187 results about "Shear modulus" patented technology

The invention provides a petroleum drilling geomechanical characteristic estimation method based on deep learning, and aims to solve the problems of high measurement cost and poor real-time performance of shear wave velocity Vs in traditional geomechanical analysis by fusing logging while drilling LWD data and real-time drilling engineering parameters. According to the method, a Transformer model is adopted to carry out depth correction on logging-while-drilling data, depth offset of a drill bit and a logging sensor is eliminated, and real-time drilling parameters such as torque T, bit pressure WOB and drilling speed ROP are combined and input into a multi-layer perceptron MLP network to predict the shear wave speed Vs. And further calculating key geomechanical parameters based on the predicted shear wave velocity Vs. In practical application, the method improves the shear wave velocity prediction accuracy to 97.2%, the mean absolute error MAE of the shear modulus is reduced from 0.186 to 0.059, and the bulk modulus is reduced from 0.189 to 0.040. The method can be used for outputting stratum elastic parameters, optimizing bit pressure, pre-warning well wall instability and adjusting a well track, well drilling safety and efficiency are improved, and meanwhile dependence on an expensive well logging technology is reduced.

The invention relates to the technical field of oil and gas geophysical exploration, and particularly discloses a tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system.The method comprises the steps that a reflection coefficient expression containing a fluid mobility item is constructed, and a formula for calculating fluid mobility through frequency dispersion attributes is deduced; constructing a fluid mobility gradient attribute related to the frequency and the incident angle of the seismic wave; the method comprises the following steps: establishing a double-pore rock physical model, generating a synthetic seismic record, applying frequency variation AVO inversion to the synthetic seismic record, and extracting a bulk modulus dispersion attribute and a shear modulus dispersion attribute; and calculating the fluid fluidity changing along with the frequency and the incident angle, and calculating the gradient attribute of the fluid fluidity based on a gradient attribute calculation formula and the fluid fluidity. According to the method, seismic wave frequency dispersion and attenuation response caused by permeability and gas saturation are fully utilized, the seismic gradient attribute of the fluid fluidity and the calculation method are constructed, and high-precision prediction of the fluid fluidity by applying seismic signal elasticity and frequency dispersion rock physical information is realized.

The invention relates to the technical field of slope reinforcement, and particularly discloses a slope reinforcement system and method for building municipal administration, slope rock mass strain time sequence data is collected through a distributed optical fiber sensing system, slope deformation monitoring data is obtained through a spaceborne interferometric synthetic aperture radar, and a three-dimensional deformation monitoring data set is constructed; an LSTM-rock constitutive model fusing a DFOS strain field and an InSAR deformation field is established, strain time sequence data and deformation data are input into the model for three-dimensional stress field inversion, and shear modulus degradation rate parameters, creep coefficient parameters and displacement increment prediction data are output; shear modulus degradation rate parameters, creep coefficient parameters and displacement increment prediction data are processed, regulation and control strategy codes of anchor rod tensioning force gradients and grouting pressure intervals are generated and uploaded to a control terminal, the precision and timeliness of slope stability analysis are remarkably improved, accurate intervention can be conducted in time according to potential risks of a slope, and the stability of the slope is improved. The probability of geological disasters such as landslide is reduced, and life and property safety of people is protected.

The invention relates to a dot matrix cell element filling structure design method considering a material shearing effect, which comprises the following steps: acquiring a plurality of dot matrix cell elements, and extracting configuration data of each dot matrix cell element; training a U-Net neural network by using the configuration data to obtain a dot matrix cell element configuration reverse generation model; establishing a cantilever beam flexibility minimization objective function considering the shear modulus, and adopting a variable density topology to optimize a cantilever beam example to generate a global stiffness matrix of the shear modulus containing dot matrix cell elements; and performing reverse mapping on the global stiffness matrix by using the dot matrix cell configuration reverse generation model to obtain the cell configuration of the dot matrix cell filling structure. According to the method, the dot matrix filling structure design capable of considering the cell shear modulus distribution is realized.

