing cold and hot microchannel models for the cold and hot microchannels, and respectively constructing cold and hot runner system models for the cold and hot runner systems; dividing a plurality of heat exchange units for the cold and hot microchannel geometric models respectively, constructing three-dimensional flow heat exchange models for each heat exchange unit, and constructing a one-dimensional axial temperature distribution model of the heat exchanger; obtaining flow distribution calculation results of the cold and hot microchannels through simulation; obtaining outlet temperatures and heat exchange amounts of the cold and hot processing units of each heat exchange unit through simulation calculation of each three-dimensional flow heat exchange model according to the flow distribution calculation results of the cold and hot microchannels and temperature working condition tables, and further obtaining a convective heat exchange coefficient and substituting the same into the one-dimensional axial temperature distribution model of the heat exchanger to obtain an axial temperature distribution of the heat exchanger.

The application discloses a multi-agent material calculation consistency calibration method, belonging to the cross field of material science, artificial intelligence and computational physics. The method adopts a master-slave structure multi-agent system, containing one master agent and at least three slave agents. The master agent is responsible for overall coordination, embedding physical mechanism constraints, consistency calibration and output results. The method steps are: constructing a calculation system, introducing physical mechanism constraints and embedding slave agent calculation models, collecting calculation data, performing bias analysis, adjusting parameters or correcting results through iterative calibration, and finally verifying and outputting the final results. The application introduces physical mechanism constraints, combines bias analysis and iterative calibration, and solves the problems of poor consistency of existing multi-agent material calculation results and easy violation of physical laws. Experiments show that the method reduces the deviation of the calculation results and the experimental measured values to below 3%, improves the calibration efficiency by more than 40%, and improves the calculation accuracy by more than 35% compared with the prior art, thereby improving the accuracy and engineering practicability of high-throughput calculation of material performance.

The present invention relates to the field of flow field analysis. The present invention discloses a flow field detection method, device, equipment and medium, including obtaining experimental original data from an atmospheric turbulence simulation device; establishing a mathematical simulation model according to the experimental original data, and obtaining simulation data from the mathematical simulation model; performing data verification on the simulation data and the experimental original data to obtain training data; establishing a deep learning model; training the deep learning model according to the training data to obtain an optimized deep learning model; performing inversion calculation on the internal flow field of the atmospheric turbulence simulation device by optimizing the deep learning model to obtain inversion data; thanks to the fast inversion capability of the deep learning model, the calculation cycle of the mathematical simulation model is significantly shortened, and the simulation efficiency is improved, so that the experimenter can perform real-time regulation and control of the atmospheric turbulence simulation device based on the inversion data, respond to the experimental needs in real time, and improve the accuracy and efficiency of the experiment.

The invention discloses a user energy storage capacity optimal configuration method, which overcomes the problems that the power utilization cost cannot be effectively reduced by too small energy storage capacity and the investment cost is too high possibly due to too large energy storage capacity in the prior art, and comprises the following steps: calculating a user typical energy utilization curve based on historical energy utilization data; calculating the electricity consumption of the user in the peak period and the measurement step length of the distribution storage capacity of the user; dynamically measuring and calculating user energy storage daily earnings under different distribution and storage capacities based on the distribution and storage capacity measurement and calculation step length; and calculating the energy storage configuration capacity of the user as the optimal configuration capacity by taking the optimal user income as an objective function. The optimal configuration capacity and the net income of the energy storage system are optimally calculated, and the optimal income can be achieved for user capacity configuration; the charging and discharging strategy can be adjusted at any time according to the power grid load condition, the power grid is helped to deal with emergencies and faults, and the toughness and anti-interference capability of the power grid are improved.

The invention discloses a pod propulsor structure optimization design method based on data driving. Comprising the steps of defining a design variable and an optimization target, constructing a parameterized geometric model, building a full-process automatic simulation analysis framework, generating a sample space through experimental design, obtaining a complete sample data set, constructing a high-precision agent model, carrying out algorithm optimization based on the agent model, verifying optimal design and calculating a data closed loop. And continuously updating the model. According to the method, the trained data driving agent model is utilized, in a huge design space, performance evaluation can be completed only in an extremely short time, the calculation period is greatly shortened, and a global optimal solution set can be rapidly obtained in combination with a global optimization algorithm; according to the method, various factors such as design requirements, test design, an agent model construction method and an optimization algorithm are comprehensively considered, the method can be suitable for structural design of other pod propellers with different production models or different design requirements, and effective guidance is provided for subsequent design of the pod propellers.

