2536 results about "Multiple component" patented technology

The invention belongs to the technical field of industrial automation control, and particularly relates to a dynamic optimization control method and system for multi-component batching of a paste making machine, and the method comprises the steps: generating a characteristic waveform spectrum corresponding to a residue molecular structure; dynamically generating electric lubricating medium parameters containing the electroosmotic liquid concentration and the release rate; triggering a low-frequency vibration module of the material layer to generate vibration waves, and enabling the solution and the vibration waves to form a molecular-level synergistic stripping effect; calculating a nanoparticle dispersity index, and generating an inverse gradient mixing instruction when the index exceeds a threshold value; activating a hot vortex ring in a spiral flow guide convex pattern area and establishing a directional heat energy migration channel; and verifying the dynamic equilibrium state of the temperature of the paste core area and the viscoelasticity of the target formula, and triggering a phase lock control signal to terminate the parameter adjustment chain when the energy consumption rate reaches a stable interval. According to the invention, the problems that the transition period during formula switching is prolonged and the phase differences among the execution mechanisms are difficult to match in real time due to a traditional staged regulation and control mode are solved.

The invention relates to the field of building construction simulation, in particular to a building construction simulation model construction method and system based on a BIM model. The method comprises the following steps of obtaining a multi-source design material of a building project, and performing BIM format heterogeneous conversion so as to generate multi-source heterogeneous conversion BIM data; generating a plurality of component independent sub-models based on the multi-source heterogeneous conversion BIM data; according to the multiple component independent sub-models, building component space position positioning calculation is carried out one by one, global BIM modeling is carried out, and a building global BIM model is constructed; performing inter-component structure collision identification on the building global BIM model, and performing collision conflict optimization so as to construct a conflict optimization BIM model; building construction behaviors are analyzed one by one based on the multi-source heterogeneous conversion BIM data, then construction sequential sequence fitting is conducted, and a construction process behavior sequence is constructed. Through efficient and refined building construction simulation model construction, the construction efficiency is improved, and construction resource allocation is optimized.

The invention belongs to the crossing field of environmental engineering and hydrology and hydrodynamics, and particularly relates to a traceability method based on coupling hydrodynamics and a pollutant degradation equation, which comprises the following steps: firstly, acquiring and preprocessing multi-source heterogeneous monitoring data, then selecting a one-dimensional Saint-Venant equation or a two-dimensional shallow water equation according to a water body form to solve a hydrodynamic field, and finally, determining the hydrodynamic field. A multi-component convection-diffusion-reaction equation is coupled to simulate pollutant migration and transformation; an LSTM module is introduced to identify suspected pollution events, pollution source parameters are inverted through a two-channel framework of PDE constraint optimization and Bayesian inference, uncertainty is quantified, model parameters are updated online in combination with data assimilation, and finally the uncertainty is quantified and verified. The method considers traceability precision, efficiency and compliance, supports multiple water bodies and multiple data sources, and is suitable for complex water body pollution traceability.

The invention discloses a high-toughness impervious polymer modified cement-based grouting material and a preparation method thereof, and belongs to the technical field of building repair materials. The component A is prepared from a cementing material, an admixture, a fine aggregate, a composite expanding agent, a polymer for concrete modification, fibers, an early strength agent, a water reducing agent, a composite retarder, a defoaming agent, an air entraining agent, a nano material and a functional component. The system solves the technical contradiction of toughness-strength-impermeability in the polymer modified cement-based material, and the material has excellent comprehensive performance: the initial fluidity is greater than or equal to 330 mm, the 28d compressive strength is greater than or equal to 82 MPa, the breaking strength is greater than or equal to 16.8 MPa, the bending-compression ratio is greater than or equal to 0.19, the impermeability pressure value is greater than or equal to 2.6 MPa, and the material is suitable for the fields of prefabricated buildings, tunnel engineering and the like.