A clampless synthetic jet actuator includes a cavity layer having an internal cavity for reception of a fluid volume and an orifice providing a fluid communication between the cavity and an external atmosphere; and an oscillatory membrane having a piezoelectric material adapted to deflect the oscillatory membrane in response to an electrical signal. The cavity has an opening in at least one planar surface of the cavity layer, and the cavity layer and the oscillatory membrane are joined by a high strength, low shear modulus adhesive material with the oscillatory membrane positioned adjacent to the planar surface having the cavity opening and adapted as an enclosing surface to said cavity opening. The oscillatory membrane is adapted to compress and expand a volume within the cavity, based on a deflection generated by the piezoelectric material, for generating a fluid flow between the cavity and the external atmosphere through the orifice.

This invention discloses a quantitative evaluation method for the homogeneity of lightweight aggregate concrete based on rapid ultrasonic testing, belonging to the field of engineering materials testing technology. The method includes: S1, obtaining the shear wave velocity and longitudinal wave velocity at multiple test points of a series of lightweight aggregate concrete reference specimens; S2, calculating the shear modulus and bulk modulus at each test point of each reference specimen; S3, calculating the elastic modulus at each test point of each reference specimen; S4, constructing a relationship between the lightweight aggregate volume content, shear wave velocity, and longitudinal wave velocity based on the elastic modulus obtained in step S3; S5, obtaining the shear wave velocity and longitudinal wave velocity at each test point of the specimen to be tested, and calculating the lightweight aggregate volume content at each test point of the specimen to be tested based on the relationship; S6, evaluating the homogeneity of the specimen to be tested based on the lightweight aggregate volume content calculated in step S5. This invention solves the technical problem of insufficient accuracy in ultrasonic testing results for the homogeneity of lightweight aggregate concrete.

The application discloses a micro-nano circular plate fracture analysis method considering coupling of surface effect and plastic zone, and firstly establishes a three-dimensional curved surface coordinate system suitable for a surface layer, and then further corrects a Dugdale cohesion force model according to a superposition principle after considering surface correlation of the plate, and then simplifies the Dugdale cohesion force model into a hyper-singular integral equation by using Hankel transformation, and finally obtains influences of the surface effect on the plastic zone size and crack surface displacement by numerically solving the hyper-singular integral differential equation.The method can accurately capture the nonlinear coupling relationship between the crack size, the surface shear modulus, the torsional displacement and the stress intensity factor under the micro-nano scale, effectively corrects calculation deviation generated by traditional classical theory when the surface effect is ignored, ensures the accuracy of the fracture analysis under different scales, and realizes more accurate and more comprehensive theoretical description of the elastic-plastic fracture behavior of the micro-scale material.

The invention relates to a tyre (1) provided with a crown (4) comprising a crown reinforcement (20), a sublayer (7) and a tread (6). The lower layer (7) comprises a first base layer (71) radially outside the crown reinforcement (20) and a second cover layer (72) radially outside the first base layer (71) and radially inside the tread (6). The dynamic shear modulus G1 * of the first base layer is 1.5 MPa or less, and the dynamic shear modulus of the second cover layer is 5 MPa or more. The thickness E72 of the second cover layer (72) is associated with the maximum thickness ESC under the cut by the following relational expressions: E72 (mm) is greater than or equal to (0.53 * ESC + 0.1), E72 (mm) is less than or equal to (0.47 * esc + 1.1), ESC is in [1; 3.5] mm.

The present application relates to oil and gas geophysical exploration technology field, specifically disclose a kind of tight sandstone gas reservoir fluid mobility gradient attribute prediction method and system, the method includes constructing fluid mobility term's reflection coefficient expression, and deduce the formula for calculating fluid mobility using dispersion attribute, construct and frequency and seismic wave incidence angle related fluid mobility gradient attribute;Establish double-pore petrophysical model, generate synthetic seismogram, apply frequency-variable AVO inversion to the synthetic seismogram, extract bulk modulus dispersion attribute and shear modulus dispersion attribute;Fluid mobility changing with frequency and incidence angle is calculated, based on gradient attribute calculation formula and fluid mobility, fluid mobility gradient attribute is calculated.The present application makes full use of the response of the seismic wave dispersion and attenuation caused by permeability and gas saturation, constructs the seismic gradient attribute and calculation method of fluid mobility, realizes the high-precision prediction of fluid mobility by applying the elastic and dispersion petrophysical information of seismic signal.

