52 results about "Computer modelling" patented technology

The invention provides a CAD model reconstruction method and device for a topological optimization result, and relates to the technical field of computer modeling, and the method comprises the steps: carrying out grid preprocessing, carrying out component type grid segmentation, carrying out patch type grid segmentation, obtaining at least two sub-grid patches, carrying out parameterization on each sub-grid patch, and obtaining a final parameterization result. And performing uniform interpolation sampling based on the final parameterization result to obtain sampling points, generating a spline surface by using the sampling points, assembling the spline surface, and generating a reconstructed CAD model corresponding to the three-dimensional topological optimization fruit. The grid model reconstruction method has the advantages of being high in automation degree, high in realizability, easy to operate and the like, is not limited to a tubular topological optimization structure, has no obvious difference in effect when processing tubular and non-tubular model characteristics, has higher universality, can adapt to the diversity requirements of industrial structure optimization, and is suitable for large-scale popularization and application. And meanwhile, the reconstruction efficiency and the reconstruction effect from the triangular mesh model to the CAD model can be improved.

Systems and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular disease, cancer, neurological disorders, immune system disorders and genetic diseases.

Described herein are systems and methods for detecting flaws during an additive manufacturing (AM) process. A method can include accessing, by a computer, simulation results of a computer-modelled part representing a physical part to be formed using the AM process. The simulation includes a thermal history model for the computer-modelled part. During run-time formation of the physical part, the method includes receiving, from sensor devices, real-time sensor data of temperature values for nodes within regions of the physical part as each region is formed. The method also includes determining, for each region as the region is formed in the physical part, a deviation between the real-time sensor data of temperature values for nodes within the region and temperature values of the thermal history model for the computer-modelled part, and identifying flaws in the physical part based on determining that the deviation satisfies criteria indicating a flaw.

A chamber, e.g. in a heat exchanger or flowing electrolytic half-cell, for through flow of a fluid which is capable of elastic turbulence has an internal structure with obstructions to compel flow to undergo successive changes of direction thereby applying stress to the flow of fluid through the chamber. The internal structure comprises an upstream portion in which the applied stress induces elastic turbulence to begin and a downstream portion which applies less stress per unit length and sustains the elastic turbulence while providing economy of pressure to propel the fluid. Configuration of the upstream portion may be planned with computer modeling so as to avoid formation of stagnant zones.

The invention relates to the technical field of computer modeling, in particular to an earthquake resistance and disaster reduction simulation system for a liquefiable foundation. The system comprises a cyclic stress ratio field analysis unit, an excess pore pressure ratio evolution analysis unit and a stress coupling correction unit, the cyclic stress ratio field analysis unit is used for generating a cyclic stress ratio field by using a depth reduction relation; the excess pore pressure ratio evolution analysis unit is used for deducing an excess pore pressure ratio and establishing an evolution relation of the excess pore pressure ratio along with time and depth; and the stress coupling correction unit is used for updating the effective vertical stress value based on the excess pore pressure ratio, synchronously correcting the shear modulus according to the coupling relationship between the shear wave velocity and the excess pore pressure ratio, and feeding back the corrected shear modulus to the excess pore pressure ratio evolution analysis unit. According to the method, the scientificity and engineering applicability of earthquake resistance and disaster reduction of the liquefiable foundation are effectively improved.

A chamber, e.g. in a heat exchanger or flowing electrolytic half-cell, for through flow of a fluid which is capable of elastic turbulence has an internal structure with obstructions to compel flow to undergo successive changes of direction thereby applying stress to the flow of fluid through the chamber. The internal structure comprises an upstream portion in which the applied stress induces elastic turbulence to begin and a downstream portion which applies less stress per unit length and sustains the elastic turbulence while providing economy of pressure to propel the fluid. Configuration of the upstream portion may be planned with computer modeling so as to avoid formation of stagnant zones.

The invention belongs to the technical field of crossing of rock soil, geological engineering and computer modeling, and discloses a three-dimensional fractured rock anisotropic fragmentation and expansion structure generation method and system, and the method comprises the following steps: generating tightly embedded initial blocks in an expansion domain according to the number of control blocks and the initial equivalent size of the blocks; on the basis of the node information of the initial block, anisotropic fragmentation and expansion mapping geometric transformation is carried out on the cell elements, and node coordinate information after fragmentation and expansion and form control is carried out is obtained; calculating the volume ratio of blocks in the target area to obtain a current volume fraction; extracting a target domain in the extended domain, performing constraint smoothing, abandoning an external block, and retaining node coordinate information in the target domain; and exporting the reserved node coordinate information, the current volume fraction and the geometric structure to obtain the fragmentation and expansion structure.

