9 results about "Digital material" patented technology

The embodiment of the invention provides a method and system for determining a rapid propagation threshold value of a weld crack, and the method comprises the steps: receiving original data obtained through a plurality of groups of material mechanical tests, the original data comprising fracture strain of a target material in different stress states and corresponding stress triaxial degrees; calling a data fitting algorithm module to process the original data so as to establish a digital material damage model representing a material damage accumulation rule; inputting the digital material damage model as a material attribute into a finite element simulation calculation module, setting a boundary condition and a load step of simulation, running a simulation program, and calculating mechanical response and damage evolution of the material under a virtual service condition; and monitoring and judging the damage variable of each unit of the material in the calculation process of the simulation program until the damage variable reaches a critical value, triggering fracture judgment, and outputting a strain value corresponding to the moment as a crack rapid expansion threshold value. The method can quantitatively determine the rapid crack propagation threshold.

The invention discloses a building full life cycle environment evaluation management method based on a BIM technology, and belongs to the technical field of building management, and the method specifically comprises the steps: creating a digital material label containing raw material composition, a residual life prediction value and a preset recovery process path for each building component in a BIM model, binding material batch number information and writing detection report data into a label extension attribute library; the stress deformation data of the component are collected through the Internet of Things equipment, and the residual life prediction value is dynamically corrected; during building demolition, a robot scans to obtain a damage image, and identifies internal structure defects in combination with material components; activating an environmental benefit simulation engine to generate an adaptive regeneration path based on the corrected life and defect; and finally, calculating the carbon emission equivalent, and generating a component-level recovery process environmental benefit comparison report. According to the invention, fine management of environmental benefits in the whole life cycle of the building is realized, and the resource regeneration efficiency and the environmental protection level are improved.

The embodiment of the application provides a method and system for determining a weld crack rapid expansion threshold, comprising: receiving original data obtained through a plurality of sets of material mechanics tests, wherein the original data contains fracture strain and corresponding stress triaxiality of a target material under different stress states; calling a data fitting algorithm module to process the original data to establish a digital material damage model representing material damage accumulation rules; inputting the digital material damage model as material properties into a finite element simulation calculation module, setting boundary conditions and load steps of simulation, running a simulation program and calculating mechanical response and damage evolution of the material under virtual service conditions; monitoring and judging damage variables of each unit of the material in the calculation process of the simulation program until the damage variable reaches a critical value, triggering a fracture judgment, and outputting a corresponding strain value at this moment as a crack rapid expansion threshold. The application can quantitatively determine the crack rapid expansion threshold.

This invention discloses a staged prediction method for stress-strain curves based on digital experiments, belonging to the fields of electronic engineering and computer science. It includes: designing a data processing module to acquire stress-strain related data and perform data cleaning and classification; designing an offline training module to build three prediction models in stages and achieve model integration; and designing an online testing module to test the test dataset within the integrated model, outputting stress-strain curves and evaluation indicators, forming a closed-loop optimization. This invention can achieve accurate prediction of curves in stress-strain experiments through the fusion of PINN and liquid networks, realizing continuous reconstruction of material properties from the elastic to the plastic stage, significantly reducing the number of tensile and compressive mechanical tests, reducing reliance on high-cost mechanical loading and destructive testing, and is applicable to various materials and working conditions, possessing value for engineering promotion and digital materials research and development.

This invention relates to the field of machine tool control technology, and particularly to a machine learning-based adaptive machining control method and system for CNC machine tools. First, a digital material sample is constructed based on the workpiece material grade and heat treatment state, establishing a quantitative mapping relationship set between microstructure and macroscopic properties. Then, a digital twin is constructed by combining the tool and machine tool models to predict microstructure evolution and update material properties. Next, using multi-objective optimization and material micro-fluctuations as variables, an optimal robustness parameter package and parameter sensitivity map are obtained. During actual machining, this parameter package is loaded, and an online fine-tuning module generates fine-tuning instructions based on real-time sensor data and the sensitivity map. Finally, the instructions are executed to complete the machining, and the digital twin is updated based on the machining data. By implementing this invention, the consistency of machining quality and the stability of machining efficiency for high-end parts can be significantly improved.

The invention discloses an indexing method, system and device for a Monte Carlo feedback calculation area and a medium, relates to the technical field of nuclear reactor core program design, and solves the problem that an existing indexing mode is low in retrieval efficiency when the number of geometric grids of a Monte Carlo model is too large. According to the technical scheme, the method is characterized by comprising the steps that the maximum value of all geometric grid digital material numbers in a Monte Carlo model is obtained; all the digital material numbers are input into a thermal program for digital material number synchronous processing, and a data file output by the thermal program is obtained; generating a storage space according to the maximum value of the number of the digital material; reconstructing the storage space according to the data file to obtain an index space; and obtaining a to-be-indexed number of the simulation particle entering the geometric grid in Monte Carlo calculation, and accessing the index space by taking the to-be-indexed number as an array subscript to obtain a material attribute value.

This invention provides a closed-loop virtual simulation system and method for structural thermal testing, comprising: performing heat transfer analysis and calculation for the virtual test using finite element analysis; applying thermal load to the virtual test using heating elements as basic units; implementing closed-loop control for the virtual test; visualizing the virtual test; classifying and managing the three-dimensional numerical models of the structural thermal test virtual simulation, including a digital material library and various digital models; modeling various test models for the structural thermal test, establishing a digital model of the test object, meshing the digital model, and assigning material properties from the digital material library to it, thus establishing a complete digital model library; and refining the established models. The structural thermal test virtual simulation system of this invention has predictive and guiding functions for structural thermal testing. Virtual testing and simulation verification have become major ways to shorten development cycles, reduce project risks, and lower development costs.

Intralogistics system (10) which features: a transport network (14) comprising a plurality of transport units (15; 16, 18) and designed to implement a material flow within the intralogistics system (10) caused by transport orders (22), wherein each of the transport facilities (15) is operated with at least one preset, variable operating parameter (36); a large number of sensors (28) that cyclically detect current operating states (34); and a control system (26) which includes a material flow computer (30) that initially plans and generates the transport orders (22), and which cyclically coordinates the implementation of the transport orders (22) based on the current operating states (34); wherein the control (26) further comprises a digital material flow twin (32) which includes a material flow simulation model (40), an operating parameter optimization device (42) and an analysis device (44) and is set up: to cyclically simulate the material flow based on the respective current operating states (34) with and without varying operating parameters (36) of the transport equipment (15), to analyze the simulated material flows with regard to throughput improvement, and in the event that a throughput improvement is analyzed, to transmit the correspondingly varied operating parameters (36) to the corresponding transport facilities (15), which are then operated based on the varied operating parameters (36).

The invention discloses a calcareous sand two-dimensional porous microstructure reconstruction processing method, system and platform based on a diffusion model and a storage medium. High-fidelity reconstruction and generation of a calcareous sand microstructure with an extremely complex form are realized by integrating principal component analysis directional alignment and a v prediction diffusion model; wherein the generated two-dimensional microstructure image is not only highly matched with a real CT slice in vision, but also shows high consistency in statistical distribution of 14 key morphology parameters such as porosity, fractal dimension, skeleton complexity and the like, and verifies the physical authenticity of the two-dimensional microstructure image. The method has dual capabilities of unconditional generation and conditional reconstruction, can synthesize a large number of statistical reasonable digital samples from zero to expand a scarce data set, and can intelligently enhance low-quality experimental images. And a stable, efficient and extensible digital material source is provided for discrete element numerical simulation, permeability characteristic prediction and microstructure-oriented constitutive model development of the calcareous sand.