The invention discloses a foamed rubber asphalt formula determination method. The method comprises the following steps: S1, constructing a molecular model of a foamed rubber asphalt composite system; s2, performing molecular dynamics simulation on the molecular model to obtain a balanced stable structure configuration; s3, based on the stable structure configuration, under the conditions of different rubber mixing amounts, foaming medium mixing amounts and temperatures, calculating the shear modulus, interface adhesion work and fracture energy of the foam rubber asphalt system; and S4, performing multi-objective optimization by taking the shear modulus, the interface adhesion work and the fracture energy as performance indexes, and determining a combination of the temperature, the foaming medium mixing amount and the rubber mixing amount of the optimal formula of the foamed rubber asphalt. According to the method, the combination of the foaming temperature, the foaming medium mixing amount and the rubber mixing amount is determined through molecular modeling and a multi-objective optimization algorithm, and performance prediction and parameter optimization of the foamed rubber asphalt are achieved.

The invention belongs to the technical field of bridge steel shell hoisting construction, and particularly relates to a fine adjustment device suitable for stability of a gravity center changing curve type steel shell, the fine adjustment device comprises a steel shell, mounting angle blocks are symmetrically arranged on the side face of the upper end of the steel shell, and an adjusting mechanism is arranged at the upper end of each mounting angle block. According to the fine adjustment device, a flexible adjustment structure composed of the magnetorheological elastomer and the electromagnetic coil is arranged, and a steel cable traction adjustment mechanism driven by the hydraulic motor is combined, so that bidirectional precise regulation and control over the stability of the steel shell are achieved, and the shear modulus of the magnetorheological elastomer can be linearly regulated and controlled through the current of the electromagnetic coil; the stress change caused by gravity center shift can be quickly responded, and the dynamic unbalance force can be counteracted in real time.

The invention relates to a tyre (1) provided with a crown (4) which is optimized for an advantageous compromise between drivability and rolling resistance. The crown (4) comprises a crown reinforcement (20), a lower layer (7) and a tread (6). The lower layer (7) comprises a first base layer (71) radially outside the crown reinforcement (20) and a second cover layer (72) radially outside the first base layer (71) and radially inside the tread (6). The dynamic shear modulus G1 * of the first base layer is 1.5 MPa or less, and the dynamic shear modulus of the second cover layer is 5 MPa or more. The thickness of the second cover layer (72) is [20%; 80%].

The invention discloses an oil and gas development favorable area prediction method based on Winsored particle size mean curve simulation, and the method comprises the following steps: based on laser particle size experiment data, employing a Winsored algorithm to process rock particle size data, removing abnormal interference values, and simulating a well hole particle size mean longitudinal curve through inputting logging response parameters by means of an XLSTM-Transform hybrid neural network model; selecting a shear modulus density and a longitudinal and transverse wave velocity ratio as sensitive attribute parameters of a granularity mean value in combination with seismic data, and forming two sets of three-dimensional attribute data volumes in combination with waveform structure inversion; according to the method, model training is carried out on the nonlinear relation between the particle size mean value and the seismic sensitive attribute parameters based on a machine learning method, and finally a Winsored particle size mean value inversion body is formed, so that the spatial distribution rule of a relatively large particle size reservoir can be defined, and effective prediction of a development favorable area is realized.

The embodiment of the application relates to the technical field of sandstone type uranium ore exploration, and particularly relates to a method for determining a favorable area of a sandstone type uranium ore, which comprises the following steps: collecting well logging data of an exploration area of the sandstone type uranium ore, and gradually determining argillaceous content, total porosity of the exploration area, sandstone content of a sand and shale mixed matrix, longitudinal wave time difference, transverse wave time difference and density, equivalent elastic modulus of dry rock of the exploration area, and conversion relationship between longitudinal wave velocity and transverse wave velocity of rock under saturated fluid condition and a transverse wave velocity prediction curve; then, longitudinal wave impedance, velocity ratio of longitudinal wave and transverse wave and a density model are established; according to the model, three-dimensional elastic data bodies of impedance, density and shear modulus of longitudinal wave and transverse wave are determined by inversion; and according to the three-dimensional elastic data bodies, the favorable area of the sandstone type uranium ore is determined. The method for determining the favorable area of the sandstone type uranium ore according to the embodiment of the application can effectively improve the prediction accuracy of a favorable area of a sandstone type uranium ore.