The invention discloses ardealite-based concrete and a preparation method thereof, and belongs to the technical field of building materials. The ardealite-based concrete is prepared from the following raw materials in parts by weight: 40 to 60 parts of ardealite powder, 10 to 15 parts of cement, 8 to 10.5 parts of slag powder, 5 to 7 parts of fly ash, 4 to 6 parts of desulfurized fly ash, 5 to 10 parts of natural sand, 10 to 15 parts of ardealite-based artificial aggregate, 3 to 5 parts of eggshell powder, 1.5 to 3 parts of nano silicon dioxide, 0.5 to 1.5 parts of a water reducing agent, 0.05 to 0.2 part of a retarder, 0.1 to 0.5 part of an exciting agent and 0.3 to 1 part of an antifreeze agent. According to the invention, through process innovation of multi-component collaborative design and gradient aggregate doping, the technical bottlenecks of low strength, poor durability, high environmental protection risk and the like of traditional ardealite concrete are overcome while large-scale resource utilization of ardealite is realized, and a new thought is provided for high-valued utilization of industrial solid wastes.

Described are embodiments that include methods and devices for separating components from multi-component fluids. Embodiments may involve use of separation vessels and movement of components into and out of separation vessels through ports. Embodiments may involve the separation of plasma from whole blood. Also described are embodiments that include methods and devices for positioning portions, e.g., loops, of disposables in medical devices. Embodiments may involve use of surfaces for automatically guiding loops to position them into a predetermined position.

The invention discloses a home page multi-component parallel prefetching and rendering first screen acceleration method and device and a storage medium, and the method comprises the following steps: constructing a global dependency relationship model based on the metadata and dependency relationship of each component of a home page, and calculating the priority for each component according to a predefined priority evaluation strategy, generating a component scheduling sequence constrained by the priority and the dependency relationship; controlling a concurrency control strategy of the component; preferentially rendering a visual placeholder structure, and smoothly replacing the real content to a user visible area through a progressive rendering replacement strategy; when the variable quantity of the component data exceeds a preset threshold value, triggering an increment updating strategy based on the difference content; generating a cache identifier according to component granularity, reading and writing data in a multi-level cache structure based on the cache identifier, and ensuring data consistency by adopting a background asynchronous verification strategy; and collecting performance indexes in a page rendering process, and adjusting the priority evaluation strategy, the concurrency control strategy and the increment updating strategy according to the performance indexes.

The invention discloses a server power consumption management method and device, electronic equipment and a storage medium, and relates to the technical field of computers, the future load change trend of a server can be predicted according to the load data of the server at the current moment, and a power consumption management strategy of the server is generated according to the load data and the load change trend at the current moment. The power consumption management strategy is utilized to adjust the operation parameters of at least one component in the multiple components, and the power consumption management strategy is predicted in advance and adjusted in real time, so that the load fluctuation of the server can be dynamically adapted, and insufficient resource allocation of the server under different load conditions due to a fixed static power consumption management strategy is avoided. Therefore, the technical problems that the resource allocation of the server is unbalanced and the energy efficiency is low due to the fact that the power consumption management strategy cannot be dynamically adjusted in related technologies can be solved, and the purposes of optimizing the resource allocation of the server and improving the energy efficiency of the server are achieved.

The embodiment of the invention discloses a method for generating page codes and electronic equipment. The method comprises the steps that a design file provided for a target page or a target area in the page is acquired; extracting visual feature information respectively corresponding to a plurality of design elements from the design file; the visual feature information of the design elements is assembled to a preset prompt information template to generate prompt information, and the prompt information template further comprises an optional component set which comprises use method information corresponding to multiple components and page development specification information; the plurality of components are respectively associated with predefined component codes; and calling an artificial intelligence (AI) generation model according to the generated prompt information, so that the AI generation model selects matched components for the plurality of design elements respectively, and generating description contents of page frame codes in a mode of quoting the components. Through the embodiment of the invention, the page development efficiency can be improved, the cost can be reduced, and the maintainability of page codes is considered.

