A method for predicting if a flow over a smooth ramp surface will separate from the ramp surface, wherein the ramp surface has a slope that is everywhere non-positive along the length of the ramp surface relative to the flow at the inflow end of the ramp surface includes i) dividing the height of the ramp surface by the length of the ramp surface to determine a height-to-length ratio of the ramp surface, ii) identifying a maximum slope magnitude of the ramp surface, iii) calculating a maximum normalized slope by dividing the maximum slope magnitude of the ramp surface by the height-to-length ratio of the ramp surface, and calculating a critical ramp slope as a linear function of the height-to-length ratio of the ramp surface. If the maximum normalized slope is greater than the critical ramp slope, the method predicts the turbulent boundary layer will separate from the ramp surface.

A method for developing a virtual testing model of a subject for use in simulated aerodynamic testing comprises providing a computer generated generic 3D mesh of the subject, identifying a dimension of the subject and at least one reference point on the subject, imaging the subject to develop point cloud data representing at least the subject's outer surface and adapting the generic 3D mesh to the subject. The generic 3D mesh is adapted by modifying it to have a corresponding dimension and at least one corresponding reference point, and applying at least a portion of the point cloud data from the imaged subject's outer surface at selected locations to scale the generic 3D mesh to correspond to the subject, thereby developing the virtual testing model specific to the subject.

A method for developing a virtual testing model of a subject for use in simulated aerodynamic testing comprises providing a computer generated generic 3D mesh of the subject, identifying a dimension of the subject and at least one reference point on the subject, imaging the subject to develop point cloud data representing at least the subject's outer surface and adapting the generic 3D mesh to the subject. The generic 3D mesh is adapted by modifying it to have a corresponding dimension and at least one corresponding reference point, and applying at least a portion of the point cloud data from the imaged subject's outer surface at selected locations to scale the generic 3D mesh to correspond to the subject, thereby developing the virtual testing model specific to the subject.

Radiation curable compositions for additive fabrication processes, the components cured therefrom, and their use in particle image velocimetry testing methods are described and claimed herein. Such compositions include compounds which induce free-radical polymerization, optionally compounds which induce cationic polymerization, a filler constituent, and a light absorbing component, wherein the compositions are configured to possess certain absorbance values at wavelengths commonly utilized in particle image velocimetry testing. In another embodiment, the compositions include a fluoroantimony-modified compound. Such compositions may be used in particle imaging velocimetry testing methods, wherein the test object utilized is created via additive fabrication and is of a substantially homogeneous construction.

An assembly quality detection device and a method for a wind screen cleaning system based on streamline pattern, includes a main body of a test bench and a detection system. The main body of the test bench includes a test bench rack and a cleaning centrifugal fan; the inside of the test bench rack is provided with a cleaning space. The detection system includes a smoke generation and transmission device, a two-degree-of-freedom smoke fixed-point release mechanism, a high-speed image acquisition system and a control system. A fixed base is installed on the upper end of the outlet of the cleaning centrifugal fan, a linear moving guide rail device is installed on the fixed base, the linear moving guide rail device is equipped with a moving slider, the moving slider is installed with a rotating mechanism, the rotating mechanism output end is provided with a smoke releasing duct, the smoke releasing duct is communicated with the smoke generation and transmission device. The detection device and method can test the manufacturing and assembly quality of the cleaning system of the combine harvester by combining the characteristics of wind tunnel streamline pattern with image processing and corresponding mathematical operation.

The invention discloses a coupled free vibration wind tunnel testing device with adjustable frequency ratio of torsional-vertical vibration, belonging to the technical field of bridge wind tunnel testing device. The device includes rigid testing model, lightweight rigid rods, lightweight rigid circular hubs, thin strings, linear tensile springs, carbon fiber ropes, and lightweight small hubs. The invention adjusts the torsional stiffness of the system by conveniently changing the diameter of the small hub, the diameter and length of the carbon fiber rope, etc. The device has the advantages of simple structure, convenient installation and avoiding the previous tedious work. It can achieve a variety of torsional-vertical vibration frequency ratio testing conditions by using only one diameter large hub. It can not only greatly save the time of replacing the large hub, but also facilitate the realization of higher torsional-vertical vibration frequency ratio testing conditions which are difficult to achieve by the previous methods.

A wing model for static aeroelasticity wind tunnel test belongs to the technical field of aeroelasticity tests. In the wing model, the model steel joint and the spar frame are connected with the composite material skin. The piezometer wing ribs are arranged among the spar frame and the plurality of supporting wing ribs. The embedded piezometer tubes are arranged in the piezometer wing ribs, the lightweight filling foam is arranged among the spar frame and the plurality of supporting wing ribs. An outer surface of a frame segment formed by the lightweight filling foam, the plurality of supporting wing ribs, the piezometer wing ribs and the spar frame is covered with the composite material skin. The frame segment is assembled on the model steel joint to form the wing model for the static aeroelasticity wind tunnel test.

A wing model for static aeroelasticity wind tunnel test belongs to the technical field of aeroelasticity tests. In the wing model, the model steel joint and the spar frame are connected with the composite material skin. The piezometer wing ribs are arranged among the spar frame and the plurality of supporting wing ribs. The embedded piezometer tubes are arranged in the piezometer wing ribs, the lightweight filling foam is arranged among the spar frame and the plurality of supporting wing ribs. An outer surface of a frame segment formed by the lightweight filling foam, the plurality of supporting wing ribs, the piezometer wing ribs and the spar frame is covered with the composite material skin. The frame segment is assembled on the model steel joint to form the wing model for the static aeroelasticity wind tunnel test.

The disclosure discloses a numerical simulation method of an influence of a polytetrafluoroethylene (PTFE)-based membrane on an aerodynamic characteristic of a wind turbine blade, and relates to the technical field of polymer composites. The simulation method comprises the following steps: selecting a wind turbine generator, a blade airfoil and a PTFE-based nano functional membrane; setting a numerical simulation computation network and a computation area of a wind energy capture area; determining main computation parameters and a Reynolds number for aerodynamic characteristic computation; establishing a geometrical model whose airfoil boundary extends by 0.26 mm (membrane thickness) along a normal direction to obtain a new computational geometry; computing by using a hydrodynamic computation method and a finite volume method; and obtaining an influence number simulation computation result.

A method for analyzing fluid around a rotating body includes: a step (S100) in which a spatial model having a rotating computational mesh cell group A and a stationary computational mesh cell group B is acquired; a step (S101) in which a storage computational mesh cell group C is established; a step (S102) in which arithmetic operations for fluid analysis are performed; a step (S103) in which the physical quantity at the computational mesh cell making up the rotating computational mesh cell group A calculated as a result of arithmetic operations for fluid analysis is copied to a corresponding computational mesh cell at the storage computational mesh cell group C; and a step (S104) in which averages over time are calculated for the physical quantities at the storage computational mesh cell group C and the stationary computational mesh cell group B.