The present invention relates to methods of applying cementitious compositions comprising de-lithiated beta-spodumene by injecting, by spraying, or by layer-by- layer deposition, to cementitious compositions comprising de-lithiated beta-spodumene, and to the use of de-lithiated beta-spodumene to increase the shear modulus G of a cementitious composition.

The present application relates to the geological exploration technical field, more particularly, to a deep water super shallow layer natural gas reservoir rock physics shear wave velocity prediction method, comprising: calculating equivalent bulk modulus, shear modulus and density of a plurality of mineral mixed matrix according to shale content; then calculating skeleton bulk modulus and shear modulus; then calculating saturated rock bulk modulus and shear modulus through a model, and calculating saturated rock density through rock matrix density; distributing longitudinal and transverse velocities of suspended state and bearing state, and calculating equivalent longitudinal and transverse wave velocities; using equivalent longitudinal wave velocity to construct an inversion objective function with longitudinal wave velocity as a known condition; comparing actual longitudinal wave velocity with calculated longitudinal wave velocity; realizing nonlinear inversion of transverse wave velocity according to an algorithm, and obtaining transverse wave velocity of a to-be-inverted work area. The present application simultaneously considers rock physics models of particle suspended state and bearing state, and realizes transverse wave velocity prediction and deep water super shallow layer natural gas reservoir transverse wave velocity direct inversion.

The invention relates to the technical field of automatic conveying and robot end executors, in particular to a conveying device and method for automobile hub bearing machining. The device comprises a multi-axis mechanical arm, a pneumatic control cabinet and a grabbing mechanism composed of a rigid framework, an inner-layer elastic bag body and an outer-layer blocking bag body filled with ceramic particles. The core is that a vacuum and positive pressure loop is mechanically coupled through a differential pressure balance valve, and when an outer-layer bag body is vacuumized to generate particle blocking phase change, the positive pressure flow of an inner layer is linearly adjusted, so that dynamic balance of inner supporting force and outer shrinkage force is realized; high shear modulus after phase change of particles is utilized to prevent high-speed conveying slippage, meanwhile, extremely low net radial force is maintained, elliptical deformation of the thin-wall bearing is effectively avoided, and machining precision is ensured.

A tire (10) for a passenger vehicle comprises a tread comprising at least one regulation wear indicator (46) defining a regulation wear threshold, a tread layer (52) comprising an elastomeric tread material exhibiting a complex dynamic shear modulus G*_1 and a dynamic loss tanD0_1, and a backing layer (54) for the tread layer (52) that comprises an elastomeric backing material exhibiting a complex dynamic shear modulus G*_2 and a dynamic loss tanD0_2 such that tanD0_2≥0.37×tanD0_1 and G*2≥0.90×G*1.

The application relates to the motor winding technology field and provides a motor winding process automatic control method and system.The method comprises the following steps: obtaining motion state information, stress state information and material characteristic information of a flat wire; inputting the motion state information, the stress state information and the material characteristic information into a preset flat wire mechanical simulation model to obtain a predicted torsion angle of the flat wire in a bending process output by the preset flat wire mechanical simulation model; obtaining an actual torsion angle of the flat wire; adjusting a parameter value of an equivalent shear modulus of the flat wire in the preset flat wire mechanical simulation model according to the predicted torsion angle and the actual torsion angle to obtain an adjusted preset flat wire mechanical simulation model; and performing winding control on the flat wire based on the adjusted preset flat wire mechanical simulation model. The accuracy of motor winding can be controlled.

This invention discloses a vibration damping mechanism for an irregularly shaped centrifuge device and its design method. The design method includes: establishing two balance reference planes corresponding to the upper and lower surfaces of the rotating module, respectively, and calculating the mass of the counterweight using the inertial force balance formula; determining the model of the vibration damping support based on the ratio of the interference frequency of the irregularly shaped centrifuge device to the natural frequency of the vibration damping mechanism being greater than a certain threshold; calculating the radial wall thickness of the suspended vibration damping sleeve based on the shear modulus of the material being prepared, and determining the axial length and outer diameter of the suspended vibration damping sleeve based on its installation inner diameter, thus obtaining the design parameters of the suspended vibration damping sleeve; after the vibration damping mechanism is assembled onto the irregularly shaped centrifuge device, using a dynamic balancing analyzer to test the vibration of the irregularly shaped centrifuge device at its rated speed to confirm the dynamic balancing effect. The design method of this invention is easier to operate and select, and through dynamic balancing verification analysis, it can effectively ensure the vibration damping and suppression effect of the vibration damping mechanism.