The invention discloses a composition based on hollow glass beads and a preparation method thereof, and relates to the technical field of material science. The preparation method comprises the following steps: firstly, constructing a pre-composite functional microsphere with a specific hierarchical structure as a core basic functional unit, then matching with a plurality of components such as a thermosetting resin matrix, a latent curing system, a functional synergistic aid package and a composite solvent system, and matching with a preparation process which has a synergistic effect with the components. The composition based on the hollow glass beads is expected to realize uniform dispersion of the hollow glass beads in a coating system and strong bonding of a microscopic interface on the premise of ensuring the structural integrity of the hollow glass beads. Therefore, the high-performance composite coating material with ultra-light weight, high heat insulation efficiency, excellent mechanical strength and long-term service stability is obtained.

A software package is received and unpacked into multiple components comprising plural functions. Each function is lifted from machine code into static single-assignment intermediate representation and tokenized to produce semantics-preserving embeddings. Intermediate-representation data-flow features are extracted, including detection of constant static variables on a stack, stack reaching definitions, uninitialized variables, and intra-procedural aliases. For each component, the embeddings and features are input to a machine-learning model trained on semantic properties derived from a corpus of software packages to generate a software supply chain risk level. Data characterizing the risk level is provided to a consuming application. When the risk level satisfies a remediation criterion, a remediation action is initiated, including generation of a source-code patch recommendation for an identified root-cause function, insertion of a runtime guard into the component, or issuance of a security advisory for distribution to a security operations dashboard.

The invention provides a pourable tumor organoid vascularization model and a construction method thereof, and relates to the technical field of organoid culture. A temperature-sensitive degradable material and a photo-crosslinking modified temperature-sensitive material are used, the composite stent is printed through two channels, a multi-component gel mask partition curing process is combined, the stability of a perfusion pipeline is improved, and a partitioned highly-bionic complex microenvironment is accurately constructed in a macroscopic three-dimensional space; and constructing to obtain the perfusion tumor organ vascularization model. The model is high in bionic degree and stable in structure, can be applied to deepening cell and microenvironment interaction research and tumor-related drug screening, and has a good application prospect.

The invention belongs to the technical field of film materials, and particularly relates to a lower supporting film for a flexible folding display screen and a preparation method of the lower supporting film. The supporting film sequentially comprises a protective film layer, a stainless steel base material layer, an adhesive layer and a release film layer from top to bottom; wherein the adhesive layer is prepared by coating a release film with modified organic silica gel liquid, drying and curing. The ultra-thin stainless steel is used as the base material layer, can resist external force impact and scraping, is low and stable in thermal expansion coefficient, can reduce the influence of environment temperature and humidity on the size of the supporting film, and guarantees the structural consistency of the screen module in long-term use; and through multi-component composite modification of polyurethane-thiazole-organic silicon, the peeling strength of the adhesive layer and stainless steel and the bending frequency of the supporting film are improved, and the service life of the supporting film is prolonged.

A masking system for selectively masking a component includes a housing made of high-temperature material. The housing has a first shell and a second shell. The first shell has a first receiving area and a first window that extends through the first shell. The masking system has a liner that includes elastomeric material. The liner has a back side configured to fit within the first receiving area and a front side having a retaining feature configured to receive and retain the component. When the liner is disposed within the first receiving area and the component is received by the retaining feature, the first window corresponds to at least one portion of the component that is accessible.

The invention relates to the technical field of gas detection, and provides a multi-component gas detection method and system.The method comprises the steps that an MEMS-MOS gas sensor array is designed to be composed of a plurality of miniature gas sensing units; each temperature control loop is used for controlling each micro gas sensing unit to maintain the working temperature aiming at the target gas, so that each micro gas sensing unit generates differentiated and complementary dynamic resistance response signals in a mixed gas environment; collecting the resistance change of each micro gas sensing unit in the gas exposure process in real time, and generating a multi-channel digital time sequence data flow; reconstructing the multi-channel digital time sequence data stream into a two-dimensional matrix of channel number * time step; and inputting the two-dimensional matrix into a trained lightweight convolutional neural network model, and outputting gas types and corresponding concentration values contained in the mixed gas. According to the invention, rapid and accurate detection of multi-component gas can be realized in a complex environment, and the sensor has the characteristics of high sensitivity, low power consumption, suitability for portable deployment and the like.

