26 results about "Computational simulation" patented technology

This invention discloses a method for directional experimental verification and performance testing guided by computational simulation in materials chemistry, belonging to the field of materials performance testing technology. The method includes: acquiring the structural parameters of semiconductor devices and initial parameters of interface defects; calculating the characteristic time constant of carrier trapping by interface traps; simulating and generating a theoretical capacitance-voltage hysteresis loop; then performing bidirectional voltage scan tests within a sensitive scan rate range; finally, updating the inversion parameters and resimulating, iteratively adjusting until the characteristic deviation between the theoretical loop and the measured data meets the convergence condition, thus outputting an interface state density distribution map. This invention, through computational simulation-guided directional experiments, achieves accurate capture and non-destructive in-situ characterization of the dynamic response characteristics of interface states, effectively establishing the dynamic structure-property relationship between microscopic interface defects and macroscopic device performance, and significantly improving the accuracy and reliability of interface defect parameter inversion.

The application discloses a blood sample image intelligent recognition and classification system based on computer vision, relates to the technical field of pathological image analysis and computer vision, and comprises the following steps: acquiring an original collected image and performing nonlinear concentration mapping to generate a biochemical layered image containing measured concentration data; locking a cell center and dividing an initial jurisdiction through center response calculation to construct an ideal simulation single-cell layer; calculating a difference image of a simulation superimposed image and a measured image, iteratively correcting the simulation layer in a reverse direction by using concentration difference data until an independent single-cell layer containing recovered texture is obtained; and finally generating an overlapping complexity weight map based on the difference image, constructing a multi-dimensional feature data packet and inputting the multi-dimensional feature data packet into a convolutional neural network to output a classification result; the application effectively solves the recognition problem caused by cell overlapping in high-density samples by combining physical model decoupling with deep learning.

A metal modified graphene structure model is applied to predict hydrogen storage materials, comprising a structure simulation unit, a simulation data unit, a preparation measurement unit, a data processing unit and a parameter feedback unit; the structure simulation unit includes a graphene base structure composed of carbon atoms and a plurality of modified structure models pre-prepared for metal modification of the graphene base, combined into hydrogen storage materials; the simulation data unit calculates the structure of H2 molecules adsorbed on the hydrogen storage materials and calculates the simulation hydrogen storage data; the preparation measurement unit actually prepares the hydrogen storage materials and measures the actual hydrogen storage data; when the actual hydrogen storage rate data is greater than or equal to the first threshold value, the data processing unit calculates the difference percentage of the actual hydrogen storage data and the simulation hydrogen storage data, and outputs the data difference degree; otherwise, an abnormal warning signal is output; when the data difference degree is less than or equal to the second threshold value, the parameter feedback unit outputs that the hydrogen storage data of the preparation measurement unit is qualified, otherwise, an abnormal warning signal is output and feedback is performed, and data optimization is performed.

The invention belongs to the field of oil and gas field exploration and development, and discloses a numerical reservoir model optimization and history fitting method and related device.The method comprises the steps that firstly, geological exploration data are utilized, a spatial clustering algorithm is adopted to automatically determine the local updating range of a structural model, and structural layers and stratums are optimized through spatial interpolation; outputting an optimized construction model and uncertainty measurement; based on the model and logging lithofacies attribute data, adaptively identifying a lithofacies updating key area and variation function parameters by applying a machine learning algorithm, and performing lithofacies simulation to output an optimized lithofacies model; combining the porosity, permeability and saturation attribute data, adaptively determining an attribute optimization range and variation function parameters by adopting a probabilistic neural network, and outputting an optimized attribute model through phase control attribute modeling; a three-dimensional oil-water two-phase black oil seepage model is constructed, a global optimization algorithm is adopted to automatically adjust parameters based on a target function, simulation data is calculated until convergence, optimal parameters are output to complete historical fitting, and efficient and reliable intelligent support is provided for complex oil reservoir development.