This disclosure provides an analytical calculation method for the air gap magnetic flux density of unequally magnetized rotor poles. The method includes: determining the remanent magnetization distribution identifier of the permanent magnet in the unipolar permanent magnet based on the number of permanent magnets in the surface-mounted permanent magnet synchronous motor; determining the magnetic field distribution of the permanent magnet corresponding to the remanent magnetization distribution identifier; determining the magnetization intensity of the unipolar permanent magnet based on the magnetic field distribution and the shape of the permanent magnet; and determining the remanent magnetization density of the unipolar permanent magnet based on the magnetization intensity of the unipolar permanent magnet.

The invention discloses a convolutional neural network CNN-based underground water pollution source identification method and system under a strong heterogeneous condition, and relates to the technical field of underground water environmental protection. Reasonably generalizing hydrogeological conditions, and constructing a groundwater solute transport conceptual model; generating a plurality of groups of working conditions representing the emission intensity of the pollution source by adopting a random sampling method, and generating an aquifer permeability coefficient field through sequential Gaussian simulation; based on the aquifer permeability coefficient field, constructing an underground water solute transport-double-domain reference model; inputting a plurality of groups of working conditions into the groundwater solute transport-double-domain reference model one by one so as to form samples of'model input-model response 'and form a training sample set and a test sample set; the underground water pollution source identification model is constructed based on the training sample set by adopting the deep learning-CNN algorithm, and the position and the emission intensity of the pollution source can be accurately identified by using the model, so that the pollution source identification efficiency and precision are effectively improved, and a reliable solution can be provided for underground water pollution treatment.

The application discloses a van der waals correction calculation method based on a heterogeneous computing architecture and related equipment, and belongs to the technical field of data processing. The method comprises the following steps: in response to a van der waals correction calculation task instruction, a standard data packet transmitted by a master processor is received; based on the standard data packet, a van der waals correction calculation process is performed in combination with on-chip core storage of a slave processor, and a van der waals correction calculation result is obtained; and the van der waals correction calculation result is returned to the master processor. The application realizes heterogeneous computing by adopting a master processor and a slave processor in cooperation with a hardware architecture design, clearly defines the task boundary of different processors, avoids resource redundancy and waste of computing power, and realizes integrated storage and calculation design by performing van der waals correction calculation in combination with on-chip core storage of the slave processor, breaks through the data carrying bottleneck of the traditional architecture, greatly shortens the calculation period of a large-scale system, and reduces the consumption of computing power.

The application provides a method, device, medium and product for determining the component ratio of a multi-component molten salt, and relates to the technical field of molten salt materials. The method comprises the following steps: determining a plurality of pure components that constitute a multi-component molten salt, and determining the interaction coefficient between any two pure components; determining a plurality of mixed ratios of the multi-component molten salt based on the plurality of pure components; determining the melting enthalpy corresponding to each of the plurality of mixed ratios based on the plurality of mixed ratios and the interaction coefficient between any two pure components, and determining the mixed ratio with the maximum melting enthalpy in the plurality of mixed ratios as the component ratio of the multi-component molten salt. The method corrects the melting enthalpy error caused by anion interaction in the molten salt system by utilizing the interaction between different pure components, realizes the rapid prediction of the melting enthalpy of the multi-component mixed molten salt, significantly improves the prediction accuracy of the melting enthalpy, and is suitable for complex multi-component mixed molten salt systems.

This invention relates to a method and system for converting plane stress element meshes for engine rotor blades. The method includes setting up 3D element arrays and 2D element arrays; traversing the node numbers of all elements in all layers of the 3D element array to obtain the overall 2D node number and calculating its coordinate values; calculating the element node number of the 2D element based on the overall 2D element node number; traversing the nodes of all elements in all layers of the 3D element array to calculate the volume of the 3D element array, and traversing the nodes of the 2D element array to calculate the area of ​​the 2D element array; calculating the thickness of the 2D element array based on the volume of the 3D element array and the area of ​​the 2D element array; and outputting the node coordinates and element information of the 2D element array. This invention can automatically convert aero-engine rotor blades from 20-node hexahedral solid element meshes to 8-node quadrilateral plane stress element meshes, thereby saving a significant amount of manpower, greatly shortening the calculation cycle, and providing a foundation for subsequent high-precision finite element calculations and optimization design of the rotor.