The invention relates to the technical field of medium phase state determination, in particular to a PVT analyzer and method suitable for multi-component fluid medium phase state determination, and the PVT analyzer comprises a determination assembly, a test cylinder, a balance cylinder, a pressurization cylinder, a gas distribution pipeline, a first driving mechanism and a second driving mechanism. The structure is reasonable and compact, combination of gas with various components can be achieved through the multiple gas cylinders and the gas distribution pipeline, mixing of the gas according to the set ratio can be achieved by adjusting the gas distribution valve, the multiple gas cylinders can inject the gas into a rodless cavity of the pressurization air cylinder through the gas distribution valve and the gas distribution pipeline, and the gas injection efficiency is improved. The second driving mechanism drives the piston rod of the pressurizing air cylinder to continuously input gas in the rodless cavity of the pressurizing air cylinder into the rodless cavity of the balance air cylinder through the pressurizing pipeline and the one-way valve, so that the pressure of the rodless cavity of the balance air cylinder can be increased; and the precise gas distribution and gas pre-pressurization functions of multi-component gas can be realized.

A wireless communication interface is included in a surgical robotic arm and is used to detect various components of the robotic arm, including, an instrument drive unit, a sterile interface module (e.g., adapter), an instrument, an access port, etc. Detection of the components is used to confirm that each of the components are properly assembled by splitting up tag assemblies between multiple components, such that when the components are properly assembled, so are the tag assemblies, allowing for interrogation thereof by the wireless communication interface.

The invention discloses a multi-scale wear fatigue joint simulation method and system for a valve element and a valve sleeve of a servo valve, and relates to the technical field of hydraulic control. A geometric model is designed according to structural parameters of a valve structure, and the geometric model is divided into multiple assemblies; defining material parameters of each component, and correspondingly associating the material parameters with each component; defining a wear model of the contact surface of the valve core and the valve sleeve; defining a nonlinear mechanism of the fatigue model; defining a coupling model of a coupling relationship between the wear model and the fatigue model; performing grid division on the geometric model by adopting a dynamic grid updating model, and taking all grid units as simulation analysis objects; performing simulation analysis on the coupling model; according to the simulation result, the wear fatigue coupling failure behavior of the valve element and the valve sleeve is predicted, and the design of the valve element and the valve sleeve is optimized. According to the method, the submicron wear depth prediction precision can be realized, the service life prediction error is reduced compared with that of a traditional method, and a quantitative basis is provided for reliability design and condition-based maintenance of a high-precision servo valve.

The invention discloses a multi-component gas detection device and method based on a metasurface quasi-continuous domain bound state. The advanced nanometer manufacturing technology and the deep learning algorithm are adopted, and high-precision, high-sensitivity and high-selectivity gas detection is achieved. According to the invention, the metasurface array with specific design is utilized, and the quasi-continuous domain bound state in the middle-infrared band is realized by accurately regulating and controlling the geometric parameters and material characteristics of the microstructure, so that excellent optical response is obtained. In combination with a deep learning algorithm, complex spectral information is converted into accurate gas composition and concentration information, and a reliable solution is provided for the fields of environmental monitoring, industrial production, safety monitoring and the like.

The invention discloses an artificial SEI material and a preparation method thereof, an artificial SEI film and an artificial SEI film modified negative electrode. The artificial SEI material is an organic polymer brush (CNF-g-PSSX) prepared by grafting cellulose nanofibers with polystyrene sulfonate. The polymer brush is of a crystal structure and has a firm framework; and the side chain of polystyrene sulfonate has rich-SO3 functional groups which are matched with cations in sulfonate, so that a rapid ion transmission channel is provided, high-current-density circulation can be realized, and good interface contact is ensured. Due to a special molecular topological structure and a multi-component synergistic effect, when the organic polymer brush forms an artificial SEI film, high mechanical strength, high ionic conductivity and low interface impedance can be obtained at the same time, and through strong electrostatic repulsion between a negatively charged-SO3 group and the surface of a negatively charged lithium dendrite tip, the electrochemical performance of the artificial SEI film is improved. An obvious inhibition effect is shown on the continuous growth of dendritic crystals.