The application belongs to the field of material calculation simulation, and relates to a prediction method for magnetic coupling evolution characteristics of two-dimensional Janus materials based on first principles. The technical problem to be solved is that the existing technology fails to uniformly analyze the magnetic freedom and structural evolution behavior, resulting in interlayer abnormal shrinkage, spontaneous bond collapse and lack of judgment basis for the coupling relationship between magnetism and interlayer structure. The technical scheme comprises the following steps: establishing a crystal structure model taking MA2Z4 material as a mother body; cutting and constructing an asymmetric Janus single layer; constructing a double-layer AA stacking initial model; performing geometric structure optimization and static self-consistent calculation under non-spin polarization and spin polarization conditions respectively; comparing the interlayer spacing, magnetic moment distribution and electronic state characteristics under the two conditions; analyzing the inhibitory effect of interface magnetism on interlayer bonding tendency by combining the electron localization function and the crystal orbital Hamiltonian population; and finally establishing the cooperative evolution relationship among magnetism, interlayer coupling and electronic structure, thereby providing a theoretical basis for identifying stable double-layer van der Waals configuration.

The application discloses a kind of RN / RD simulator course angle calibration methods based on frequency domain single channel, comprising the following steps: RN / RD simulator sets static scene, obtains the frequency deviation Δf0 of RN / RD simulator output signal;RN / RD simulator sets dynamic scene, course angle is set to 0, obtains the frequency deviation Δf of each digital channel signal of RN / RD simulator 11 ~ Δf 1n , calculate the frequency deviation Δf1 of RN / RD simulator output signal;According to the frequency deviation Δf1 of RN / RD simulator output signal, calculate the speed error Δv and course angle error Δθ0 of RN / RD simulator output signal;RN / RD simulator course angle is set to other angles, respectively calculated to obtain course angle error, and the control precision Δθ of course angle error is calculated.The application measures angle by carrier wave mode, improves quadrant information resolution, and is more compatible and has high measurement accuracy.

This invention discloses a method for extracting reaction kinetic parameters from experiments for polymer reaction simulation. The method includes setting the optimization range of elementary reactions and related parameters, obtaining experimental molecular weight distribution curves, setting parameters for a high-dimensional search optimization algorithm and kinetic Monte Carlo simulation parameters, uniformly sampling the combination of reaction kinetic parameters, performing kinetic Monte Carlo simulation to obtain simulated molecular weight distribution curves, calculating the root mean square error between the simulated and experimental molecular weight distribution curves, and updating the combination of reaction kinetic parameters using a high-dimensional search optimization algorithm. This invention can optimize and fit reaction kinetic parameters within the assumed reaction mechanism based solely on the polymer molecular weight distribution curve obtained from a single polymerization experiment. The obtained reaction kinetic parameters can be directly used to predict the results of the next batch of polymerization reactions. Furthermore, through multiple iterations of experiments and simulations, the prediction accuracy of the reaction kinetic parameters can be continuously optimized.

This application provides a computational simulation-based method, system, device, and storage medium for strong earthquake assessment of high dams, relating to the field of earthquake monitoring technology. It aims to address the multi-dimensional needs of rapid response, focused attention, and comprehensive assessment for strong earthquake assessment of high dams. The method includes: acquiring post-earthquake data of the high dam; performing simulation analysis on the post-earthquake data of the high dam using an overall model to obtain a first assessment result, wherein the overall model is obtained by simulating the high dam using a fixed grid; based on the first assessment result, identifying potential weak areas of the high dam and loading a refined model that needs to be activated, wherein the refined model is obtained by simulating the high dam using a locally variable grid, the size of which is smaller than the size of the fixed grid; performing simulation analysis on the post-earthquake data of the high dam using the activated refined model to obtain a second assessment result; and generating a strong earthquake assessment report for the high dam based on the first and second assessment results.

This invention relates to the field of intelligent prediction technology, and discloses a method and system for predicting the effect of roadbed solidification based on deep learning. The method includes evaluating the matching degree between the soil and the solidifying agent and generating a score. If qualified, a preliminary strength trend curve is constructed based on the material ratio and ambient temperature, and its baseline slope is determined. Subsequently, the slope is analyzed in conjunction with environmental geological parameters to identify nonlinear critical nodes and potential inflection intervals in the solidification process. For this interval, the soil moisture content and ambient temperature are extracted, and the preliminary trend curve is dynamically coupled and corrected to generate an optimized strength growth model. The model is used to calculate simulated predicted values, and the deviation from the actual values ​​is used to determine iterative correction parameters, thereby optimizing and generating a corrected strength distribution map. This map is compared with a safety threshold to complete the solidification effect evaluation. Finally, an optimized ratio scheme is generated based on the evaluation conclusions. This method can improve the accuracy of predicting the inflection point of solidification strength.

