8results about How to "Solve the stiffness problem" patented technology

The utility model provides a kind of collision energy-absorbing box and vehicle, it is related to vehicle parts technical field, collision energy-absorbing box includes shell and energy-absorbing component, shell is used to connect between car body longitudinal beam and crash beam;Energy-absorbing component includes flexible container and filled shear thickening fluid in it, flexible container is set in shell;Flexible container has a stress part, stress part extends to the outside of shell and is used to bear collision force;Shear thickening fluid can change its viscosity in response to different collision speed transmitted by stress part, and change by the deformation resistance of flexible container, so that energy-absorbing box presents different rigidity.The utility model integrates energy-absorbing component in shell, and makes energy-absorbing component consist of flexible container and filled shear thickening fluid in it, realizes the self-adapting adjustment of energy-absorbing box rigidity by the self-adapting change of shear thickening fluid viscosity, solves the contradiction that traditional energy-absorbing box cannot consider low speed and high speed crash performance.

A rigidity-constrained sine compression-torsion metamaterial band gap design method comprises the following steps: S100, aiming at a sine compression-torsion metamaterial unit, establishing an analytical model among geometric parameters, equivalent rigidity and band gap boundary frequency of the sine compression-torsion metamaterial unit, so as to obtain a constraint equation describing the geometric parameters and the equivalent rigidity and the band gap boundary frequency; s200, fusing the constraint equation generated in the step S100, and constructing and training a physical information neural network for realizing high-precision and high-efficiency forward mapping from unit geometric parameters to rigidity and band gap frequency; s300, constructing and training a neural network for realizing reverse mapping from target stiffness and band gap frequency to unit geometric parameters, and providing an initial scheme for rapid customized design; and S400, setting target rigidity and band gap conditions, and adopting an intelligent optimization algorithm to call the trained physical information neural network model as a performance evaluator to perform iterative optimization. The method aims at solving the problems that in the prior art, rigidity constraint and band gap performance cannot be effectively balanced, and design and calculation efficiency is low.

The present disclosure provides a kind of blade section bending stiffness optimization method and device, electronic equipment and storage medium, it is related to blade structure design technical field, by establishing the design architecture of basic reinforcement layer, main reinforcement layer and auxiliary reinforcement layer cooperation, first in first preset position setting main reinforcement layer and iteration adjustment its geometric parameter, after main reinforcement layer reaches process limit, again in second preset position, add auxiliary reinforcement layer, and fixed main reinforcement layer parameter iteration optimization auxiliary reinforcement layer geometric parameter, formed the systematic design system of multiple reinforcement layer, multiple preset position, geometric parameter iteration adjustment, therefore, it can solve the problem that the stiffness direction imbalance caused by lacking multidimensional parameter collaborative adjustment system in prior art, only using single reinforcement strategy and not setting reinforcement layer position reasonably, difficult to meet preset tolerance, material redundancy and high risk of structural failure.

This invention discloses a rear frame structure for a vehicle cargo box and its assembly method, belonging to the field of automotive manufacturing technology. The structure connects the cargo box crossbeam assembly and the rear outer panel assembly to form a composite beam, with three-dimensional limiting socket interfaces at both ends. The left and right rear pillar assemblies of the cargo box are equipped with matching sockets, which can be inserted vertically into the interfaces to achieve automatic guidance and horizontal limiting, greatly simplifying assembly. After socketing, a combination of internal welding and external bolts ensures strength and utilizes bolt preload to actively level surface differences. The cargo box crossbeam assembly adopts a U-shaped cross-section design, with built-in support plates and pre-set suspension mounting points, improving overall rigidity and assembly accuracy. This invention effectively solves the problems of poor welding quality, low assembly accuracy, and poor appearance matching in traditional cargo box rear structures.

The utility model provides a core column reinforced wall, and belongs to the technical field of wall reinforcement. The core column reinforced wall body comprises a wall body to be reinforced, a rib material and filler. The rib material is embedded in the groove in the wall body to be reinforced, meanwhile, the two ends of the rib material are embedded in the upper ring beam and the lower ring beam respectively, meanwhile, the groove is filled with the filler, the rib material and the wall body to be reinforced are connected through the filler, and the rib material plays a riveting role, so that the wall body to be reinforced is connected with the upper ring beam and the lower ring beam into a whole through the rib material. The bearing capacity and rigidity of the to-be-reinforced wall body are improved, and the technical problem that in the prior art, the bearing capacity or rigidity of the to-be-reinforced wall body and a brick wall are insufficient due to aging of the wall body is solved.

The application relates to the technical field of building engineering construction, and provides a shearing jack synchronous telescopic deformation joint profiling aluminum mold structure and a construction method, which comprises two pieces of oppositely arranged aluminum alloy wallboards; the two pieces of aluminum alloy wallboards are arranged in a back-to-back vertical parallel mode, and the gap between the two pieces of aluminum alloy wallboards constitutes a deformation joint cavity; a shearing jack array arranged in multiple rows and multiple columns is arranged between the two pieces of aluminum alloy wallboards, the two ends of the shearing jack are fixedly connected with the opposite inner sides of the aluminum alloy wallboards on the two sides, and the two pieces of aluminum alloy wallboards are connected into an integrated structure capable of being integrally hoisted. When the application is used, the multiple-row and multiple-column shearing jack array arranged between the two pieces of aluminum alloy wallboards solves the industry common problem that personnel cannot enter the construction due to the narrow space in the deformation joint cavity, greatly improves the construction efficiency, and reduces the operation difficulty and safety risk.

The application provides a tuned mass damper, a structural assembly of a wind turbine generator and a wind turbine generator. The tuned mass damper comprises a base, an elastic body and a main mass module arranged on the base, and a sub-mass module connected with the main mass module. The main mass module comprises a first mass body, the elastic body comprises a first elastic body arranged between the first mass body and the base, and a first connecting member connects the first mass body, the first elastic body and the base (100). The sub-mass module is detachably connected with the main mass module on the side opposite to the base, so as to adjust the mass of the tuned mass damper, thereby being capable of adapting to different platform requirements.

The application discloses an underground structure parameterized intelligent design and automatic reinforcement optimization method and system, relates to the field of computer-aided design, and comprises the following steps: obtaining segmented data, segment boundary data, load working condition data and initial internal force data, and generating a reinforcement scheme set; obtaining segment demand parameters of each segment based on internal force envelopes and geometric normalization; performing segment internal checking and cost evaluation on the reinforcement scheme, determining a reference reinforcement scheme and a segment internal surplus value; combining adjacent segment relationships, the reference reinforcement scheme, the segment demand parameters and segment boundary allowed deformation threshold values, obtaining segment boundary risk weights; constructing a joint objective function and combining solving on the basis, obtaining a current reinforcement scheme combination; and then obtaining segment boundary feedback parameters through reanalysis, iteratively updating the segment boundary risk weights, and outputting segmented reinforcement schemes meeting convergence conditions until the segmented reinforcement schemes are output. The application can improve the overall coordination, engineering applicability and economy of underground structure reinforcement design.