The application provides a CAD model reconstruction method and device for topology optimization results, and relates to the technical field of computer modeling. The method comprises the following steps: grid preprocessing, component type grid segmentation, sheet type grid segmentation, obtaining at least two sub-grid sheets, parameterizing each sub-grid sheet to obtain a final parameterization result, performing uniform interpolation sampling based on the final parameterization result to obtain sampling points, generating a spline surface by using the sampling points, assembling the spline surface, and generating a reconstructed CAD model corresponding to the three-dimensional topology optimization result. The grid model reconstruction method has the advantages of high automation degree, strong realizability, simple operation, etc., is not limited to a tubular topology optimization structure, has no obvious difference in processing tubular and non-tubular model characteristics, has stronger universality, can adapt to the diversity demand of industrial structure optimization, and can improve the reconstruction efficiency and reconstruction effect of the triangular grid model to the CAD model.

The present invention discloses an energy optimization scheduling method based on eigenspace, which includes the following steps: S1: constructing a microgrid economy and carbon emission calculation model based on eigenspace; S2: collecting microgrid input variables and input parameters, and configuring them in the microgrid economy and carbon emission calculation model; S3: in the eigenspace, based on multiple specific eigenstates and corresponding input variables, multiple corresponding output functions are obtained, and the net electricity cost of the microgrid and the carbon emissions caused by the microgrid are calculated independently according to the output functions; S4: setting optimization objectives and constraints; S5: using particle swarm algorithm to achieve energy optimization scheduling. The energy optimization scheduling method proposed by the present invention adopts the eigenstate method in the field of linear algebra in the calculation model, which can conveniently decouple multiple key outputs from each other, and then solve the energy optimization scheduling problem within and between energy sources through computer modeling.

System and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular

The present invention discloses a construction engineering plastering construction process and system using three-dimensional optical scanning technology. The process comprises: obtaining a measured model of a built wall surface to be plastered by three-dimensional optical scanning, and obtaining a design model corresponding to the built wall surface to be plastered by computer modeling; comparing and analyzing the measured model with the design model using a construction engineering plastering control target information generating device to generate plastering control target information, the plastering control target information including plastering control target location information and plastering control target calibration piece thickness information; obtaining a plastering control target calibration piece of corresponding thickness based on the plastering control target calibration piece thickness information, and installing the plastering control target calibration piece at a corresponding position on the built wall surface to be plastered based on the plastering control target location information; and performing plastering construction on the built wall surface to be plastered.

Methods and systems are presented for providing a framework that configures a machine learning model to be insensitive to changes in input features. A computer modeling system determines data sources from which attribute values associated with transactions can be obtained. Instead of configuring the machine learning model to accept the attribute values as inputs, the computer modeling system may configure the machine learning model to accept a vector representation in a multi-dimensional space as input values. The computer modeling system then generates an encoder for each data source. Each encoder is configured to encode attribute values from a corresponding data source to a representation representing the attribute values. Further, each encoder is trained to minimize a variance between outputs of the different encoders. The computer modeling system determines a vector representation based on the representations generated by the encoders and provide the vector representation to the machine learning model.

Compositions of peptides modified to enhance HLA binding or T cell recognition while preserving reactivity to target neoepitopes enhance the activation of neoantigen-specific T cells. The method of use involves treating cancer by administering one or more of these peptides, which are produced by computer modeling.

In an exemplary embodiment, software made in accordance with the present invention generates a request for quote (RFQ) based on user-provided information, presents a user interface allowing a user to customize the RFQ, generates an e-mail including the RFQ, and sends the e-mail to one or more suppliers. Various corresponding and related systems, methods, and software are described.

The invention discloses an airport clearance area scene twin modeling and dynamic target safety prediction method, belongs to the technical field of digital twin and computer modeling, and solves the problem of high difficulty in automatic modeling of a large airport scene. The method comprises the following steps: acquiring point cloud data of a static target in an airport clearance area and preprocessing the point cloud data; performing curved surface reconstruction by adopting a point cloud projection reconstruction method to obtain rapid three-dimensional modeling of the static target, including the three-dimensional coordinate of the static target and the semantic relationship of the static target; performing dynamic target recognition on the obtained video of the airport clearance area in real time by using an improved YOLOv8 network to obtain classified dynamic targets and a semantic relationship between the dynamic targets; performing real-time positioning on the identified dynamic target based on the improved BP network to obtain a three-dimensional coordinate of the dynamic target; and fusing the three-dimensional coordinates of the static target and the dynamic target in an un-ity engine to realize twin modeling of the clearance area, and dynamically updating in real time. The method is used for airport clearance area scene twin modeling.