The present application relates to the technical field of production planning of refining enterprises, in particular to a selection method and system for multi-target crude oil mixing production of a refining enterprise, which comprises the following steps: creating a crude oil evaluation database containing various crude oil property data, and establishing a production optimization target system covering the target properties of mixed crude oil and the control targets of production cost; constructing a crude oil mixing and production process simulation model, which can simulate the properties of mixed crude oil through weighted calculation and account for the total cost; on the basis of the above, searching the database and optimizing the calculation under the premise of meeting the preset constraints, determining the candidate crude oil formula and mixing ratio that make the simulated properties closest to the target properties and the total cost closest to the control target; and performing robustness evaluation on the candidate scheme and screening the final crude oil mixing scheme that meets the anti-interference requirement. The present application realizes the collaborative optimization of the crude oil mixing scheme in terms of properties and cost, and enhances the practical stability of the scheme.

The present application relates to a kind of metal corrosion protection-oriented nanofiller system in the prediction method of inhibitor loading performance, device, electronic equipment and storage medium, forms the functionalized nano carrier structure of reasonable structure and reliable performance, establishes a set of standardization simulation and performance prediction method, and proposes the quantitative prediction model of inhibitor specificity loading performance, also establishes the multi-dimensional parameter comprehensive evaluation model of inhibitor loading performance, realizes the accurate and stable prediction of inhibitor loading performance in nanofiller system;And the device, electronic equipment and storage medium provided by the present application are used to realize the prediction method, the screening of nanofiller system is from complex experiment cycle front to calculation simulation stage, and the development cycle is shortened by several times to several tens of times, and the development cost is effectively reduced;The present application is closely combined with the demand of metal anticorrosion coating field, has definite engineering application value and good popularization prospect.

This invention discloses a method, apparatus, and storage medium for evaluating the structure and properties of surface-modified carbon nanotubes based on first-principles calculations, belonging to the field of computational simulation and design of nanomaterials. First, this invention constructs modified carbon nanotube models for different active grafting sites or different types of functional grafted functional groups in the initial carbon nanotube model, and performs geometric optimization to obtain stable configurations. Then, it calculates the microstructure and electronic properties of the stable configurations. Next, it selects the stable configuration from the previous step, constructs grafted single-walled carbon nanotube models with different doping gradients, and performs geometric optimization to obtain stable configurations. Then, it calculates the energy levels and binding density of states based on the optimized stable configurations with different doping levels. Finally, it evaluates the structure and properties of the surface-modified carbon nanotubes. This invention studies the structural changes and performance improvements brought about by functional group grafting to carbon nanotubes, avoiding the costs associated with experiments and mitigating many uncertainties in experiments.

The present invention relates generally to the field of heart modeling and more specifically to computational simulation of the anatomical structures and intracardiac hemodynamics of heart with Atrial Septal Defect in a patient. The present disclosure provides a new and useful system and methods thereof for computational simulation of the anatomical structures and intracardiac hemodynamics of heart with Atrial Septal Defect in a patient. The system and methods according to the present invention provide patient-specific editable animated three-dimensional anatomic model of heart and atrial septum with integrated intracardiac hemodynamics. The system and methods according to the present invention further provide a computational simulation for development of pathological processes attributed to the Atrial Septal Defect in a patient and provide data for What-If analysis.

Methods to enhance the computational localization of cardiac arrhythmia sources are provided. A method may include receiving, from a first user, clinical data associated with a clinical case. The clinical data may include a patient anatomic information, diagnostic and / or treatment modalities, treatment parameters, treatment outcome, and medical literature. The clinical case may be indexed based on a first plurality of characteristics associated with the clinical data. The indexing may include associating at least a portion of the clinical data with a computational simulation of cardiac arrhythmia having a second plurality of characteristics matching the first plurality of characteristics. At least a portion of the clinical data associated with the indexed case may be provided to a second user in response to a query from the user. Related systems and articles of manufacture are also provided.