The invention discloses a soil nonlinear site seismic shear stress determination method, which comprises the following steps of: firstly, constructing a site stratified soil simplified model, and fitting a soil dynamic curve; then, the equal-amplitude cyclic stress of the seismic oscillation waves is vertically incident from the bottom of the site bedrock; constructing a transfer matrix to obtain an amplitude matrix of each soil layer, solving to obtain seismic shear stress of each soil layer, calculating normalized dynamic shear strain of each soil layer by using a time-domain dynamic shear strain component, substituting the normalized dynamic shear strain into a soil dynamic curve, determining new dynamic shear modulus and damping ratio of each soil layer, and calculating the seismic shear stress of each soil layer. Iteration calculation of the new dynamic shear modulus and the damping ratio is repeated, the dynamic shear modulus and the damping ratio output after iteration are called as the equivalent shear modulus and the equivalent damping ratio, and the seismic shear stress of each soil layer of a non-linear field of a soil body is solved when seismic waves are vertically incident, so that a foundation is provided for earth and rockfill dam seismic response research; and reference is provided for site selection of a proposed project, design of a site anti-liquefaction scheme and the like.

The invention relates to a multi-principal-element alloy strength prediction and design method driven by experimental data. The method comprises the following steps: data acquisition, feature engineering, model construction, component design, solving of yield strength of different alloys by multiple analytical formulas, and screening of alloy components with large product of electronegativity difference and shear modulus. And determining a single-phase FCC component window through phase diagram calculation. According to the method, the component design efficiency is improved; a quantitative design tool is provided for high-strength material development in the fields of aerospace, nuclear energy and the like, and the research and development period is shortened.

The invention relates to the technical field of tantalate thermal barrier coatings, in particular to a construction method and application of a rare earth tantalate material multi-performance prediction model, and the construction method comprises the following steps: collecting Young modulus, shear modulus, thermal expansion coefficient and thermal conductivity data of a rare earth tantalate material; an initial feature set is constructed based on material component features, and redundant features are deleted by using a Pearson correlation analysis method to reduce the complexity of the model. And modeling and evaluating various machine learning models. And on the basis of each performance optimal model, SFFS sequence floating forward feature subset screening is carried out. And finally, integrating the optimal feature set of each performance, and constructing a multi-performance integrated prediction model of the rare earth tantalate material. According to the method, the high-precision component-multi-performance mapping model can be constructed, the Young modulus, the shear modulus, the thermal expansion coefficient and the thermal conductivity of the rare earth tantalate material can be quickly and accurately predicted, the consumption of experiment resources is reduced, and the experiment progress is accelerated.

The application discloses a viscoelasticity parameter inversion method, and belongs to the field of medical image processing and computational imaging. The method obtains the time-space image sequence data of the measured soft tissue after excitation, extracts the shear wave group velocity by using the time-of-flight method, and equivalently takes the shear wave group velocity as the phase velocity anchor point under the zero-frequency limit condition to determine the static shear modulus; the two-dimensional fast Fourier transform is used to extract the middle-high frequency band phase velocity dispersion curve; the rheological model of the measured soft tissue is constrained based on the static shear modulus, and the single-parameter fitting of the viscosity coefficient is combined with the middle-high frequency band phase velocity dispersion curve to obtain the viscoelasticity parameter.