The application relates to the technical field of computer 3D modeling, and discloses a city three-dimensional terrain rapid modeling method and system based on AI point cloud semantic segmentation. According to city terrain semantic point cloud fusion preprocessing data set and in cooperation with a point cloud three-dimensional modeling platform, high-quality three-dimensional modeling of feature objects in a target city terrain is carried out, and precise modeling under a city terrain limited point cloud data state is realized based on semantic segmentation and point cloud fusion. Through the point cloud three-dimensional modeling platform and screenshot software, city terrain three-dimensional model image information is accurately collected, and intelligent identification of city terrain three-dimensional model modeling defects is carried out in combination with AI algorithms and city terrain feature object standard modeling defect image data. Based on city terrain three-dimensional model data and in cooperation with the point cloud three-dimensional modeling platform, dynamic and efficient repair and reconstruction processing of city terrain three-dimensional model modeling defects is carried out, and precise modeling and repair and reconstruction under a city terrain limited point cloud data state are realized based on model repair.

Computer-based system, method and apparatus aggregating data of equity and debt securities, and investment portfolios, to benefit multiple investment companies (ICs) with complementary objectives by transforming an investment portfolio into a source of significantly more returns for each investor IC's objectives by apportioning unequally the portfolio's benefits, risks and obligations to each IC invested in the portfolio. Components include a securities data aggregation computer (SDAC), a portfolio data aggregation computer (PDAC), a portfolio comparison computer (PCC), a Portfolio Modeling Computer (PMC), a computer modeling and displaying ways to optimize the benefits and obligations of the portfolio (CDBO). Computers use investment characteristics to dynamically display the portfolios and combinations of portfolios, to model alternative portfolios to serve the complementary objectives of each IC. An embodiment of the invention unites, in the creation and management of a single portfolio, two or more ICs with complementary objectives.

Continuously learning and optimizing artificial intelligence (AI) adaptive neural network (ANN) computer modeling methods and systems, designated human affect computer modeling (HACM) or affective neuron (AN), and, more particularly, to AI methods, systems and devices that can recognize, interpret, process and simulate human reactions and affects such as emotional responses to internal and external sensory stimuli, that provides real-time reinforcement learning modeling that reproduces human affects and / or reactions, wherein the human affect modeling (HACM) can be used singularly or collectively to modeling and predict complex human reactions and affects.

A system stores instructions including, in response to receiving user input, identifying a first event type and a first security identifier and obtaining a first set of event dates from the event database and, for each event date of the first set of event dates, obtaining a corresponding event value on the corresponding event date of the first security identifier. The instructions include, for a first day related to each event date of the first set of event dates: obtaining a corresponding value on the first day of the first security identifier, determining a corresponding difference value between the corresponding event value and the corresponding value, and storing the corresponding difference value in a set of difference values. The instructions include calculating an average difference on the first day using the set of difference values and displaying the average difference and an event indicator corresponding to the first event type.

The invention provides a special-shaped plate stamping die reset process simulation method and system combined with data modeling, and relates to the technical field of computer modeling. Firstly, a special-shaped plate reset dynamic topology model is constructed based on special-shaped plate three-dimensional shape data and die reset component motion feature data; associating the contact area with the acting force transmission path through the topological node; then, shape deformation data and mold reset force real-time data in the reset process are collected to generate a shape force coupling data chain; inputting the morphological force coupling data chain into a special-shaped plate reset dynamic topology model to drive topology nodes to dynamically recombine and generate topology recombination data; generating dynamic adaptive reset path data based on the topology recombination data; and finally, reversely inputting the dynamic adaptive reset path data into the special-shaped plate reset dynamic topology model for iterative optimization, and generating simulation complete data. According to the invention, the reset process of the special-shaped plate stamping die can be accurately simulated, and the simulation accuracy and reliability are improved.

Methods, systems, and devices (including media encoded computer program products) for computer-aided design and manufacturing of physical structures by generating a prismatic CAD model using machine learning include obtaining an input embedding encoding a representation of a target two-dimensional (2D) shape; processing the input embedding using a 2D decoder of a 2D autoencoder to obtain a decoded representation of the target 2D shape; determining a fitted 2D parametric sketch model for the input embedding, including finding a 2D parametric sketch model for the input embedding using a search in an embedding space of the 2D autoencoder and a database of sketch models associated with the 2D autoencoder, and fitting the 2D parametric sketch model to the decoded representation of the target 2D shape; and using the fitted 2D parametric sketch model in a computer modeling program.