Embodiments of the present application disclose a kind of thermal management system simulation method, device, electronic equipment and storage medium.The method can include: obtaining the vehicle physical model irrelevant to temperature coupling and the temperature coupling heat source model and thermal management system model related to temperature coupling which have been built, and obtaining the automobile operating condition prepared in advance;The automobile operating condition is input into the vehicle physical model for calculation, and the vehicle demand associated with the temperature coupling heat source model is input into the temperature coupling heat source model calculated;The calculation result output by the temperature coupling heat source model is input into the thermal management system model, to complete the simulation of the thermal management system characterized by the thermal management system model.The technical scheme of the embodiment of the present application solves the problem that model building is complicated, the demand of computing power is large and the calculation period is long.

The invention discloses a convolutional spiking neural network recognition system and method for high-dynamic single-photon imaging, and the system comprises a photon event compression module which carries out the sparse processing and event flow reconstruction of a continuous photon trigger sequence in a high-dynamic range, so as to reduce the data bandwidth and highlight the effective photon trigger information; the counting pulse time conversion module is used for mapping the compressed photon event sequence to a time domain feature so as to realize unified expression of high photon flow and low photon flow conditions; the common-mode noise suppression module is used for filtering noise and intercepting effective data in a time domain; the pipelined convolution pulse operation module is used for performing efficient feature extraction on the preprocessed photon event data; and the storage module is used for storing the convolution weight and the neuron membrane potential required in the convolution operation module. According to the invention, real-time feature extraction with low resource consumption can be realized under a high-dynamic photon event condition, and SPAD image processing and intelligent identification performance can be improved.

This invention relates to the field of tunnel boring machine (TBM) design technology and discloses a tool layout method for a circular cutterhead of a TBM. The method includes: constructing a mathematical model of tool layout incorporating cutting force data from a CSM model; determining the optimization objective and constraints for minimizing eccentric force and eccentric moment; initializing a gray wolf population by mapping discrete permutations to continuous vectors using a continuous encoding strategy and calculating fitness values; executing a global iteration of the gray wolf optimization algorithm, using social hierarchy to guide population updates; embedding a tabu search strategy in the global iteration to perform local neighborhood search on the optimal individual to generate and selectively replace the optimal solution; and finally outputting the tool layout scheme and verifying its feasibility. This invention effectively solves the problem of tool layout easily getting trapped in local optima through the synergistic cooperation of the gray wolf algorithm and tabu search, improving the mechanical balance and solution efficiency of the cutterhead design, and reducing design and production costs.

The invention relates to a transformer substation relay protection setting value intelligent calculation system based on big data analysis, and belongs to the technical field of power system protection and automation. The system comprises a data acquisition module, a constant value equipment classification module, a data preprocessing module, a feature extraction module, a feature construction module, a feature coding module, a model construction module and a constant value result calculation output module. According to the system, the efficiency and accuracy of relay protection setting value calculation can be improved, and the calculation period is shortened; the manual intervention degree is reduced, and human errors are reduced; and a powerful guarantee is provided for safe and stable operation of a power system.

The application relates to the technical field of engineering simulation, and discloses a multi-working-condition parallel scheduling method and system based on an offshore wind power simulation platform, which comprises the following steps: state initialization is performed on a working-condition list in a single solving stage in an offshore wind power integrated simulation process to obtain an ordered task queue; the working conditions in the ordered task queue are dispatched to a solver backend by using a movable pointer type even distribution scheduling index; a configurable regular expression is used to identify the working conditions with transient I / O errors in the output stream of the solver backend; the working conditions with transient I / O errors are subjected to exponential backoff retry, and the working conditions after the exponential backoff retry are subjected to scheduling circulation; when the working conditions in the single solving stage reach a termination state, the working conditions in the next solving stage are subjected to parallel solving by using a cross-stage pipeline incremental readiness semantic, and the offshore wind power integrated simulation is completed. In the application, the resource utilization rate of the offshore wind power simulation platform is significantly improved, and the simulation calculation period is greatly shortened.