The invention discloses a variable-stiffness magnetorheological fluid elastic vibration isolator for a variable-speed rotorcraft, which comprises a closed cavity formed by a magnetic flux outer cylinder, a magnetic flux inner cylinder and an annular magnetorheological elastomer connected between the magnetic flux outer cylinder and the magnetic flux inner cylinder, inertia liquid is filled in the cavity, and a magnet exciting coil is arranged in an outer ring groove of the magnetic flux inner cylinder. The magnetic flux outer cylinder, the magneto-rheological elastomer and the magnetic flux inner cylinder form a closed magnetic circuit, and the magnetic field intensity is changed by adjusting the current of the magnet exciting coil, so that the shear modulus of the magneto-rheological elastomer is continuously and reversibly adjusted and controlled, and online adjustment of the rigidity of the vibration isolator is achieved. The inner cylinder connected with the magnetic flux inner cylinder is provided with an inertia channel, when external vibration is introduced, liquid flows in the channel, and inertia force opposite to exciting force is generated at an anti-resonance frequency point to achieve efficient vibration isolation. The variable vibration frequency of the rotor wing is dynamically matched through the electronic control rigidity, the problems that a traditional vibration isolator is narrow in frequency band, and a mechanical frequency conversion scheme is slow in response and complex in structure are solved, and the vibration isolator has the advantages of being fast in response and compact in structure.

A method and an apparatus for measuring ultrasonic viscoelasticity, a device and a medium are provided. The method includes: establishing an inhomogeneous viscoelastic wave equation; coding the inhomogeneous viscoelastic wave equation as a loss function, and constructing a physics-informed neural network, where the spatial-temporal neural network is configured to predict a stream function, the inhomogeneous viscoelastic wave equation is used to obtain vertical vibration velocity of particles based on the stream function outputted, the spatial neural network is configured to predict shear modulus and viscosity, and the loss function is used to calculate an aggregate loss; inputting the multi-frame vertical vibration velocity of particles of the object to be measured as supervisory data into the physics-informed neural network, to obtain a spatial distribution of the shear modulus and a spatial distribution of the viscosity of the object to be measured.

The invention provides a modeling method and a saturation prediction method of a rock physical model containing non-uniformly distributed hydrate sediments. Comprising the steps of obtaining model parameters, calculating the porosity of a mineral skeleton based on the model parameters, calculating the bulk modulus and the shear modulus of a dry hydrate skeleton, calculating the bulk modulus and the shear modulus of a dry mineral skeleton, and calculating the bulk modulus and the shear modulus of a dry composite skeleton composed of the dry mineral skeleton and the dry hydrate skeleton. And calculating the rock bulk modulus and shear modulus when the fluid is saturated, calculating the rock density value when the fluid is saturated, and calculating the stratum longitudinal wave velocity and the stratum transverse wave velocity. According to the method, on the basis of the forming mechanism and distribution characteristics of the non-uniformly distributed hydrates, the non-uniformity of the hydrates and mineral particles is considered in the modeling process, the hydrates and the mineral particles are regarded as two independent rock frameworks, and the isotropic rock physical model suitable for the non-uniformly distributed hydrates is constructed.

This invention discloses a damage evolution prediction system for heavy-duty traffic asphalt pavement, relating to the field of road engineering technology. The system includes: a data acquisition module for acquiring continuous multi-frame time-series images of pavement cracks, vehicle axle load spectra, and environmental temperature and humidity data; an image processing and spatiotemporal modeling module for performing multi-scale fractal processing and dynamic time warping on the time-series images to calculate the fractal dimension sequence across scales; a material property correlation module for establishing and updating a probabilistic correlation model between fractal dimension and shear modulus in real time using dynamic shear rheometer test data; a multi-physics data fusion module for fusing multi-physics features through a fractal attention network to generate a multi-physics collaborative damage correction factor; and a damage prediction and early warning module for predicting the fractal dimension growth trend using a fractal domain adaptive transfer learning algorithm and outputting a damage evolution early warning based on viscoelastic phase consistency verification results.

The embodiment of the application provides a casing inner diameter calculation model training method and a method for determining the casing inner diameter, and belongs to the technical field of computers. The casing inner diameter calculation model training method comprises the following steps: acquiring microseismic data and a shear modulus, determining a distance range of fault slip based on the microseismic data and the shear modulus, acquiring a geological parameter variation range of geological engineering parameters and a wellbore parameter variation range of wellbore parameters, determining engineering parameters based on the distance range, the geological parameter variation range and the wellbore parameter variation range, performing numerical simulation according to the engineering parameters to obtain a casing inner diameter result corresponding to the engineering parameters, training a BP neural network model based on the engineering parameters and the casing inner diameter result to obtain a casing inner diameter calculation model. Through the casing inner diameter calculation model, the calculation error is effectively reduced, and the convenience of casing inner diameter calculation is improved.