Provided is a modified peptide composition which is modified to enhance HLA binding or T cell recognition and improve activation of neoantigen-specific T cells while preserving reactivity to a target neoepitope. Methods of use include the treatment of cancer by administering one or more of these peptides generated by computer modeling.

Video compression method and apparatus wherein a scene image is captured and compared to an expected scene image that was generated based on a computer-modeled scene and wherein the difference data – if any exists, is transmitted and / or stored, thereby reducing the requisite bandwidth and / or storage space. Optionally, difference data that is considered unimportant can be ignored or otherwise omitted from transmission and / or storage. Embodiments of the present invention can replicate all or a portion of real-world camera or other sensor and scene characteristics, preferably using predictive modeling and adaptive analysis, to efficiently encode and transmit video data. Embodiments of the invention thus encompass methods for scene reconstruction, object tracking, parameter updating, and / or bandwidth-adaptive streaming, with particular applications in space-based imaging and video processing.

The present application relates to the technical field of computer modeling, and particularly relates to a three-dimensional geological model automatic generation method, system and electronic equipment, the method comprises the following steps: obtaining three-dimensional geological modeling requirement data and modeling data input by a user, and processing the modeling data; generating a modeling instruction stream through a large model after reinforcement learning, and performing feasibility verification on the generated modeling instruction stream; if the verification result is feasible, the modeling instruction stream is sent to a three-dimensional geological modeling software to generate a three-dimensional geological model; obtaining feedback information of a modeling expert adjusting the three-dimensional geological model and diagnosing and analyzing the modeling instruction stream generated by the large model, and storing the feedback information in a knowledge base; if the verification result is unfeasible, problem matching is performed in the knowledge base, and the result is input to the large model, after analysis, a modeling instruction stream is regenerated to drive the three-dimensional modeling software to model; thus, the present application can automatically generate a three-dimensional geological model.

A method of forming an additively manufactured part includes: converting a desired final three-dimensional part geometry into a flattened, computer-modeled shape; operating a printhead to deposit a first layer of a part-forming material on a substrate, the first layer being one of a plurality of iteratively deposited layers of an additive build according to the flattened, computer-modeled shape, such that the additive build is comprised of successive layers of the deposited part material on the substrate; and creating a part by manipulating one or more portions of the additive build at one or more predetermined locations to form the additive build into a final shape having the desired final three-dimensional part geometry. The part-forming material and the substrate each may include a thermoset or thermoplastic, and may include a curable resin. The substrate may be in the form of an impregnated or unimpregnated sheet, film, fabric, laminated fabric, or weave.

At least one processor configured to perform operations including receiving data from a plurality of disparate data sources, the data including a plurality of variables associated a plurality of entities and characteristics of the entities; extracting one or more associations from the data, wherein each of the one or more associations includes one or more probabilistic distributions based on a relationship between the performance metrics and the entities and their positions; generating, based on the associations, a flight index for each of the entities; wherein the flight index is a statistical measure of a likelihood that an entity will leave the organization; generating a performance index to each of the entities; identifying, based on a comparison between the flight index and the performance index, a flight probability the entities being higher than a threshold flight probability; implementing, based on the identification, policy changes in the organization.

The invention relates to the technical field of computer modeling analysis, and particularly discloses a finite element analysis-based FPSO large-scale pipe support strength and fatigue life evaluation method, which comprises the following steps of: establishing a three-dimensional finite element model comprising a large-scale pipe support and an FPSO ship body structure connected with the large-scale pipe support; the installation mode of the large pipe support is at least one of a base plate type and a base type. A load used for structural strength analysis is applied to the three-dimensional finite element model, and the load combination is at least one preset working condition. According to the invention, by systematically applying various complex working condition combinations including marine specific dynamic loads such as ship motion inertia force and wave load, the stress state of the pipe support in an actual service environment can be simulated more truly and comprehensively, and the accuracy and reliability of structural strength evaluation are greatly improved; and the potential safety hazard caused by incomplete consideration of the key load is effectively avoided.

This application provides a method for preparing personalized skincare products based on quantitative biology, characterized by the following steps: Step S10, collecting user skin data and environmental characteristics to form phenomenon data; Step S20, using computer modeling, intelligently combining and matching the phenomenon data with pre-stored product data including the formulation activity and effects of each ingredient, as well as pre-stored result data including historical feedback and closed-loop optimization, to obtain a combined formula; Step S30, preparing skincare products using the combined formula and providing them to the user.