The invention provides a rotating disc type multi-component injection molding device and a control method thereof.The device comprises a device base, a rotating disc assembly is arranged on the device base and comprises a rotating disc and a rotating driving device, and a plurality of cavities are formed in the peripheral wall face of the rotating disc around the rotating axis of the rotating disc; a plurality of injection molding stations and an unloading station are arranged on the radial outer side of the rotary disc around the rotary disc, and the rotary driving device can drive the rotary disc to rotate so that the cavities can be switched between the injection molding stations and the unloading station. The steps of material injection, cooling and part taking of the cavities can be synchronously carried out at the corresponding stations and do not interfere with one another, independent mold opening and part taking time is not needed, the production cycle can be remarkably shortened, and the production rhythm and the production efficiency can be improved; the overall size of the rotary table is remarkably reduced, the requirement for device installation space is lowered, the requirement for rotation driving power is lowered, rotation controllability is higher, and meanwhile material cost is lowered.

Certain aspects of the present disclosure provide a method for wireless communications by a user equipment (UE). The method generally includes waiting for a multiple component carrier (multi-CC) uplink slot in which an uplink slot on a first component carrier (CC) overlaps with an uplink slot of a second CC in order to transmit a periodic power headroom report (PHR) in a current PHR period and transmitting, in the multi-CC uplink slot, the periodic PHR with power headroom (PH) values for the first CC and the second CC.

The invention discloses a shale oil reservoir flow simulation method based on a limited fluid state equation, which belongs to the technical field of oil-gas field development and comprises the following steps of: establishing a limited fluid generalized state equation by considering a nano confinement effect; oil / gas phase balance is calculated based on the limited fluid generalized state equation; oil / gas two-phase physical property parameters are calculated; and establishing a multi-component multi-phase flow shale oil flow simulation formula. By adopting the method, the P-R state equation is corrected based on the nano confinement effect, phase equilibrium calculation is performed based on the corrected P-R state equation, the oil / gas two-phase physical property parameters are calculated, the parameters are substituted into the shale oil reservoir flow equation, the flow characteristics of the shale oil reservoir are defined, and the simulation efficiency is improved.

A valve system includes at least one spin chamber having an outlet drain configured to allow flow out of the spin chamber. A main spin surface of the at least one spin chamber is defined around the outlet drain. A directional jet system is in fluid communication with the at least one spin chamber. The directional jet system includes a plurality of members each is configured to move between a first position for directing a tangential flow around the drain of the at least one spin chamber and a second position for directing a radial flow toward the drain of the at least one spin chamber.

The invention discloses a multi-component catalyst active site prediction system and method fused with quantum embedding, and relates to the technical field of catalysis and material informatics, and the system comprises a structure and site enumeration module which generates candidate sites; the adaptive quantum embedding calculation module obtains key reaction microcosmic parameters; the unified site fingerprint and feature engineering module constructs and fuses standard site fingerprints; the physical consistency machine learning module predicts adsorption energy and other parameters and uncertainty thereof; the active learning and sample selection module selects a high-value sample optimization model; the microdynamics evaluation module calculates index values such as activity; and the multi-objective optimization and sorting module generates an optimization sorting list. According to the method, the unification of calculation precision and efficiency is realized, the problem of non-unification of locus characterization is solved, the model interpretability and extrapolation reliability are improved, and the comprehensive evaluation and optimization sorting of multi-target performance are completed.

The invention relates to the field of assembly equipment, in particular to a safety lock assembly device based on an industrial robot, which comprises an assembly machine, the assembly machine comprises a rack, an assembly feeding assembly is arranged at the top of the rack, an adaptive positioning assembly is arranged on one side of the assembly feeding assembly, and a screw assembly assembly is mounted on the adaptive positioning assembly; the assembly feeding assembly is used for completing the accessory feeding assembly during assembly; the adaptive positioning assembly is used for conducting positioning and adaptive adjustment on the thread assembling assembly according to the assembling progress. The screw assembling assembly is used for connecting and assembling all accessories of the safety lock through assembling screws. And the adaptive positioning assembly comprises mounting frames, a lifting frame is slidably connected between the mounting frames, and a fixing disc and a sliding block are slidably connected to the bottom of the inner side of the lifting frame. Through cooperation of multiple components, full-plane flexible positioning of the screw assembling assembly is achieved, manual operation is reduced, and the assembling efficiency is remarkably improved.

