9 results about "Atom model" patented technology

This invention discloses a method for analyzing the wear of micro-milling tools, relating to the fields of wear mechanism research and molecular dynamics analysis in micro-milling. Specifically, it includes: constructing atomic models of the tool and workpiece, incorporating the geometric features of the cutting edge arc; setting up a simulation environment and dividing the workpiece atoms into boundary layers, isothermal layers, and Newtonian layers; assigning potential functions to the atoms and performing energy minimization and relaxation; constructing a dimensionless scale ratio loading condition based on the equivalent uncut thickness and the cutting edge arc radius; extracting the mechanothermal process quantities and quantitatively characterizing the wear state according to the number of detached atoms, the change in effective cutting edge radius, and interface mixing indices. The aim is to achieve atomic-level quantitative characterization of the wear process of micro-milling tools.

This invention provides an atomic-level electron tomography 3D reconstruction method. Its core is to match the simulated projection of an atomic model with experimental images through iterative optimization. The method first constructs a 3D space based on the sample contour and initializes the atomic model parameters. Then, it acquires experimental images from multiple angles and their imaging parameters. In each iteration, a simulated projection image is generated based on the current atomic model and imaging parameters, and the difference between it and the corresponding experimental image is calculated as the loss value. An optimization algorithm dynamically adjusts atomic parameters (position, size, etc.) and imaging parameters (such as focus distance and aberrations) to minimize the total loss. This process includes intelligent simplification steps, which can merge or delete atoms to optimize model complexity. Finally, using the converged high-precision atomic model, 3D reconstructed images with arbitrary viewpoints and depths can be generated. This method can achieve high-precision atomic-level 3D reconstruction without completely relying on 360-degree scan data, helping to reduce data acquisition costs.

This invention discloses a method for generating typical underwater acoustic functional components based on an open architecture, belonging to the field of underwater acoustic system technology. The core of this method lies in pre-establishing an underwater acoustic functional model library containing standardized interface underwater acoustic functional atomic models, and a component configuration rule library containing configuration templates and constraints. When a component generation request is received, the system automatically selects, instantiates, and logically links multiple atomic models from the model library according to the rule library to form an initial functional component. Then, the component undergoes rigorous static verification and high-fidelity dynamic simulation verification combined with a physical model. After successful verification, the component is compiled and packaged into an executable functional component conforming to the open architecture standard. This invention solves the technical problems existing in traditional underwater acoustic system development, such as tight hardware-software coupling, poor reusability of functional components, long development and verification cycles, and insufficient deployment flexibility, through a standardized, modular, automated, and verification-driven integrated process.

The present application relates to the technical field of signal processing, and provides a kind of catenary non-stationary vibration signal sparse decomposition method, the method comprises: collecting impact vibration response signal, and carrying out denoising pretreatment;Establish parametric impact response atom model, and construct over-complete parametric atom dictionary;Using matching pursuit algorithm and combining sparse decomposition algorithm, obtain a series of linear combination of sparse atom components;According to the best matching atom set and its corresponding parameter vector obtained in iteration process, the incident wave component set and the reflected wave component set are obtained, and the decoupled incident wave signal and reflected wave signal are reconstructed.The present application realizes the accurate separation and reconstruction of rigid catenary mixed vibration waveform by constructing over-complete parametric atom library containing frequency modulation factor, combined with matching pursuit algorithm.

The application is a method and system for constructing a wide-temperature-range constitutive model of a viscoelastic fluid in a space environment, which relates to the cross-technical field of computational materials science, aerospace tribology and fluid dynamics, and comprises the following steps: performing sinusoidal shearing on a balanced full-atom model at multiple key temperature points, simulating the dynamic response under sinusoidal shearing to obtain original strain time series data and original stress time series data, performing filtering and smoothing processing and feature extraction to obtain waveform features, and calculating shear rate time series data; inputting the filtered and smoothed original strain time series data and the shear rate time series data into a constitutive mathematical model to obtain predicted stress, minimizing the error between the predicted stress and the filtered and smoothed original stress time series data for multi-stage optimization, and obtaining a wide-temperature-range constitutive model of a viscoelastic fluid. The application solves the technical problem that the constitutive model is difficult to obtain rheological parameters of a space lubricating fluid under wide-temperature-range and large-amplitude shearing, resulting in low prediction accuracy.

This invention relates to the fields of materials science and computational chemistry, and particularly to a design method for sludge-based porous ceramic modifiers based on molecular dynamics simulation. The method constructs a multi-scale atomic model of the sludge matrix and candidate modifiers based on sludge component characterization data, establishing a periodic simulation system. It performs molecular dynamics simulations of interface evolution and high-temperature sintering phase transitions, outputting a multi-scale spatiotemporal trajectory dataset. A decomposition-pore-forming phase transition synchronization dynamic descriptor is constructed, and a kinetic synchronization index characterizing the matching degree between gas production rate and glass phase encapsulation ability is calculated. A molecular configuration back-optimization algorithm is run, combined with a graph neural network surrogate model and a multi-objective Bayesian optimization strategy, to output the optimal modifier molecular topology, functional group arrangement, and mass ratio. This invention effectively overcomes the shortcomings of traditional trial-and-error methods, which are characterized by high blindness and long cycles, significantly improving the pore uniformity, mechanical strength, and R&D efficiency of porous ceramics.

The application provides a cryo-EM protein model building method based on a neural network and a storage medium, the storage medium stores a deep neural network, the deep neural network comprises a cryo-conversion module stack, the cryo-conversion module stack comprises a plurality of cryo-conversion modules Cryoformer; the Cryoformer comprises an encoder and a decoder; the decoder is used for learning the matching of sequence-related representation and three-dimensional space information of a cryo-EM density map, and cross-fusion is performed on the sequence-related representation and the three-dimensional space information output by the encoder. The deep neural network can be used for processing the cryo-EM density map, obtaining the atomic model of the corresponding protein complex structure, being efficient and accurate, and being capable of processing low-resolution density maps, so that the application range of automatic cryo-EM model building is greatly expanded.

This invention relates to the field of iron and steel metallurgy, and more particularly to a molecular dynamics modeling method for predicting the viscosity of blast furnace hot metal, specifically for blast furnace hot metal composition systems with a C content of 4wt%–5wt%, a Ti content of 0.01wt%–0.2wt%, and a Si content of 0.01wt%–0.5wt%. The method includes constructing a Fe-C-Ti-Si quaternary iron-based melt atomic model, using a hybrid / overlay mixing potential function to describe the interaction forces of all atoms within the system, performing molecular dynamics simulations of the Fe-C-Ti-Si iron-based melt, analyzing the microstructure characteristics of the obtained Fe-C-Ti-Si iron-based melt using molecular dynamics simulations, and calculating the melt viscosity. This invention can accurately describe the many-body interactions and structural evolution characteristics among the quaternary components Fe, C, Ti, and Si, achieving reliable simulation and prediction of melt viscosity.

This paper considers the Protein Joint Atom Modeling (SPICA) strategy and the corresponding elastic network model of physical interactions, belonging to the field of protein dynamics characterization (computational) technology. First, test sets were constructed, including 135 and 6 protein experimental crystal structures respectively. Then, the following five steps were performed: 1. Construction of the protein joint atom model; 2. Initial parameter setting and force field parameter pairing; 3. Calculation of spring force constants; 4. Construction of the Hessian matrix; 5. Parameter optimization and dynamic analysis. This method is the first to introduce the protein joint atom modeling strategy into the traditional elastic network model computational framework, while integrating the corresponding physical interaction forces, significantly improving computational accuracy while maintaining computational efficiency.