A production simulation kit consisting of one or more processors and a set of storage equipment. One or more records where one or more recording devices will store the recorded information. Production, which includes information about the start time as recorded and the end time as recorded. Each stage of the production process and its simulation models include information about the time. Each step involves a group of production resources that can be allocated to that step. Operating time of each production resource within each group of production resources, and the rules for... To control the production line, one or more processors will use production record information. And the simulation model is used to perform the simulation, and to make a comparison between the recorded information and the results. Production and simulation results are used to calculate simulation errors;

The application provides a SiC coating thermal shock damage cross-scale simulation method, first, the evolution law of the mechanical properties of SiC single crystal and grain boundary with temperature is obtained through molecular dynamics simulation; then, a cross-scale parameter mapping model is established, the intrinsic performance law at the atomic scale is converted into a temperature-dependent constitutive relationship in the mesoscopic finite element model; then, a coating system finite element model containing parameterized interface roughness and polycrystalline structure is constructed, the damage initiation and propagation process of the coating system under thermal shock load is simulated through thermal-mechanical coupling calculation, and the influence of microstructure parameters and thermal shock temperature is evaluated. The SiC coating thermal shock damage cross-scale simulation method is used, the cross-scale physical correlation from the atomic scale mechanism to the mesoscopic scale morphology to the macroscopic scale failure is realized, the thermal shock failure behavior of the SiC coating can be more accurately predicted, and a theoretical tool is provided for performance evaluation and microstructure design of the coating.

Systems and methods for automatically training a machine learning model are described herein. An example method includes performing a set of computational simulations; and assembling a data set associated with the set of computational simulations. The data set includes data associated with at least one simulation result for at least one computational simulation in the set of computational simulations. The method also includes training a machine learning model with the data set. At least one feature and at least one target for the machine learning model are part of the data set.

The application discloses a kind of shape memory alloy point defects and magnetic configuration Synergistic control method, belong to new material technical field, it is related to a kind of calculation simulation method based on density functional theory.The application first constructs the crystal structure of shape memory alloy containing point defects in parent phase by Materials Studio software, with the aid of vaspkit software under Linux system, its file type is changed into.vasp format.Point defect and magnetic configuration are synergistically controlled in the constraint condition, the formation energy of ferromagnetic and ferrimagnetic structure is quantified respectively, and the physical properties of the final product are predicted by the tetragonal distortion method.The application can accurately design the alloy defect type at atomic scale, determine the optimal crystal configuration of point defects, and clarify the root cause of the influence of point defects on the stability of parent phase from the perspective of electronic state density, thereby achieving the purpose of accurately controlling the physical properties of alloy.

A method for training an operator of a spray drying plant, the spray drying plant including a plurality of plant elements including pre-processing elements, a spray drying element, post-processing elements, powder recovery elements, and a programmable logic controller, PLC. The method including the steps of: obtaining a transient model of the spray drying plant, wherein the transient model includes transient sub-models of the plurality of plant elements; calculating repeatedly simulated sensor data based on the obtained transient model, using a processing unit; displaying on a display a training human machine interface, tHMI, configured to communicate with the transient model of the spray drying plant, and to display the simulated sensor data and control data for the transient model; and updating the transient model based on operator input on the tHMI, for controlling the transient model of the spray drying plant.

This invention discloses an integrated simulation method and system for non-impact ignition and combustion-explosion reactions of solid propellants, belonging to the field of aerospace propulsion and solid rocket motor safety assessment technology. To address the problem of the inability to achieve integrated simulation of the entire process from local ignition triggered by fragment impact to overall combustion-explosion, this invention constructs an ignition model to calculate flow stress, plastic strain, pressure, heat transfer, and thermal decomposition reactions during fragment intrusion. An adaptive finite element-smooth particle fluid dynamics coupling algorithm is employed to convert failed elements into further mechanical and thermal calculations. The process from fragment intrusion, structural failure, hot spot formation to ignition is simulated. Based on the ignition threshold judgment, the recorded ignition parameters are used as initial conditions, and the combustion-explosion model is used to simulate subsequent combustion wave propagation, shell rupture, and other evolutionary processes. This invention can simulate the entire chain of physical processes with high confidence and is mainly used for the safety design and assessment of solid rocket motors.