A digital twin service of a provider network allows a user to build high fidelity models (“digital twins”) for components and for systems of multiple components. For a given component, the digital twin service receives, from a user, identification of interactions for the component (e.g., inputs / outputs at the boundary), identification of data sources at the system (e.g., sensor that stream data), and / or a definition of behavior of the component (e.g., one or more behavior functions to simulate the component). The digital twin service builds a digital twin model of the component based at least on the interactions, the data sources, and the behavior. The digital twin service may also receive, from the user, an indication to bind one or more outputs of the digital twin model to one or more inputs of at least another of the digital twin models to build a digital twin model of the system.

The invention provides a drinking water pipeline anti-corrosion powder coating multi-component proportioning intelligent batching method and system, and relates to the technical field of intelligent manufacturing, and the method comprises the following steps: obtaining drinking water pipeline anti-corrosion powder coating raw material parameters and formula information; constructing a quantitative characteristic volume element numerical simulation unit, and performing multi-scale bridging calculation in combination with microscopic molecular dynamics and a macroscopic discrete element method; inputting parameters, calculating, correcting a formula, and converting into control parameters; dynamically adjusting parameters through a regression network self-learning feedback compensation algorithm; starting mixing equipment for batching, calculating the uniformity in real time, stopping mixing after the uniformity reaches the standard, detecting a finished product, and generating a report. According to the invention, through a self-learning feedback compensation algorithm based on a regression network, in combination with real-time weight detection and a material blockage identification result, intelligent dynamic adjustment of quantitative feeding control parameters is realized.

The invention discloses an infrared calibration temperature measurement method based on a multi-component insulating gas multispectral imaging device, belongs to the technical field of electric power safety detection, and solves the problem of how to improve the temperature measurement precision of electric power equipment. The non-uniformity correction calibrates the response and bias of each pixel to the same numerical value, the temperature correction eliminates the influence of the lens temperature and the movement temperature on the received electric signal, the shading shutter correction ensures the accuracy and consistency of the shutter or the shading system, the radiation calibration is adopted to convert the measured blackbody voltage value into the temperature value, and the temperature value is converted into the temperature value. The real temperature of the surface of the detected electrical equipment is calculated by combining the temperature value after radiometric calibration conversion, the influence of the atmospheric environment on temperature measurement is eliminated, and the temperature measurement function of the electrical equipment based on an infrared multispectral imaging detector for insulating gas leakage in a complex environment can be realized. And a foundation is laid for further forming portable power multifunctional monitoring.

According to the invention, the multi-mode time-frequency domain conversion and the deep learning technology are combined, and a multi-component mixed Raman spectrum unmixing method is developed, so that clinical in-vivo and in-situ detection and disease diagnosis of novel Raman probes, instruments and the like are facilitated. The method comprises the following steps: (1) converting a mixed Raman spectrum from a time domain to a frequency domain by using fast Fourier transform (FFT), discrete cosine transform (DCT) and discrete sine transform (DST), and extracting frequency domain features; (2) extracting multi-scale local time-frequency domain characteristics of the mixed spectrum by using short-time Fourier transform (STFT) and discrete wavelet transform (DWT); (3) carrying out spectral unmixing calculation in each mode in combination with a one-dimensional attention mechanism U-shaped neural network model; and (4) fusing various modal unmixing results by using a meta-learning method, and analyzing the weight of each modal to obtain an accurate unmixing spectrum. Compared with a traditional Raman spectrum analysis method, the Raman spectrum multi-component signal unmixing method based on multi-modal time-frequency domain transformation and deep learning can accurately separate independent Raman signals of different tissue structures and biochemical components in a complex environment in a living body, so that the unmixing accuracy of the Raman spectrum multi-component signal is improved. Therefore, convenience is provided for subsequent disease mechanism analysis and diagnosis. The method provides an innovative and potential solution for in-vivo and in-situ detection analysis and disease diagnosis of medical clinical Raman spectroscopy.